id	sid	tid	token	lemma	pos
admet-2772	1	1	leveraging	leverage	VERB
admet-2772	1	2	machine	machine	NOUN
admet-2772	1	3	learning	learning	NOUN
admet-2772	1	4	models	model	NOUN
admet-2772	1	5	in	in	ADP
admet-2772	1	6	evaluating	evaluate	VERB
admet-2772	1	7	admet	admet	NOUN
admet-2772	1	8	properties	property	NOUN
admet-2772	1	9	for	for	ADP
admet-2772	1	10	drug	drug	NOUN
admet-2772	1	11	discovery	discovery	NOUN
admet-2772	1	12	and	and	CCONJ
admet-2772	1	13	development	development	NOUN
admet-2772	1	14	doi	doi	PROPN
admet-2772	1	15	:	:	PUNCT
admet-2772	1	16	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	1	17	1	1	NUM
admet-2772	1	18	admet	admet	X
admet-2772	1	19	&	&	CCONJ
admet-2772	1	20	dmpk	dmpk	PROPN
admet-2772	1	21	13(3	13(3	NUM
admet-2772	1	22	)	)	PUNCT
admet-2772	1	23	(	(	PUNCT
admet-2772	1	24	2025	2025	NUM
admet-2772	1	25	)	)	PUNCT
admet-2772	1	26	2772	2772	NUM
admet-2772	1	27	;	;	PUNCT
admet-2772	1	28	doi	doi	NOUN
admet-2772	1	29	:	:	PUNCT
admet-2772	1	30	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	1	31	open	open	ADJ
admet-2772	1	32	access	access	NOUN
admet-2772	1	33	:	:	PUNCT
admet-2772	1	34	issn	issn	PROPN
admet-2772	1	35	:	:	PUNCT
admet-2772	1	36	1848	1848	NUM
admet-2772	1	37	-	-	SYM
admet-2772	1	38	7718	7718	NUM
admet-2772	1	39	http://www.pub.iapchem.org/ojs/index.php/admet/index	http://www.pub.iapchem.org/ojs/index.php/admet/index	NOUN
admet-2772	1	40	review	review	VERB
admet-2772	1	41	leveraging	leverage	VERB
admet-2772	1	42	machine	machine	NOUN
admet-2772	1	43	learning	learning	NOUN
admet-2772	1	44	models	model	NOUN
admet-2772	1	45	in	in	ADP
admet-2772	1	46	evaluating	evaluate	VERB
admet-2772	1	47	admet	admet	NOUN
admet-2772	1	48	properties	property	NOUN
admet-2772	1	49	for	for	ADP
admet-2772	1	50	drug	drug	NOUN
admet-2772	1	51	discovery	discovery	NOUN
admet-2772	1	52	and	and	CCONJ
admet-2772	1	53	development	development	NOUN
admet-2772	1	54	magesh	magesh	PROPN
admet-2772	1	55	venkataraman	venkataraman	PROPN
admet-2772	1	56	,	,	PUNCT
admet-2772	1	57	gopi	gopi	PROPN
admet-2772	1	58	chand	chand	PROPN
admet-2772	1	59	rao	rao	PROPN
admet-2772	1	60	,	,	PUNCT
admet-2772	1	61	jeevan	jeevan	PROPN
admet-2772	1	62	karthik	karthik	PROPN
admet-2772	1	63	madavareddi	madavareddi	PROPN
admet-2772	1	64	and	and	CCONJ
admet-2772	1	65	srinivas	srinivas	PROPN
admet-2772	1	66	rao	rao	PROPN
admet-2772	1	67	maddi	maddi	PROPN
admet-2772	1	68	*	*	PROPN
admet-2772	1	69	department	department	PROPN
admet-2772	1	70	of	of	ADP
admet-2772	1	71	pharmacology	pharmacology	NOUN
admet-2772	1	72	,	,	PUNCT
admet-2772	1	73	acubiosys	acubiosys	PROPN
admet-2772	1	74	private	private	ADJ
admet-2772	1	75	limited	limited	ADJ
admet-2772	1	76	,	,	PUNCT
admet-2772	1	77	hyderabad	hyderabad	PROPN
admet-2772	1	78	,	,	PUNCT
admet-2772	1	79	telangana	telangana	PROPN
admet-2772	1	80	,	,	PUNCT
admet-2772	1	81	india	india	PROPN
admet-2772	1	82	corresponding	corresponding	PROPN
admet-2772	1	83	author	author	NOUN
admet-2772	1	84	:	:	PUNCT
admet-2772	1	85	e	e	NOUN
admet-2772	1	86	-	-	NOUN
admet-2772	1	87	mail	mail	NOUN
admet-2772	1	88	:	:	PUNCT
admet-2772	1	89	*	*	PUNCT
admet-2772	1	90	srinivasm@acubiosys.com	srinivasm@acubiosys.com	PROPN
admet-2772	1	91	received	receive	VERB
admet-2772	1	92	:	:	PUNCT
admet-2772	1	93	april	april	PROPN
admet-2772	1	94	4	4	NUM
admet-2772	1	95	,	,	PUNCT
admet-2772	1	96	2025	2025	NUM
admet-2772	1	97	;	;	PUNCT
admet-2772	1	98	revised	revise	VERB
admet-2772	1	99	:	:	PUNCT
admet-2772	1	100	june	june	PROPN
admet-2772	1	101	6	6	NUM
admet-2772	1	102	,	,	PUNCT
admet-2772	1	103	2025	2025	NUM
admet-2772	1	104	;	;	PUNCT
admet-2772	1	105	published	publish	VERB
admet-2772	1	106	:	:	PUNCT
admet-2772	1	107	june	june	PROPN
admet-2772	1	108	7	7	NUM
admet-2772	1	109	,	,	PUNCT
admet-2772	1	110	2025	2025	NUM
admet-2772	1	111	abstract	abstract	ADJ
admet-2772	1	112	background	background	NOUN
admet-2772	1	113	and	and	CCONJ
admet-2772	1	114	purpose	purpose	NOUN
admet-2772	1	115	:	:	PUNCT
admet-2772	1	116	the	the	DET
admet-2772	1	117	evaluation	evaluation	NOUN
admet-2772	1	118	of	of	ADP
admet-2772	1	119	admet	admet	PROPN
admet-2772	1	120	properties	property	NOUN
admet-2772	1	121	remains	remain	VERB
admet-2772	1	122	a	a	DET
admet-2772	1	123	critical	critical	ADJ
admet-2772	1	124	bottleneck	bottleneck	NOUN
admet-2772	1	125	in	in	ADP
admet-2772	1	126	drug	drug	NOUN
admet-2772	1	127	discovery	discovery	NOUN
admet-2772	1	128	and	and	CCONJ
admet-2772	1	129	development	development	NOUN
admet-2772	1	130	,	,	PUNCT
admet-2772	1	131	contributing	contribute	VERB
admet-2772	1	132	significantly	significantly	ADV
admet-2772	1	133	to	to	ADP
admet-2772	1	134	the	the	DET
admet-2772	1	135	high	high	ADJ
admet-2772	1	136	attrition	attrition	NOUN
admet-2772	1	137	rate	rate	NOUN
admet-2772	1	138	of	of	ADP
admet-2772	1	139	drug	drug	NOUN
admet-2772	1	140	candidates	candidate	NOUN
admet-2772	1	141	.	.	PUNCT
admet-2772	2	1	traditional	traditional	ADJ
admet-2772	2	2	experimental	experimental	ADJ
admet-2772	2	3	approaches	approach	NOUN
admet-2772	2	4	are	be	AUX
admet-2772	2	5	often	often	ADV
admet-2772	2	6	time	time	NOUN
admet-2772	2	7	-	-	PUNCT
admet-2772	2	8	consuming	consume	VERB
admet-2772	2	9	,	,	PUNCT
admet-2772	2	10	cost	cost	NOUN
admet-2772	2	11	-	-	PUNCT
admet-2772	2	12	intensive	intensive	ADJ
admet-2772	2	13	,	,	PUNCT
admet-2772	2	14	and	and	CCONJ
admet-2772	2	15	limited	limit	VERB
admet-2772	2	16	in	in	ADP
admet-2772	2	17	scalability	scalability	NOUN
admet-2772	2	18	.	.	PUNCT
admet-2772	3	1	this	this	DET
admet-2772	3	2	review	review	NOUN
admet-2772	3	3	aims	aim	VERB
admet-2772	3	4	to	to	PART
admet-2772	3	5	investigate	investigate	VERB
admet-2772	3	6	how	how	SCONJ
admet-2772	3	7	recent	recent	ADJ
admet-2772	3	8	advances	advance	NOUN
admet-2772	3	9	in	in	ADP
admet-2772	3	10	machine	machine	NOUN
admet-2772	3	11	learning	learning	NOUN
admet-2772	3	12	(	(	PUNCT
admet-2772	3	13	ml	ml	NOUN
admet-2772	3	14	)	)	PUNCT
admet-2772	3	15	models	model	NOUN
admet-2772	3	16	are	be	AUX
admet-2772	3	17	revolutionizing	revolutionize	VERB
admet-2772	3	18	admet	admet	ADJ
admet-2772	3	19	prediction	prediction	NOUN
admet-2772	3	20	by	by	ADP
admet-2772	3	21	enhancing	enhance	VERB
admet-2772	3	22	accuracy	accuracy	NOUN
admet-2772	3	23	,	,	PUNCT
admet-2772	3	24	reducing	reduce	VERB
admet-2772	3	25	experimental	experimental	ADJ
admet-2772	3	26	burden	burden	NOUN
admet-2772	3	27	,	,	PUNCT
admet-2772	3	28	and	and	CCONJ
admet-2772	3	29	accelerating	accelerate	VERB
admet-2772	3	30	decision	decision	NOUN
admet-2772	3	31	-	-	PUNCT
admet-2772	3	32	making	making	NOUN
admet-2772	3	33	during	during	ADP
admet-2772	3	34	early	early	ADJ
admet-2772	3	35	-	-	PUNCT
admet-2772	3	36	stage	stage	NOUN
admet-2772	3	37	drug	drug	NOUN
admet-2772	3	38	development	development	NOUN
admet-2772	3	39	.	.	PUNCT
admet-2772	4	1	experimental	experimental	ADJ
admet-2772	4	2	approach	approach	NOUN
admet-2772	4	3	:	:	PUNCT
admet-2772	4	4	this	this	DET
admet-2772	4	5	article	article	NOUN
admet-2772	4	6	systematically	systematically	ADV
admet-2772	4	7	examines	examine	VERB
admet-2772	4	8	the	the	DET
admet-2772	4	9	current	current	ADJ
admet-2772	4	10	landscape	landscape	NOUN
admet-2772	4	11	of	of	ADP
admet-2772	4	12	ml	ml	NOUN
admet-2772	4	13	applications	application	NOUN
admet-2772	4	14	in	in	ADP
admet-2772	4	15	admet	admet	PROPN
admet-2772	4	16	prediction	prediction	NOUN
admet-2772	4	17	,	,	PUNCT
admet-2772	4	18	including	include	VERB
admet-2772	4	19	the	the	DET
admet-2772	4	20	types	type	NOUN
admet-2772	4	21	of	of	ADP
admet-2772	4	22	algorithms	algorithm	NOUN
admet-2772	4	23	employed	employ	VERB
admet-2772	4	24	,	,	PUNCT
admet-2772	4	25	common	common	ADJ
admet-2772	4	26	molecular	molecular	ADJ
admet-2772	4	27	descriptors	descriptor	NOUN
admet-2772	4	28	and	and	CCONJ
admet-2772	4	29	datasets	dataset	NOUN
admet-2772	4	30	used	use	VERB
admet-2772	4	31	,	,	PUNCT
admet-2772	4	32	and	and	CCONJ
admet-2772	4	33	model	model	NOUN
admet-2772	4	34	development	development	NOUN
admet-2772	4	35	workflows	workflow	NOUN
admet-2772	4	36	.	.	PUNCT
admet-2772	5	1	it	it	PRON
admet-2772	5	2	also	also	ADV
admet-2772	5	3	explores	explore	VERB
admet-2772	5	4	public	public	ADJ
admet-2772	5	5	databases	database	NOUN
admet-2772	5	6	,	,	PUNCT
admet-2772	5	7	model	model	NOUN
admet-2772	5	8	evaluation	evaluation	NOUN
admet-2772	5	9	metrics	metric	NOUN
admet-2772	5	10	,	,	PUNCT
admet-2772	5	11	and	and	CCONJ
admet-2772	5	12	regulatory	regulatory	ADJ
admet-2772	5	13	considerations	consideration	NOUN
admet-2772	5	14	relevant	relevant	ADJ
admet-2772	5	15	to	to	ADP
admet-2772	5	16	computational	computational	ADJ
admet-2772	5	17	toxicology	toxicology	NOUN
admet-2772	5	18	.	.	PUNCT
admet-2772	6	1	emphasis	emphasis	NOUN
admet-2772	6	2	is	be	AUX
admet-2772	6	3	placed	place	VERB
admet-2772	6	4	on	on	ADP
admet-2772	6	5	supervised	supervised	ADJ
admet-2772	6	6	and	and	CCONJ
admet-2772	6	7	deep	deep	ADJ
admet-2772	6	8	learning	learning	NOUN
admet-2772	6	9	techniques	technique	NOUN
admet-2772	6	10	,	,	PUNCT
admet-2772	6	11	model	model	NOUN
admet-2772	6	12	validation	validation	NOUN
admet-2772	6	13	strategies	strategy	NOUN
admet-2772	6	14	,	,	PUNCT
admet-2772	6	15	and	and	CCONJ
admet-2772	6	16	the	the	DET
admet-2772	6	17	challenges	challenge	NOUN
admet-2772	6	18	of	of	ADP
admet-2772	6	19	data	datum	NOUN
admet-2772	6	20	imbalance	imbalance	NOUN
admet-2772	6	21	and	and	CCONJ
admet-2772	6	22	model	model	NOUN
admet-2772	6	23	interpretability	interpretability	NOUN
admet-2772	6	24	.	.	PUNCT
admet-2772	7	1	key	key	ADJ
admet-2772	7	2	results	result	NOUN
admet-2772	7	3	:	:	PUNCT
admet-2772	7	4	ml	ml	VERB
admet-2772	7	5	-	-	PUNCT
admet-2772	7	6	based	base	VERB
admet-2772	7	7	models	model	NOUN
admet-2772	7	8	have	have	AUX
admet-2772	7	9	demonstrated	demonstrate	VERB
admet-2772	7	10	significant	significant	ADJ
admet-2772	7	11	promise	promise	NOUN
admet-2772	7	12	in	in	ADP
admet-2772	7	13	predicting	predict	VERB
admet-2772	7	14	key	key	ADJ
admet-2772	7	15	admet	admet	PROPN
admet-2772	7	16	endpoints	endpoint	NOUN
admet-2772	7	17	,	,	PUNCT
admet-2772	7	18	outperforming	outperform	VERB
admet-2772	7	19	some	some	DET
admet-2772	7	20	traditional	traditional	ADJ
admet-2772	7	21	quantitative	quantitative	ADJ
admet-2772	7	22	structure	structure	NOUN
admet-2772	7	23	activity	activity	NOUN
admet-2772	7	24	relationship	relationship	NOUN
admet-2772	7	25	(	(	PUNCT
admet-2772	7	26	qsar	qsar	NOUN
admet-2772	7	27	)	)	PUNCT
admet-2772	7	28	models	model	NOUN
admet-2772	7	29	.	.	PUNCT
admet-2772	8	1	these	these	DET
admet-2772	8	2	approaches	approach	NOUN
admet-2772	8	3	provide	provide	VERB
admet-2772	8	4	rapid	rapid	ADJ
admet-2772	8	5	,	,	PUNCT
admet-2772	8	6	cost	cost	NOUN
admet-2772	8	7	-	-	PUNCT
admet-2772	8	8	effective	effective	ADJ
admet-2772	8	9	,	,	PUNCT
admet-2772	8	10	and	and	CCONJ
admet-2772	8	11	reproducible	reproducible	VERB
admet-2772	8	12	alternatives	alternative	NOUN
admet-2772	8	13	that	that	PRON
admet-2772	8	14	integrate	integrate	VERB
admet-2772	8	15	seamlessly	seamlessly	ADV
admet-2772	8	16	with	with	ADP
admet-2772	8	17	existing	exist	VERB
admet-2772	8	18	drug	drug	NOUN
admet-2772	8	19	discovery	discovery	NOUN
admet-2772	8	20	pipelines	pipeline	NOUN
admet-2772	8	21	.	.	PUNCT
admet-2772	9	1	case	case	NOUN
admet-2772	9	2	studies	study	NOUN
admet-2772	9	3	discussed	discuss	VERB
admet-2772	9	4	in	in	ADP
admet-2772	9	5	this	this	DET
admet-2772	9	6	review	review	NOUN
admet-2772	9	7	illustrate	illustrate	VERB
admet-2772	9	8	the	the	DET
admet-2772	9	9	successful	successful	ADJ
admet-2772	9	10	deployment	deployment	NOUN
admet-2772	9	11	of	of	ADP
admet-2772	9	12	ml	ml	NOUN
admet-2772	9	13	models	model	NOUN
admet-2772	9	14	for	for	ADP
admet-2772	9	15	solubility	solubility	NOUN
admet-2772	9	16	,	,	PUNCT
admet-2772	9	17	permeability	permeability	NOUN
admet-2772	9	18	,	,	PUNCT
admet-2772	9	19	metabolism	metabolism	NOUN
admet-2772	9	20	,	,	PUNCT
admet-2772	9	21	and	and	CCONJ
admet-2772	9	22	toxicity	toxicity	NOUN
admet-2772	9	23	predictions	prediction	NOUN
admet-2772	9	24	.	.	PUNCT
admet-2772	10	1	conclusion	conclusion	NOUN
admet-2772	10	2	:	:	PUNCT
admet-2772	10	3	machine	machine	NOUN
admet-2772	10	4	learning	learning	NOUN
admet-2772	10	5	has	have	AUX
admet-2772	10	6	emerged	emerge	VERB
admet-2772	10	7	as	as	ADP
admet-2772	10	8	a	a	DET
admet-2772	10	9	transformative	transformative	ADJ
admet-2772	10	10	tool	tool	NOUN
admet-2772	10	11	in	in	ADP
admet-2772	10	12	admet	admet	PROPN
admet-2772	10	13	prediction	prediction	NOUN
admet-2772	10	14	,	,	PUNCT
admet-2772	10	15	offering	offer	VERB
admet-2772	10	16	new	new	ADJ
admet-2772	10	17	opportunities	opportunity	NOUN
admet-2772	10	18	for	for	ADP
admet-2772	10	19	early	early	ADJ
admet-2772	10	20	risk	risk	NOUN
admet-2772	10	21	assessment	assessment	NOUN
admet-2772	10	22	and	and	CCONJ
admet-2772	10	23	compound	compound	NOUN
admet-2772	10	24	prioritization	prioritization	NOUN
admet-2772	10	25	.	.	PUNCT
admet-2772	11	1	while	while	SCONJ
admet-2772	11	2	challenges	challenge	NOUN
admet-2772	11	3	such	such	ADJ
admet-2772	11	4	as	as	ADP
admet-2772	11	5	data	datum	NOUN
admet-2772	11	6	quality	quality	NOUN
admet-2772	11	7	,	,	PUNCT
admet-2772	11	8	algorithm	algorithm	NOUN
admet-2772	11	9	transparency	transparency	NOUN
admet-2772	11	10	,	,	PUNCT
admet-2772	11	11	and	and	CCONJ
admet-2772	11	12	regulatory	regulatory	ADJ
admet-2772	11	13	acceptance	acceptance	NOUN
admet-2772	11	14	persist	persist	NOUN
admet-2772	11	15	,	,	PUNCT
admet-2772	11	16	continued	continued	ADJ
admet-2772	11	17	integration	integration	NOUN
admet-2772	11	18	of	of	ADP
admet-2772	11	19	ml	ml	NOUN
admet-2772	11	20	with	with	ADP
admet-2772	11	21	experimental	experimental	ADJ
admet-2772	11	22	pharmacology	pharmacology	NOUN
admet-2772	11	23	holds	hold	VERB
admet-2772	11	24	the	the	DET
admet-2772	11	25	potential	potential	NOUN
admet-2772	11	26	to	to	PART
admet-2772	11	27	substantially	substantially	ADV
admet-2772	11	28	improve	improve	VERB
admet-2772	11	29	drug	drug	NOUN
admet-2772	11	30	development	development	NOUN
admet-2772	11	31	efficiency	efficiency	NOUN
admet-2772	11	32	and	and	CCONJ
admet-2772	11	33	reduce	reduce	VERB
admet-2772	11	34	late	late	ADJ
admet-2772	11	35	-	-	PUNCT
admet-2772	11	36	stage	stage	NOUN
admet-2772	11	37	failures	failure	NOUN
admet-2772	11	38	.	.	PUNCT
admet-2772	12	1	©	©	X
admet-2772	12	2	2025	2025	NUM
admet-2772	12	3	by	by	ADP
admet-2772	12	4	the	the	DET
admet-2772	12	5	authors	author	NOUN
admet-2772	12	6	.	.	PUNCT
admet-2772	13	1	this	this	DET
admet-2772	13	2	article	article	NOUN
admet-2772	13	3	is	be	AUX
admet-2772	13	4	an	an	DET
admet-2772	13	5	open	open	ADJ
admet-2772	13	6	-	-	PUNCT
admet-2772	13	7	access	access	NOUN
admet-2772	13	8	article	article	NOUN
admet-2772	13	9	distributed	distribute	VERB
admet-2772	13	10	under	under	ADP
admet-2772	13	11	the	the	DET
admet-2772	13	12	terms	term	NOUN
admet-2772	13	13	and	and	CCONJ
admet-2772	13	14	conditions	condition	NOUN
admet-2772	13	15	of	of	ADP
admet-2772	13	16	the	the	DET
admet-2772	13	17	creative	creative	ADJ
admet-2772	13	18	commons	common	NOUN
admet-2772	13	19	attribution	attribution	NOUN
admet-2772	13	20	license	license	NOUN
admet-2772	13	21	(	(	PUNCT
admet-2772	13	22	http://creativecommons.org/licenses/by/4.0/	http://creativecommons.org/licenses/by/4.0/	PROPN
admet-2772	13	23	)	)	PUNCT
admet-2772	13	24	.	.	PUNCT
admet-2772	14	1	keywords	keyword	NOUN
admet-2772	14	2	admet	admet	PROPN
admet-2772	14	3	prediction	prediction	PROPN
admet-2772	14	4	,	,	PUNCT
admet-2772	14	5	ai	ai	VERB
admet-2772	14	6	/	/	SYM
admet-2772	14	7	ml	ml	NOUN
admet-2772	14	8	,	,	PUNCT
admet-2772	14	9	pharmacokinetics	pharmacokinetic	NOUN
admet-2772	14	10	,	,	PUNCT
admet-2772	14	11	computational	computational	ADJ
admet-2772	14	12	toxicology	toxicology	NOUN
admet-2772	14	13	,	,	PUNCT
admet-2772	14	14	molecular	molecular	ADJ
admet-2772	14	15	descriptors	descriptor	NOUN
admet-2772	14	16	introduction	introduction	VERB
admet-2772	14	17	the	the	DET
admet-2772	14	18	typical	typical	ADJ
admet-2772	14	19	timeframe	timeframe	NOUN
admet-2772	14	20	for	for	ADP
admet-2772	14	21	drug	drug	NOUN
admet-2772	14	22	discovery	discovery	NOUN
admet-2772	14	23	and	and	CCONJ
admet-2772	14	24	development	development	NOUN
admet-2772	14	25	of	of	ADP
admet-2772	14	26	a	a	DET
admet-2772	14	27	new	new	ADJ
admet-2772	14	28	drug	drug	NOUN
admet-2772	14	29	spans	span	NOUN
admet-2772	14	30	from	from	ADP
admet-2772	14	31	10	10	NUM
admet-2772	14	32	to	to	PART
admet-2772	14	33	15	15	NUM
admet-2772	14	34	years	year	NOUN
admet-2772	14	35	of	of	ADP
admet-2772	14	36	rigorous	rigorous	ADJ
admet-2772	14	37	research	research	NOUN
admet-2772	14	38	and	and	CCONJ
admet-2772	14	39	testing	testing	NOUN
admet-2772	14	40	[	[	X
admet-2772	14	41	1	1	NUM
admet-2772	14	42	]	]	PUNCT
admet-2772	14	43	.	.	PUNCT
admet-2772	15	1	the	the	DET
admet-2772	15	2	sheer	sheer	ADJ
admet-2772	15	3	volume	volume	NOUN
admet-2772	15	4	of	of	ADP
admet-2772	15	5	potential	potential	ADJ
admet-2772	15	6	drug	drug	NOUN
admet-2772	15	7	candidates	candidate	NOUN
admet-2772	15	8	renders	render	VERB
admet-2772	15	9	traditional	traditional	ADJ
admet-2772	15	10	wet	wet	ADJ
admet-2772	15	11	lab	lab	NOUN
admet-2772	15	12	experiments	experiment	NOUN
admet-2772	15	13	impractical	impractical	ADJ
admet-2772	15	14	.	.	PUNCT
admet-2772	16	1	however	however	ADV
admet-2772	16	2	,	,	PUNCT
admet-2772	16	3	advancements	advancement	NOUN
admet-2772	16	4	in	in	ADP
admet-2772	16	5	data	datum	NOUN
admet-2772	16	6	science	science	NOUN
admet-2772	16	7	over	over	ADP
admet-2772	16	8	the	the	DET
admet-2772	16	9	past	past	ADJ
admet-2772	16	10	decade	decade	NOUN
admet-2772	16	11	,	,	PUNCT
admet-2772	16	12	coupled	couple	VERB
admet-2772	16	13	with	with	ADP
admet-2772	16	14	enhanced	enhanced	ADJ
admet-2772	16	15	computational	computational	ADJ
admet-2772	16	16	capabilities	capability	NOUN
admet-2772	16	17	,	,	PUNCT
admet-2772	16	18	have	have	AUX
admet-2772	16	19	paved	pave	VERB
admet-2772	16	20	the	the	DET
admet-2772	16	21	way	way	NOUN
admet-2772	16	22	for	for	ADP
admet-2772	16	23	in	in	ADP
admet-2772	16	24	silico	silico	NOUN
admet-2772	16	25	methodologies	methodology	NOUN
admet-2772	16	26	for	for	ADP
admet-2772	16	27	screening	screen	VERB
admet-2772	16	28	extensive	extensive	ADJ
admet-2772	16	29	drug	drug	NOUN
admet-2772	16	30	libraries	library	NOUN
admet-2772	16	31	.	.	PUNCT
admet-2772	17	1	this	this	DET
admet-2772	17	2	preliminary	preliminary	ADJ
admet-2772	17	3	step	step	NOUN
admet-2772	17	4	,	,	PUNCT
admet-2772	17	5	preceding	precede	VERB
admet-2772	17	6	preclinical	preclinical	ADJ
admet-2772	17	7	studies	study	NOUN
admet-2772	17	8	,	,	PUNCT
admet-2772	17	9	significantly	significantly	ADV
admet-2772	17	10	reduces	reduce	VERB
admet-2772	17	11	costs	cost	NOUN
admet-2772	17	12	and	and	CCONJ
admet-2772	17	13	expands	expand	VERB
admet-2772	17	14	the	the	DET
admet-2772	17	15	scope	scope	NOUN
admet-2772	17	16	of	of	ADP
admet-2772	17	17	drug	drug	NOUN
admet-2772	17	18	discovery	discovery	NOUN
admet-2772	17	19	efforts	effort	NOUN
admet-2772	17	20	[	[	X
admet-2772	17	21	2	2	NUM
admet-2772	17	22	]	]	PUNCT
admet-2772	17	23	.	.	PUNCT
admet-2772	18	1	machine	machine	NOUN
admet-2772	18	2	learning	learning	NOUN
admet-2772	18	3	(	(	PUNCT
admet-2772	18	4	ml	ml	NOUN
admet-2772	18	5	)	)	PUNCT
admet-2772	18	6	is	be	AUX
admet-2772	18	7	a	a	DET
admet-2772	18	8	method	method	NOUN
admet-2772	18	9	of	of	ADP
admet-2772	18	10	data	datum	NOUN
admet-2772	18	11	analysis	analysis	NOUN
admet-2772	18	12	involving	involve	VERB
admet-2772	18	13	the	the	PRON
admet-2772	18	14	of	of	ADP
admet-2772	18	15	new	new	ADJ
admet-2772	18	16	algorithms	algorithm	NOUN
admet-2772	18	17	and	and	CCONJ
admet-2772	18	18	models	model	NOUN
admet-2772	18	19	capable	capable	ADJ
admet-2772	18	20	of	of	ADP
admet-2772	18	21	interpreting	interpret	VERB
admet-2772	18	22	a	a	DET
admet-2772	18	23	multitude	multitude	NOUN
admet-2772	18	24	of	of	ADP
admet-2772	18	25	data	datum	NOUN
admet-2772	18	26	.	.	PUNCT
admet-2772	19	1	within	within	ADP
admet-2772	19	2	this	this	DET
admet-2772	19	3	framework	framework	NOUN
admet-2772	19	4	,	,	PUNCT
admet-2772	19	5	ml	ml	AUX
admet-2772	19	6	techniques	technique	NOUN
admet-2772	19	7	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	19	8	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	19	9	http://www.pub.iapchem.org/ojs/index.php/admet/index	http://www.pub.iapchem.org/ojs/index.php/admet/index	NOUN
admet-2772	19	10	mailto:srinivasm@acubiosys.com	mailto:srinivasm@acubiosys.com	X
admet-2772	20	1	http://creativecommons.org/licenses/by/4.0/	http://creativecommons.org/licenses/by/4.0/	PROPN
admet-2772	20	2	m.	m.	PROPN
admet-2772	20	3	venkataraman	venkataraman	PROPN
admet-2772	20	4	et	et	PROPN
admet-2772	20	5	al	al	PROPN
admet-2772	20	6	.	.	PROPN
admet-2772	20	7	admet	admet	PROPN
admet-2772	20	8	&	&	CCONJ
admet-2772	20	9	dmpk	dmpk	PROPN
admet-2772	20	10	13(3	13(3	NUM
admet-2772	20	11	)	)	PUNCT
admet-2772	20	12	(	(	PUNCT
admet-2772	20	13	2025	2025	NUM
admet-2772	20	14	)	)	PUNCT
admet-2772	20	15	2772	2772	NUM
admet-2772	20	16	2	2	NUM
admet-2772	20	17	have	have	AUX
admet-2772	20	18	emerged	emerge	VERB
admet-2772	20	19	as	as	ADP
admet-2772	20	20	pivotal	pivotal	ADJ
admet-2772	20	21	tools	tool	NOUN
admet-2772	20	22	in	in	ADP
admet-2772	20	23	the	the	DET
admet-2772	20	24	pharmaceutical	pharmaceutical	ADJ
admet-2772	20	25	drug	drug	NOUN
admet-2772	20	26	discovery	discovery	NOUN
admet-2772	20	27	and	and	CCONJ
admet-2772	20	28	development	development	NOUN
admet-2772	20	29	field	field	NOUN
admet-2772	20	30	[	[	X
admet-2772	20	31	3	3	NUM
admet-2772	20	32	]	]	PUNCT
admet-2772	20	33	.	.	PUNCT
admet-2772	21	1	recent	recent	ADJ
admet-2772	21	2	progress	progress	NOUN
admet-2772	21	3	in	in	ADP
admet-2772	21	4	ml	ml	ADP
admet-2772	21	5	algorithms	algorithm	NOUN
admet-2772	21	6	,	,	PUNCT
admet-2772	21	7	coupled	couple	VERB
admet-2772	21	8	with	with	ADP
admet-2772	21	9	the	the	DET
admet-2772	21	10	accessibility	accessibility	NOUN
admet-2772	21	11	of	of	ADP
admet-2772	21	12	extensive	extensive	ADJ
admet-2772	21	13	proprietary	proprietary	ADJ
admet-2772	21	14	and	and	CCONJ
admet-2772	21	15	public	public	ADJ
admet-2772	21	16	absorption	absorption	NOUN
admet-2772	21	17	,	,	PUNCT
admet-2772	21	18	distribution	distribution	NOUN
admet-2772	21	19	,	,	PUNCT
admet-2772	21	20	metabolism	metabolism	NOUN
admet-2772	21	21	,	,	PUNCT
admet-2772	21	22	excretion	excretion	NOUN
admet-2772	21	23	and	and	CCONJ
admet-2772	21	24	toxicity	toxicity	NOUN
admet-2772	21	25	(	(	PUNCT
admet-2772	21	26	admet	admet	NOUN
admet-2772	21	27	)	)	PUNCT
admet-2772	21	28	datasets	dataset	NOUN
admet-2772	21	29	,	,	PUNCT
admet-2772	21	30	has	have	AUX
admet-2772	21	31	sparked	spark	VERB
admet-2772	21	32	enthusiasm	enthusiasm	NOUN
admet-2772	21	33	among	among	ADP
admet-2772	21	34	academic	academic	ADJ
admet-2772	21	35	and	and	CCONJ
admet-2772	21	36	pharmaceutical	pharmaceutical	NOUN
admet-2772	21	37	science	science	NOUN
admet-2772	21	38	circles	circle	NOUN
admet-2772	21	39	in	in	ADP
admet-2772	21	40	predicting	predict	VERB
admet-2772	21	41	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	21	42	and	and	CCONJ
admet-2772	21	43	physicochemical	physicochemical	ADJ
admet-2772	21	44	endpoints	endpoint	NOUN
admet-2772	21	45	in	in	ADP
admet-2772	21	46	early	early	ADJ
admet-2772	21	47	drug	drug	NOUN
admet-2772	21	48	discovery	discovery	NOUN
admet-2772	21	49	[	[	X
admet-2772	21	50	4	4	NUM
admet-2772	21	51	]	]	PUNCT
admet-2772	21	52	.	.	PUNCT
admet-2772	22	1	it	it	PRON
admet-2772	22	2	has	have	AUX
admet-2772	22	3	been	be	AUX
admet-2772	22	4	widely	widely	ADV
admet-2772	22	5	recognized	recognize	VERB
admet-2772	22	6	that	that	SCONJ
admet-2772	22	7	admet	admet	PROPN
admet-2772	22	8	should	should	AUX
admet-2772	22	9	be	be	AUX
admet-2772	22	10	evaluated	evaluate	VERB
admet-2772	22	11	as	as	ADV
admet-2772	22	12	early	early	ADV
admet-2772	22	13	as	as	ADP
admet-2772	22	14	possible	possible	ADJ
admet-2772	22	15	[	[	X
admet-2772	22	16	5	5	NUM
admet-2772	22	17	]	]	PUNCT
admet-2772	22	18	.	.	PUNCT
admet-2772	23	1	figure	figure	NOUN
admet-2772	23	2	1	1	NUM
admet-2772	23	3	illustrates	illustrate	VERB
admet-2772	23	4	the	the	DET
admet-2772	23	5	schematic	schematic	ADJ
admet-2772	23	6	representation	representation	NOUN
admet-2772	23	7	of	of	ADP
admet-2772	23	8	the	the	DET
admet-2772	23	9	adme	adme	NOUN
admet-2772	23	10	process	process	NOUN
admet-2772	23	11	for	for	ADP
admet-2772	23	12	orally	orally	ADV
admet-2772	23	13	administered	administer	VERB
admet-2772	23	14	drugs	drug	NOUN
admet-2772	23	15	,	,	PUNCT
admet-2772	23	16	illustrating	illustrate	VERB
admet-2772	23	17	key	key	ADJ
admet-2772	23	18	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	23	19	phases	phase	NOUN
admet-2772	23	20	including	include	VERB
admet-2772	23	21	absorption	absorption	NOUN
admet-2772	23	22	in	in	ADP
admet-2772	23	23	the	the	DET
admet-2772	23	24	gastrointestinal	gastrointestinal	ADJ
admet-2772	23	25	tract	tract	NOUN
admet-2772	23	26	,	,	PUNCT
admet-2772	23	27	metabolism	metabolism	NOUN
admet-2772	23	28	in	in	ADP
admet-2772	23	29	the	the	DET
admet-2772	23	30	liver	liver	NOUN
admet-2772	23	31	,	,	PUNCT
admet-2772	23	32	distribution	distribution	NOUN
admet-2772	23	33	via	via	ADP
admet-2772	23	34	systemic	systemic	ADJ
admet-2772	23	35	circulation	circulation	NOUN
admet-2772	23	36	,	,	PUNCT
admet-2772	23	37	and	and	CCONJ
admet-2772	23	38	excretion	excretion	VERB
admet-2772	23	39	through	through	ADP
admet-2772	23	40	renal	renal	ADJ
admet-2772	23	41	clearance	clearance	NOUN
admet-2772	23	42	.	.	PUNCT
admet-2772	24	1	in	in	ADP
admet-2772	24	2	silico	silico	NOUN
admet-2772	24	3	adme	adme	NOUN
admet-2772	24	4	-	-	PUNCT
admet-2772	24	5	toxicity	toxicity	NOUN
admet-2772	24	6	(	(	PUNCT
admet-2772	24	7	admetox	admetox	ADJ
admet-2772	24	8	)	)	PUNCT
admet-2772	24	9	evaluation	evaluation	NOUN
admet-2772	24	10	models	model	NOUN
admet-2772	24	11	have	have	AUX
admet-2772	24	12	been	be	AUX
admet-2772	24	13	developed	develop	VERB
admet-2772	24	14	as	as	ADP
admet-2772	24	15	an	an	DET
admet-2772	24	16	additional	additional	ADJ
admet-2772	24	17	tool	tool	NOUN
admet-2772	24	18	to	to	PART
admet-2772	24	19	assist	assist	VERB
admet-2772	24	20	medicinal	medicinal	ADJ
admet-2772	24	21	chemists	chemist	NOUN
admet-2772	24	22	in	in	ADP
admet-2772	24	23	the	the	DET
admet-2772	24	24	design	design	NOUN
admet-2772	24	25	and	and	CCONJ
admet-2772	24	26	optimization	optimization	NOUN
admet-2772	24	27	of	of	ADP
admet-2772	24	28	leads	lead	NOUN
admet-2772	24	29	[	[	X
admet-2772	24	30	6	6	NUM
admet-2772	24	31	]	]	PUNCT
admet-2772	24	32	.	.	PUNCT
admet-2772	25	1	the	the	DET
admet-2772	25	2	majority	majority	NOUN
admet-2772	25	3	of	of	ADP
admet-2772	25	4	the	the	DET
admet-2772	25	5	problems	problem	NOUN
admet-2772	25	6	arising	arise	VERB
admet-2772	25	7	during	during	ADP
admet-2772	25	8	the	the	DET
admet-2772	25	9	process	process	NOUN
admet-2772	25	10	of	of	ADP
admet-2772	25	11	drug	drug	NOUN
admet-2772	25	12	discovery	discovery	NOUN
admet-2772	25	13	include	include	VERB
admet-2772	25	14	unfavourable	unfavourable	ADJ
admet-2772	25	15	admet	admet	NOUN
admet-2772	25	16	properties	property	NOUN
admet-2772	25	17	,	,	PUNCT
admet-2772	25	18	which	which	PRON
admet-2772	25	19	have	have	AUX
admet-2772	25	20	been	be	AUX
admet-2772	25	21	known	know	VERB
admet-2772	25	22	to	to	PART
admet-2772	25	23	be	be	AUX
admet-2772	25	24	a	a	DET
admet-2772	25	25	major	major	ADJ
admet-2772	25	26	cause	cause	NOUN
admet-2772	25	27	of	of	ADP
admet-2772	25	28	failure	failure	NOUN
admet-2772	25	29	of	of	ADP
admet-2772	25	30	the	the	DET
admet-2772	25	31	potential	potential	ADJ
admet-2772	25	32	molecules	molecule	NOUN
admet-2772	25	33	in	in	ADP
admet-2772	25	34	the	the	DET
admet-2772	25	35	drug	drug	NOUN
admet-2772	25	36	development	development	NOUN
admet-2772	25	37	pipeline	pipeline	NOUN
admet-2772	25	38	,	,	PUNCT
admet-2772	25	39	contributing	contribute	VERB
admet-2772	25	40	to	to	ADP
admet-2772	25	41	large	large	ADJ
admet-2772	25	42	consumption	consumption	NOUN
admet-2772	25	43	of	of	ADP
admet-2772	25	44	time	time	NOUN
admet-2772	25	45	,	,	PUNCT
admet-2772	25	46	capital	capital	NOUN
admet-2772	25	47	and	and	CCONJ
admet-2772	25	48	human	human	ADJ
admet-2772	25	49	resources	resource	NOUN
admet-2772	25	50	[	[	X
admet-2772	25	51	7	7	NUM
admet-2772	25	52	]	]	PUNCT
admet-2772	25	53	.	.	PUNCT
admet-2772	26	1	figure	figure	NOUN
admet-2772	26	2	1	1	NUM
admet-2772	26	3	.	.	PUNCT
admet-2772	27	1	this	this	DET
admet-2772	27	2	figure	figure	NOUN
admet-2772	27	3	depicts	depict	VERB
admet-2772	27	4	the	the	DET
admet-2772	27	5	absorption	absorption	NOUN
admet-2772	27	6	,	,	PUNCT
admet-2772	27	7	distribution	distribution	NOUN
admet-2772	27	8	,	,	PUNCT
admet-2772	27	9	metabolism	metabolism	NOUN
admet-2772	27	10	,	,	PUNCT
admet-2772	27	11	and	and	CCONJ
admet-2772	27	12	excretion	excretion	NOUN
admet-2772	27	13	(	(	PUNCT
admet-2772	27	14	adme	adme	NOUN
admet-2772	27	15	)	)	PUNCT
admet-2772	27	16	process	process	NOUN
admet-2772	27	17	for	for	ADP
admet-2772	27	18	drugs	drug	NOUN
admet-2772	27	19	administered	administer	VERB
admet-2772	27	20	orally	orally	ADV
admet-2772	27	21	.	.	PUNCT
admet-2772	28	1	when	when	SCONJ
admet-2772	28	2	a	a	DET
admet-2772	28	3	tablet	tablet	NOUN
admet-2772	28	4	or	or	CCONJ
admet-2772	28	5	capsule	capsule	NOUN
admet-2772	28	6	is	be	AUX
admet-2772	28	7	ingested	ingest	VERB
admet-2772	28	8	,	,	PUNCT
admet-2772	28	9	it	it	PRON
admet-2772	28	10	disintegrates	disintegrate	VERB
admet-2772	28	11	in	in	ADP
admet-2772	28	12	the	the	DET
admet-2772	28	13	gastrointestinal	gastrointestinal	ADJ
admet-2772	28	14	(	(	PUNCT
admet-2772	28	15	gi	gi	INTJ
admet-2772	28	16	)	)	PUNCT
admet-2772	28	17	tract	tract	NOUN
admet-2772	28	18	,	,	PUNCT
admet-2772	28	19	releasing	release	VERB
admet-2772	28	20	drug	drug	NOUN
admet-2772	28	21	molecules	molecule	NOUN
admet-2772	28	22	.	.	PUNCT
admet-2772	29	1	these	these	DET
admet-2772	29	2	molecules	molecule	NOUN
admet-2772	29	3	either	either	CCONJ
admet-2772	29	4	dissolve	dissolve	VERB
admet-2772	29	5	for	for	ADP
admet-2772	29	6	absorption	absorption	NOUN
admet-2772	29	7	or	or	CCONJ
admet-2772	29	8	remain	remain	VERB
admet-2772	29	9	in	in	ADP
admet-2772	29	10	a	a	DET
admet-2772	29	11	precipitated	precipitate	VERB
admet-2772	29	12	state	state	NOUN
admet-2772	29	13	,	,	PUNCT
admet-2772	29	14	eventually	eventually	ADV
admet-2772	29	15	being	be	AUX
admet-2772	29	16	excreted	excrete	VERB
admet-2772	29	17	.	.	PUNCT
admet-2772	30	1	absorbed	absorb	VERB
admet-2772	30	2	drug	drug	NOUN
admet-2772	30	3	molecules	molecule	NOUN
admet-2772	30	4	must	must	AUX
admet-2772	30	5	cross	cross	VERB
admet-2772	30	6	the	the	DET
admet-2772	30	7	gut	gut	NOUN
admet-2772	30	8	wall	wall	NOUN
admet-2772	30	9	,	,	PUNCT
admet-2772	30	10	where	where	SCONJ
admet-2772	30	11	they	they	PRON
admet-2772	30	12	may	may	AUX
admet-2772	30	13	be	be	AUX
admet-2772	30	14	transported	transport	VERB
admet-2772	30	15	back	back	ADV
admet-2772	30	16	into	into	ADP
admet-2772	30	17	the	the	DET
admet-2772	30	18	intestinal	intestinal	ADJ
admet-2772	30	19	lumen	luman	NOUN
admet-2772	30	20	or	or	CCONJ
admet-2772	30	21	metabolized	metabolize	VERB
admet-2772	30	22	by	by	ADP
admet-2772	30	23	enzymes	enzyme	NOUN
admet-2772	30	24	.	.	PUNCT
admet-2772	31	1	those	those	PRON
admet-2772	31	2	that	that	PRON
admet-2772	31	3	successfully	successfully	ADV
admet-2772	31	4	traverse	traverse	VERB
admet-2772	31	5	the	the	DET
admet-2772	31	6	gut	gut	NOUN
admet-2772	31	7	barrier	barrier	NOUN
admet-2772	31	8	enter	enter	VERB
admet-2772	31	9	the	the	DET
admet-2772	31	10	liver	liver	NOUN
admet-2772	31	11	via	via	ADP
admet-2772	31	12	the	the	DET
admet-2772	31	13	portal	portal	ADJ
admet-2772	31	14	circulation	circulation	NOUN
admet-2772	31	15	.	.	PUNCT
admet-2772	32	1	the	the	DET
admet-2772	32	2	liver	liver	NOUN
admet-2772	32	3	plays	play	VERB
admet-2772	32	4	a	a	DET
admet-2772	32	5	crucial	crucial	ADJ
admet-2772	32	6	role	role	NOUN
admet-2772	32	7	in	in	ADP
admet-2772	32	8	drug	drug	NOUN
admet-2772	32	9	metabolism	metabolism	NOUN
admet-2772	32	10	,	,	PUNCT
admet-2772	32	11	utilizing	utilize	VERB
admet-2772	32	12	phase	phase	NOUN
admet-2772	32	13	i	i	PRON
admet-2772	32	14	(	(	PUNCT
admet-2772	32	15	modification	modification	NOUN
admet-2772	32	16	)	)	PUNCT
admet-2772	32	17	and	and	CCONJ
admet-2772	32	18	phase	phase	NOUN
admet-2772	32	19	ii	ii	PROPN
admet-2772	32	20	(	(	PUNCT
admet-2772	32	21	conjugation	conjugation	NOUN
admet-2772	32	22	)	)	PUNCT
admet-2772	32	23	enzymatic	enzymatic	ADJ
admet-2772	32	24	reactions	reaction	NOUN
admet-2772	32	25	to	to	PART
admet-2772	32	26	increase	increase	VERB
admet-2772	32	27	the	the	DET
admet-2772	32	28	hydrophilicity	hydrophilicity	NOUN
admet-2772	32	29	of	of	ADP
admet-2772	32	30	xenobiotics	xenobiotic	NOUN
admet-2772	32	31	,	,	PUNCT
admet-2772	32	32	facilitating	facilitate	VERB
admet-2772	32	33	their	their	PRON
admet-2772	32	34	elimination	elimination	NOUN
admet-2772	32	35	through	through	ADP
admet-2772	32	36	the	the	DET
admet-2772	32	37	kidneys	kidney	NOUN
admet-2772	32	38	.	.	PUNCT
admet-2772	33	1	drugs	drug	NOUN
admet-2772	33	2	that	that	PRON
admet-2772	33	3	escape	escape	VERB
admet-2772	33	4	metabolism	metabolism	NOUN
admet-2772	33	5	enter	enter	VERB
admet-2772	33	6	systemic	systemic	ADJ
admet-2772	33	7	circulation	circulation	NOUN
admet-2772	33	8	,	,	PUNCT
admet-2772	33	9	though	though	SCONJ
admet-2772	33	10	a	a	DET
admet-2772	33	11	portion	portion	NOUN
admet-2772	33	12	binds	bind	VERB
admet-2772	33	13	to	to	ADP
admet-2772	33	14	plasma	plasma	NOUN
admet-2772	33	15	proteins	protein	NOUN
admet-2772	33	16	,	,	PUNCT
admet-2772	33	17	limiting	limit	VERB
admet-2772	33	18	their	their	PRON
admet-2772	33	19	bioavailability	bioavailability	NOUN
admet-2772	33	20	.	.	PUNCT
admet-2772	34	1	only	only	ADV
admet-2772	34	2	the	the	DET
admet-2772	34	3	free	free	ADJ
admet-2772	34	4	,	,	PUNCT
admet-2772	34	5	unbound	unbound	NOUN
admet-2772	34	6	drug	drug	NOUN
admet-2772	34	7	and	and	CCONJ
admet-2772	34	8	its	its	PRON
admet-2772	34	9	metabolites	metabolite	NOUN
admet-2772	34	10	can	can	AUX
admet-2772	34	11	reach	reach	VERB
admet-2772	34	12	target	target	NOUN
admet-2772	34	13	cells	cell	NOUN
admet-2772	34	14	and	and	CCONJ
admet-2772	34	15	interact	interact	VERB
admet-2772	34	16	with	with	ADP
admet-2772	34	17	biomolecules	biomolecule	NOUN
admet-2772	34	18	to	to	PART
admet-2772	34	19	exert	exert	VERB
admet-2772	34	20	therapeutic	therapeutic	ADJ
admet-2772	34	21	effects	effect	NOUN
admet-2772	34	22	.	.	PUNCT
admet-2772	35	1	meanwhile	meanwhile	ADV
admet-2772	35	2	,	,	PUNCT
admet-2772	35	3	some	some	DET
admet-2772	35	4	drug	drug	NOUN
admet-2772	35	5	molecules	molecule	NOUN
admet-2772	35	6	are	be	AUX
admet-2772	35	7	rapidly	rapidly	ADV
admet-2772	35	8	cleared	clear	VERB
admet-2772	35	9	by	by	ADP
admet-2772	35	10	the	the	DET
admet-2772	35	11	kidneys	kidney	NOUN
admet-2772	35	12	.	.	PUNCT
admet-2772	36	1	the	the	DET
admet-2772	36	2	drug	drug	NOUN
admet-2772	36	3	’s	’s	PART
admet-2772	36	4	efficacy	efficacy	NOUN
admet-2772	36	5	is	be	AUX
admet-2772	36	6	determined	determine	VERB
admet-2772	36	7	by	by	ADP
admet-2772	36	8	its	its	PRON
admet-2772	36	9	ability	ability	NOUN
admet-2772	36	10	to	to	PART
admet-2772	36	11	reach	reach	VERB
admet-2772	36	12	and	and	CCONJ
admet-2772	36	13	maintain	maintain	VERB
admet-2772	36	14	an	an	DET
admet-2772	36	15	optimal	optimal	ADJ
admet-2772	36	16	concentration	concentration	NOUN
admet-2772	36	17	at	at	ADP
admet-2772	36	18	the	the	DET
admet-2772	36	19	site	site	NOUN
admet-2772	36	20	of	of	ADP
admet-2772	36	21	action	action	NOUN
admet-2772	36	22	while	while	SCONJ
admet-2772	36	23	navigating	navigate	VERB
admet-2772	36	24	these	these	DET
admet-2772	36	25	physiological	physiological	ADJ
admet-2772	36	26	processes	process	NOUN
admet-2772	36	27	(	(	PUNCT
admet-2772	36	28	courtesy	courtesy	NOUN
admet-2772	36	29	:	:	PUNCT
admet-2772	36	30	nih	nih	PROPN
admet-2772	36	31	bioart	bioart	PROPN
admet-2772	36	32	;	;	PUNCT
admet-2772	36	33	bioicons	bioicon	NOUN
admet-2772	36	34	)	)	PUNCT
admet-2772	36	35	.	.	PUNCT
admet-2772	37	1	this	this	PRON
admet-2772	37	2	has	have	AUX
admet-2772	37	3	increased	increase	VERB
admet-2772	37	4	the	the	DET
admet-2772	37	5	interest	interest	NOUN
admet-2772	37	6	in	in	ADP
admet-2772	37	7	the	the	DET
admet-2772	37	8	early	early	ADJ
admet-2772	37	9	-	-	PUNCT
admet-2772	37	10	stage	stage	NOUN
admet-2772	37	11	prediction	prediction	NOUN
admet-2772	37	12	of	of	ADP
admet-2772	37	13	admet	admet	NOUN
admet-2772	37	14	properties	property	NOUN
admet-2772	37	15	of	of	ADP
admet-2772	37	16	drug	drug	NOUN
admet-2772	37	17	candidates	candidate	NOUN
admet-2772	37	18	so	so	SCONJ
admet-2772	37	19	that	that	SCONJ
admet-2772	37	20	the	the	DET
admet-2772	37	21	success	success	NOUN
admet-2772	37	22	rate	rate	NOUN
admet-2772	37	23	of	of	ADP
admet-2772	37	24	a	a	DET
admet-2772	37	25	compound	compound	NOUN
admet-2772	37	26	reaching	reach	VERB
admet-2772	37	27	the	the	DET
admet-2772	37	28	later	later	ADJ
admet-2772	37	29	stages	stage	NOUN
admet-2772	37	30	of	of	ADP
admet-2772	37	31	drug	drug	NOUN
admet-2772	37	32	development	development	NOUN
admet-2772	37	33	can	can	AUX
admet-2772	37	34	be	be	AUX
admet-2772	37	35	enhanced	enhance	VERB
admet-2772	37	36	.	.	PUNCT
admet-2772	38	1	ml	ml	AUX
admet-2772	38	2	has	have	AUX
admet-2772	38	3	admet	admet	PROPN
admet-2772	38	4	&	&	CCONJ
admet-2772	38	5	dmpk	dmpk	PROPN
admet-2772	38	6	13(3	13(3	NUM
admet-2772	38	7	)	)	PUNCT
admet-2772	38	8	(	(	PUNCT
admet-2772	38	9	2025	2025	NUM
admet-2772	38	10	)	)	PUNCT
admet-2772	38	11	2772	2772	NUM
admet-2772	38	12	machine	machine	NOUN
admet-2772	38	13	learning	learning	NOUN
admet-2772	38	14	models	model	NOUN
admet-2772	38	15	for	for	ADP
admet-2772	38	16	admet	admet	ADJ
admet-2772	38	17	prediction	prediction	NOUN
admet-2772	38	18	in	in	ADP
admet-2772	38	19	drug	drug	NOUN
admet-2772	38	20	development	development	NOUN
admet-2772	38	21	doi	doi	PROPN
admet-2772	38	22	:	:	PUNCT
admet-2772	38	23	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	38	24	3	3	NUM
admet-2772	38	25	been	be	AUX
admet-2772	38	26	effectively	effectively	ADV
admet-2772	38	27	utilized	utilize	VERB
admet-2772	38	28	to	to	PART
admet-2772	38	29	develop	develop	VERB
admet-2772	38	30	models	model	NOUN
admet-2772	38	31	and	and	CCONJ
admet-2772	38	32	prediction	prediction	NOUN
admet-2772	38	33	tools	tool	NOUN
admet-2772	38	34	for	for	ADP
admet-2772	38	35	admet	admet	NOUN
admet-2772	38	36	properties	property	NOUN
admet-2772	38	37	.	.	PUNCT
admet-2772	39	1	apart	apart	ADV
admet-2772	39	2	from	from	ADP
admet-2772	39	3	property	property	NOUN
admet-2772	39	4	predictions	prediction	NOUN
admet-2772	39	5	,	,	PUNCT
admet-2772	39	6	ml	ml	PROPN
admet-2772	39	7	has	have	AUX
admet-2772	39	8	also	also	ADV
admet-2772	39	9	contributed	contribute	VERB
admet-2772	39	10	to	to	ADP
admet-2772	39	11	early	early	ADJ
admet-2772	39	12	phases	phase	NOUN
admet-2772	39	13	of	of	ADP
admet-2772	39	14	drug	drug	NOUN
admet-2772	39	15	discovery	discovery	NOUN
admet-2772	39	16	,	,	PUNCT
admet-2772	39	17	like	like	ADP
admet-2772	39	18	de	de	X
admet-2772	39	19	novo	novo	NOUN
admet-2772	39	20	designing	designing	NOUN
admet-2772	39	21	of	of	ADP
admet-2772	39	22	chemical	chemical	NOUN
admet-2772	39	23	compounds	compound	NOUN
admet-2772	39	24	and	and	CCONJ
admet-2772	39	25	peptides	peptide	NOUN
admet-2772	39	26	[	[	X
admet-2772	39	27	8	8	NUM
admet-2772	39	28	]	]	PUNCT
admet-2772	39	29	.	.	PUNCT
admet-2772	40	1	moreover	moreover	ADV
admet-2772	40	2	,	,	PUNCT
admet-2772	40	3	companies	company	NOUN
admet-2772	40	4	involved	involve	VERB
admet-2772	40	5	in	in	ADP
admet-2772	40	6	clinical	clinical	ADJ
admet-2772	40	7	research	research	NOUN
admet-2772	40	8	have	have	AUX
admet-2772	40	9	ascertained	ascertain	VERB
admet-2772	40	10	that	that	SCONJ
admet-2772	40	11	revising	revise	VERB
admet-2772	40	12	the	the	DET
admet-2772	40	13	research	research	NOUN
admet-2772	40	14	strategies	strategy	NOUN
admet-2772	40	15	by	by	ADP
admet-2772	40	16	introducing	introduce	VERB
admet-2772	40	17	ml	ml	NOUN
admet-2772	40	18	-	-	PUNCT
admet-2772	40	19	based	base	VERB
admet-2772	40	20	techniques	technique	NOUN
admet-2772	40	21	has	have	AUX
admet-2772	40	22	resulted	result	VERB
admet-2772	40	23	in	in	ADP
admet-2772	40	24	greater	great	ADJ
admet-2772	40	25	success	success	NOUN
admet-2772	40	26	rates	rate	NOUN
admet-2772	40	27	in	in	ADP
admet-2772	40	28	both	both	CCONJ
admet-2772	40	29	preclinical	preclinical	ADJ
admet-2772	40	30	and	and	CCONJ
admet-2772	40	31	clinical	clinical	ADJ
admet-2772	40	32	trials	trial	NOUN
admet-2772	41	1	[	[	X
admet-2772	41	2	9	9	NUM
admet-2772	41	3	]	]	PUNCT
admet-2772	41	4	.	.	PUNCT
admet-2772	42	1	after	after	ADP
admet-2772	42	2	high	high	ADJ
admet-2772	42	3	-	-	PUNCT
admet-2772	42	4	throughput	throughput	NOUN
admet-2772	42	5	screening	screening	NOUN
admet-2772	42	6	,	,	PUNCT
admet-2772	42	7	the	the	DET
admet-2772	42	8	chosen	choose	VERB
admet-2772	42	9	compounds	compound	NOUN
admet-2772	42	10	,	,	PUNCT
admet-2772	42	11	often	often	ADV
admet-2772	42	12	referred	refer	VERB
admet-2772	42	13	to	to	ADP
admet-2772	42	14	as	as	ADP
admet-2772	42	15	hit	hit	VERB
admet-2772	42	16	compounds	compound	NOUN
admet-2772	42	17	,	,	PUNCT
admet-2772	42	18	are	be	AUX
admet-2772	42	19	analysed	analyse	VERB
admet-2772	42	20	for	for	ADP
admet-2772	42	21	their	their	PRON
admet-2772	42	22	biological	biological	ADJ
admet-2772	42	23	activity	activity	NOUN
admet-2772	42	24	via	via	ADP
admet-2772	42	25	in	in	ADP
admet-2772	42	26	vitro	vitro	X
admet-2772	42	27	studies	study	NOUN
admet-2772	42	28	.	.	PUNCT
admet-2772	43	1	the	the	DET
admet-2772	43	2	most	most	ADV
admet-2772	43	3	potent	potent	ADJ
admet-2772	43	4	compounds	compound	NOUN
admet-2772	43	5	obtained	obtain	VERB
admet-2772	43	6	from	from	ADP
admet-2772	43	7	in	in	ADP
admet-2772	43	8	vitro	vitro	X
admet-2772	43	9	activity	activity	NOUN
admet-2772	43	10	data	datum	NOUN
admet-2772	43	11	are	be	AUX
admet-2772	43	12	developed	develop	VERB
admet-2772	43	13	into	into	ADP
admet-2772	43	14	lead	lead	NOUN
admet-2772	43	15	compounds	compound	NOUN
admet-2772	43	16	through	through	ADP
admet-2772	43	17	a	a	DET
admet-2772	43	18	lead	lead	ADJ
admet-2772	43	19	optimization	optimization	NOUN
admet-2772	43	20	process	process	NOUN
admet-2772	43	21	[	[	X
admet-2772	43	22	10	10	NUM
admet-2772	43	23	]	]	PUNCT
admet-2772	43	24	.	.	PUNCT
admet-2772	44	1	during	during	ADP
admet-2772	44	2	the	the	DET
admet-2772	44	3	lead	lead	ADJ
admet-2772	44	4	optimization	optimization	NOUN
admet-2772	44	5	phase	phase	NOUN
admet-2772	44	6	,	,	PUNCT
admet-2772	44	7	the	the	DET
admet-2772	44	8	compounds	compound	NOUN
admet-2772	44	9	are	be	AUX
admet-2772	44	10	modified	modify	VERB
admet-2772	44	11	to	to	PART
admet-2772	44	12	improve	improve	VERB
admet-2772	44	13	their	their	PRON
admet-2772	44	14	bioavailability	bioavailability	NOUN
admet-2772	44	15	,	,	PUNCT
admet-2772	44	16	solubility	solubility	NOUN
admet-2772	44	17	,	,	PUNCT
admet-2772	44	18	partition	partition	NOUN
admet-2772	44	19	coefficient	coefficient	NOUN
admet-2772	44	20	,	,	PUNCT
admet-2772	44	21	and	and	CCONJ
admet-2772	44	22	stability	stability	NOUN
admet-2772	44	23	as	as	SCONJ
admet-2772	44	24	these	these	DET
admet-2772	44	25	factors	factor	NOUN
admet-2772	44	26	can	can	AUX
admet-2772	44	27	have	have	VERB
admet-2772	44	28	a	a	DET
admet-2772	44	29	direct	direct	ADJ
admet-2772	44	30	impact	impact	NOUN
admet-2772	44	31	on	on	ADP
admet-2772	44	32	the	the	DET
admet-2772	44	33	drug	drug	NOUN
admet-2772	44	34	's	's	PART
admet-2772	44	35	therapeutic	therapeutic	ADJ
admet-2772	44	36	efficacy	efficacy	NOUN
admet-2772	44	37	and	and	CCONJ
admet-2772	44	38	potency	potency	NOUN
admet-2772	44	39	[	[	X
admet-2772	44	40	11	11	NUM
admet-2772	44	41	]	]	PUNCT
admet-2772	44	42	.	.	PUNCT
admet-2772	45	1	the	the	DET
admet-2772	45	2	molecules	molecule	NOUN
admet-2772	45	3	with	with	ADP
admet-2772	45	4	optimized	optimize	VERB
admet-2772	45	5	admet	admet	NOUN
admet-2772	45	6	properties	property	NOUN
admet-2772	45	7	are	be	AUX
admet-2772	45	8	then	then	ADV
admet-2772	45	9	further	far	ADV
admet-2772	45	10	evaluated	evaluate	VERB
admet-2772	45	11	for	for	ADP
admet-2772	45	12	their	their	PRON
admet-2772	45	13	effectiveness	effectiveness	NOUN
admet-2772	45	14	using	use	VERB
admet-2772	45	15	suitable	suitable	ADJ
admet-2772	45	16	animal	animal	NOUN
admet-2772	45	17	models	model	NOUN
admet-2772	45	18	[	[	X
admet-2772	45	19	12	12	NUM
admet-2772	45	20	]	]	PUNCT
admet-2772	45	21	.	.	PUNCT
admet-2772	46	1	the	the	DET
admet-2772	46	2	optimized	optimize	VERB
admet-2772	46	3	compounds	compound	NOUN
admet-2772	46	4	are	be	AUX
admet-2772	46	5	tested	test	VERB
admet-2772	46	6	in	in	ADP
admet-2772	46	7	human	human	ADJ
admet-2772	46	8	subjects	subject	NOUN
admet-2772	46	9	in	in	ADP
admet-2772	46	10	order	order	NOUN
admet-2772	46	11	to	to	PART
admet-2772	46	12	validate	validate	VERB
admet-2772	46	13	and	and	CCONJ
admet-2772	46	14	confirm	confirm	VERB
admet-2772	46	15	the	the	DET
admet-2772	46	16	potency	potency	NOUN
admet-2772	46	17	,	,	PUNCT
admet-2772	46	18	therapeutic	therapeutic	ADJ
admet-2772	46	19	efficacy	efficacy	NOUN
admet-2772	46	20	,	,	PUNCT
admet-2772	46	21	admet	admet	NOUN
admet-2772	46	22	and	and	CCONJ
admet-2772	46	23	possible	possible	ADJ
admet-2772	46	24	adverse	adverse	ADJ
admet-2772	46	25	drug	drug	NOUN
admet-2772	46	26	reactions	reaction	NOUN
admet-2772	46	27	through	through	ADP
admet-2772	46	28	a	a	DET
admet-2772	46	29	four	four	NUM
admet-2772	46	30	-	-	PUNCT
admet-2772	46	31	step	step	NOUN
admet-2772	46	32	process	process	NOUN
admet-2772	46	33	called	call	VERB
admet-2772	46	34	clinical	clinical	ADJ
admet-2772	46	35	trials	trial	NOUN
admet-2772	46	36	,	,	PUNCT
admet-2772	46	37	in	in	ADP
admet-2772	46	38	which	which	PRON
admet-2772	46	39	each	each	DET
admet-2772	46	40	step	step	NOUN
admet-2772	46	41	is	be	AUX
admet-2772	46	42	carried	carry	VERB
admet-2772	46	43	out	out	ADP
admet-2772	46	44	in	in	ADP
admet-2772	46	45	a	a	DET
admet-2772	46	46	varying	vary	VERB
admet-2772	46	47	number	number	NOUN
admet-2772	46	48	of	of	ADP
admet-2772	46	49	human	human	ADJ
admet-2772	46	50	subjects	subject	NOUN
admet-2772	46	51	in	in	ADP
admet-2772	46	52	a	a	DET
admet-2772	46	53	randomized	randomized	ADJ
admet-2772	46	54	control	control	NOUN
admet-2772	46	55	manner	manner	NOUN
admet-2772	46	56	[	[	X
admet-2772	46	57	13	13	NUM
admet-2772	46	58	]	]	PUNCT
admet-2772	46	59	.	.	PUNCT
admet-2772	47	1	this	this	DET
admet-2772	47	2	review	review	NOUN
admet-2772	47	3	mainly	mainly	ADV
admet-2772	47	4	focuses	focus	VERB
admet-2772	47	5	on	on	ADP
admet-2772	47	6	the	the	DET
admet-2772	47	7	ml	ml	ADV
admet-2772	47	8	-	-	PUNCT
admet-2772	47	9	based	base	VERB
admet-2772	47	10	tools	tool	NOUN
admet-2772	47	11	used	use	VERB
admet-2772	47	12	in	in	ADP
admet-2772	47	13	admet	admet	PROPN
admet-2772	47	14	properties	property	NOUN
admet-2772	47	15	.	.	PUNCT
admet-2772	48	1	we	we	PRON
admet-2772	48	2	have	have	AUX
admet-2772	48	3	given	give	VERB
admet-2772	48	4	a	a	DET
admet-2772	48	5	general	general	ADJ
admet-2772	48	6	introduction	introduction	NOUN
admet-2772	48	7	to	to	ADP
admet-2772	48	8	the	the	DET
admet-2772	48	9	drug	drug	NOUN
admet-2772	48	10	discovery	discovery	NOUN
admet-2772	48	11	process	process	NOUN
admet-2772	48	12	,	,	PUNCT
admet-2772	48	13	machine	machine	NOUN
admet-2772	48	14	learning	learning	NOUN
admet-2772	48	15	and	and	CCONJ
admet-2772	48	16	dl	dl	PROPN
admet-2772	48	17	techniques	technique	NOUN
admet-2772	48	18	,	,	PUNCT
admet-2772	48	19	followed	follow	VERB
admet-2772	48	20	by	by	ADP
admet-2772	48	21	specific	specific	ADJ
admet-2772	48	22	examples	example	NOUN
admet-2772	48	23	and	and	CCONJ
admet-2772	48	24	discussion	discussion	NOUN
admet-2772	48	25	on	on	ADP
admet-2772	48	26	various	various	ADJ
admet-2772	48	27	ml	ml	NOUN
admet-2772	48	28	and	and	CCONJ
admet-2772	48	29	artificial	artificial	ADJ
admet-2772	48	30	intelligence	intelligence	NOUN
admet-2772	48	31	(	(	PUNCT
admet-2772	48	32	ai	ai	NOUN
admet-2772	48	33	)	)	PUNCT
admet-2772	48	34	based	base	VERB
admet-2772	48	35	tools	tool	NOUN
admet-2772	48	36	for	for	ADP
admet-2772	48	37	drug	drug	NOUN
admet-2772	48	38	development	development	NOUN
admet-2772	48	39	.	.	PUNCT
admet-2772	49	1	we	we	PRON
admet-2772	49	2	also	also	ADV
admet-2772	49	3	pointed	point	VERB
admet-2772	49	4	out	out	ADP
admet-2772	49	5	some	some	DET
admet-2772	49	6	notable	notable	ADJ
admet-2772	49	7	success	success	NOUN
admet-2772	49	8	stories	story	NOUN
admet-2772	49	9	in	in	ADP
admet-2772	49	10	the	the	DET
admet-2772	49	11	use	use	NOUN
admet-2772	49	12	of	of	ADP
admet-2772	49	13	ai	ai	NOUN
admet-2772	49	14	and	and	CCONJ
admet-2772	49	15	ml	ml	X
admet-2772	49	16	in	in	ADP
admet-2772	49	17	admet	admet	X
admet-2772	49	18	.	.	PUNCT
admet-2772	50	1	2	2	X
admet-2772	50	2	.	.	X
admet-2772	50	3	fundamentals	fundamental	NOUN
admet-2772	50	4	of	of	ADP
admet-2772	50	5	machine	machine	NOUN
admet-2772	50	6	learning	learning	NOUN
admet-2772	50	7	in	in	ADP
admet-2772	50	8	drug	drug	NOUN
admet-2772	50	9	discovery	discovery	NOUN
admet-2772	50	10	2.1	2.1	NUM
admet-2772	50	11	.	.	PUNCT
admet-2772	51	1	basics	basic	NOUN
admet-2772	51	2	of	of	ADP
admet-2772	51	3	machine	machine	NOUN
admet-2772	51	4	learning	learning	NOUN
admet-2772	51	5	models	model	NOUN
admet-2772	51	6	ml	ml	AUX
admet-2772	51	7	starts	start	VERB
admet-2772	51	8	with	with	ADP
admet-2772	51	9	obtaining	obtain	VERB
admet-2772	51	10	a	a	DET
admet-2772	51	11	suitable	suitable	ADJ
admet-2772	51	12	dataset	dataset	NOUN
admet-2772	51	13	,	,	PUNCT
admet-2772	51	14	often	often	ADV
admet-2772	51	15	from	from	ADP
admet-2772	51	16	publicly	publicly	ADV
admet-2772	51	17	available	available	ADJ
admet-2772	51	18	sources	source	NOUN
admet-2772	51	19	,	,	PUNCT
admet-2772	51	20	and	and	CCONJ
admet-2772	51	21	has	have	AUX
admet-2772	51	22	become	become	VERB
admet-2772	51	23	increasingly	increasingly	ADV
admet-2772	51	24	prominent	prominent	ADJ
admet-2772	51	25	in	in	ADP
admet-2772	51	26	admet	admet	PROPN
admet-2772	51	27	prediction	prediction	NOUN
admet-2772	51	28	,	,	PUNCT
admet-2772	51	29	offering	offer	VERB
admet-2772	51	30	valuable	valuable	ADJ
admet-2772	51	31	tools	tool	NOUN
admet-2772	51	32	for	for	ADP
admet-2772	51	33	drug	drug	NOUN
admet-2772	51	34	development	development	NOUN
admet-2772	51	35	and	and	CCONJ
admet-2772	51	36	toxicity	toxicity	NOUN
admet-2772	51	37	[	[	X
admet-2772	51	38	14	14	NUM
admet-2772	51	39	]	]	PUNCT
admet-2772	51	40	.	.	PUNCT
admet-2772	52	1	ml	ml	PROPN
admet-2772	52	2	methods	method	NOUN
admet-2772	52	3	are	be	AUX
admet-2772	52	4	generally	generally	ADV
admet-2772	52	5	divided	divide	VERB
admet-2772	52	6	into	into	ADP
admet-2772	52	7	supervised	supervised	ADJ
admet-2772	52	8	and	and	CCONJ
admet-2772	52	9	unsupervised	unsupervised	ADJ
admet-2772	52	10	approaches	approach	NOUN
admet-2772	52	11	.	.	PUNCT
admet-2772	53	1	in	in	ADP
admet-2772	53	2	supervised	supervised	ADJ
admet-2772	53	3	learning	learning	NOUN
admet-2772	53	4	,	,	PUNCT
admet-2772	53	5	models	model	NOUN
admet-2772	53	6	are	be	AUX
admet-2772	53	7	trained	train	VERB
admet-2772	53	8	using	use	VERB
admet-2772	53	9	labelled	label	VERB
admet-2772	53	10	data	datum	NOUN
admet-2772	53	11	to	to	PART
admet-2772	53	12	make	make	VERB
admet-2772	53	13	predictions	prediction	NOUN
admet-2772	53	14	,	,	PUNCT
admet-2772	53	15	such	such	ADJ
admet-2772	53	16	as	as	ADP
admet-2772	53	17	predicting	predict	VERB
admet-2772	53	18	properties	property	NOUN
admet-2772	53	19	like	like	ADP
admet-2772	53	20	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	53	21	(	(	PUNCT
admet-2772	53	22	pk	pk	NOUN
admet-2772	53	23	)	)	PUNCT
admet-2772	53	24	properties	property	NOUN
admet-2772	53	25	,	,	PUNCT
admet-2772	53	26	based	base	VERB
admet-2772	53	27	on	on	ADP
admet-2772	53	28	input	input	NOUN
admet-2772	53	29	attributes	attribute	NOUN
admet-2772	53	30	like	like	ADP
admet-2772	53	31	chemical	chemical	NOUN
admet-2772	53	32	descriptors	descriptor	NOUN
admet-2772	53	33	of	of	ADP
admet-2772	53	34	new	new	ADJ
admet-2772	53	35	compounds	compound	NOUN
admet-2772	53	36	.	.	PUNCT
admet-2772	54	1	on	on	ADP
admet-2772	54	2	the	the	DET
admet-2772	54	3	other	other	ADJ
admet-2772	54	4	hand	hand	NOUN
admet-2772	54	5	,	,	PUNCT
admet-2772	54	6	unsupervised	unsupervised	ADJ
admet-2772	54	7	learning	learning	NOUN
admet-2772	54	8	aims	aim	VERB
admet-2772	54	9	to	to	PART
admet-2772	54	10	find	find	VERB
admet-2772	54	11	patterns	pattern	NOUN
admet-2772	54	12	,	,	PUNCT
admet-2772	54	13	structures	structure	NOUN
admet-2772	54	14	,	,	PUNCT
admet-2772	54	15	or	or	CCONJ
admet-2772	54	16	relationships	relationship	NOUN
admet-2772	54	17	within	within	ADP
admet-2772	54	18	a	a	DET
admet-2772	54	19	dataset	dataset	NOUN
admet-2772	54	20	without	without	ADP
admet-2772	54	21	using	use	VERB
admet-2772	54	22	labelled	label	VERB
admet-2772	54	23	or	or	CCONJ
admet-2772	54	24	predefined	predefine	VERB
admet-2772	54	25	outputs	output	NOUN
admet-2772	54	26	.	.	PUNCT
admet-2772	55	1	its	its	PRON
admet-2772	55	2	goal	goal	NOUN
admet-2772	55	3	is	be	AUX
admet-2772	55	4	to	to	PART
admet-2772	55	5	uncover	uncover	VERB
admet-2772	55	6	inherent	inherent	ADJ
admet-2772	55	7	structures	structure	NOUN
admet-2772	55	8	and	and	CCONJ
admet-2772	55	9	insights	insight	NOUN
admet-2772	55	10	,	,	PUNCT
admet-2772	55	11	which	which	PRON
admet-2772	55	12	are	be	AUX
admet-2772	55	13	sometimes	sometimes	ADV
admet-2772	55	14	missed	miss	VERB
admet-2772	55	15	in	in	ADP
admet-2772	55	16	supervised	supervised	ADJ
admet-2772	55	17	learning	learning	NOUN
admet-2772	55	18	approaches	approach	NOUN
admet-2772	55	19	because	because	SCONJ
admet-2772	55	20	they	they	PRON
admet-2772	55	21	rely	rely	VERB
admet-2772	55	22	on	on	ADP
admet-2772	55	23	pre	pre	ADJ
admet-2772	55	24	-	-	ADJ
admet-2772	55	25	defined	define	VERB
admet-2772	55	26	answers	answer	NOUN
admet-2772	55	27	[	[	X
admet-2772	55	28	3	3	NUM
admet-2772	55	29	]	]	X
admet-2772	55	30	common	common	ADJ
admet-2772	55	31	ml	ml	NOUN
admet-2772	55	32	algorithms	algorithm	NOUN
admet-2772	55	33	used	use	VERB
admet-2772	55	34	in	in	ADP
admet-2772	55	35	this	this	DET
admet-2772	55	36	field	field	NOUN
admet-2772	55	37	include	include	VERB
admet-2772	55	38	supervised	supervise	VERB
admet-2772	55	39	methods	method	NOUN
admet-2772	55	40	such	such	ADJ
admet-2772	55	41	as	as	ADP
admet-2772	55	42	support	support	NOUN
admet-2772	55	43	vector	vector	NOUN
admet-2772	55	44	machines	machine	NOUN
admet-2772	55	45	,	,	PUNCT
admet-2772	55	46	random	random	ADJ
admet-2772	55	47	forests	forest	NOUN
admet-2772	55	48	,	,	PUNCT
admet-2772	55	49	decision	decision	NOUN
admet-2772	55	50	trees	tree	NOUN
admet-2772	55	51	,	,	PUNCT
admet-2772	55	52	and	and	CCONJ
admet-2772	55	53	neural	neural	ADJ
admet-2772	55	54	networks	network	NOUN
admet-2772	55	55	,	,	PUNCT
admet-2772	55	56	as	as	ADV
admet-2772	55	57	well	well	ADV
admet-2772	55	58	as	as	ADP
admet-2772	55	59	unsupervised	unsupervised	ADJ
admet-2772	55	60	approaches	approach	NOUN
admet-2772	55	61	like	like	ADP
admet-2772	55	62	kohonen	kohonen	PROPN
admet-2772	55	63	's	's	PART
admet-2772	55	64	selforganizing	selforganize	VERB
admet-2772	55	65	maps	map	NOUN
admet-2772	55	66	[	[	X
admet-2772	55	67	15	15	NUM
admet-2772	55	68	]	]	X
admet-2772	55	69	(	(	PUNCT
admet-2772	55	70	figure	figure	NOUN
admet-2772	55	71	2	2	NUM
admet-2772	55	72	)	)	PUNCT
admet-2772	55	73	.	.	PUNCT
admet-2772	56	1	these	these	DET
admet-2772	56	2	methods	method	NOUN
admet-2772	56	3	can	can	AUX
admet-2772	56	4	be	be	AUX
admet-2772	56	5	applied	apply	VERB
admet-2772	56	6	to	to	ADP
admet-2772	56	7	various	various	ADJ
admet-2772	56	8	types	type	NOUN
admet-2772	56	9	of	of	ADP
admet-2772	56	10	input	input	NOUN
admet-2772	56	11	data	datum	NOUN
admet-2772	56	12	,	,	PUNCT
admet-2772	56	13	ranging	range	VERB
admet-2772	56	14	from	from	ADP
admet-2772	56	15	chemical	chemical	ADJ
admet-2772	56	16	structural	structural	ADJ
admet-2772	56	17	descriptors	descriptor	NOUN
admet-2772	56	18	to	to	ADP
admet-2772	56	19	transcriptome	transcriptome	ADJ
admet-2772	56	20	analysis	analysis	NOUN
admet-2772	56	21	,	,	PUNCT
admet-2772	56	22	enhancing	enhance	VERB
admet-2772	56	23	prediction	prediction	NOUN
admet-2772	56	24	accuracy	accuracy	NOUN
admet-2772	56	25	[	[	X
admet-2772	56	26	16	16	NUM
admet-2772	56	27	]	]	PUNCT
admet-2772	56	28	.	.	PUNCT
admet-2772	57	1	the	the	DET
admet-2772	57	2	selection	selection	NOUN
admet-2772	57	3	of	of	ADP
admet-2772	57	4	appropriate	appropriate	ADJ
admet-2772	57	5	ml	ml	NOUN
admet-2772	57	6	techniques	technique	NOUN
admet-2772	57	7	depends	depend	VERB
admet-2772	57	8	on	on	ADP
admet-2772	57	9	the	the	DET
admet-2772	57	10	characteristics	characteristic	NOUN
admet-2772	57	11	of	of	ADP
admet-2772	57	12	available	available	ADJ
admet-2772	57	13	data	datum	NOUN
admet-2772	57	14	and	and	CCONJ
admet-2772	57	15	the	the	DET
admet-2772	57	16	specific	specific	ADJ
admet-2772	57	17	admet	admet	NOUN
admet-2772	57	18	property	property	NOUN
admet-2772	57	19	being	be	AUX
admet-2772	57	20	predicted	predict	VERB
admet-2772	57	21	[	[	X
admet-2772	57	22	15	15	NUM
admet-2772	57	23	]	]	PUNCT
admet-2772	57	24	.	.	PUNCT
admet-2772	58	1	the	the	DET
admet-2772	58	2	development	development	NOUN
admet-2772	58	3	of	of	ADP
admet-2772	58	4	a	a	DET
admet-2772	58	5	robust	robust	ADJ
admet-2772	58	6	machine	machine	NOUN
admet-2772	58	7	learning	learning	NOUN
admet-2772	58	8	model	model	NOUN
admet-2772	58	9	for	for	ADP
admet-2772	58	10	admet	admet	ADJ
admet-2772	58	11	predictions	prediction	NOUN
admet-2772	58	12	begins	begin	VERB
admet-2772	58	13	with	with	ADP
admet-2772	58	14	raw	raw	ADJ
admet-2772	58	15	data	datum	NOUN
admet-2772	58	16	collection	collection	NOUN
admet-2772	58	17	,	,	PUNCT
admet-2772	58	18	which	which	PRON
admet-2772	58	19	includes	include	VERB
admet-2772	58	20	both	both	CCONJ
admet-2772	58	21	labelled	label	VERB
admet-2772	58	22	and	and	CCONJ
admet-2772	58	23	unlabelled	unlabelled	ADJ
admet-2772	58	24	datasets	dataset	NOUN
admet-2772	58	25	.	.	PUNCT
admet-2772	59	1	this	this	DET
admet-2772	59	2	data	data	NOUN
admet-2772	59	3	undergoes	undergoe	NOUN
admet-2772	59	4	preprocessing	preprocessing	NOUN
admet-2772	59	5	,	,	PUNCT
admet-2772	59	6	ensuring	ensure	VERB
admet-2772	59	7	quality	quality	NOUN
admet-2772	59	8	and	and	CCONJ
admet-2772	59	9	consistency	consistency	NOUN
admet-2772	59	10	before	before	ADP
admet-2772	59	11	being	be	AUX
admet-2772	59	12	split	split	VERB
admet-2772	59	13	into	into	ADP
admet-2772	59	14	training	training	NOUN
admet-2772	59	15	and	and	CCONJ
admet-2772	59	16	testing	testing	NOUN
admet-2772	59	17	datasets	dataset	NOUN
admet-2772	59	18	.	.	PUNCT
admet-2772	60	1	various	various	ADJ
admet-2772	60	2	ml	ml	NOUN
admet-2772	60	3	algorithms	algorithm	NOUN
admet-2772	60	4	,	,	PUNCT
admet-2772	60	5	such	such	ADJ
admet-2772	60	6	as	as	ADP
admet-2772	60	7	supervised	supervised	ADJ
admet-2772	60	8	,	,	PUNCT
admet-2772	60	9	unsupervised	unsupervised	ADJ
admet-2772	60	10	,	,	PUNCT
admet-2772	60	11	and	and	CCONJ
admet-2772	60	12	deep	deep	ADJ
admet-2772	60	13	learning	learning	NOUN
admet-2772	60	14	approaches	approach	NOUN
admet-2772	60	15	,	,	PUNCT
admet-2772	60	16	are	be	AUX
admet-2772	60	17	then	then	ADV
admet-2772	60	18	applied	apply	VERB
admet-2772	60	19	to	to	ADP
admet-2772	60	20	the	the	DET
admet-2772	60	21	training	training	NOUN
admet-2772	60	22	data	datum	NOUN
admet-2772	60	23	to	to	PART
admet-2772	60	24	develop	develop	VERB
admet-2772	60	25	predictive	predictive	ADJ
admet-2772	60	26	models	model	NOUN
admet-2772	60	27	.	.	PUNCT
admet-2772	61	1	to	to	PART
admet-2772	61	2	enhance	enhance	VERB
admet-2772	61	3	model	model	NOUN
admet-2772	61	4	accuracy	accuracy	NOUN
admet-2772	61	5	and	and	CCONJ
admet-2772	61	6	generalizability	generalizability	NOUN
admet-2772	61	7	,	,	PUNCT
admet-2772	61	8	feature	feature	NOUN
admet-2772	61	9	selection	selection	NOUN
admet-2772	61	10	and	and	CCONJ
admet-2772	61	11	hyperparameter	hyperparameter	NOUN
admet-2772	61	12	optimization	optimization	NOUN
admet-2772	61	13	are	be	AUX
admet-2772	61	14	performed	perform	VERB
admet-2772	61	15	,	,	PUNCT
admet-2772	61	16	followed	follow	VERB
admet-2772	61	17	by	by	ADP
admet-2772	61	18	cross	cross	ADJ
admet-2772	61	19	-	-	ADJ
admet-2772	61	20	validation	validation	ADJ
admet-2772	61	21	techniques	technique	NOUN
admet-2772	61	22	like	like	ADP
admet-2772	61	23	k	k	ADJ
admet-2772	61	24	-	-	ADJ
admet-2772	61	25	fold	fold	ADJ
admet-2772	61	26	validation	validation	NOUN
admet-2772	61	27	.	.	PUNCT
admet-2772	62	1	finally	finally	ADV
admet-2772	62	2	,	,	PUNCT
admet-2772	62	3	the	the	DET
admet-2772	62	4	optimized	optimize	VERB
admet-2772	62	5	model	model	NOUN
admet-2772	62	6	is	be	AUX
admet-2772	62	7	tested	test	VERB
admet-2772	62	8	using	use	VERB
admet-2772	62	9	an	an	DET
admet-2772	62	10	independent	independent	ADJ
admet-2772	62	11	dataset	dataset	NOUN
admet-2772	62	12	to	to	PART
admet-2772	62	13	evaluate	evaluate	VERB
admet-2772	62	14	its	its	PRON
admet-2772	62	15	performance	performance	NOUN
admet-2772	62	16	based	base	VERB
admet-2772	62	17	on	on	ADP
admet-2772	62	18	classification	classification	NOUN
admet-2772	62	19	and	and	CCONJ
admet-2772	62	20	regression	regression	NOUN
admet-2772	62	21	metrics	metric	NOUN
admet-2772	62	22	.	.	PUNCT
admet-2772	63	1	figure	figure	NOUN
admet-2772	63	2	3	3	NUM
admet-2772	63	3	illustrates	illustrate	VERB
admet-2772	63	4	the	the	DET
admet-2772	63	5	stepwise	stepwise	ADJ
admet-2772	63	6	workflow	workflow	NOUN
admet-2772	63	7	for	for	ADP
admet-2772	63	8	generating	generate	VERB
admet-2772	63	9	an	an	DET
admet-2772	63	10	ml	ml	NOUN
admet-2772	63	11	model	model	NOUN
admet-2772	63	12	,	,	PUNCT
admet-2772	63	13	detailing	detail	VERB
admet-2772	63	14	each	each	DET
admet-2772	63	15	phase	phase	NOUN
admet-2772	63	16	from	from	ADP
admet-2772	63	17	data	datum	NOUN
admet-2772	63	18	preprocessing	preprocesse	VERB
admet-2772	63	19	to	to	ADP
admet-2772	63	20	model	model	NOUN
admet-2772	63	21	evaluation	evaluation	NOUN
admet-2772	63	22	.	.	PUNCT
admet-2772	64	1	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	64	2	m.	m.	PROPN
admet-2772	64	3	venkataraman	venkataraman	PROPN
admet-2772	64	4	et	et	PROPN
admet-2772	64	5	al	al	PROPN
admet-2772	64	6	.	.	PROPN
admet-2772	64	7	admet	admet	PROPN
admet-2772	64	8	&	&	CCONJ
admet-2772	64	9	dmpk	dmpk	PROPN
admet-2772	64	10	13(3	13(3	NUM
admet-2772	64	11	)	)	PUNCT
admet-2772	64	12	(	(	PUNCT
admet-2772	64	13	2025	2025	NUM
admet-2772	64	14	)	)	PUNCT
admet-2772	64	15	2772	2772	NUM
admet-2772	64	16	4	4	NUM
admet-2772	64	17	figure	figure	NOUN
admet-2772	64	18	2	2	NUM
admet-2772	64	19	.	.	PUNCT
admet-2772	64	20	commonly	commonly	ADV
admet-2772	64	21	used	use	VERB
admet-2772	64	22	ai	ai	NOUN
admet-2772	64	23	/	/	SYM
admet-2772	64	24	ml	ml	NOUN
admet-2772	64	25	algorithms	algorithm	NOUN
admet-2772	64	26	for	for	ADP
admet-2772	64	27	developing	develop	VERB
admet-2772	64	28	admet	admet	NOUN
admet-2772	64	29	prediction	prediction	NOUN
admet-2772	64	30	models	model	NOUN
admet-2772	64	31	figure	figure	VERB
admet-2772	64	32	3	3	NUM
admet-2772	64	33	.	.	PUNCT
admet-2772	65	1	the	the	DET
admet-2772	65	2	diagram	diagram	NOUN
admet-2772	65	3	illustrates	illustrate	VERB
admet-2772	65	4	the	the	DET
admet-2772	65	5	stepwise	stepwise	ADJ
admet-2772	65	6	workflow	workflow	NOUN
admet-2772	65	7	for	for	ADP
admet-2772	65	8	generating	generate	VERB
admet-2772	65	9	a	a	DET
admet-2772	65	10	machine	machine	NOUN
admet-2772	65	11	learning	learn	VERB
admet-2772	65	12	model	model	NOUN
admet-2772	65	13	,	,	PUNCT
admet-2772	65	14	starting	start	VERB
admet-2772	65	15	from	from	ADP
admet-2772	65	16	raw	raw	ADJ
admet-2772	65	17	data	datum	NOUN
admet-2772	65	18	collection	collection	NOUN
admet-2772	65	19	to	to	AUX
admet-2772	65	20	model	model	NOUN
admet-2772	65	21	evaluation	evaluation	NOUN
admet-2772	65	22	.	.	PUNCT
admet-2772	66	1	initially	initially	ADV
admet-2772	66	2	,	,	PUNCT
admet-2772	66	3	raw	raw	ADJ
admet-2772	66	4	data	datum	NOUN
admet-2772	66	5	,	,	PUNCT
admet-2772	66	6	which	which	PRON
admet-2772	66	7	can	can	AUX
admet-2772	66	8	include	include	VERB
admet-2772	66	9	both	both	DET
admet-2772	66	10	labeled	label	VERB
admet-2772	66	11	and	and	CCONJ
admet-2772	66	12	unlabeled	unlabeled	ADJ
admet-2772	66	13	datasets	dataset	NOUN
admet-2772	66	14	,	,	PUNCT
admet-2772	66	15	undergoes	undergoe	NOUN
admet-2772	66	16	preprocessing	preprocessing	NOUN
admet-2772	66	17	and	and	CCONJ
admet-2772	66	18	structuring	structuring	NOUN
admet-2772	66	19	.	.	PUNCT
admet-2772	67	1	this	this	DET
admet-2772	67	2	iterative	iterative	NOUN
admet-2772	67	3	step	step	NOUN
admet-2772	67	4	ensures	ensure	VERB
admet-2772	67	5	data	datum	NOUN
admet-2772	67	6	quality	quality	NOUN
admet-2772	67	7	before	before	ADP
admet-2772	67	8	proceeding	proceed	VERB
admet-2772	67	9	further	far	ADV
admet-2772	67	10	.	.	PUNCT
admet-2772	68	1	once	once	SCONJ
admet-2772	68	2	the	the	DET
admet-2772	68	3	data	data	NOUN
admet-2772	68	4	is	be	AUX
admet-2772	68	5	refined	refine	VERB
admet-2772	68	6	,	,	PUNCT
admet-2772	68	7	it	it	PRON
admet-2772	68	8	is	be	AUX
admet-2772	68	9	split	split	VERB
admet-2772	68	10	into	into	ADP
admet-2772	68	11	training	training	NOUN
admet-2772	68	12	and	and	CCONJ
admet-2772	68	13	test	test	NOUN
admet-2772	68	14	sets	set	NOUN
admet-2772	68	15	,	,	PUNCT
admet-2772	68	16	commonly	commonly	ADV
admet-2772	68	17	in	in	ADP
admet-2772	68	18	an	an	DET
admet-2772	68	19	80:20	80:20	NUM
admet-2772	68	20	ratio	ratio	NOUN
admet-2772	68	21	of	of	ADP
admet-2772	68	22	the	the	DET
admet-2772	68	23	total	total	ADJ
admet-2772	68	24	volume	volume	NOUN
admet-2772	68	25	of	of	ADP
admet-2772	68	26	the	the	DET
admet-2772	68	27	data	datum	NOUN
admet-2772	68	28	.	.	PUNCT
admet-2772	69	1	the	the	DET
admet-2772	69	2	80	80	NUM
admet-2772	69	3	%	%	NOUN
admet-2772	69	4	training	training	NOUN
admet-2772	69	5	data	datum	NOUN
admet-2772	69	6	is	be	AUX
admet-2772	69	7	then	then	ADV
admet-2772	69	8	subjected	subject	VERB
admet-2772	69	9	to	to	ADP
admet-2772	69	10	various	various	ADJ
admet-2772	69	11	machine	machine	NOUN
admet-2772	69	12	learning	learn	VERB
admet-2772	69	13	algorithms	algorithm	NOUN
admet-2772	69	14	,	,	PUNCT
admet-2772	69	15	including	include	VERB
admet-2772	69	16	supervised	supervised	ADJ
admet-2772	69	17	,	,	PUNCT
admet-2772	69	18	unsupervised	unsupervised	ADJ
admet-2772	69	19	,	,	PUNCT
admet-2772	69	20	reinforcement	reinforcement	NOUN
admet-2772	69	21	learning	learning	NOUN
admet-2772	69	22	,	,	PUNCT
admet-2772	69	23	and	and	CCONJ
admet-2772	69	24	deep	deep	ADJ
admet-2772	69	25	learning	learning	NOUN
admet-2772	69	26	approaches	approach	NOUN
admet-2772	69	27	.	.	PUNCT
admet-2772	70	1	through	through	ADP
admet-2772	70	2	an	an	DET
admet-2772	70	3	iterative	iterative	NOUN
admet-2772	70	4	process	process	NOUN
admet-2772	70	5	,	,	PUNCT
admet-2772	70	6	the	the	DET
admet-2772	70	7	best	well	ADV
admet-2772	70	8	-	-	PUNCT
admet-2772	70	9	performing	perform	VERB
admet-2772	70	10	candidate	candidate	NOUN
admet-2772	70	11	model	model	NOUN
admet-2772	70	12	is	be	AUX
admet-2772	70	13	selected	select	VERB
admet-2772	70	14	.	.	PUNCT
admet-2772	71	1	the	the	DET
admet-2772	71	2	chosen	choose	VERB
admet-2772	71	3	candidate	candidate	NOUN
admet-2772	71	4	model	model	NOUN
admet-2772	71	5	is	be	AUX
admet-2772	71	6	further	far	ADV
admet-2772	71	7	refined	refine	VERB
admet-2772	71	8	through	through	ADP
admet-2772	71	9	hyperparameter	hyperparameter	NOUN
admet-2772	71	10	optimization	optimization	NOUN
admet-2772	71	11	and	and	CCONJ
admet-2772	71	12	feature	feature	NOUN
admet-2772	71	13	selection	selection	NOUN
admet-2772	71	14	,	,	PUNCT
admet-2772	71	15	leading	lead	VERB
admet-2772	71	16	to	to	ADP
admet-2772	71	17	the	the	DET
admet-2772	71	18	final	final	ADJ
admet-2772	71	19	optimized	optimize	VERB
admet-2772	71	20	model	model	NOUN
admet-2772	71	21	.	.	PUNCT
admet-2772	72	1	this	this	DET
admet-2772	72	2	model	model	NOUN
admet-2772	72	3	is	be	AUX
admet-2772	72	4	then	then	ADV
admet-2772	72	5	validated	validate	VERB
admet-2772	72	6	using	use	VERB
admet-2772	72	7	cross	cross	ADJ
admet-2772	72	8	-	-	ADJ
admet-2772	72	9	validation	validation	ADJ
admet-2772	72	10	techniques	technique	NOUN
admet-2772	72	11	such	such	ADJ
admet-2772	72	12	as	as	ADP
admet-2772	72	13	5	5	NUM
admet-2772	72	14	-	-	ADJ
admet-2772	72	15	fold	fold	ADJ
admet-2772	72	16	cross	cross	NOUN
admet-2772	72	17	-	-	NOUN
admet-2772	72	18	validation	validation	NOUN
admet-2772	72	19	to	to	PART
admet-2772	72	20	ensure	ensure	VERB
admet-2772	72	21	robustness	robustness	NOUN
admet-2772	72	22	.	.	PUNCT
admet-2772	73	1	following	follow	VERB
admet-2772	73	2	validation	validation	NOUN
admet-2772	73	3	,	,	PUNCT
admet-2772	73	4	the	the	DET
admet-2772	73	5	model	model	NOUN
admet-2772	73	6	is	be	AUX
admet-2772	73	7	tested	test	VERB
admet-2772	73	8	using	use	VERB
admet-2772	73	9	the	the	DET
admet-2772	73	10	20	20	NUM
admet-2772	73	11	%	%	NOUN
admet-2772	73	12	test	test	NOUN
admet-2772	73	13	dataset	dataset	NOUN
admet-2772	73	14	.	.	PUNCT
admet-2772	74	1	the	the	DET
admet-2772	74	2	predicted	predict	VERB
admet-2772	74	3	outcomes	outcome	NOUN
admet-2772	74	4	(	(	PUNCT
admet-2772	74	5	y	y	NOUN
admet-2772	74	6	-	-	PUNCT
admet-2772	74	7	values	value	NOUN
admet-2772	74	8	)	)	PUNCT
admet-2772	74	9	are	be	AUX
admet-2772	74	10	analysed	analyse	VERB
admet-2772	74	11	,	,	PUNCT
admet-2772	74	12	and	and	CCONJ
admet-2772	74	13	the	the	DET
admet-2772	74	14	model	model	NOUN
admet-2772	74	15	's	's	PART
admet-2772	74	16	performance	performance	NOUN
admet-2772	74	17	is	be	AUX
admet-2772	74	18	evaluated	evaluate	VERB
admet-2772	74	19	using	use	VERB
admet-2772	74	20	classification	classification	NOUN
admet-2772	74	21	and	and	CCONJ
admet-2772	74	22	regression	regression	NOUN
admet-2772	74	23	metrics	metric	NOUN
admet-2772	74	24	,	,	PUNCT
admet-2772	74	25	ensuring	ensure	VERB
admet-2772	74	26	its	its	PRON
admet-2772	74	27	reliability	reliability	NOUN
admet-2772	74	28	and	and	CCONJ
admet-2772	74	29	accuracy	accuracy	NOUN
admet-2772	74	30	for	for	ADP
admet-2772	74	31	real	real	ADJ
admet-2772	74	32	-	-	PUNCT
admet-2772	74	33	world	world	NOUN
admet-2772	74	34	applications	application	NOUN
admet-2772	74	35	(	(	PUNCT
admet-2772	74	36	courtesy	courtesy	NOUN
admet-2772	74	37	:	:	PUNCT
admet-2772	74	38	bioicons	bioicon	NOUN
admet-2772	74	39	;	;	PUNCT
admet-2772	74	40	flaticon	flaticon	NOUN
admet-2772	74	41	)	)	PUNCT
admet-2772	74	42	.	.	PUNCT
admet-2772	75	1	2.2	2.2	NUM
admet-2772	75	2	.	.	PUNCT
admet-2772	76	1	data	datum	NOUN
admet-2772	76	2	requirements	requirement	NOUN
admet-2772	76	3	and	and	CCONJ
admet-2772	76	4	preprocessing	preprocesse	VERB
admet-2772	76	5	the	the	DET
admet-2772	76	6	standard	standard	NOUN
admet-2772	76	7	ml	ml	ADP
admet-2772	76	8	methodology	methodology	NOUN
admet-2772	76	9	starts	start	VERB
admet-2772	76	10	with	with	ADP
admet-2772	76	11	obtaining	obtain	VERB
admet-2772	76	12	a	a	DET
admet-2772	76	13	suitable	suitable	ADJ
admet-2772	76	14	dataset	dataset	NOUN
admet-2772	76	15	,	,	PUNCT
admet-2772	76	16	often	often	ADV
admet-2772	76	17	from	from	ADP
admet-2772	76	18	publicly	publicly	ADV
admet-2772	76	19	available	available	ADJ
admet-2772	76	20	repositories	repository	NOUN
admet-2772	76	21	tailored	tailor	VERB
admet-2772	76	22	for	for	ADP
admet-2772	76	23	drug	drug	NOUN
admet-2772	76	24	discovery	discovery	NOUN
admet-2772	76	25	.	.	PUNCT
admet-2772	77	1	the	the	DET
admet-2772	77	2	quality	quality	NOUN
admet-2772	77	3	of	of	ADP
admet-2772	77	4	data	datum	NOUN
admet-2772	77	5	is	be	AUX
admet-2772	77	6	crucial	crucial	ADJ
admet-2772	77	7	for	for	ADP
admet-2772	77	8	successful	successful	ADJ
admet-2772	77	9	ml	ml	NOUN
admet-2772	77	10	tasks	task	NOUN
admet-2772	77	11	,	,	PUNCT
admet-2772	77	12	as	as	SCONJ
admet-2772	77	13	it	it	PRON
admet-2772	77	14	directly	directly	ADV
admet-2772	77	15	impacts	impact	VERB
admet-2772	77	16	model	model	NOUN
admet-2772	77	17	performance	performance	NOUN
admet-2772	77	18	.	.	PUNCT
admet-2772	78	1	various	various	ADJ
admet-2772	78	2	databases	database	NOUN
admet-2772	78	3	provide	provide	VERB
admet-2772	78	4	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	78	5	and	and	CCONJ
admet-2772	78	6	physicochemical	physicochemical	ADJ
admet-2772	78	7	properties	property	NOUN
admet-2772	78	8	,	,	PUNCT
admet-2772	78	9	enabling	enable	VERB
admet-2772	78	10	robust	robust	ADJ
admet-2772	78	11	model	model	NOUN
admet-2772	78	12	training	training	NOUN
admet-2772	78	13	and	and	CCONJ
admet-2772	78	14	validation	validation	NOUN
admet-2772	78	15	[	[	X
admet-2772	78	16	4	4	NUM
admet-2772	78	17	]	]	PUNCT
admet-2772	78	18	.	.	PUNCT
admet-2772	79	1	a	a	DET
admet-2772	79	2	comprehensive	comprehensive	ADJ
admet-2772	79	3	list	list	NOUN
admet-2772	79	4	of	of	ADP
admet-2772	79	5	such	such	ADJ
admet-2772	79	6	databases	database	NOUN
admet-2772	79	7	is	be	AUX
admet-2772	79	8	presented	present	VERB
admet-2772	79	9	in	in	ADP
admet-2772	79	10	table	table	NOUN
admet-2772	79	11	1	1	NUM
admet-2772	79	12	.	.	PUNCT
admet-2772	79	13	data	datum	NOUN
admet-2772	79	14	preprocessing	preprocessing	NOUN
admet-2772	79	15	,	,	PUNCT
admet-2772	79	16	including	include	VERB
admet-2772	79	17	cleaning	cleaning	NOUN
admet-2772	79	18	,	,	PUNCT
admet-2772	79	19	normalization	normalization	NOUN
admet-2772	79	20	,	,	PUNCT
admet-2772	79	21	and	and	CCONJ
admet-2772	79	22	feature	feature	NOUN
admet-2772	79	23	selection	selection	NOUN
admet-2772	79	24	,	,	PUNCT
admet-2772	79	25	is	be	AUX
admet-2772	79	26	essential	essential	ADJ
admet-2772	79	27	for	for	ADP
admet-2772	79	28	improving	improve	VERB
admet-2772	79	29	data	datum	NOUN
admet-2772	79	30	quality	quality	NOUN
admet-2772	79	31	admet	admet	PROPN
admet-2772	79	32	&	&	CCONJ
admet-2772	79	33	dmpk	dmpk	PROPN
admet-2772	79	34	13(3	13(3	NUM
admet-2772	79	35	)	)	PUNCT
admet-2772	79	36	(	(	PUNCT
admet-2772	79	37	2025	2025	NUM
admet-2772	79	38	)	)	PUNCT
admet-2772	79	39	2772	2772	NUM
admet-2772	79	40	machine	machine	NOUN
admet-2772	79	41	learning	learning	NOUN
admet-2772	79	42	models	model	NOUN
admet-2772	79	43	for	for	ADP
admet-2772	79	44	admet	admet	ADJ
admet-2772	79	45	prediction	prediction	NOUN
admet-2772	79	46	in	in	ADP
admet-2772	79	47	drug	drug	NOUN
admet-2772	79	48	development	development	NOUN
admet-2772	79	49	doi	doi	PROPN
admet-2772	79	50	:	:	PUNCT
admet-2772	79	51	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	79	52	5	5	NUM
admet-2772	79	53	and	and	CCONJ
admet-2772	79	54	reducing	reduce	VERB
admet-2772	79	55	irrelevant	irrelevant	ADJ
admet-2772	79	56	or	or	CCONJ
admet-2772	79	57	redundant	redundant	ADJ
admet-2772	79	58	information	information	NOUN
admet-2772	79	59	[	[	X
admet-2772	79	60	17	17	NUM
admet-2772	79	61	]	]	PUNCT
admet-2772	79	62	.	.	PUNCT
admet-2772	80	1	feature	feature	NOUN
admet-2772	80	2	quality	quality	NOUN
admet-2772	80	3	,	,	PUNCT
admet-2772	80	4	such	such	ADJ
admet-2772	80	5	as	as	ADP
admet-2772	80	6	relevant	relevant	ADJ
admet-2772	80	7	,	,	PUNCT
admet-2772	80	8	informative	informative	ADJ
admet-2772	80	9	,	,	PUNCT
admet-2772	80	10	and	and	CCONJ
admet-2772	80	11	predictive	predictive	VERB
admet-2772	80	12	a	a	DET
admet-2772	80	13	specific	specific	ADJ
admet-2772	80	14	feature	feature	NOUN
admet-2772	80	15	is	be	AUX
admet-2772	80	16	within	within	ADP
admet-2772	80	17	a	a	DET
admet-2772	80	18	dataset	dataset	NOUN
admet-2772	80	19	has	have	AUX
admet-2772	80	20	been	be	AUX
admet-2772	80	21	shown	show	VERB
admet-2772	80	22	to	to	PART
admet-2772	80	23	be	be	AUX
admet-2772	80	24	more	more	ADV
admet-2772	80	25	important	important	ADJ
admet-2772	80	26	than	than	ADP
admet-2772	80	27	feature	feature	NOUN
admet-2772	80	28	quantity	quantity	NOUN
admet-2772	80	29	,	,	PUNCT
admet-2772	80	30	with	with	ADP
admet-2772	80	31	models	model	NOUN
admet-2772	80	32	trained	train	VERB
admet-2772	80	33	on	on	ADP
admet-2772	80	34	non	non	ADJ
admet-2772	80	35	-	-	ADJ
admet-2772	80	36	redundant	redundant	ADJ
admet-2772	80	37	data	datum	NOUN
admet-2772	80	38	achieving	achieve	VERB
admet-2772	80	39	higher	high	ADJ
admet-2772	80	40	accuracy	accuracy	NOUN
admet-2772	80	41	(	(	PUNCT
admet-2772	80	42	>	>	SYM
admet-2772	80	43	80	80	NUM
admet-2772	80	44	%	%	NOUN
admet-2772	80	45	)	)	PUNCT
admet-2772	80	46	compared	compare	VERB
admet-2772	80	47	to	to	ADP
admet-2772	80	48	those	those	PRON
admet-2772	80	49	trained	train	VERB
admet-2772	80	50	on	on	ADP
admet-2772	80	51	all	all	DET
admet-2772	80	52	features	feature	NOUN
admet-2772	80	53	[	[	X
admet-2772	80	54	18	18	NUM
admet-2772	80	55	]	]	PUNCT
admet-2772	80	56	.	.	PUNCT
admet-2772	81	1	when	when	SCONJ
admet-2772	81	2	dealing	deal	VERB
admet-2772	81	3	with	with	ADP
admet-2772	81	4	imbalanced	imbalanced	ADJ
admet-2772	81	5	datasets	dataset	NOUN
admet-2772	81	6	,	,	PUNCT
admet-2772	81	7	combining	combine	VERB
admet-2772	81	8	feature	feature	NOUN
admet-2772	81	9	selection	selection	NOUN
admet-2772	81	10	and	and	CCONJ
admet-2772	81	11	data	datum	NOUN
admet-2772	81	12	sampling	sample	VERB
admet-2772	81	13	techniques	technique	NOUN
admet-2772	81	14	can	can	AUX
admet-2772	81	15	significantly	significantly	ADV
admet-2772	81	16	improve	improve	VERB
admet-2772	81	17	software	software	NOUN
admet-2772	81	18	defect	defect	NOUN
admet-2772	81	19	prediction	prediction	NOUN
admet-2772	81	20	performance	performance	NOUN
admet-2772	81	21	.	.	PUNCT
admet-2772	82	1	empirical	empirical	ADJ
admet-2772	82	2	results	result	NOUN
admet-2772	82	3	suggest	suggest	VERB
admet-2772	82	4	that	that	SCONJ
admet-2772	82	5	feature	feature	NOUN
admet-2772	82	6	selection	selection	NOUN
admet-2772	82	7	based	base	VERB
admet-2772	82	8	on	on	ADP
admet-2772	82	9	sampled	sample	VERB
admet-2772	82	10	data	data	NOUN
admet-2772	82	11	outperforms	outperform	NOUN
admet-2772	82	12	feature	feature	NOUN
admet-2772	82	13	selection	selection	NOUN
admet-2772	82	14	based	base	VERB
admet-2772	82	15	on	on	ADP
admet-2772	82	16	original	original	ADJ
admet-2772	82	17	data	datum	NOUN
admet-2772	82	18	[	[	X
admet-2772	82	19	19	19	NUM
admet-2772	82	20	]	]	PUNCT
admet-2772	82	21	.	.	PUNCT
admet-2772	83	1	these	these	DET
admet-2772	83	2	findings	finding	NOUN
admet-2772	83	3	highlight	highlight	VERB
admet-2772	83	4	the	the	DET
admet-2772	83	5	importance	importance	NOUN
admet-2772	83	6	of	of	ADP
admet-2772	83	7	carefully	carefully	ADV
admet-2772	83	8	considering	consider	VERB
admet-2772	83	9	data	datum	NOUN
admet-2772	83	10	quality	quality	NOUN
admet-2772	83	11	,	,	PUNCT
admet-2772	83	12	feature	feature	NOUN
admet-2772	83	13	selection	selection	NOUN
admet-2772	83	14	,	,	PUNCT
admet-2772	83	15	and	and	CCONJ
admet-2772	83	16	handling	handling	NOUN
admet-2772	83	17	of	of	ADP
admet-2772	83	18	imbalanced	imbalanced	ADJ
admet-2772	83	19	datasets	dataset	NOUN
admet-2772	83	20	in	in	ADP
admet-2772	83	21	ml	ml	NOUN
admet-2772	83	22	tasks	task	NOUN
admet-2772	83	23	to	to	PART
admet-2772	83	24	achieve	achieve	VERB
admet-2772	83	25	optimal	optimal	ADJ
admet-2772	83	26	model	model	NOUN
admet-2772	83	27	performance	performance	NOUN
admet-2772	83	28	.	.	PUNCT
admet-2772	84	1	table	table	NOUN
admet-2772	84	2	1	1	NUM
admet-2772	84	3	.	.	PUNCT
admet-2772	85	1	a	a	DET
admet-2772	85	2	list	list	NOUN
admet-2772	85	3	of	of	ADP
admet-2772	85	4	databases	database	NOUN
admet-2772	85	5	that	that	PRON
admet-2772	85	6	contain	contain	VERB
admet-2772	85	7	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	85	8	data	datum	NOUN
admet-2772	85	9	for	for	ADP
admet-2772	85	10	machine	machine	NOUN
admet-2772	85	11	learning	learning	NOUN
admet-2772	85	12	analyses	analyse	VERB
admet-2772	85	13	database	database	NOUN
admet-2772	85	14	source	source	NOUN
admet-2772	85	15	ref	ref	NOUN
admet-2772	85	16	.	.	PUNCT
admet-2772	86	1	pk	pk	NOUN
admet-2772	86	2	-	-	PUNCT
admet-2772	86	3	dbpharmacokinetics	dbpharmacokinetic	NOUN
admet-2772	86	4	database	database	NOUN
admet-2772	86	5	https://pk-db.com/	https://pk-db.com/	NOUN
admet-2772	87	1	[	[	X
admet-2772	87	2	20	20	NUM
admet-2772	87	3	]	]	X
admet-2772	87	4	e	e	X
admet-2772	87	5	-	-	NOUN
admet-2772	87	6	drug3d	drug3d	ADJ
admet-2772	87	7	https://chemoinfo.ipmc.cnrs.fr/moldb/index.php	https://chemoinfo.ipmc.cnrs.fr/moldb/index.php	VERB
admet-2772	88	1	[	[	X
admet-2772	88	2	21	21	NUM
admet-2772	88	3	]	]	PUNCT
admet-2772	88	4	drugbank	drugbank	NOUN
admet-2772	88	5	https://go.drugbank.com	https://go.drugbank.com	NOUN
admet-2772	89	1	[	[	X
admet-2772	89	2	22	22	NUM
admet-2772	89	3	]	]	PUNCT
admet-2772	89	4	chembl	chembl	NOUN
admet-2772	89	5	https://www.ebi.ac.uk/chembl/	https://www.ebi.ac.uk/chembl/	PROPN
admet-2772	90	1	[	[	X
admet-2772	90	2	23	23	NUM
admet-2772	90	3	]	]	X
admet-2772	90	4	therapeutic	therapeutic	ADJ
admet-2772	90	5	target	target	NOUN
admet-2772	90	6	database	database	NOUN
admet-2772	90	7	https://db.idrblab.net/ttd/	https://db.idrblab.net/ttd/	NOUN
admet-2772	90	8	[	[	X
admet-2772	90	9	24	24	NUM
admet-2772	90	10	]	]	PUNCT
admet-2772	90	11	cvtdb	cvtdb	NOUN
admet-2772	90	12	https://github.com/usepa/comptox-pk-cvtdb	https://github.com/usepa/comptox-pk-cvtdb	PRON
admet-2772	91	1	[	[	X
admet-2772	91	2	25	25	NUM
admet-2772	91	3	]	]	PUNCT
admet-2772	91	4	pubchem	pubchem	NOUN
admet-2772	91	5	https://pubchem.ncbi.nlm.nih.gov/	https://pubchem.ncbi.nlm.nih.gov/	VERB
admet-2772	91	6	[	[	X
admet-2772	91	7	26	26	NUM
admet-2772	91	8	]	]	PUNCT
admet-2772	91	9	zinc	zinc	NOUN
admet-2772	91	10	https://zinc15.docking.org/	https://zinc15.docking.org/	NOUN
admet-2772	92	1	[	[	X
admet-2772	92	2	27	27	NUM
admet-2772	92	3	]	]	PUNCT
admet-2772	92	4	supercyp	supercyp	NOUN
admet-2772	93	1	https://insilico-cyp.charite.de/supercypspred/	https://insilico-cyp.charite.de/supercypspred/	X
admet-2772	94	1	[	[	X
admet-2772	94	2	28	28	NUM
admet-2772	94	3	]	]	X
admet-2772	94	4	the	the	DET
admet-2772	94	5	admet	admet	PROPN
admet-2772	94	6	prediction	prediction	NOUN
admet-2772	94	7	database	database	NOUN
admet-2772	94	8	http://modem.ucsd.edu/adme/databases/databases.htm	http://modem.ucsd.edu/adme/databases/databases.htm	PROPN
admet-2772	95	1	[	[	X
admet-2772	95	2	29	29	NUM
admet-2772	95	3	]	]	SYM
admet-2772	95	4	2.3	2.3	NUM
admet-2772	95	5	.	.	PUNCT
admet-2772	96	1	feature	feature	NOUN
admet-2772	96	2	engineering	engineering	NOUN
admet-2772	96	3	in	in	ADP
admet-2772	96	4	adme	adme	NOUN
admet-2772	96	5	-	-	PUNCT
admet-2772	96	6	tox	tox	NOUN
admet-2772	96	7	prediction	prediction	NOUN
admet-2772	96	8	feature	feature	NOUN
admet-2772	96	9	engineering	engineering	NOUN
admet-2772	96	10	plays	play	VERB
admet-2772	96	11	a	a	DET
admet-2772	96	12	crucial	crucial	ADJ
admet-2772	96	13	role	role	NOUN
admet-2772	96	14	in	in	ADP
admet-2772	96	15	improving	improve	VERB
admet-2772	96	16	admet	admet	NOUN
admet-2772	96	17	prediction	prediction	NOUN
admet-2772	96	18	accuracy	accuracy	NOUN
admet-2772	96	19	.	.	PUNCT
admet-2772	97	1	traditional	traditional	ADJ
admet-2772	97	2	approaches	approach	NOUN
admet-2772	97	3	rely	rely	VERB
admet-2772	97	4	on	on	ADP
admet-2772	97	5	fixed	fix	VERB
admet-2772	97	6	fingerprint	fingerprint	NOUN
admet-2772	97	7	,	,	PUNCT
admet-2772	97	8	i.e.	i.e.	X
admet-2772	97	9	an	an	DET
admet-2772	97	10	efficient	efficient	ADJ
admet-2772	97	11	and	and	CCONJ
admet-2772	97	12	quick	quick	ADJ
admet-2772	97	13	means	mean	NOUN
admet-2772	97	14	of	of	ADP
admet-2772	97	15	portraying	portray	VERB
admet-2772	97	16	fixed	fix	VERB
admet-2772	97	17	-	-	PUNCT
admet-2772	97	18	length	length	NOUN
admet-2772	97	19	data	datum	NOUN
admet-2772	97	20	,	,	PUNCT
admet-2772	97	21	ignoring	ignore	VERB
admet-2772	97	22	the	the	DET
admet-2772	97	23	internal	internal	ADJ
admet-2772	97	24	substructures	substructure	NOUN
admet-2772	97	25	within	within	ADP
admet-2772	97	26	representations	representation	NOUN
admet-2772	97	27	of	of	ADP
admet-2772	97	28	molecules	molecule	NOUN
admet-2772	97	29	[	[	X
admet-2772	97	30	30	30	NUM
admet-2772	97	31	]	]	PUNCT
admet-2772	97	32	.	.	PUNCT
admet-2772	98	1	however	however	ADV
admet-2772	98	2	,	,	PUNCT
admet-2772	98	3	recent	recent	ADJ
admet-2772	98	4	advancements	advancement	NOUN
admet-2772	98	5	involve	involve	VERB
admet-2772	98	6	learning	learn	VERB
admet-2772	98	7	task	task	NOUN
admet-2772	98	8	-	-	PUNCT
admet-2772	98	9	specific	specific	ADJ
admet-2772	98	10	features	feature	NOUN
admet-2772	98	11	by	by	ADP
admet-2772	98	12	representing	represent	VERB
admet-2772	98	13	molecules	molecule	NOUN
admet-2772	98	14	as	as	ADP
admet-2772	98	15	graphs	graph	NOUN
admet-2772	98	16	,	,	PUNCT
admet-2772	98	17	where	where	SCONJ
admet-2772	98	18	atoms	atom	NOUN
admet-2772	98	19	are	be	AUX
admet-2772	98	20	nodes	node	NOUN
admet-2772	98	21	and	and	CCONJ
admet-2772	98	22	bonds	bond	NOUN
admet-2772	98	23	are	be	AUX
admet-2772	98	24	edges	edge	NOUN
admet-2772	98	25	.	.	PUNCT
admet-2772	99	1	graph	graph	NOUN
admet-2772	99	2	convolutions	convolution	NOUN
admet-2772	99	3	applied	apply	VERB
admet-2772	99	4	to	to	ADP
admet-2772	99	5	these	these	DET
admet-2772	99	6	explicit	explicit	ADJ
admet-2772	99	7	molecular	molecular	ADJ
admet-2772	99	8	representations	representation	NOUN
admet-2772	99	9	have	have	AUX
admet-2772	99	10	achieved	achieve	VERB
admet-2772	99	11	unprecedented	unprecedented	ADJ
admet-2772	99	12	accuracy	accuracy	NOUN
admet-2772	99	13	in	in	ADP
admet-2772	99	14	admet	admet	PROPN
admet-2772	99	15	property	property	NOUN
admet-2772	99	16	prediction	prediction	NOUN
admet-2772	100	1	[	[	X
admet-2772	100	2	31	31	NUM
admet-2772	100	3	]	]	PUNCT
admet-2772	100	4	.	.	PUNCT
admet-2772	101	1	feature	feature	NOUN
admet-2772	101	2	selection	selection	NOUN
admet-2772	101	3	methods	method	NOUN
admet-2772	101	4	can	can	AUX
admet-2772	101	5	help	help	VERB
admet-2772	101	6	determine	determine	VERB
admet-2772	101	7	relevant	relevant	ADJ
admet-2772	101	8	properties	property	NOUN
admet-2772	101	9	for	for	ADP
admet-2772	101	10	specific	specific	ADJ
admet-2772	101	11	classification	classification	NOUN
admet-2772	101	12	or	or	CCONJ
admet-2772	101	13	regression	regression	NOUN
admet-2772	101	14	tasks	task	NOUN
admet-2772	101	15	,	,	PUNCT
admet-2772	101	16	alleviating	alleviate	VERB
admet-2772	101	17	the	the	DET
admet-2772	101	18	need	need	NOUN
admet-2772	101	19	for	for	ADP
admet-2772	101	20	time	time	NOUN
admet-2772	101	21	-	-	PUNCT
admet-2772	101	22	consuming	consume	VERB
admet-2772	101	23	experimental	experimental	ADJ
admet-2772	101	24	assessments	assessment	NOUN
admet-2772	101	25	[	[	X
admet-2772	101	26	32	32	NUM
admet-2772	101	27	]	]	PUNCT
admet-2772	101	28	.	.	PUNCT
admet-2772	102	1	filter	filter	NOUN
admet-2772	102	2	methods	method	NOUN
admet-2772	102	3	are	be	AUX
admet-2772	102	4	employed	employ	VERB
admet-2772	102	5	during	during	ADP
admet-2772	102	6	the	the	DET
admet-2772	102	7	pre	pre	ADJ
admet-2772	102	8	-	-	ADJ
admet-2772	102	9	processing	processing	ADJ
admet-2772	102	10	stage	stage	NOUN
admet-2772	102	11	to	to	PART
admet-2772	102	12	select	select	VERB
admet-2772	102	13	features	feature	NOUN
admet-2772	102	14	from	from	ADP
admet-2772	102	15	the	the	DET
admet-2772	102	16	dataset	dataset	NOUN
admet-2772	102	17	without	without	ADP
admet-2772	102	18	relying	rely	VERB
admet-2772	102	19	on	on	ADP
admet-2772	102	20	any	any	DET
admet-2772	102	21	specific	specific	ADJ
admet-2772	102	22	machine	machine	NOUN
admet-2772	102	23	learning	learning	NOUN
admet-2772	102	24	algorithm	algorithm	NOUN
admet-2772	102	25	.	.	PUNCT
admet-2772	103	1	these	these	DET
admet-2772	103	2	methods	method	NOUN
admet-2772	103	3	swiftly	swiftly	ADV
admet-2772	103	4	identify	identify	VERB
admet-2772	103	5	and	and	CCONJ
admet-2772	103	6	eliminate	eliminate	VERB
admet-2772	103	7	duplicated	duplicate	VERB
admet-2772	103	8	,	,	PUNCT
admet-2772	103	9	correlated	correlate	VERB
admet-2772	103	10	,	,	PUNCT
admet-2772	103	11	and	and	CCONJ
admet-2772	103	12	redundant	redundant	ADJ
admet-2772	103	13	features	feature	NOUN
admet-2772	103	14	,	,	PUNCT
admet-2772	103	15	making	make	VERB
admet-2772	103	16	them	they	PRON
admet-2772	103	17	highly	highly	ADV
admet-2772	103	18	efficient	efficient	ADJ
admet-2772	103	19	in	in	ADP
admet-2772	103	20	computational	computational	ADJ
admet-2772	103	21	terms	term	NOUN
admet-2772	103	22	[	[	X
admet-2772	103	23	33	33	NUM
admet-2772	103	24	]	]	PUNCT
admet-2772	103	25	.	.	PUNCT
admet-2772	104	1	they	they	PRON
admet-2772	104	2	excel	excel	VERB
admet-2772	104	3	at	at	ADP
admet-2772	104	4	isolating	isolate	VERB
admet-2772	104	5	individual	individual	ADJ
admet-2772	104	6	features	feature	NOUN
admet-2772	104	7	for	for	ADP
admet-2772	104	8	evaluation	evaluation	NOUN
admet-2772	104	9	,	,	PUNCT
admet-2772	104	10	which	which	PRON
admet-2772	104	11	proves	prove	VERB
admet-2772	104	12	beneficial	beneficial	ADJ
admet-2772	104	13	when	when	SCONJ
admet-2772	104	14	features	feature	NOUN
admet-2772	104	15	operate	operate	VERB
admet-2772	104	16	independently	independently	ADV
admet-2772	104	17	.	.	PUNCT
admet-2772	105	1	however	however	ADV
admet-2772	105	2	,	,	PUNCT
admet-2772	105	3	they	they	PRON
admet-2772	105	4	fall	fall	VERB
admet-2772	105	5	short	short	ADV
admet-2772	105	6	in	in	ADP
admet-2772	105	7	addressing	address	VERB
admet-2772	105	8	multicollinearity	multicollinearity	NOUN
admet-2772	105	9	,	,	PUNCT
admet-2772	105	10	as	as	SCONJ
admet-2772	105	11	they	they	PRON
admet-2772	105	12	do	do	AUX
admet-2772	105	13	not	not	PART
admet-2772	105	14	mitigate	mitigate	VERB
admet-2772	105	15	the	the	DET
admet-2772	105	16	interdependencies	interdependency	NOUN
admet-2772	105	17	between	between	ADP
admet-2772	105	18	features	feature	NOUN
admet-2772	105	19	.	.	PUNCT
admet-2772	106	1	despite	despite	SCONJ
admet-2772	106	2	their	their	PRON
admet-2772	106	3	speed	speed	NOUN
admet-2772	106	4	and	and	CCONJ
admet-2772	106	5	cost	cost	NOUN
admet-2772	106	6	-	-	PUNCT
admet-2772	106	7	effectiveness	effectiveness	NOUN
admet-2772	106	8	,	,	PUNCT
admet-2772	106	9	filter	filter	NOUN
admet-2772	106	10	methods	method	NOUN
admet-2772	106	11	may	may	AUX
admet-2772	106	12	not	not	PART
admet-2772	106	13	capture	capture	VERB
admet-2772	106	14	the	the	DET
admet-2772	106	15	potential	potential	ADJ
admet-2772	106	16	performance	performance	NOUN
admet-2772	106	17	enhancements	enhancement	NOUN
admet-2772	106	18	achievable	achievable	ADJ
admet-2772	106	19	through	through	ADP
admet-2772	106	20	feature	feature	NOUN
admet-2772	106	21	combinations	combination	NOUN
admet-2772	106	22	[	[	X
admet-2772	106	23	34	34	NUM
admet-2772	106	24	]	]	PUNCT
admet-2772	106	25	.	.	PUNCT
admet-2772	107	1	in	in	ADP
admet-2772	107	2	a	a	DET
admet-2772	107	3	study	study	NOUN
admet-2772	107	4	by	by	ADP
admet-2772	107	5	ahmed	ahmed	PROPN
admet-2772	107	6	and	and	CCONJ
admet-2772	107	7	ramakrishnan	ramakrishnan	PROPN
admet-2772	107	8	[	[	X
admet-2772	107	9	35	35	NUM
admet-2772	107	10	]	]	PUNCT
admet-2772	107	11	,	,	PUNCT
admet-2772	107	12	correlation	correlation	NOUN
admet-2772	107	13	-	-	PUNCT
admet-2772	107	14	based	base	VERB
admet-2772	107	15	feature	feature	NOUN
admet-2772	107	16	selection	selection	NOUN
admet-2772	107	17	(	(	PUNCT
admet-2772	107	18	cfs	cfs	PROPN
admet-2772	107	19	)	)	PUNCT
admet-2772	107	20	,	,	PUNCT
admet-2772	107	21	a	a	DET
admet-2772	107	22	type	type	NOUN
admet-2772	107	23	of	of	ADP
admet-2772	107	24	filter	filter	NOUN
admet-2772	107	25	method	method	NOUN
admet-2772	107	26	to	to	PART
admet-2772	107	27	identify	identify	VERB
admet-2772	107	28	fundamental	fundamental	ADJ
admet-2772	107	29	molecular	molecular	ADJ
admet-2772	107	30	descriptors	descriptor	NOUN
admet-2772	107	31	for	for	ADP
admet-2772	107	32	predicting	predict	VERB
admet-2772	107	33	oral	oral	ADJ
admet-2772	107	34	bioavailability	bioavailability	NOUN
admet-2772	107	35	.	.	PUNCT
admet-2772	108	1	out	out	ADP
admet-2772	108	2	of	of	ADP
admet-2772	108	3	247	247	NUM
admet-2772	108	4	physicochemical	physicochemical	ADJ
admet-2772	108	5	descriptors	descriptor	NOUN
admet-2772	108	6	from	from	ADP
admet-2772	108	7	2279	2279	NUM
admet-2772	108	8	molecules	molecule	NOUN
admet-2772	108	9	,	,	PUNCT
admet-2772	108	10	47	47	NUM
admet-2772	108	11	were	be	AUX
admet-2772	108	12	found	find	VERB
admet-2772	108	13	to	to	PART
admet-2772	108	14	be	be	AUX
admet-2772	108	15	major	major	ADJ
admet-2772	108	16	contributors	contributor	NOUN
admet-2772	108	17	to	to	ADP
admet-2772	108	18	oral	oral	ADJ
admet-2772	108	19	bioavailability	bioavailability	NOUN
admet-2772	108	20	,	,	PUNCT
admet-2772	108	21	as	as	SCONJ
admet-2772	108	22	confirmed	confirm	VERB
admet-2772	108	23	by	by	ADP
admet-2772	108	24	the	the	DET
admet-2772	108	25	logistic	logistic	ADJ
admet-2772	108	26	algorithm	algorithm	NOUN
admet-2772	108	27	with	with	ADP
admet-2772	108	28	a	a	DET
admet-2772	108	29	predictive	predictive	ADJ
admet-2772	108	30	accuracy	accuracy	NOUN
admet-2772	108	31	exceeding	exceed	VERB
admet-2772	108	32	71	71	NUM
admet-2772	108	33	%	%	NOUN
admet-2772	108	34	.	.	PUNCT
admet-2772	109	1	wrapper	wrapper	NOUN
admet-2772	109	2	methods	method	NOUN
admet-2772	109	3	,	,	PUNCT
admet-2772	109	4	also	also	ADV
admet-2772	109	5	known	know	VERB
admet-2772	109	6	as	as	ADP
admet-2772	109	7	greedy	greedy	ADJ
admet-2772	109	8	algorithms	algorithm	NOUN
admet-2772	109	9	,	,	PUNCT
admet-2772	109	10	iteratively	iteratively	ADV
admet-2772	109	11	train	train	VERB
admet-2772	109	12	the	the	DET
admet-2772	109	13	algorithm	algorithm	NOUN
admet-2772	109	14	using	use	VERB
admet-2772	109	15	subsets	subset	NOUN
admet-2772	109	16	of	of	ADP
admet-2772	109	17	features	feature	NOUN
admet-2772	109	18	.	.	PUNCT
admet-2772	110	1	these	these	DET
admet-2772	110	2	methods	method	NOUN
admet-2772	110	3	dynamically	dynamically	ADV
admet-2772	110	4	add	add	VERB
admet-2772	110	5	and	and	CCONJ
admet-2772	110	6	remove	remove	VERB
admet-2772	110	7	features	feature	NOUN
admet-2772	110	8	based	base	VERB
admet-2772	110	9	on	on	ADP
admet-2772	110	10	insights	insight	NOUN
admet-2772	110	11	gained	gain	VERB
admet-2772	110	12	during	during	ADP
admet-2772	110	13	previous	previous	ADJ
admet-2772	110	14	model	model	NOUN
admet-2772	110	15	training	training	NOUN
admet-2772	110	16	iterations	iteration	NOUN
admet-2772	110	17	[	[	X
admet-2772	110	18	36	36	NUM
admet-2772	110	19	]	]	PUNCT
admet-2772	110	20	.	.	PUNCT
admet-2772	111	1	unlike	unlike	ADP
admet-2772	111	2	filter	filter	NOUN
admet-2772	111	3	methods	method	NOUN
admet-2772	111	4	,	,	PUNCT
admet-2772	111	5	wrapper	wrapper	NOUN
admet-2772	111	6	methods	method	NOUN
admet-2772	111	7	offer	offer	VERB
admet-2772	111	8	an	an	DET
admet-2772	111	9	optimal	optimal	ADJ
admet-2772	111	10	feature	feature	NOUN
admet-2772	111	11	set	set	VERB
admet-2772	111	12	for	for	ADP
admet-2772	111	13	model	model	NOUN
admet-2772	111	14	training	training	NOUN
admet-2772	111	15	,	,	PUNCT
admet-2772	111	16	leading	lead	VERB
admet-2772	111	17	to	to	ADP
admet-2772	111	18	superior	superior	ADJ
admet-2772	111	19	accuracy	accuracy	NOUN
admet-2772	111	20	.	.	PUNCT
admet-2772	112	1	however	however	ADV
admet-2772	112	2	,	,	PUNCT
admet-2772	112	3	their	their	PRON
admet-2772	112	4	computational	computational	ADJ
admet-2772	112	5	demands	demand	NOUN
admet-2772	112	6	are	be	AUX
admet-2772	112	7	higher	high	ADJ
admet-2772	112	8	compared	compare	VERB
admet-2772	112	9	to	to	ADP
admet-2772	112	10	filter	filter	NOUN
admet-2772	112	11	methods	method	NOUN
admet-2772	112	12	due	due	ADP
admet-2772	112	13	to	to	ADP
admet-2772	112	14	the	the	DET
admet-2772	112	15	iterative	iterative	ADJ
admet-2772	112	16	nature	nature	NOUN
admet-2772	112	17	of	of	ADP
admet-2772	112	18	the	the	DET
admet-2772	112	19	process	process	NOUN
admet-2772	112	20	[	[	X
admet-2772	112	21	33	33	NUM
admet-2772	112	22	]	]	PUNCT
admet-2772	112	23	.	.	PUNCT
admet-2772	113	1	in	in	ADP
admet-2772	113	2	embedded	embed	VERB
admet-2772	113	3	methods	method	NOUN
admet-2772	113	4	,	,	PUNCT
admet-2772	113	5	the	the	DET
admet-2772	113	6	feature	feature	NOUN
admet-2772	113	7	selection	selection	NOUN
admet-2772	113	8	algorithm	algorithm	NOUN
admet-2772	113	9	is	be	AUX
admet-2772	113	10	integrated	integrate	VERB
admet-2772	113	11	into	into	ADP
admet-2772	113	12	the	the	DET
admet-2772	113	13	learning	learning	NOUN
admet-2772	113	14	algorithm	algorithm	NOUN
admet-2772	113	15	,	,	PUNCT
admet-2772	113	16	possessing	possess	VERB
admet-2772	113	17	inherent	inherent	ADJ
admet-2772	113	18	feature	feature	NOUN
admet-2772	113	19	selection	selection	NOUN
admet-2772	113	20	capabilities	capability	NOUN
admet-2772	113	21	.	.	PUNCT
admet-2772	114	1	the	the	DET
admet-2772	114	2	models	model	NOUN
admet-2772	114	3	combine	combine	AUX
admet-2772	114	4	filtering	filter	VERB
admet-2772	114	5	and	and	CCONJ
admet-2772	114	6	wrapping	wrap	VERB
admet-2772	114	7	techniques	technique	NOUN
admet-2772	114	8	to	to	ADP
admet-2772	114	9	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	114	10	https://pk-db.com/	https://pk-db.com/	NOUN
admet-2772	114	11	https://chemoinfo.ipmc.cnrs.fr/moldb/index.php	https://chemoinfo.ipmc.cnrs.fr/moldb/index.php	VERB
admet-2772	114	12	https://go.drugbank.com/	https://go.drugbank.com/	PROPN
admet-2772	114	13	https://www.ebi.ac.uk/chembl/	https://www.ebi.ac.uk/chembl/	PROPN
admet-2772	114	14	https://db.idrblab.net/ttd/	https://db.idrblab.net/ttd/	PROPN
admet-2772	114	15	https://github.com/usepa/comptox-pk-cvtdb	https://github.com/usepa/comptox-pk-cvtdb	PRON
admet-2772	114	16	https://pubchem.ncbi.nlm.nih.gov/	https://pubchem.ncbi.nlm.nih.gov/	VERB
admet-2772	114	17	https://zinc15.docking.org/	https://zinc15.docking.org/	PRON
admet-2772	115	1	https://insilico-cyp.charite.de/supercypspred/	https://insilico-cyp.charite.de/supercypspred/	NOUN
admet-2772	115	2	http://modem.ucsd.edu/adme/databases/databases.htm	http://modem.ucsd.edu/adme/databases/databases.htm	PROPN
admet-2772	115	3	m.	m.	NOUN
admet-2772	115	4	venkataraman	venkataraman	PROPN
admet-2772	115	5	et	et	PROPN
admet-2772	115	6	al	al	PROPN
admet-2772	115	7	.	.	PROPN
admet-2772	115	8	admet	admet	PROPN
admet-2772	115	9	&	&	CCONJ
admet-2772	115	10	dmpk	dmpk	PROPN
admet-2772	115	11	13(3	13(3	NUM
admet-2772	115	12	)	)	PUNCT
admet-2772	115	13	(	(	PUNCT
admet-2772	115	14	2025	2025	NUM
admet-2772	115	15	)	)	PUNCT
admet-2772	115	16	2772	2772	NUM
admet-2772	115	17	6	6	NUM
admet-2772	115	18	optimize	optimize	NOUN
admet-2772	115	19	feature	feature	NOUN
admet-2772	115	20	selection	selection	NOUN
admet-2772	115	21	.	.	PUNCT
admet-2772	116	1	initially	initially	ADV
admet-2772	116	2	,	,	PUNCT
admet-2772	116	3	these	these	DET
admet-2772	116	4	models	model	NOUN
admet-2772	116	5	utilize	utilize	VERB
admet-2772	116	6	a	a	DET
admet-2772	116	7	filter	filter	NOUN
admet-2772	116	8	-	-	PUNCT
admet-2772	116	9	based	base	VERB
admet-2772	116	10	approach	approach	NOUN
admet-2772	116	11	to	to	PART
admet-2772	116	12	reduce	reduce	VERB
admet-2772	116	13	the	the	DET
admet-2772	116	14	feature	feature	NOUN
admet-2772	116	15	space	space	NOUN
admet-2772	116	16	dimensionality	dimensionality	NOUN
admet-2772	116	17	.	.	PUNCT
admet-2772	117	1	subsequently	subsequently	ADV
admet-2772	117	2	,	,	PUNCT
admet-2772	117	3	the	the	DET
admet-2772	117	4	best	good	ADJ
admet-2772	117	5	subset	subset	NOUN
admet-2772	117	6	of	of	ADP
admet-2772	117	7	features	feature	NOUN
admet-2772	117	8	identified	identify	VERB
admet-2772	117	9	through	through	ADP
admet-2772	117	10	the	the	DET
admet-2772	117	11	filter	filter	NOUN
admet-2772	117	12	-	-	PUNCT
admet-2772	117	13	based	base	VERB
admet-2772	117	14	step	step	NOUN
admet-2772	117	15	is	be	AUX
admet-2772	117	16	incorporated	incorporate	VERB
admet-2772	117	17	using	use	VERB
admet-2772	117	18	a	a	DET
admet-2772	117	19	wrapper	wrapper	NOUN
admet-2772	117	20	technique	technique	NOUN
admet-2772	117	21	[	[	X
admet-2772	117	22	37	37	NUM
admet-2772	117	23	]	]	PUNCT
admet-2772	117	24	.	.	PUNCT
admet-2772	118	1	embedded	embed	VERB
admet-2772	118	2	methods	method	NOUN
admet-2772	118	3	combine	combine	VERB
admet-2772	118	4	the	the	DET
admet-2772	118	5	strengths	strength	NOUN
admet-2772	118	6	of	of	ADP
admet-2772	118	7	filter	filter	NOUN
admet-2772	118	8	and	and	CCONJ
admet-2772	118	9	wrapper	wrapper	NOUN
admet-2772	118	10	techniques	technique	NOUN
admet-2772	118	11	while	while	SCONJ
admet-2772	118	12	mitigating	mitigate	VERB
admet-2772	118	13	their	their	PRON
admet-2772	118	14	respective	respective	ADJ
admet-2772	118	15	drawbacks	drawback	NOUN
admet-2772	118	16	.	.	PUNCT
admet-2772	119	1	they	they	PRON
admet-2772	119	2	inherit	inherit	VERB
admet-2772	119	3	the	the	DET
admet-2772	119	4	speed	speed	NOUN
admet-2772	119	5	of	of	ADP
admet-2772	119	6	filter	filter	NOUN
admet-2772	119	7	methods	method	NOUN
admet-2772	119	8	while	while	SCONJ
admet-2772	119	9	surpassing	surpass	VERB
admet-2772	119	10	them	they	PRON
admet-2772	119	11	in	in	ADP
admet-2772	119	12	accuracy	accuracy	NOUN
admet-2772	120	1	[	[	X
admet-2772	120	2	38	38	NUM
admet-2772	120	3	]	]	PUNCT
admet-2772	120	4	.	.	PUNCT
admet-2772	121	1	2.4	2.4	NUM
admet-2772	121	2	.	.	PUNCT
admet-2772	122	1	molecular	molecular	ADJ
admet-2772	122	2	descriptors	descriptor	NOUN
admet-2772	122	3	molecular	molecular	ADJ
admet-2772	122	4	descriptors	descriptor	NOUN
admet-2772	122	5	(	(	PUNCT
admet-2772	122	6	md	md	PROPN
admet-2772	122	7	)	)	PUNCT
admet-2772	122	8	are	be	AUX
admet-2772	122	9	crucial	crucial	ADJ
admet-2772	122	10	components	component	NOUN
admet-2772	122	11	in	in	ADP
admet-2772	122	12	in	in	ADP
admet-2772	122	13	-	-	PUNCT
admet-2772	122	14	silico	silico	NOUN
admet-2772	122	15	research	research	NOUN
admet-2772	122	16	,	,	PUNCT
admet-2772	122	17	serving	serve	VERB
admet-2772	122	18	as	as	ADP
admet-2772	122	19	numerical	numerical	ADJ
admet-2772	122	20	representations	representation	NOUN
admet-2772	122	21	that	that	PRON
admet-2772	122	22	accurately	accurately	ADV
admet-2772	122	23	convey	convey	VERB
admet-2772	122	24	the	the	DET
admet-2772	122	25	structural	structural	ADJ
admet-2772	122	26	and	and	CCONJ
admet-2772	122	27	physicochemical	physicochemical	ADJ
admet-2772	122	28	attributes	attribute	NOUN
admet-2772	122	29	of	of	ADP
admet-2772	122	30	compounds	compound	NOUN
admet-2772	122	31	based	base	VERB
admet-2772	122	32	on	on	ADP
admet-2772	122	33	their	their	PRON
admet-2772	122	34	1d	1d	NUM
admet-2772	122	35	,	,	PUNCT
admet-2772	122	36	2d	2d	NOUN
admet-2772	122	37	,	,	PUNCT
admet-2772	122	38	or	or	CCONJ
admet-2772	122	39	3d	3d	NUM
admet-2772	122	40	structures	structure	NOUN
admet-2772	122	41	[	[	X
admet-2772	122	42	39	39	NUM
admet-2772	122	43	]	]	PUNCT
admet-2772	122	44	.	.	PUNCT
admet-2772	123	1	various	various	ADJ
admet-2772	123	2	software	software	NOUN
admet-2772	123	3	tools	tool	NOUN
admet-2772	123	4	are	be	AUX
admet-2772	123	5	available	available	ADJ
admet-2772	123	6	for	for	ADP
admet-2772	123	7	the	the	DET
admet-2772	123	8	calculation	calculation	NOUN
admet-2772	123	9	of	of	ADP
admet-2772	123	10	molecular	molecular	ADJ
admet-2772	123	11	descriptors	descriptor	NOUN
admet-2772	123	12	,	,	PUNCT
admet-2772	123	13	facilitating	facilitate	VERB
admet-2772	123	14	the	the	DET
admet-2772	123	15	extraction	extraction	NOUN
admet-2772	123	16	of	of	ADP
admet-2772	123	17	relevant	relevant	ADJ
admet-2772	123	18	features	feature	NOUN
admet-2772	123	19	for	for	ADP
admet-2772	123	20	predictive	predictive	ADJ
admet-2772	123	21	modelling	modelling	NOUN
admet-2772	123	22	.	.	PUNCT
admet-2772	124	1	table	table	NOUN
admet-2772	124	2	2	2	NUM
admet-2772	124	3	provides	provide	VERB
admet-2772	124	4	a	a	DET
admet-2772	124	5	comprehensive	comprehensive	ADJ
admet-2772	124	6	list	list	NOUN
admet-2772	124	7	of	of	ADP
admet-2772	124	8	software	software	NOUN
admet-2772	124	9	packages	package	NOUN
admet-2772	124	10	commonly	commonly	ADV
admet-2772	124	11	used	use	VERB
admet-2772	124	12	in	in	ADP
admet-2772	124	13	cheminformatics	cheminformatic	NOUN
admet-2772	124	14	and	and	CCONJ
admet-2772	124	15	computational	computational	ADJ
admet-2772	124	16	drug	drug	NOUN
admet-2772	124	17	discovery	discovery	NOUN
admet-2772	124	18	for	for	ADP
admet-2772	124	19	descriptor	descriptor	NOUN
admet-2772	124	20	generation	generation	NOUN
admet-2772	124	21	.	.	PUNCT
admet-2772	125	1	these	these	DET
admet-2772	125	2	programs	program	NOUN
admet-2772	125	3	offer	offer	VERB
admet-2772	125	4	a	a	DET
admet-2772	125	5	wide	wide	ADJ
admet-2772	125	6	array	array	NOUN
admet-2772	125	7	of	of	ADP
admet-2772	125	8	over	over	ADP
admet-2772	125	9	5000	5000	NUM
admet-2772	125	10	descriptors	descriptor	NOUN
admet-2772	125	11	,	,	PUNCT
admet-2772	125	12	encompassing	encompass	VERB
admet-2772	125	13	constitutional	constitutional	ADJ
admet-2772	125	14	descriptors	descriptor	NOUN
admet-2772	125	15	as	as	ADV
admet-2772	125	16	well	well	ADV
admet-2772	125	17	as	as	ADP
admet-2772	125	18	more	more	ADV
admet-2772	125	19	intricate	intricate	ADJ
admet-2772	125	20	2d	2d	NOUN
admet-2772	125	21	and	and	CCONJ
admet-2772	125	22	3d	3d	NUM
admet-2772	125	23	descriptors	descriptor	NOUN
admet-2772	125	24	that	that	PRON
admet-2772	125	25	capture	capture	VERB
admet-2772	125	26	various	various	ADJ
admet-2772	125	27	geometric	geometric	ADJ
admet-2772	125	28	,	,	PUNCT
admet-2772	125	29	connectivity	connectivity	NOUN
admet-2772	125	30	,	,	PUNCT
admet-2772	125	31	and	and	CCONJ
admet-2772	125	32	physicochemical	physicochemical	ADJ
admet-2772	125	33	properties	property	NOUN
admet-2772	125	34	[	[	X
admet-2772	125	35	40	40	NUM
admet-2772	125	36	]	]	PUNCT
admet-2772	125	37	.	.	PUNCT
admet-2772	126	1	the	the	DET
admet-2772	126	2	choice	choice	NOUN
admet-2772	126	3	of	of	ADP
admet-2772	126	4	molecular	molecular	ADJ
admet-2772	126	5	representation	representation	NOUN
admet-2772	126	6	determines	determine	VERB
admet-2772	126	7	whether	whether	SCONJ
admet-2772	126	8	a	a	DET
admet-2772	126	9	molecule	molecule	NOUN
admet-2772	126	10	is	be	AUX
admet-2772	126	11	described	describe	VERB
admet-2772	126	12	using	use	VERB
admet-2772	126	13	experimental	experimental	ADJ
admet-2772	126	14	descriptors	descriptor	NOUN
admet-2772	126	15	or	or	CCONJ
admet-2772	126	16	theoretical	theoretical	ADJ
admet-2772	126	17	descriptors	descriptor	NOUN
admet-2772	126	18	.	.	PUNCT
admet-2772	127	1	experimental	experimental	ADJ
admet-2772	127	2	descriptors	descriptor	NOUN
admet-2772	127	3	encompass	encompass	VERB
admet-2772	127	4	all	all	DET
admet-2772	127	5	measurements	measurement	NOUN
admet-2772	127	6	obtained	obtain	VERB
admet-2772	127	7	through	through	ADP
admet-2772	127	8	experiments	experiment	NOUN
admet-2772	127	9	,	,	PUNCT
admet-2772	127	10	such	such	ADJ
admet-2772	127	11	as	as	ADP
admet-2772	127	12	the	the	DET
admet-2772	127	13	octanolwater	octanolwater	NOUN
admet-2772	127	14	partition	partition	PROPN
admet-2772	127	15	coefficient	coefficient	NOUN
admet-2772	127	16	,	,	PUNCT
admet-2772	127	17	molar	molar	ADJ
admet-2772	127	18	refractivity	refractivity	NOUN
admet-2772	127	19	,	,	PUNCT
admet-2772	127	20	polarizability	polarizability	NOUN
admet-2772	127	21	,	,	PUNCT
admet-2772	127	22	and	and	CCONJ
admet-2772	127	23	various	various	ADJ
admet-2772	127	24	other	other	ADJ
admet-2772	127	25	physicochemical	physicochemical	ADJ
admet-2772	127	26	properties	property	NOUN
admet-2772	127	27	obtained	obtain	VERB
admet-2772	127	28	through	through	ADP
admet-2772	127	29	specific	specific	ADJ
admet-2772	127	30	experimental	experimental	ADJ
admet-2772	127	31	procedures	procedure	NOUN
admet-2772	127	32	[	[	X
admet-2772	127	33	41	41	NUM
admet-2772	127	34	]	]	PUNCT
admet-2772	127	35	.	.	PUNCT
admet-2772	128	1	conversely	conversely	ADV
admet-2772	128	2	,	,	PUNCT
admet-2772	128	3	theoretical	theoretical	ADJ
admet-2772	128	4	molecular	molecular	ADJ
admet-2772	128	5	descriptors	descriptor	NOUN
admet-2772	128	6	span	span	VERB
admet-2772	128	7	0d	0d	NOUN
admet-2772	128	8	,	,	PUNCT
admet-2772	128	9	1d	1d	NUM
admet-2772	128	10	,	,	PUNCT
admet-2772	128	11	2d	2d	NOUN
admet-2772	128	12	,	,	PUNCT
admet-2772	128	13	3d	3d	NUM
admet-2772	128	14	and	and	CCONJ
admet-2772	128	15	4d	4d	NUM
admet-2772	128	16	molecular	molecular	ADJ
admet-2772	128	17	descriptors	descriptor	NOUN
admet-2772	128	18	,	,	PUNCT
admet-2772	128	19	which	which	PRON
admet-2772	128	20	are	be	AUX
admet-2772	128	21	derived	derive	VERB
admet-2772	128	22	from	from	ADP
admet-2772	128	23	defined	define	VERB
admet-2772	128	24	chemoinformatic	chemoinformatic	ADJ
admet-2772	128	25	algorithms	algorithm	NOUN
admet-2772	128	26	applied	apply	VERB
admet-2772	128	27	to	to	ADP
admet-2772	128	28	a	a	DET
admet-2772	128	29	clear	clear	ADJ
admet-2772	128	30	molecular	molecular	ADJ
admet-2772	128	31	representation	representation	NOUN
admet-2772	128	32	[	[	X
admet-2772	128	33	42	42	NUM
admet-2772	128	34	]	]	SYM
admet-2772	128	35	table	table	NOUN
admet-2772	128	36	2	2	NUM
admet-2772	128	37	.	.	X
admet-2772	128	38	list	list	NOUN
admet-2772	128	39	of	of	ADP
admet-2772	128	40	software	software	NOUN
admet-2772	128	41	packages	package	NOUN
admet-2772	128	42	for	for	ADP
admet-2772	128	43	the	the	DET
admet-2772	128	44	calculation	calculation	NOUN
admet-2772	128	45	of	of	ADP
admet-2772	128	46	molecular	molecular	ADJ
admet-2772	128	47	descriptors	descriptor	NOUN
admet-2772	128	48	name	name	NOUN
admet-2772	128	49	organization	organization	NOUN
admet-2772	128	50	/	/	SYM
admet-2772	128	51	institution	institution	NOUN
admet-2772	128	52	availability	availability	NOUN
admet-2772	128	53	rdkit	rdkit	NOUN
admet-2772	128	54	github	github	PROPN
admet-2772	128	55	https://github.com/rdkit	https://github.com/rdkit	PROPN
admet-2772	128	56	padelpy	padelpy	PROPN
admet-2772	128	57	university	university	PROPN
admet-2772	128	58	of	of	ADP
admet-2772	128	59	massachusetts	massachusetts	PROPN
admet-2772	128	60	lowell	lowell	PROPN
admet-2772	128	61	https://github.com/ecrl/padelpy	https://github.com/ecrl/padelpy	PROPN
admet-2772	128	62	admet	admet	PROPN
admet-2772	128	63	predictor	predictor	PROPN
admet-2772	128	64	simulations	simulation	NOUN
admet-2772	128	65	plus	plus	CCONJ
admet-2772	128	66	,	,	PUNCT
admet-2772	128	67	inc	inc	PROPN
admet-2772	128	68	https://www.simulations-plus.com/	https://www.simulations-plus.com/	PROPN
admet-2772	128	69	codessa	codessa	PROPN
admet-2772	128	70	™	™	PROPN
admet-2772	128	71	semichem	semichem	VERB
admet-2772	128	72	http://www.semichem.com/codessa/default.php	http://www.semichem.com/codessa/default.php	PROPN
admet-2772	128	73	dragon	dragon	PROPN
admet-2772	128	74	talete	talete	PROPN
admet-2772	128	75	srl	srl	PROPN
admet-2772	128	76	https://www.talete.mi.it/products/dragon_description.htm	https://www.talete.mi.it/products/dragon_description.htm	X
admet-2772	128	77	episuite	episuite	VERB
admet-2772	128	78	™	™	VERB
admet-2772	128	79	united	united	PROPN
admet-2772	128	80	states	states	PROPN
admet-2772	128	81	environmental	environmental	PROPN
admet-2772	128	82	protection	protection	PROPN
admet-2772	128	83	agency	agency	PROPN
admet-2772	128	84	https://www.epa.gov/tsca-screening-tools/epi-suitetmestimation-program-interface	https://www.epa.gov/tsca-screening-tools/epi-suitetmestimation-program-interface	NOUN
admet-2772	128	85	moe	moe	NOUN
admet-2772	128	86	chemical	chemical	NOUN
admet-2772	128	87	computing	computing	NOUN
admet-2772	128	88	group	group	NOUN
admet-2772	128	89	https://www.chemcomp.com/products.htm	https://www.chemcomp.com/products.htm	PROPN
admet-2772	128	90	molconn	molconn	PROPN
admet-2772	128	91	-	-	PUNCT
admet-2772	128	92	z	z	ADJ
admet-2772	128	93	™	™	PROPN
admet-2772	128	94	edusoft	edusoft	NOUN
admet-2772	128	95	http://www.edusoft-lc.com/molconn/	http://www.edusoft-lc.com/molconn/	NOUN
admet-2772	128	96	mold2	mold2	NOUN
admet-2772	128	97	national	national	ADJ
admet-2772	128	98	center	center	NOUN
admet-2772	128	99	for	for	ADP
admet-2772	128	100	toxicological	toxicological	ADJ
admet-2772	128	101	research	research	NOUN
admet-2772	128	102	https://www.fda.gov/science-research/bioinformaticstools/mold2	https://www.fda.gov/science-research/bioinformaticstools/mold2	PROPN
admet-2772	128	103	molgen	molgen	PROPN
admet-2772	128	104	university	university	PROPN
admet-2772	128	105	of	of	ADP
admet-2772	128	106	bayreuth	bayreuth	PROPN
admet-2772	128	107	https://www.molgen.de/	https://www.molgen.de/	X
admet-2772	128	108	powermv	powermv	PROPN
admet-2772	128	109	national	national	PROPN
admet-2772	128	110	institute	institute	PROPN
admet-2772	128	111	of	of	ADP
admet-2772	128	112	statistical	statistical	ADJ
admet-2772	128	113	sciences	science	NOUN
admet-2772	128	114	https://www.niss.org/research/software/powermv	https://www.niss.org/research/software/powermv	ADJ
admet-2772	128	115	alvadesc	alvadesc	PRON
admet-2772	128	116	alvascience	alvascience	VERB
admet-2772	128	117	https://www.alvascience.com/alvadesc/	https://www.alvascience.com/alvadesc/	X
admet-2772	128	118	coral	coral	PROPN
admet-2772	128	119	mario	mario	PROPN
admet-2772	128	120	negri	negri	PROPN
admet-2772	128	121	institute	institute	PROPN
admet-2772	128	122	for	for	ADP
admet-2772	128	123	pharmacological	pharmacological	ADJ
admet-2772	128	124	research	research	NOUN
admet-2772	128	125	http://www.insilico.eu/coral/softwarecoral.html	http://www.insilico.eu/coral/softwarecoral.html	VERB
admet-2772	128	126	the	the	DET
admet-2772	128	127	0d	0d	NUM
admet-2772	128	128	molecular	molecular	ADJ
admet-2772	128	129	descriptors	descriptor	NOUN
admet-2772	128	130	are	be	AUX
admet-2772	128	131	straightforward	straightforward	ADJ
admet-2772	128	132	and	and	CCONJ
admet-2772	128	133	convenient	convenient	ADJ
admet-2772	128	134	to	to	PART
admet-2772	128	135	compute	compute	VERB
admet-2772	128	136	and	and	CCONJ
admet-2772	128	137	interpret	interpret	VERB
admet-2772	128	138	because	because	SCONJ
admet-2772	128	139	they	they	PRON
admet-2772	128	140	do	do	AUX
admet-2772	128	141	n't	not	PART
admet-2772	128	142	require	require	VERB
admet-2772	128	143	structural	structural	ADJ
admet-2772	128	144	information	information	NOUN
admet-2772	128	145	or	or	CCONJ
admet-2772	128	146	connectivity	connectivity	NOUN
admet-2772	128	147	between	between	ADP
admet-2772	128	148	atoms	atom	NOUN
admet-2772	128	149	.	.	PUNCT
admet-2772	129	1	they	they	PRON
admet-2772	129	2	are	be	AUX
admet-2772	129	3	independent	independent	ADJ
admet-2772	129	4	of	of	ADP
admet-2772	129	5	molecular	molecular	ADJ
admet-2772	129	6	conformation	conformation	NOUN
admet-2772	129	7	and	and	CCONJ
admet-2772	129	8	optimization	optimization	NOUN
admet-2772	129	9	[	[	X
admet-2772	129	10	43	43	NUM
admet-2772	129	11	]	]	PUNCT
admet-2772	129	12	.	.	PUNCT
admet-2772	130	1	while	while	SCONJ
admet-2772	130	2	they	they	PRON
admet-2772	130	3	offer	offer	VERB
admet-2772	130	4	limited	limited	ADJ
admet-2772	130	5	information	information	NOUN
admet-2772	130	6	content	content	NOUN
admet-2772	130	7	,	,	PUNCT
admet-2772	130	8	they	they	PRON
admet-2772	130	9	still	still	ADV
admet-2772	130	10	play	play	VERB
admet-2772	130	11	a	a	DET
admet-2772	130	12	vital	vital	ADJ
admet-2772	130	13	role	role	NOUN
admet-2772	130	14	in	in	ADP
admet-2772	130	15	modelling	model	VERB
admet-2772	130	16	various	various	ADJ
admet-2772	130	17	physicochemical	physicochemical	ADJ
admet-2772	130	18	properties	property	NOUN
admet-2772	130	19	or	or	CCONJ
admet-2772	130	20	contributing	contribute	VERB
admet-2772	130	21	to	to	ADP
admet-2772	130	22	more	more	ADJ
admet-2772	130	23	complex	complex	ADJ
admet-2772	130	24	models	model	NOUN
admet-2772	130	25	[	[	X
admet-2772	130	26	44	44	NUM
admet-2772	130	27	]	]	PUNCT
admet-2772	130	28	.	.	PUNCT
admet-2772	131	1	descriptors	descriptor	NOUN
admet-2772	131	2	that	that	PRON
admet-2772	131	3	compute	compute	VERB
admet-2772	131	4	information	information	NOUN
admet-2772	131	5	from	from	ADP
admet-2772	131	6	fractions	fraction	NOUN
admet-2772	131	7	of	of	ADP
admet-2772	131	8	a	a	DET
admet-2772	131	9	molecule	molecule	NOUN
admet-2772	131	10	fall	fall	NOUN
admet-2772	131	11	into	into	ADP
admet-2772	131	12	the	the	DET
admet-2772	131	13	1d	1d	NUM
admet-2772	131	14	molecular	molecular	ADJ
admet-2772	131	15	descriptors	descriptor	NOUN
admet-2772	131	16	category	category	NOUN
admet-2772	131	17	,	,	PUNCT
admet-2772	131	18	often	often	ADV
admet-2772	131	19	represented	represent	VERB
admet-2772	131	20	as	as	ADP
admet-2772	131	21	fingerprints	fingerprint	NOUN
admet-2772	131	22	binary	binary	ADJ
admet-2772	131	23	vectors	vector	NOUN
admet-2772	131	24	where	where	SCONJ
admet-2772	131	25	1	1	NUM
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admet-2772	131	27	a	a	DET
admet-2772	131	28	substructure	substructure	NOUN
admet-2772	131	29	's	's	PART
admet-2772	131	30	presence	presence	NOUN
admet-2772	131	31	and	and	CCONJ
admet-2772	131	32	0	0	NUM
admet-2772	131	33	its	its	PRON
admet-2772	131	34	absence	absence	NOUN
admet-2772	131	35	[	[	X
admet-2772	131	36	45	45	NUM
admet-2772	131	37	]	]	PUNCT
admet-2772	131	38	.	.	PUNCT
admet-2772	132	1	similar	similar	ADJ
admet-2772	132	2	to	to	ADP
admet-2772	132	3	0d	0d	PROPN
admet-2772	132	4	descriptors	descriptor	NOUN
admet-2772	132	5	,	,	PUNCT
admet-2772	132	6	they	they	PRON
admet-2772	132	7	're	be	AUX
admet-2772	132	8	straightforward	straightforward	ADJ
admet-2772	132	9	to	to	PART
admet-2772	132	10	calculate	calculate	VERB
admet-2772	132	11	,	,	PUNCT
admet-2772	132	12	interpretable	interpretable	ADJ
admet-2772	132	13	,	,	PUNCT
admet-2772	132	14	and	and	CCONJ
admet-2772	132	15	conformation	conformation	NOUN
admet-2772	132	16	-	-	PUNCT
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admet-2772	133	1	[	[	X
admet-2772	133	2	46	46	NUM
admet-2772	133	3	]	]	PUNCT
admet-2772	133	4	.	.	PUNCT
admet-2772	134	1	twodimensional	twodimensional	ADJ
admet-2772	134	2	descriptors	descriptor	NOUN
admet-2772	134	3	describe	describe	VERB
admet-2772	134	4	properties	property	NOUN
admet-2772	134	5	computable	computable	ADJ
admet-2772	134	6	from	from	ADP
admet-2772	134	7	2d	2d	NUM
admet-2772	134	8	molecular	molecular	ADJ
admet-2772	134	9	representations	representation	NOUN
admet-2772	134	10	,	,	PUNCT
admet-2772	134	11	relying	rely	VERB
admet-2772	134	12	on	on	ADP
admet-2772	134	13	graph	graph	NOUN
admet-2772	134	14	https://github.com/rdkit	https://github.com/rdkit	PROPN
admet-2772	134	15	https://github.com/ecrl/padelpy	https://github.com/ecrl/padelpy	NOUN
admet-2772	134	16	https://www.simulations-plus.com/	https://www.simulations-plus.com/	PROPN
admet-2772	135	1	http://www.semichem.com/codessa/default.php	http://www.semichem.com/codessa/default.php	PROPN
admet-2772	135	2	https://www.talete.mi.it/products/dragon_description.htm	https://www.talete.mi.it/products/dragon_description.htm	X
admet-2772	136	1	https://www.epa.gov/tsca-screening-tools/epi-suitetm-estimation-program-interface	https://www.epa.gov/tsca-screening-tools/epi-suitetm-estimation-program-interface	NOUN
admet-2772	136	2	https://www.epa.gov/tsca-screening-tools/epi-suitetm-estimation-program-interface	https://www.epa.gov/tsca-screening-tools/epi-suitetm-estimation-program-interface	NOUN
admet-2772	136	3	https://www.chemcomp.com/products.htm	https://www.chemcomp.com/products.htm	PROPN
admet-2772	136	4	http://www.edusoft-lc.com/molconn/	http://www.edusoft-lc.com/molconn/	NOUN
admet-2772	136	5	https://www.fda.gov/science-research/bioinformatics-tools/mold2	https://www.fda.gov/science-research/bioinformatics-tools/mold2	PRON
admet-2772	136	6	https://www.fda.gov/science-research/bioinformatics-tools/mold2	https://www.fda.gov/science-research/bioinformatics-tools/mold2	PRON
admet-2772	136	7	https://www.molgen.de/	https://www.molgen.de/	X
admet-2772	136	8	https://www.niss.org/research/software/powermv	https://www.niss.org/research/software/powermv	ADJ
admet-2772	136	9	https://www.alvascience.com/alvadesc/	https://www.alvascience.com/alvadesc/	X
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admet-2772	136	11	admet	admet	PROPN
admet-2772	136	12	&	&	CCONJ
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admet-2772	136	14	13(3	13(3	NUM
admet-2772	136	15	)	)	PUNCT
admet-2772	136	16	(	(	PUNCT
admet-2772	136	17	2025	2025	NUM
admet-2772	136	18	)	)	PUNCT
admet-2772	136	19	2772	2772	NUM
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admet-2772	136	21	learning	learning	NOUN
admet-2772	136	22	models	model	NOUN
admet-2772	136	23	for	for	ADP
admet-2772	136	24	admet	admet	ADJ
admet-2772	136	25	prediction	prediction	NOUN
admet-2772	136	26	in	in	ADP
admet-2772	136	27	drug	drug	NOUN
admet-2772	136	28	development	development	NOUN
admet-2772	136	29	doi	doi	PROPN
admet-2772	136	30	:	:	PUNCT
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admet-2772	136	32	7	7	NUM
admet-2772	136	33	theory	theory	NOUN
admet-2772	136	34	and	and	CCONJ
admet-2772	136	35	maintaining	maintain	VERB
admet-2772	136	36	theoretical	theoretical	ADJ
admet-2772	136	37	properties	property	NOUN
admet-2772	136	38	through	through	ADP
admet-2772	136	39	isomorphism	isomorphism	NOUN
admet-2772	136	40	.	.	PUNCT
admet-2772	137	1	they	they	PRON
admet-2772	137	2	're	be	AUX
admet-2772	137	3	sensitive	sensitive	ADJ
admet-2772	137	4	to	to	ADP
admet-2772	137	5	molecular	molecular	ADJ
admet-2772	137	6	characteristics	characteristic	NOUN
admet-2772	137	7	like	like	ADP
admet-2772	137	8	size	size	NOUN
admet-2772	137	9	,	,	PUNCT
admet-2772	137	10	shape	shape	NOUN
admet-2772	137	11	,	,	PUNCT
admet-2772	137	12	and	and	CCONJ
admet-2772	137	13	chemical	chemical	NOUN
admet-2772	137	14	information	information	NOUN
admet-2772	137	15	[	[	X
admet-2772	137	16	46	46	NUM
admet-2772	137	17	]	]	PUNCT
admet-2772	137	18	.	.	PUNCT
admet-2772	138	1	they	they	PRON
admet-2772	138	2	're	be	AUX
admet-2772	138	3	divided	divide	VERB
admet-2772	138	4	into	into	ADP
admet-2772	138	5	structural	structural	ADJ
admet-2772	138	6	-	-	PUNCT
admet-2772	138	7	topological	topological	ADJ
admet-2772	138	8	indices	index	NOUN
admet-2772	138	9	,	,	PUNCT
admet-2772	138	10	encoding	encode	VERB
admet-2772	138	11	adjacency	adjacency	NOUN
admet-2772	138	12	and	and	CCONJ
admet-2772	138	13	distance	distance	NOUN
admet-2772	138	14	,	,	PUNCT
admet-2772	138	15	and	and	CCONJ
admet-2772	138	16	topochemical	topochemical	ADJ
admet-2772	138	17	indices	index	NOUN
admet-2772	138	18	,	,	PUNCT
admet-2772	138	19	quantifying	quantify	VERB
admet-2772	138	20	topology	topology	NOUN
admet-2772	138	21	and	and	CCONJ
admet-2772	138	22	atomic	atomic	ADJ
admet-2772	138	23	properties	property	NOUN
admet-2772	138	24	[	[	X
admet-2772	138	25	47	47	NUM
admet-2772	138	26	]	]	PUNCT
admet-2772	138	27	.	.	PUNCT
admet-2772	139	1	three	three	NUM
admet-2772	139	2	-	-	PUNCT
admet-2772	139	3	dimensional	dimensional	ADJ
admet-2772	139	4	descriptors	descriptor	NOUN
admet-2772	139	5	relate	relate	VERB
admet-2772	139	6	to	to	ADP
admet-2772	139	7	the	the	DET
admet-2772	139	8	3d	3d	PROPN
admet-2772	139	9	representation	representation	NOUN
admet-2772	139	10	of	of	ADP
admet-2772	139	11	molecules	molecule	NOUN
admet-2772	139	12	,	,	PUNCT
admet-2772	139	13	incorporating	incorporate	VERB
admet-2772	139	14	molecular	molecular	ADJ
admet-2772	139	15	conformations	conformation	NOUN
admet-2772	139	16	,	,	PUNCT
admet-2772	139	17	bond	bond	NOUN
admet-2772	139	18	distances	distance	NOUN
admet-2772	139	19	,	,	PUNCT
admet-2772	139	20	angles	angle	NOUN
admet-2772	139	21	,	,	PUNCT
admet-2772	139	22	and	and	CCONJ
admet-2772	139	23	dihedral	dihedral	ADJ
admet-2772	139	24	angles	angle	NOUN
admet-2772	139	25	to	to	PART
admet-2772	139	26	describe	describe	VERB
admet-2772	139	27	stereochemical	stereochemical	ADJ
admet-2772	139	28	properties	property	NOUN
admet-2772	139	29	[	[	X
admet-2772	139	30	39	39	NUM
admet-2772	139	31	]	]	PUNCT
admet-2772	139	32	.	.	PUNCT
admet-2772	140	1	popular	popular	ADJ
admet-2772	140	2	types	type	NOUN
admet-2772	140	3	include	include	VERB
admet-2772	140	4	pharmacophore	pharmacophore	ADJ
admet-2772	140	5	representations	representation	NOUN
admet-2772	140	6	,	,	PUNCT
admet-2772	140	7	characterizing	characterize	VERB
admet-2772	140	8	steric	steric	ADJ
admet-2772	140	9	and	and	CCONJ
admet-2772	140	10	electronic	electronic	ADJ
admet-2772	140	11	features	feature	NOUN
admet-2772	140	12	crucial	crucial	ADJ
admet-2772	140	13	for	for	ADP
admet-2772	140	14	interactions	interaction	NOUN
admet-2772	140	15	with	with	ADP
admet-2772	140	16	biological	biological	ADJ
admet-2772	140	17	targets	target	NOUN
admet-2772	140	18	[	[	X
admet-2772	140	19	48	48	NUM
admet-2772	140	20	]	]	PUNCT
admet-2772	140	21	.	.	PUNCT
admet-2772	141	1	grid	grid	NOUN
admet-2772	141	2	-	-	PUNCT
admet-2772	141	3	based	base	VERB
admet-2772	141	4	descriptors	descriptor	NOUN
admet-2772	141	5	,	,	PUNCT
admet-2772	141	6	also	also	ADV
admet-2772	141	7	called	call	VERB
admet-2772	141	8	4d	4d	NUM
admet-2772	141	9	,	,	PUNCT
admet-2772	141	10	introduce	introduce	VERB
admet-2772	141	11	a	a	DET
admet-2772	141	12	fourth	fourth	ADJ
admet-2772	141	13	dimension	dimension	NOUN
admet-2772	141	14	to	to	PART
admet-2772	141	15	capture	capture	VERB
admet-2772	141	16	interactions	interaction	NOUN
admet-2772	141	17	between	between	ADP
admet-2772	141	18	molecules	molecule	NOUN
admet-2772	141	19	,	,	PUNCT
admet-2772	141	20	their	their	PRON
admet-2772	141	21	conformations	conformation	NOUN
admet-2772	141	22	,	,	PUNCT
admet-2772	141	23	and	and	CCONJ
admet-2772	141	24	biological	biological	ADJ
admet-2772	141	25	receptor	receptor	NOUN
admet-2772	141	26	active	active	ADJ
admet-2772	141	27	sites	site	NOUN
admet-2772	141	28	.	.	PUNCT
admet-2772	142	1	by	by	ADP
admet-2772	142	2	considering	consider	VERB
admet-2772	142	3	ligand	ligand	ADJ
admet-2772	142	4	conformational	conformational	ADJ
admet-2772	142	5	variation	variation	NOUN
admet-2772	142	6	and	and	CCONJ
admet-2772	142	7	interactions	interaction	NOUN
admet-2772	142	8	within	within	ADP
admet-2772	142	9	binding	bind	VERB
admet-2772	142	10	pockets	pocket	NOUN
admet-2772	142	11	,	,	PUNCT
admet-2772	142	12	they	they	PRON
admet-2772	142	13	aim	aim	VERB
admet-2772	142	14	to	to	PART
admet-2772	142	15	enhance	enhance	VERB
admet-2772	142	16	quantitative	quantitative	ADJ
admet-2772	142	17	structure	structure	NOUN
admet-2772	142	18	-	-	PUNCT
admet-2772	142	19	activity	activity	NOUN
admet-2772	142	20	relationship	relationship	NOUN
admet-2772	142	21	(	(	PUNCT
admet-2772	142	22	qsar	qsar	NOUN
admet-2772	142	23	)	)	PUNCT
admet-2772	142	24	model	model	NOUN
admet-2772	142	25	reliability	reliability	NOUN
admet-2772	142	26	[	[	X
admet-2772	142	27	49	49	NUM
admet-2772	142	28	]	]	PUNCT
admet-2772	142	29	.	.	PUNCT
admet-2772	143	1	3	3	X
admet-2772	143	2	.	.	X
admet-2772	143	3	machine	machine	NOUN
admet-2772	143	4	learning	learn	VERB
admet-2772	143	5	applications	application	NOUN
admet-2772	143	6	in	in	ADP
admet-2772	143	7	predicting	predict	VERB
admet-2772	143	8	adme	adme	NOUN
admet-2772	143	9	properties	property	NOUN
admet-2772	143	10	3.1	3.1	NUM
admet-2772	143	11	.	.	PUNCT
admet-2772	144	1	absorption	absorption	NOUN
admet-2772	144	2	prediction	prediction	NOUN
admet-2772	144	3	machine	machine	NOUN
admet-2772	144	4	learning	learning	NOUN
admet-2772	144	5	models	model	NOUN
admet-2772	144	6	have	have	AUX
admet-2772	144	7	shown	show	VERB
admet-2772	144	8	promise	promise	NOUN
admet-2772	144	9	in	in	ADP
admet-2772	144	10	predicting	predict	VERB
admet-2772	144	11	intestinal	intestinal	ADJ
admet-2772	144	12	absorption	absorption	NOUN
admet-2772	144	13	and	and	CCONJ
admet-2772	144	14	permeability	permeability	NOUN
admet-2772	144	15	of	of	ADP
admet-2772	144	16	compounds	compound	NOUN
admet-2772	144	17	.	.	PUNCT
admet-2772	145	1	various	various	ADJ
admet-2772	145	2	approaches	approach	NOUN
admet-2772	145	3	have	have	AUX
admet-2772	145	4	been	be	AUX
admet-2772	145	5	employed	employ	VERB
admet-2772	145	6	,	,	PUNCT
admet-2772	145	7	including	include	VERB
admet-2772	145	8	artificial	artificial	ADJ
admet-2772	145	9	neural	neural	ADJ
admet-2772	145	10	networks	network	NOUN
admet-2772	145	11	for	for	ADP
admet-2772	145	12	oligopeptides	oligopeptide	NOUN
admet-2772	145	13	[	[	X
admet-2772	145	14	50	50	NUM
admet-2772	145	15	]	]	PUNCT
admet-2772	145	16	,	,	PUNCT
admet-2772	145	17	support	support	VERB
admet-2772	145	18	vector	vector	NOUN
admet-2772	145	19	machines	machine	NOUN
admet-2772	145	20	for	for	ADP
admet-2772	145	21	general	general	ADJ
admet-2772	145	22	compounds	compound	NOUN
admet-2772	145	23	[	[	X
admet-2772	145	24	51	51	NUM
admet-2772	145	25	]	]	PUNCT
admet-2772	145	26	,	,	PUNCT
admet-2772	145	27	and	and	CCONJ
admet-2772	145	28	ensemble	ensemble	ADJ
admet-2772	145	29	methods	method	NOUN
admet-2772	145	30	combining	combine	VERB
admet-2772	145	31	support	support	NOUN
admet-2772	145	32	vector	vector	NOUN
admet-2772	145	33	machines	machine	NOUN
admet-2772	145	34	(	(	PUNCT
admet-2772	145	35	svm	svm	PROPN
admet-2772	145	36	)	)	PUNCT
admet-2772	145	37	,	,	PUNCT
admet-2772	145	38	random	random	ADJ
admet-2772	145	39	forest	forest	NOUN
admet-2772	145	40	(	(	PUNCT
admet-2772	145	41	rf	rf	NOUN
admet-2772	145	42	)	)	PUNCT
admet-2772	145	43	,	,	PUNCT
admet-2772	145	44	and	and	CCONJ
admet-2772	145	45	gradient	gradient	NOUN
admet-2772	145	46	boosting	boost	VERB
admet-2772	145	47	for	for	ADP
admet-2772	145	48	natural	natural	ADJ
admet-2772	145	49	products	product	NOUN
admet-2772	145	50	[	[	X
admet-2772	145	51	52	52	NUM
admet-2772	145	52	]	]	PUNCT
admet-2772	145	53	(	(	PUNCT
admet-2772	145	54	a	a	DET
admet-2772	145	55	summary	summary	NOUN
admet-2772	145	56	of	of	ADP
admet-2772	145	57	machine	machine	NOUN
admet-2772	145	58	learning	learning	NOUN
admet-2772	145	59	-	-	PUNCT
admet-2772	145	60	based	base	VERB
admet-2772	145	61	models	model	NOUN
admet-2772	145	62	for	for	ADP
admet-2772	145	63	absorption	absorption	NOUN
admet-2772	145	64	prediction	prediction	NOUN
admet-2772	145	65	is	be	AUX
admet-2772	145	66	presented	present	VERB
admet-2772	145	67	in	in	ADP
admet-2772	145	68	table	table	NOUN
admet-2772	145	69	3	3	NUM
admet-2772	145	70	.	.	PUNCT
admet-2772	145	71	)	)	PUNCT
admet-2772	145	72	.	.	PUNCT
admet-2772	146	1	these	these	DET
admet-2772	146	2	models	model	NOUN
admet-2772	146	3	have	have	AUX
admet-2772	146	4	demonstrated	demonstrate	VERB
admet-2772	146	5	high	high	ADJ
admet-2772	146	6	predictive	predictive	ADJ
admet-2772	146	7	accuracy	accuracy	NOUN
admet-2772	146	8	,	,	PUNCT
admet-2772	146	9	with	with	ADP
admet-2772	146	10	support	support	NOUN
admet-2772	146	11	vector	vector	NOUN
admet-2772	146	12	machines	machine	NOUN
admet-2772	146	13	achieving	achieve	VERB
admet-2772	146	14	up	up	ADP
admet-2772	146	15	to	to	ADP
admet-2772	146	16	91.54	91.54	NUM
admet-2772	146	17	%	%	NOUN
admet-2772	146	18	accuracy	accuracy	NOUN
admet-2772	146	19	[	[	X
admet-2772	146	20	51	51	NUM
admet-2772	146	21	]	]	PUNCT
admet-2772	146	22	.	.	PUNCT
admet-2772	147	1	computational	computational	ADJ
admet-2772	147	2	models	model	NOUN
admet-2772	147	3	based	base	VERB
admet-2772	147	4	on	on	ADP
admet-2772	147	5	molecular	molecular	ADJ
admet-2772	147	6	descriptors	descriptor	NOUN
admet-2772	147	7	,	,	PUNCT
admet-2772	147	8	such	such	ADJ
admet-2772	147	9	as	as	ADP
admet-2772	147	10	polar	polar	ADJ
admet-2772	147	11	surface	surface	NOUN
admet-2772	147	12	area	area	NOUN
admet-2772	147	13	,	,	PUNCT
admet-2772	147	14	have	have	AUX
admet-2772	147	15	also	also	ADV
admet-2772	147	16	been	be	AUX
admet-2772	147	17	developed	develop	VERB
admet-2772	147	18	to	to	PART
admet-2772	147	19	predict	predict	VERB
admet-2772	147	20	intestinal	intestinal	ADJ
admet-2772	147	21	permeability	permeability	NOUN
admet-2772	147	22	[	[	X
admet-2772	147	23	53	53	NUM
admet-2772	147	24	]	]	PUNCT
admet-2772	147	25	.	.	PUNCT
admet-2772	148	1	these	these	PRON
admet-2772	148	2	in	in	ADP
admet-2772	148	3	silico	silico	NOUN
admet-2772	148	4	methods	method	NOUN
admet-2772	148	5	offer	offer	VERB
admet-2772	148	6	quick	quick	ADJ
admet-2772	148	7	and	and	CCONJ
admet-2772	148	8	cost	cost	NOUN
admet-2772	148	9	-	-	PUNCT
admet-2772	148	10	effective	effective	ADJ
admet-2772	148	11	alternatives	alternative	NOUN
admet-2772	148	12	to	to	ADP
admet-2772	148	13	experimental	experimental	ADJ
admet-2772	148	14	techniques	technique	NOUN
admet-2772	148	15	like	like	ADP
admet-2772	148	16	caco-2	caco-2	NUM
admet-2772	148	17	cell	cell	NOUN
admet-2772	148	18	assays	assay	NOUN
admet-2772	148	19	.	.	PUNCT
admet-2772	149	1	table	table	NOUN
admet-2772	149	2	3	3	NUM
admet-2772	149	3	.	.	PUNCT
admet-2772	150	1	summary	summary	NOUN
admet-2772	150	2	of	of	ADP
admet-2772	150	3	machine	machine	NOUN
admet-2772	150	4	learning	learning	NOUN
admet-2772	150	5	-	-	PUNCT
admet-2772	150	6	based	base	VERB
admet-2772	150	7	models	model	NOUN
admet-2772	150	8	for	for	ADP
admet-2772	150	9	absorption	absorption	NOUN
admet-2772	150	10	prediction	prediction	NOUN
admet-2772	150	11	no	no	INTJ
admet-2772	150	12	.	.	PUNCT
admet-2772	150	13	of	of	ADP
admet-2772	150	14	comp	comp	PROPN
admet-2772	150	15	.	.	PUNCT
admet-2772	151	1	target	target	NOUN
admet-2772	151	2	descriptors	descriptor	NOUN
admet-2772	151	3	modelling	model	VERB
admet-2772	151	4	method	method	NOUN
admet-2772	151	5	performance	performance	NOUN
admet-2772	151	6	ref	ref	NOUN
admet-2772	151	7	.	.	PUNCT
admet-2772	152	1	1242	1242	NUM
admet-2772	152	2	hia	hia	PROPN
admet-2772	152	3	1d	1d	NUM
admet-2772	152	4	and	and	CCONJ
admet-2772	152	5	2d	2d	NUM
admet-2772	152	6	molecular	molecular	ADJ
admet-2772	152	7	descriptors	descriptor	NOUN
admet-2772	152	8	svm	svm	VERB
admet-2772	152	9	accuracy	accuracy	NOUN
admet-2772	152	10	:	:	PUNCT
admet-2772	152	11	training	training	NOUN
admet-2772	152	12	set	set	NOUN
admet-2772	152	13	=	=	SYM
admet-2772	152	14	90.38	90.38	NUM
admet-2772	152	15	%	%	NOUN
admet-2772	152	16	;	;	PUNCT
admet-2772	152	17	test	test	NOUN
admet-2772	152	18	set	set	NOUN
admet-2772	152	19	=	=	SYM
admet-2772	152	20	91.54	91.54	NUM
admet-2772	152	21	%	%	NOUN
admet-2772	152	22	;	;	PUNCT
admet-2772	152	23	mcc	mcc	PROPN
admet-2772	152	24	=	=	PROPN
admet-2772	152	25	0.80	0.80	NUM
admet-2772	152	26	,	,	PUNCT
admet-2772	152	27	auc	auc	NOUN
admet-2772	152	28	=	=	NOUN
admet-2772	152	29	0.885	0.885	NUM
admet-2772	153	1	[	[	X
admet-2772	153	2	51	51	NUM
admet-2772	153	3	]	]	SYM
admet-2772	153	4	67	67	NUM
admet-2772	153	5	hia	hia	PROPN
admet-2772	153	6	1d	1d	NUM
admet-2772	153	7	3d	3d	NOUN
admet-2772	153	8	theoretical	theoretical	ADJ
admet-2772	153	9	descriptors	descriptor	NOUN
admet-2772	153	10	plus	plus	CCONJ
admet-2772	153	11	one	one	NUM
admet-2772	153	12	of	of	ADP
admet-2772	153	13	abraham	abraham	PROPN
admet-2772	153	14	’s	’s	PART
admet-2772	153	15	solvation	solvation	PROPN
admet-2772	153	16	param	param	PROPN
admet-2772	153	17	.	.	PUNCT
admet-2772	154	1	mars	mars	PROPN
admet-2772	154	2	whole	whole	ADJ
admet-2772	154	3	data	datum	NOUN
admet-2772	154	4	set	set	VERB
admet-2772	154	5	:	:	PUNCT
admet-2772	154	6	rmse	rmse	PROPN
admet-2772	155	1	=	=	SYM
admet-2772	155	2	 	 	SPACE
admet-2772	155	3	7.2	7.2	NUM
admet-2772	155	4	%	%	NOUN
admet-2772	155	5	whole	whole	ADJ
admet-2772	155	6	data	datum	NOUN
admet-2772	155	7	set	set	VERB
admet-2772	155	8	:	:	PUNCT
admet-2772	155	9	r2	r2	PROPN
admet-2772	155	10	=	=	PUNCT
admet-2772	156	1	0.93	0.93	NUM
admet-2772	157	1	[	[	X
admet-2772	157	2	54	54	NUM
admet-2772	157	3	]	]	SYM
admet-2772	157	4	31	31	NUM
admet-2772	157	5	ka	ka	NOUN
admet-2772	157	6	moe	moe	PROPN
admet-2772	157	7	descriptors	descriptor	NOUN
admet-2772	157	8	xgboost	xgboost	X
admet-2772	157	9	training	training	NOUN
admet-2772	157	10	set	set	NOUN
admet-2772	157	11	:	:	PUNCT
admet-2772	157	12	rmse	rmse	NOUN
admet-2772	157	13	 	 	SPACE
admet-2772	157	14	=	=	SYM
admet-2772	157	15	 	 	SPACE
admet-2772	157	16	0.0023	0.0023	NUM
admet-2772	157	17	 	 	SPACE
admet-2772	157	18	h−1	h−1	PROPN
admet-2772	157	19	prediction	prediction	NOUN
admet-2772	157	20	set	set	NOUN
admet-2772	157	21	:	:	PUNCT
admet-2772	157	22	rmse	rmse	NOUN
admet-2772	157	23	 	 	SPACE
admet-2772	157	24	=	=	SYM
admet-2772	157	25	 	 	SPACE
admet-2772	157	26	0.0021	0.0021	NUM
admet-2772	157	27	 	 	SPACE
admet-2772	157	28	h−1	h−1	PROPN
admet-2772	158	1	[	[	X
admet-2772	158	2	52	52	NUM
admet-2772	158	3	]	]	SYM
admet-2772	158	4	160	160	NUM
admet-2772	158	5	hia	hia	PROPN
admet-2772	158	6	0d	0d	X
admet-2772	158	7	3d	3d	PROPN
admet-2772	158	8	dragon	dragon	PROPN
admet-2772	158	9	theoretical	theoretical	ADJ
admet-2772	158	10	descriptors	descriptors	PROPN
admet-2772	158	11	multilayer	multilayer	PROPN
admet-2772	158	12	perceptron	perceptron	PROPN
admet-2772	158	13	-	-	PUNCT
admet-2772	158	14	artificial	artificial	ADJ
admet-2772	158	15	neural	neural	ADJ
admet-2772	158	16	network	network	NOUN
admet-2772	158	17	,	,	PUNCT
admet-2772	158	18	svm	svm	VERB
admet-2772	158	19	training	training	NOUN
admet-2772	158	20	set	set	NOUN
admet-2772	158	21	:	:	PUNCT
admet-2772	158	22	r2=	r2=	PROPN
admet-2772	158	23	0.8	0.8	NUM
admet-2772	158	24	;	;	PUNCT
admet-2772	158	25	rmse	rmse	NOUN
admet-2772	158	26	 	 	SPACE
admet-2772	158	27	=	=	NOUN
admet-2772	158	28	 	 	SPACE
admet-2772	158	29	0.18	0.18	NUM
admet-2772	158	30	test	test	NOUN
admet-2772	158	31	set	set	NOUN
admet-2772	158	32	:	:	PUNCT
admet-2772	158	33	r2=	r2=	PROPN
admet-2772	158	34	0.66	0.66	NUM
admet-2772	158	35	;	;	PUNCT
admet-2772	158	36	rmse	rmse	NOUN
admet-2772	158	37	 	 	SPACE
admet-2772	159	1	=	=	NOUN
admet-2772	159	2	 	 	SPACE
admet-2772	159	3	0.21	0.21	NUM
admet-2772	160	1	[	[	X
admet-2772	160	2	55	55	NUM
admet-2772	160	3	]	]	SYM
admet-2772	160	4	552	552	NUM
admet-2772	160	5	hia	hia	PROPN
admet-2772	160	6	adriana	adriana	PROPN
admet-2772	160	7	code	code	PROPN
admet-2772	160	8	and	and	CCONJ
admet-2772	160	9	cerius2	cerius2	PROPN
admet-2772	160	10	0d	0d	X
admet-2772	160	11	2d	2d	NUM
admet-2772	160	12	theoretical	theoretical	ADJ
admet-2772	160	13	descriptors	descriptor	NOUN
admet-2772	160	14	genetic	genetic	ADJ
admet-2772	160	15	algorithm	algorithm	NOUN
admet-2772	160	16	,	,	PUNCT
admet-2772	160	17	partial	partial	ADJ
admet-2772	160	18	least	least	ADJ
admet-2772	160	19	squares	square	NOUN
admet-2772	160	20	regression	regression	NOUN
admet-2772	160	21	,	,	PUNCT
admet-2772	160	22	svm	svm	VERB
admet-2772	160	23	training	training	NOUN
admet-2772	160	24	set	set	NOUN
admet-2772	160	25	:	:	PUNCT
admet-2772	160	26	r2=	r2=	PROPN
admet-2772	160	27	0.66	0.66	NUM
admet-2772	160	28	;	;	PUNCT
admet-2772	160	29	rmse	rmse	NOUN
admet-2772	160	30	 	 	SPACE
admet-2772	160	31	=	=	SYM
admet-2772	160	32	 	 	SPACE
admet-2772	160	33	12.5	12.5	NUM
admet-2772	160	34	test	test	NOUN
admet-2772	160	35	set	set	NOUN
admet-2772	160	36	:	:	PUNCT
admet-2772	160	37	r2=	r2=	PROPN
admet-2772	160	38	0.77	0.77	NUM
admet-2772	160	39	;	;	PUNCT
admet-2772	160	40	rmse	rmse	NOUN
admet-2772	160	41	 	 	SPACE
admet-2772	161	1	=	=	NOUN
admet-2772	161	2	 	 	SPACE
admet-2772	161	3	16	16	NUM
admet-2772	162	1	[	[	X
admet-2772	162	2	56	56	NUM
admet-2772	162	3	]	]	SYM
admet-2772	162	4	1593	1593	NUM
admet-2772	163	1	hia	hia	PROPN
admet-2772	163	2	1d	1d	NUM
admet-2772	163	3	2d	2d	NUM
admet-2772	163	4	theoretical	theoretical	ADJ
admet-2772	163	5	descriptors	descriptor	NOUN
admet-2772	163	6	svm	svm	VERB
admet-2772	163	7	accuracy	accuracy	NOUN
admet-2772	163	8	:	:	PUNCT
admet-2772	163	9	training	training	NOUN
admet-2772	163	10	set	set	NOUN
admet-2772	163	11	 	 	SPACE
admet-2772	163	12	=	=	NOUN
admet-2772	163	13	 	 	SPACE
admet-2772	163	14	98.5	98.5	NUM
admet-2772	163	15	%	%	NOUN
admet-2772	163	16	,	,	PUNCT
admet-2772	163	17	test	test	NOUN
admet-2772	163	18	set	set	VERB
admet-2772	163	19	=	=	NOUN
admet-2772	163	20	 	 	SPACE
admet-2772	163	21	99	99	NUM
admet-2772	163	22	%	%	NOUN
admet-2772	164	1	[	[	X
admet-2772	164	2	57	57	NUM
admet-2772	164	3	]	]	PUNCT
admet-2772	164	4	970	970	NUM
admet-2772	164	5	hia	hia	PROPN
admet-2772	164	6	2d	2d	PROPN
admet-2772	164	7	3d	3d	PROPN
admet-2772	164	8	descriptors	descriptor	NOUN
admet-2772	164	9	,	,	PUNCT
admet-2772	164	10	molecular	molecular	ADJ
admet-2772	164	11	fingerprints	fingerprint	NOUN
admet-2772	164	12	and	and	CCONJ
admet-2772	164	13	structural	structural	ADJ
admet-2772	164	14	fragments	fragment	NOUN
admet-2772	164	15	random	random	ADJ
admet-2772	164	16	forest	forest	NOUN
admet-2772	164	17	training	training	NOUN
admet-2772	164	18	set	set	NOUN
admet-2772	164	19	:	:	PUNCT
admet-2772	164	20	se	se	X
admet-2772	164	21	 	 	SPACE
admet-2772	164	22	=	=	NOUN
admet-2772	164	23	 	 	SPACE
admet-2772	164	24	0.89	0.89	NUM
admet-2772	164	25	;	;	PUNCT
admet-2772	164	26	sp	sp	NOUN
admet-2772	164	27	 	 	SPACE
admet-2772	164	28	=	=	NOUN
admet-2772	164	29	 	 	SPACE
admet-2772	164	30	0.85	0.85	NUM
admet-2772	164	31	;	;	PUNCT
admet-2772	164	32	q	q	X
admet-2772	164	33	 	 	SPACE
admet-2772	164	34	=	=	NOUN
admet-2772	164	35	 	 	SPACE
admet-2772	164	36	0.89	0.89	NUM
admet-2772	164	37	test	test	NOUN
admet-2772	164	38	set	set	NOUN
admet-2772	164	39	:	:	PUNCT
admet-2772	164	40	se	se	X
admet-2772	164	41	 	 	SPACE
admet-2772	164	42	=	=	PRON
admet-2772	164	43	 	 	SPACE
admet-2772	164	44	0.88	0.88	NUM
admet-2772	164	45	;	;	PUNCT
admet-2772	164	46	sp	sp	NOUN
admet-2772	164	47	 	 	SPACE
admet-2772	164	48	=	=	NOUN
admet-2772	164	49	 	 	SPACE
admet-2772	164	50	0.81	0.81	NUM
admet-2772	164	51	;	;	PUNCT
admet-2772	164	52	q	q	X
admet-2772	164	53	 	 	SPACE
admet-2772	164	54	=	=	NOUN
admet-2772	164	55	 	 	SPACE
admet-2772	164	56	0.87	0.87	NUM
admet-2772	165	1	[	[	X
admet-2772	165	2	58	58	NUM
admet-2772	165	3	]	]	PUNCT
admet-2772	165	4	hia	hia	PROPN
admet-2772	165	5	human	human	ADJ
admet-2772	165	6	intestinal	intestinal	ADJ
admet-2772	165	7	absorption	absorption	NOUN
admet-2772	165	8	;	;	PUNCT
admet-2772	165	9	svm	svm	VERB
admet-2772	165	10	support	support	NOUN
admet-2772	165	11	vector	vector	NOUN
admet-2772	165	12	machines	machine	NOUN
admet-2772	165	13	;	;	PUNCT
admet-2772	165	14	mcc	mcc	PROPN
admet-2772	165	15	matthews	matthews	PROPN
admet-2772	165	16	correlation	correlation	NOUN
admet-2772	165	17	coefficient	coefficient	NOUN
admet-2772	165	18	;	;	PUNCT
admet-2772	165	19	auc	auc	NOUN
admet-2772	165	20	area	area	NOUN
admet-2772	165	21	under	under	ADP
admet-2772	165	22	the	the	DET
admet-2772	165	23	curve	curve	NOUN
admet-2772	165	24	;	;	PUNCT
admet-2772	165	25	mars	mar	NOUN
admet-2772	165	26	multivariate	multivariate	VERB
admet-2772	165	27	adaptive	adaptive	ADJ
admet-2772	165	28	regression	regression	NOUN
admet-2772	165	29	splines	spline	NOUN
admet-2772	165	30	;	;	PUNCT
admet-2772	165	31	rmseroot	rmseroot	NOUN
admet-2772	165	32	mean	mean	VERB
admet-2772	165	33	square	square	ADJ
admet-2772	165	34	error	error	NOUN
admet-2772	165	35	;	;	PUNCT
admet-2772	165	36	ka	ka	PROPN
admet-2772	165	37	absorption	absorption	NOUN
admet-2772	165	38	rate	rate	NOUN
admet-2772	165	39	constant	constant	ADJ
admet-2772	165	40	;	;	PUNCT
admet-2772	165	41	se	se	X
admet-2772	165	42	sensitivity	sensitivity	NOUN
admet-2772	165	43	;	;	PUNCT
admet-2772	165	44	sp	sp	ADP
admet-2772	165	45	specificity	specificity	NOUN
admet-2772	165	46	;	;	PUNCT
admet-2772	165	47	q	q	PUNCT
admet-2772	165	48	accuracy	accuracy	NOUN
admet-2772	165	49	the	the	DET
admet-2772	165	50	ability	ability	NOUN
admet-2772	165	51	to	to	PART
admet-2772	165	52	predict	predict	VERB
admet-2772	165	53	intestinal	intestinal	ADJ
admet-2772	165	54	absorption	absorption	NOUN
admet-2772	165	55	and	and	CCONJ
admet-2772	165	56	permeability	permeability	NOUN
admet-2772	165	57	can	can	AUX
admet-2772	165	58	significantly	significantly	ADV
admet-2772	165	59	aid	aid	VERB
admet-2772	165	60	in	in	ADP
admet-2772	165	61	drug	drug	NOUN
admet-2772	165	62	development	development	NOUN
admet-2772	165	63	by	by	ADP
admet-2772	165	64	facilitating	facilitate	VERB
admet-2772	165	65	the	the	DET
admet-2772	165	66	selection	selection	NOUN
admet-2772	165	67	of	of	ADP
admet-2772	165	68	promising	promise	VERB
admet-2772	165	69	candidates	candidate	NOUN
admet-2772	165	70	and	and	CCONJ
admet-2772	165	71	potentially	potentially	ADV
admet-2772	165	72	reducing	reduce	VERB
admet-2772	165	73	attrition	attrition	NOUN
admet-2772	165	74	rates	rate	NOUN
admet-2772	165	75	in	in	ADP
admet-2772	165	76	clinical	clinical	ADJ
admet-2772	165	77	trials	trial	NOUN
admet-2772	165	78	[	[	X
admet-2772	165	79	52	52	NUM
admet-2772	165	80	]	]	PUNCT
admet-2772	165	81	.	.	PUNCT
admet-2772	166	1	bei	bei	NOUN
admet-2772	166	2	et	et	NOUN
admet-2772	166	3	al	al	PROPN
admet-2772	166	4	.	.	PUNCT
admet-2772	167	1	[	[	X
admet-2772	167	2	59	59	NUM
admet-2772	167	3	]	]	PUNCT
admet-2772	167	4	developed	develop	VERB
admet-2772	167	5	an	an	DET
admet-2772	167	6	xgboost	xgboost	PROPN
admet-2772	167	7	model	model	NOUN
admet-2772	167	8	to	to	PART
admet-2772	167	9	predict	predict	VERB
admet-2772	167	10	the	the	DET
admet-2772	167	11	subcutaneous	subcutaneous	ADJ
admet-2772	167	12	absorption	absorption	NOUN
admet-2772	167	13	rate	rate	NOUN
admet-2772	167	14	constant	constant	ADJ
admet-2772	167	15	of	of	ADP
admet-2772	167	16	monoclonal	monoclonal	NOUN
admet-2772	167	17	antibodies	antibody	NOUN
admet-2772	167	18	using	use	VERB
admet-2772	167	19	only	only	ADV
admet-2772	167	20	their	their	PRON
admet-2772	167	21	primary	primary	ADJ
admet-2772	167	22	sequence	sequence	NOUN
admet-2772	167	23	.	.	PUNCT
admet-2772	168	1	kamiya	kamiya	PROPN
admet-2772	168	2	et	et	PROPN
admet-2772	168	3	al	al	PROPN
admet-2772	168	4	.	.	PUNCT
admet-2772	169	1	[	[	X
admet-2772	169	2	60	60	NUM
admet-2772	169	3	]	]	PUNCT
admet-2772	169	4	used	use	VERB
admet-2772	169	5	machine	machine	NOUN
admet-2772	169	6	learning	learn	VERB
admet-2772	169	7	to	to	PART
admet-2772	169	8	estimate	estimate	VERB
admet-2772	169	9	key	key	ADJ
admet-2772	169	10	physiologically	physiologically	ADV
admet-2772	169	11	based	base	VERB
admet-2772	169	12	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	169	13	model	model	NOUN
admet-2772	169	14	parameters	parameter	NOUN
admet-2772	169	15	,	,	PUNCT
admet-2772	169	16	including	include	VERB
admet-2772	169	17	absorption	absorption	NOUN
admet-2772	169	18	rate	rate	NOUN
admet-2772	169	19	constants	constant	NOUN
admet-2772	169	20	,	,	PUNCT
admet-2772	169	21	for	for	ADP
admet-2772	169	22	212	212	NUM
admet-2772	169	23	diverse	diverse	ADJ
admet-2772	169	24	chemicals	chemical	NOUN
admet-2772	169	25	.	.	PUNCT
admet-2772	170	1	karalis	karalis	PROPN
admet-2772	171	1	[	[	X
admet-2772	171	2	61	61	NUM
admet-2772	171	3	]	]	PUNCT
admet-2772	171	4	applied	apply	VERB
admet-2772	171	5	machine	machine	NOUN
admet-2772	171	6	learning	learn	VERB
admet-2772	171	7	techniques	technique	NOUN
admet-2772	171	8	to	to	PART
admet-2772	171	9	identify	identify	VERB
admet-2772	171	10	the	the	DET
admet-2772	171	11	maximum	maximum	ADJ
admet-2772	171	12	plasma	plasma	NOUN
admet-2772	171	13	concentration	concentration	NOUN
admet-2772	171	14	(	(	PUNCT
admet-2772	171	15	cmax	cmax	NOUN
admet-2772	171	16	)	)	PUNCT
admet-2772	171	17	/	/	SYM
admet-2772	171	18	time	time	NOUN
admet-2772	171	19	to	to	PART
admet-2772	171	20	reach	reach	VERB
admet-2772	171	21	cmax	cmax	NOUN
admet-2772	171	22	(	(	PUNCT
admet-2772	171	23	tmax	tmax	ADV
admet-2772	171	24	)	)	PUNCT
admet-2772	171	25	ratio	ratio	NOUN
admet-2772	171	26	as	as	ADP
admet-2772	171	27	a	a	DET
admet-2772	171	28	potentially	potentially	ADV
admet-2772	171	29	superior	superior	ADJ
admet-2772	171	30	metric	metric	NOUN
admet-2772	171	31	for	for	ADP
admet-2772	171	32	absorption	absorption	NOUN
admet-2772	171	33	rate	rate	NOUN
admet-2772	171	34	in	in	ADP
admet-2772	171	35	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	171	36	m.	m.	NOUN
admet-2772	171	37	venkataraman	venkataraman	PROPN
admet-2772	171	38	et	et	PROPN
admet-2772	171	39	al	al	PROPN
admet-2772	171	40	.	.	PROPN
admet-2772	171	41	admet	admet	PROPN
admet-2772	171	42	&	&	CCONJ
admet-2772	171	43	dmpk	dmpk	PROPN
admet-2772	171	44	13(3	13(3	NUM
admet-2772	171	45	)	)	PUNCT
admet-2772	171	46	(	(	PUNCT
admet-2772	171	47	2025	2025	NUM
admet-2772	171	48	)	)	PUNCT
admet-2772	171	49	2772	2772	NUM
admet-2772	171	50	8	8	NUM
admet-2772	171	51	bioequivalence	bioequivalence	NOUN
admet-2772	171	52	studies	study	NOUN
admet-2772	171	53	.	.	PUNCT
admet-2772	172	1	kumar	kumar	PROPN
admet-2772	172	2	et	et	PROPN
admet-2772	172	3	al	al	PROPN
admet-2772	172	4	.	.	PUNCT
admet-2772	173	1	[	[	X
admet-2772	173	2	62	62	NUM
admet-2772	173	3	]	]	PUNCT
admet-2772	173	4	implemented	implement	VERB
admet-2772	173	5	a	a	DET
admet-2772	173	6	graph	graph	NOUN
admet-2772	173	7	convolutional	convolutional	ADJ
admet-2772	173	8	neural	neural	ADJ
admet-2772	173	9	network	network	NOUN
admet-2772	173	10	model	model	NOUN
admet-2772	173	11	to	to	PART
admet-2772	173	12	predict	predict	VERB
admet-2772	173	13	18	18	NUM
admet-2772	173	14	early	early	ADJ
admet-2772	173	15	adme	adme	NOUN
admet-2772	173	16	properties	property	NOUN
admet-2772	173	17	across	across	ADP
admet-2772	173	18	an	an	DET
admet-2772	173	19	enterprise	enterprise	NOUN
admet-2772	173	20	-	-	PUNCT
admet-2772	173	21	wide	wide	ADJ
admet-2772	173	22	drug	drug	NOUN
admet-2772	173	23	discovery	discovery	NOUN
admet-2772	173	24	pipeline	pipeline	NOUN
admet-2772	173	25	.	.	PUNCT
admet-2772	174	1	an	an	DET
admet-2772	174	2	integrated	integrate	VERB
admet-2772	174	3	strategy	strategy	NOUN
admet-2772	174	4	combining	combine	VERB
admet-2772	174	5	multiple	multiple	ADJ
admet-2772	174	6	machine	machine	NOUN
admet-2772	174	7	learning	learning	NOUN
admet-2772	174	8	models	model	NOUN
admet-2772	174	9	and	and	CCONJ
admet-2772	174	10	physiologically	physiologically	ADV
admet-2772	174	11	-	-	PUNCT
admet-2772	174	12	based	base	VERB
admet-2772	174	13	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	174	14	models	model	NOUN
admet-2772	174	15	achieved	achieve	VERB
admet-2772	174	16	promising	promise	VERB
admet-2772	174	17	results	result	NOUN
admet-2772	174	18	in	in	ADP
admet-2772	174	19	predicting	predict	VERB
admet-2772	174	20	human	human	ADJ
admet-2772	174	21	oral	oral	ADJ
admet-2772	174	22	bioavailability	bioavailability	NOUN
admet-2772	174	23	directly	directly	ADV
admet-2772	174	24	from	from	ADP
admet-2772	174	25	chemical	chemical	ADJ
admet-2772	174	26	structure	structure	NOUN
admet-2772	174	27	[	[	X
admet-2772	174	28	63	63	NUM
admet-2772	174	29	]	]	PUNCT
admet-2772	174	30	.	.	PUNCT
admet-2772	175	1	artificial	artificial	ADJ
admet-2772	175	2	neural	neural	ADJ
admet-2772	175	3	networks	network	NOUN
admet-2772	175	4	outperformed	outperform	VERB
admet-2772	175	5	support	support	NOUN
admet-2772	175	6	vector	vector	NOUN
admet-2772	175	7	machines	machine	NOUN
admet-2772	175	8	in	in	ADP
admet-2772	175	9	predicting	predict	VERB
admet-2772	175	10	food	food	NOUN
admet-2772	175	11	effects	effect	NOUN
admet-2772	175	12	on	on	ADP
admet-2772	175	13	bioavailability	bioavailability	NOUN
admet-2772	175	14	,	,	PUNCT
admet-2772	175	15	with	with	ADP
admet-2772	175	16	key	key	ADJ
admet-2772	175	17	factors	factor	NOUN
admet-2772	175	18	including	include	VERB
admet-2772	175	19	octanol	octanol	NOUN
admet-2772	175	20	water	water	NOUN
admet-2772	175	21	partition	partition	NOUN
admet-2772	175	22	coefficient	coefficient	NOUN
admet-2772	175	23	,	,	PUNCT
admet-2772	175	24	hydrogen	hydrogen	NOUN
admet-2772	175	25	bond	bond	NOUN
admet-2772	175	26	donors	donor	NOUN
admet-2772	175	27	,	,	PUNCT
admet-2772	175	28	topological	topological	ADJ
admet-2772	175	29	polar	polar	ADJ
admet-2772	175	30	surface	surface	NOUN
admet-2772	175	31	area	area	NOUN
admet-2772	175	32	,	,	PUNCT
admet-2772	175	33	and	and	CCONJ
admet-2772	175	34	dose	dose	VERB
admet-2772	175	35	[	[	PUNCT
admet-2772	175	36	64	64	NUM
admet-2772	175	37	]	]	PUNCT
admet-2772	175	38	.	.	PUNCT
admet-2772	176	1	graph	graph	VERB
admet-2772	176	2	neural	neural	ADJ
admet-2772	176	3	networks	network	NOUN
admet-2772	176	4	with	with	ADP
admet-2772	176	5	transfer	transfer	NOUN
admet-2772	176	6	learning	learning	NOUN
admet-2772	176	7	have	have	AUX
admet-2772	176	8	also	also	ADV
admet-2772	176	9	shown	show	VERB
admet-2772	176	10	potential	potential	NOUN
admet-2772	176	11	in	in	ADP
admet-2772	176	12	predicting	predict	VERB
admet-2772	176	13	oral	oral	ADJ
admet-2772	176	14	bioavailability	bioavailability	NOUN
admet-2772	176	15	,	,	PUNCT
admet-2772	176	16	outperforming	outperform	VERB
admet-2772	176	17	previous	previous	ADJ
admet-2772	176	18	studies	study	NOUN
admet-2772	176	19	by	by	ADP
admet-2772	176	20	automatically	automatically	ADV
admet-2772	176	21	extracting	extract	VERB
admet-2772	176	22	important	important	ADJ
admet-2772	176	23	features	feature	NOUN
admet-2772	176	24	from	from	ADP
admet-2772	176	25	molecular	molecular	ADJ
admet-2772	176	26	structures	structure	NOUN
admet-2772	176	27	[	[	X
admet-2772	176	28	65	65	NUM
admet-2772	176	29	]	]	PUNCT
admet-2772	176	30	.	.	PUNCT
admet-2772	177	1	these	these	DET
admet-2772	177	2	studies	study	NOUN
admet-2772	177	3	demonstrate	demonstrate	VERB
admet-2772	177	4	the	the	DET
admet-2772	177	5	potential	potential	NOUN
admet-2772	177	6	of	of	ADP
admet-2772	177	7	machine	machine	NOUN
admet-2772	177	8	learning	learn	VERB
admet-2772	177	9	to	to	PART
admet-2772	177	10	enhance	enhance	VERB
admet-2772	177	11	the	the	DET
admet-2772	177	12	prediction	prediction	NOUN
admet-2772	177	13	of	of	ADP
admet-2772	177	14	absorption	absorption	NOUN
admet-2772	177	15	kinetics	kinetic	NOUN
admet-2772	177	16	and	and	CCONJ
admet-2772	177	17	other	other	ADJ
admet-2772	177	18	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	177	19	parameters	parameter	NOUN
admet-2772	177	20	,	,	PUNCT
admet-2772	177	21	potentially	potentially	ADV
admet-2772	177	22	accelerating	accelerate	VERB
admet-2772	177	23	drug	drug	NOUN
admet-2772	177	24	development	development	NOUN
admet-2772	177	25	processes	process	NOUN
admet-2772	177	26	.	.	PUNCT
admet-2772	178	1	3.2	3.2	NUM
admet-2772	178	2	.	.	PUNCT
admet-2772	178	3	distribution	distribution	NOUN
admet-2772	178	4	prediction	prediction	NOUN
admet-2772	178	5	this	this	DET
admet-2772	178	6	summary	summary	NOUN
admet-2772	178	7	examines	examine	VERB
admet-2772	178	8	models	model	NOUN
admet-2772	178	9	for	for	ADP
admet-2772	178	10	predicting	predict	VERB
admet-2772	178	11	drug	drug	NOUN
admet-2772	178	12	distribution	distribution	NOUN
admet-2772	178	13	in	in	ADP
admet-2772	178	14	the	the	DET
admet-2772	178	15	body	body	NOUN
admet-2772	178	16	,	,	PUNCT
admet-2772	178	17	focusing	focus	VERB
admet-2772	178	18	on	on	ADP
admet-2772	178	19	blood	blood	NOUN
admet-2772	178	20	-	-	PUNCT
admet-2772	178	21	brain	brain	NOUN
admet-2772	178	22	barrier	barrier	NOUN
admet-2772	178	23	(	(	PUNCT
admet-2772	178	24	bbb	bbb	NOUN
admet-2772	178	25	)	)	PUNCT
admet-2772	178	26	penetration	penetration	NOUN
admet-2772	178	27	and	and	CCONJ
admet-2772	178	28	volume	volume	NOUN
admet-2772	178	29	of	of	ADP
admet-2772	178	30	distribution	distribution	NOUN
admet-2772	178	31	.	.	PUNCT
admet-2772	179	1	physiologically	physiologically	ADV
admet-2772	179	2	-	-	PUNCT
admet-2772	179	3	based	base	VERB
admet-2772	179	4	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	179	5	(	(	PUNCT
admet-2772	179	6	pbpk	pbpk	NOUN
admet-2772	179	7	)	)	PUNCT
admet-2772	179	8	models	model	NOUN
admet-2772	179	9	are	be	AUX
admet-2772	179	10	commonly	commonly	ADV
admet-2772	179	11	used	use	VERB
admet-2772	179	12	to	to	PART
admet-2772	179	13	predict	predict	VERB
admet-2772	179	14	tissue	tissue	NOUN
admet-2772	179	15	:	:	PUNCT
admet-2772	179	16	plasma	plasma	NOUN
admet-2772	179	17	partition	partition	NOUN
admet-2772	179	18	coefficients	coefficient	NOUN
admet-2772	179	19	and	and	CCONJ
admet-2772	179	20	volume	volume	NOUN
admet-2772	179	21	of	of	ADP
admet-2772	179	22	distribution	distribution	NOUN
admet-2772	179	23	[	[	X
admet-2772	179	24	66	66	NUM
admet-2772	179	25	]	]	PUNCT
admet-2772	179	26	.	.	PUNCT
admet-2772	180	1	key	key	ADJ
admet-2772	180	2	factors	factor	NOUN
admet-2772	180	3	affecting	affect	VERB
admet-2772	180	4	bbb	bbb	NOUN
admet-2772	180	5	penetration	penetration	NOUN
admet-2772	180	6	include	include	VERB
admet-2772	180	7	permeability	permeability	NOUN
admet-2772	180	8	-	-	PUNCT
admet-2772	180	9	surface	surface	NOUN
admet-2772	180	10	area	area	NOUN
admet-2772	180	11	product	product	NOUN
admet-2772	180	12	(	(	PUNCT
admet-2772	180	13	ps	ps	NOUN
admet-2772	180	14	)	)	PUNCT
admet-2772	180	15	,	,	PUNCT
admet-2772	180	16	unbound	unbound	NOUN
admet-2772	180	17	fraction	fraction	NOUN
admet-2772	180	18	in	in	ADP
admet-2772	180	19	plasma	plasma	NOUN
admet-2772	180	20	(	(	PUNCT
admet-2772	180	21	fu	fu	ADJ
admet-2772	180	22	,	,	PUNCT
admet-2772	180	23	plasma	plasma	NOUN
admet-2772	180	24	)	)	PUNCT
admet-2772	180	25	,	,	PUNCT
admet-2772	180	26	and	and	CCONJ
admet-2772	180	27	brain	brain	NOUN
admet-2772	180	28	tissue	tissue	NOUN
admet-2772	180	29	(	(	PUNCT
admet-2772	180	30	fu	fu	ADJ
admet-2772	180	31	,	,	PUNCT
admet-2772	180	32	brain	brain	NOUN
admet-2772	180	33	)	)	PUNCT
admet-2772	181	1	[	[	X
admet-2772	181	2	67	67	NUM
admet-2772	181	3	]	]	PUNCT
admet-2772	181	4	(	(	PUNCT
admet-2772	181	5	see	see	VERB
admet-2772	181	6	table	table	NOUN
admet-2772	181	7	4	4	NUM
admet-2772	181	8	for	for	ADP
admet-2772	181	9	an	an	DET
admet-2772	181	10	overview	overview	NOUN
admet-2772	181	11	of	of	ADP
admet-2772	181	12	machine	machine	NOUN
admet-2772	181	13	learning	learning	NOUN
admet-2772	181	14	-	-	PUNCT
admet-2772	181	15	based	base	VERB
admet-2772	181	16	models	model	NOUN
admet-2772	181	17	for	for	ADP
admet-2772	181	18	distribution	distribution	NOUN
admet-2772	181	19	prediction	prediction	NOUN
admet-2772	181	20	)	)	PUNCT
admet-2772	181	21	.	.	PUNCT
admet-2772	182	1	in	in	ADP
admet-2772	182	2	vivo	vivo	ADJ
admet-2772	182	3	methods	method	NOUN
admet-2772	182	4	,	,	PUNCT
admet-2772	182	5	such	such	ADJ
admet-2772	182	6	as	as	ADP
admet-2772	182	7	brain	brain	NOUN
admet-2772	182	8	microdialysis	microdialysis	NOUN
admet-2772	182	9	and	and	CCONJ
admet-2772	182	10	in	in	ADP
admet-2772	182	11	situ	situ	ADJ
admet-2772	182	12	brain	brain	NOUN
admet-2772	182	13	perfusion	perfusion	NOUN
admet-2772	182	14	,	,	PUNCT
admet-2772	182	15	are	be	AUX
admet-2772	182	16	valuable	valuable	ADJ
admet-2772	182	17	for	for	ADP
admet-2772	182	18	assessing	assess	VERB
admet-2772	182	19	brain	brain	NOUN
admet-2772	182	20	drug	drug	NOUN
admet-2772	182	21	distribution	distribution	NOUN
admet-2772	182	22	[	[	X
admet-2772	182	23	68	68	NUM
admet-2772	182	24	]	]	PUNCT
admet-2772	182	25	.	.	PUNCT
admet-2772	183	1	table	table	NOUN
admet-2772	183	2	4	4	NUM
admet-2772	183	3	.	.	PUNCT
admet-2772	184	1	summary	summary	NOUN
admet-2772	184	2	of	of	ADP
admet-2772	184	3	machine	machine	NOUN
admet-2772	184	4	learning	learning	NOUN
admet-2772	184	5	-	-	PUNCT
admet-2772	184	6	based	base	VERB
admet-2772	184	7	models	model	NOUN
admet-2772	184	8	for	for	ADP
admet-2772	184	9	distribution	distribution	NOUN
admet-2772	184	10	prediction	prediction	NOUN
admet-2772	184	11	no	no	INTJ
admet-2772	184	12	.	.	PUNCT
admet-2772	184	13	of	of	ADP
admet-2772	184	14	comp	comp	PROPN
admet-2772	184	15	.	.	PUNCT
admet-2772	185	1	target	target	NOUN
admet-2772	185	2	descriptors	descriptor	NOUN
admet-2772	185	3	modelling	model	VERB
admet-2772	185	4	method	method	NOUN
admet-2772	185	5	performance	performance	NOUN
admet-2772	185	6	ref	ref	NOUN
admet-2772	185	7	.	.	PUNCT
admet-2772	186	1	529	529	NUM
admet-2772	186	2	kp	kp	PROPN
admet-2772	186	3	fragmental	fragmental	ADJ
admet-2772	186	4	descriptors	descriptor	NOUN
admet-2772	186	5	feed	feed	NOUN
admet-2772	186	6	-	-	PUNCT
admet-2772	186	7	forward	forward	NOUN
admet-2772	186	8	back	back	NOUN
admet-2772	186	9	propagation	propagation	NOUN
admet-2772	186	10	neural	neural	ADJ
admet-2772	186	11	network	network	NOUN
admet-2772	186	12	q	q	NOUN
admet-2772	187	1	=	=	NOUN
admet-2772	187	2	0.815	0.815	NUM
admet-2772	187	3	,	,	PUNCT
admet-2772	187	4	rmsecv	rmsecv	ADJ
admet-2772	188	1	=	=	NOUN
admet-2772	188	2	0.318	0.318	NUM
admet-2772	189	1	[	[	X
admet-2772	189	2	69	69	NUM
admet-2772	189	3	]	]	SYM
admet-2772	189	4	6741	6741	NUM
admet-2772	189	5	ppb	ppb	NOUN
admet-2772	189	6	2d	2d	NOUN
admet-2772	189	7	,	,	PUNCT
admet-2772	189	8	3d	3d	NUM
admet-2772	189	9	,	,	PUNCT
admet-2772	189	10	and	and	CCONJ
admet-2772	189	11	fingerprints	fingerprint	VERB
admet-2772	189	12	consensus	consensus	NOUN
admet-2772	189	13	of	of	ADP
admet-2772	189	14	k	k	NOUN
admet-2772	189	15	-	-	PUNCT
admet-2772	189	16	nearest	near	ADJ
admet-2772	189	17	neighbours	neighbour	NOUN
admet-2772	189	18	,	,	PUNCT
admet-2772	189	19	support	support	NOUN
admet-2772	189	20	vector	vector	NOUN
admet-2772	189	21	regression	regression	NOUN
admet-2772	189	22	,	,	PUNCT
admet-2772	189	23	rf	rf	NOUN
admet-2772	189	24	,	,	PUNCT
admet-2772	189	25	boosted	boost	VERB
admet-2772	189	26	trees	tree	NOUN
admet-2772	189	27	and	and	CCONJ
admet-2772	189	28	gradient	gradient	NOUN
admet-2772	189	29	boosting	boost	VERB
admet-2772	189	30	regressor	regressor	NOUN
admet-2772	189	31	mae	mae	PROPN
admet-2772	189	32	=	=	PROPN
admet-2772	189	33	0.089	0.089	NUM
admet-2772	189	34	,	,	PUNCT
admet-2772	189	35	rmse	rmse	NOUN
admet-2772	189	36	=	=	PROPN
admet-2772	189	37	0.153	0.153	NUM
admet-2772	189	38	;	;	PUNCT
admet-2772	189	39	r2=	r2=	NUM
admet-2772	189	40	0.738	0.738	NUM
admet-2772	189	41	[	[	X
admet-2772	189	42	70	70	NUM
admet-2772	189	43	]	]	SYM
admet-2772	189	44	21	21	NUM
admet-2772	189	45	kp	kp	NOUN
admet-2772	189	46	not	not	PART
admet-2772	189	47	explained	explain	VERB
admet-2772	189	48	bioisim	bioisim	ADJ
admet-2772	189	49	test	test	NOUN
admet-2772	189	50	set	set	NOUN
admet-2772	189	51	:	:	PUNCT
admet-2772	189	52	afe	afe	PROPN
admet-2772	189	53	=	=	PROPN
admet-2772	189	54	0.96	0.96	NUM
admet-2772	189	55	(	(	PUNCT
admet-2772	189	56	cmax	cmax	NOUN
admet-2772	189	57	)	)	PUNCT
admet-2772	189	58	,	,	PUNCT
admet-2772	189	59	0.89	0.89	NUM
admet-2772	189	60	(	(	PUNCT
admet-2772	189	61	auc	auc	NOUN
admet-2772	189	62	)	)	PUNCT
admet-2772	189	63	,	,	PUNCT
admet-2772	189	64	0.69	0.69	NUM
admet-2772	189	65	(	(	PUNCT
admet-2772	189	66	vdss	vdss	ADJ
admet-2772	189	67	)	)	PUNCT
admet-2772	189	68	;	;	PUNCT
admet-2772	189	69	aafe	aafe	NOUN
admet-2772	189	70	=	=	SYM
admet-2772	189	71	1.20	1.20	NUM
admet-2772	189	72	(	(	PUNCT
admet-2772	189	73	cmax	cmax	NOUN
admet-2772	189	74	)	)	PUNCT
admet-2772	189	75	,	,	PUNCT
admet-2772	189	76	1.30	1.30	NUM
admet-2772	189	77	(	(	PUNCT
admet-2772	189	78	auc	auc	NOUN
admet-2772	189	79	)	)	PUNCT
admet-2772	189	80	,	,	PUNCT
admet-2772	189	81	1.71	1.71	NUM
admet-2772	189	82	(	(	PUNCT
admet-2772	189	83	vdss	vdss	ADJ
admet-2772	189	84	)	)	PUNCT
admet-2772	189	85	;	;	PUNCT
admet-2772	189	86	r2=	r2=	PROPN
admet-2772	189	87	0.99	0.99	NUM
admet-2772	189	88	(	(	PUNCT
admet-2772	189	89	cmax	cmax	NOUN
admet-2772	189	90	)	)	PUNCT
admet-2772	189	91	,	,	PUNCT
admet-2772	189	92	0.98	0.98	NUM
admet-2772	189	93	(	(	PUNCT
admet-2772	189	94	auc	auc	NOUN
admet-2772	189	95	)	)	PUNCT
admet-2772	189	96	,	,	PUNCT
admet-2772	189	97	0.99	0.99	NUM
admet-2772	189	98	(	(	PUNCT
admet-2772	189	99	vdss	vdss	ADV
admet-2772	189	100	)	)	PUNCT
admet-2772	190	1	[	[	X
admet-2772	190	2	71	71	NUM
admet-2772	190	3	]	]	SYM
admet-2772	190	4	227	227	NUM
admet-2772	190	5	ppb	ppb	NOUN
admet-2772	190	6	constitutional	constitutional	ADJ
admet-2772	190	7	descriptors	descriptor	NOUN
admet-2772	190	8	,	,	PUNCT
admet-2772	190	9	topological	topological	ADJ
admet-2772	190	10	descriptors	descriptor	NOUN
admet-2772	190	11	,	,	PUNCT
admet-2772	190	12	geometric	geometric	ADJ
admet-2772	190	13	descriptors	descriptor	NOUN
admet-2772	190	14	,	,	PUNCT
admet-2772	190	15	molecular	molecular	ADJ
admet-2772	190	16	properties	property	NOUN
admet-2772	190	17	and	and	CCONJ
admet-2772	190	18	rdf	rdf	VERB
admet-2772	190	19	descriptors	descriptor	NOUN
admet-2772	190	20	qsar	qsar	NOUN
admet-2772	190	21	,	,	PUNCT
admet-2772	190	22	convolutional	convolutional	ADJ
admet-2772	190	23	neural	neural	ADJ
admet-2772	190	24	network	network	NOUN
admet-2772	190	25	,	,	PUNCT
admet-2772	190	26	feedforward	feedforward	ADJ
admet-2772	190	27	neural	neural	ADJ
admet-2772	190	28	network	network	NOUN
admet-2772	190	29	training	training	NOUN
admet-2772	190	30	set	set	NOUN
admet-2772	190	31	:	:	PUNCT
admet-2772	190	32	mae=	mae=	NOUN
admet-2772	190	33	0.066	0.066	NUM
admet-2772	190	34	,	,	PUNCT
admet-2772	190	35	r2=	r2=	PROPN
admet-2772	190	36	0.905	0.905	NUM
admet-2772	190	37	,	,	PUNCT
admet-2772	190	38	mse=	mse=	PROPN
admet-2772	190	39	0.011	0.011	NUM
admet-2772	190	40	test	test	NOUN
admet-2772	190	41	set	set	NOUN
admet-2772	190	42	:	:	PUNCT
admet-2772	190	43	mae=	mae=	NOUN
admet-2772	190	44	0.068	0.068	NUM
admet-2772	190	45	,	,	PUNCT
admet-2772	190	46	r2=	r2=	PROPN
admet-2772	190	47	0.945	0.945	NUM
admet-2772	190	48	,	,	PUNCT
admet-2772	190	49	mse=	mse=	PROPN
admet-2772	190	50	0.007	0.007	NUM
admet-2772	191	1	[	[	X
admet-2772	191	2	72	72	NUM
admet-2772	191	3	]	]	PUNCT
admet-2772	191	4	1970	1970	NUM
admet-2772	191	5	kp	kp	PROPN
admet-2772	191	6	daylight	daylight	NOUN
admet-2772	191	7	fingerprints	fingerprint	NOUN
admet-2772	191	8	,	,	PUNCT
admet-2772	191	9	atomic	atomic	ADJ
admet-2772	191	10	and	and	CCONJ
admet-2772	191	11	ring	ring	NOUN
admet-2772	191	12	multiplicities	multiplicity	NOUN
admet-2772	191	13	,	,	PUNCT
admet-2772	191	14	simple	simple	ADJ
admet-2772	191	15	molecular	molecular	ADJ
admet-2772	191	16	parameters	parameter	NOUN
admet-2772	191	17	and	and	CCONJ
admet-2772	191	18	chemical	chemical	NOUN
admet-2772	191	19	descriptors	descriptor	NOUN
admet-2772	191	20	rf	rf	VERB
admet-2772	191	21	,	,	PUNCT
admet-2772	191	22	svm	svm	VERB
admet-2772	191	23	overall	overall	ADJ
admet-2772	191	24	accuracy	accuracy	NOUN
admet-2772	191	25	of	of	ADP
admet-2772	191	26	95	95	NUM
admet-2772	191	27	%	%	NOUN
admet-2772	191	28	,	,	PUNCT
admet-2772	191	29	mean	mean	ADJ
admet-2772	191	30	square	square	ADJ
admet-2772	191	31	contingency	contingency	NOUN
admet-2772	191	32	coefficient	coefficient	NOUN
admet-2772	191	33	(	(	PUNCT
admet-2772	191	34			NOUN
admet-2772	191	35	)	)	PUNCT
admet-2772	191	36	of	of	ADP
admet-2772	191	37	0.74	0.74	NUM
admet-2772	191	38	[	[	X
admet-2772	191	39	73	73	NUM
admet-2772	191	40	]	]	SYM
admet-2772	191	41	310	310	NUM
admet-2772	191	42	bbb	bbb	PROPN
admet-2772	191	43	topological	topological	ADJ
admet-2772	191	44	descriptors	descriptor	NOUN
admet-2772	191	45	,	,	PUNCT
admet-2772	191	46	geometrical	geometrical	ADJ
admet-2772	191	47	descriptors	descriptor	NOUN
admet-2772	191	48	,	,	PUNCT
admet-2772	191	49	electrostatic	electrostatic	ADJ
admet-2772	191	50	and	and	CCONJ
admet-2772	191	51	quantum	quantum	ADJ
admet-2772	191	52	chemical	chemical	NOUN
admet-2772	191	53	descriptors	descriptor	NOUN
admet-2772	191	54	svm	svm	VERB
admet-2772	191	55	,	,	PUNCT
admet-2772	191	56	genetic	genetic	ADJ
admet-2772	191	57	algorithm	algorithm	NOUN
admet-2772	191	58	partial	partial	ADJ
admet-2772	191	59	least	least	ADJ
admet-2772	191	60	squares	square	NOUN
admet-2772	191	61	training	training	NOUN
admet-2772	191	62	set	set	NOUN
admet-2772	191	63	:	:	PUNCT
admet-2772	192	1	r2	r2	PROPN
admet-2772	192	2	=	=	SYM
admet-2772	192	3	0.98	0.98	NUM
admet-2772	192	4	,	,	PUNCT
admet-2772	192	5	rmse	rmse	NOUN
admet-2772	192	6	 	 	SPACE
admet-2772	192	7	=	=	NOUN
admet-2772	192	8	 	 	SPACE
admet-2772	192	9	0.117	0.117	NUM
admet-2772	192	10	test	test	NOUN
admet-2772	192	11	set	set	NOUN
admet-2772	192	12	:	:	PUNCT
admet-2772	192	13	r2	r2	PROPN
admet-2772	192	14	=	=	SYM
admet-2772	192	15	0.98	0.98	NUM
admet-2772	192	16	,	,	PUNCT
admet-2772	192	17	rmse	rmse	NOUN
admet-2772	192	18	 	 	SPACE
admet-2772	193	1	=	=	NOUN
admet-2772	193	2	 	 	SPACE
admet-2772	193	3	0.118	0.118	NUM
admet-2772	194	1	[	[	X
admet-2772	194	2	74	74	NUM
admet-2772	194	3	]	]	SYM
admet-2772	194	4	208	208	NUM
admet-2772	194	5	kp	kp	PROPN
admet-2772	194	6	constitutional	constitutional	ADJ
admet-2772	194	7	descriptors	descriptor	NOUN
admet-2772	194	8	,	,	PUNCT
admet-2772	194	9	topological	topological	ADJ
admet-2772	194	10	descriptors	descriptor	NOUN
admet-2772	194	11	,	,	PUNCT
admet-2772	194	12	geometric	geometric	ADJ
admet-2772	194	13	descriptors	descriptor	NOUN
admet-2772	194	14	,	,	PUNCT
admet-2772	194	15	electrostatic	electrostatic	ADJ
admet-2772	194	16	descriptors	descriptor	NOUN
admet-2772	194	17	and	and	CCONJ
admet-2772	194	18	quantum	quantum	NOUN
admet-2772	194	19	chemical	chemical	NOUN
admet-2772	194	20	descriptors	descriptor	NOUN
admet-2772	194	21	least	least	ADJ
admet-2772	194	22	squares	square	NOUN
admet-2772	194	23	svm	svm	ADJ
admet-2772	194	24	training	training	NOUN
admet-2772	194	25	set	set	NOUN
admet-2772	194	26	:	:	PUNCT
admet-2772	194	27	r2	r2	PROPN
admet-2772	194	28	=	=	SYM
admet-2772	194	29	0.97	0.97	NUM
admet-2772	194	30	,	,	PUNCT
admet-2772	194	31	rmse	rmse	NOUN
admet-2772	194	32	 	 	SPACE
admet-2772	194	33	=	=	NOUN
admet-2772	194	34	 	 	SPACE
admet-2772	194	35	0.0226	0.0226	NUM
admet-2772	194	36	test	test	NOUN
admet-2772	194	37	set	set	NOUN
admet-2772	194	38	:	:	PUNCT
admet-2772	194	39	r2	r2	PROPN
admet-2772	194	40	=	=	SYM
admet-2772	194	41	0.97	0.97	NUM
admet-2772	194	42	,	,	PUNCT
admet-2772	194	43	rmse	rmse	NOUN
admet-2772	194	44	 	 	SPACE
admet-2772	194	45	=	=	NOUN
admet-2772	194	46	 	 	SPACE
admet-2772	194	47	0.0289	0.0289	NUM
admet-2772	195	1	[	[	PUNCT
admet-2772	195	2	75	75	NUM
admet-2772	195	3	]	]	PUNCT
admet-2772	195	4	kp	kp	PROPN
admet-2772	195	5	tissue	tissue	NOUN
admet-2772	195	6	-	-	PUNCT
admet-2772	195	7	to	to	ADP
admet-2772	195	8	-	-	PUNCT
admet-2772	195	9	plasma	plasma	NOUN
admet-2772	195	10	partition	partition	NOUN
admet-2772	195	11	coefficient	coefficient	NOUN
admet-2772	195	12	;	;	PUNCT
admet-2772	195	13	ppb	ppb	NOUN
admet-2772	195	14	plasma	plasma	NOUN
admet-2772	195	15	protein	protein	NOUN
admet-2772	195	16	binding	bind	VERB
admet-2772	195	17	;	;	PUNCT
admet-2772	195	18	rf	rf	NUM
admet-2772	195	19	-random	-random	NOUN
admet-2772	195	20	forest	forest	NOUN
admet-2772	195	21	,	,	PUNCT
admet-2772	195	22	mae	mae	PROPN
admet-2772	195	23	-mean	-mean	NOUN
admet-2772	195	24	absolute	absolute	ADJ
admet-2772	195	25	error	error	NOUN
admet-2772	195	26	;	;	PUNCT
admet-2772	195	27	mse	mse	PROPN
admet-2772	195	28	mean	mean	PROPN
admet-2772	195	29	square	square	NOUN
admet-2772	195	30	error	error	NOUN
admet-2772	195	31	;	;	PUNCT
admet-2772	195	32	auc	auc	X
admet-2772	195	33	area	area	NOUN
admet-2772	195	34	under	under	ADP
admet-2772	195	35	the	the	DET
admet-2772	195	36	curve	curve	NOUN
admet-2772	195	37	;	;	PUNCT
admet-2772	195	38	afe	afe	PROPN
admet-2772	195	39	-average	-average	PROPN
admet-2772	195	40	fold	fold	NOUN
admet-2772	195	41	error	error	NOUN
admet-2772	195	42	;	;	PUNCT
admet-2772	195	43	aafe	aafe	ADJ
admet-2772	195	44	absolute	absolute	ADJ
admet-2772	195	45	average	average	ADJ
admet-2772	195	46	fold	fold	ADJ
admet-2772	195	47	error	error	NOUN
admet-2772	195	48	;	;	PUNCT
admet-2772	195	49	vdss	vdss	ADJ
admet-2772	195	50	volume	volume	NOUN
admet-2772	195	51	of	of	ADP
admet-2772	195	52	distribution	distribution	NOUN
admet-2772	195	53	at	at	ADP
admet-2772	195	54	steady	steady	ADJ
admet-2772	195	55	-	-	PUNCT
admet-2772	195	56	state	state	NOUN
admet-2772	195	57	.	.	PUNCT
admet-2772	196	1	a	a	DET
admet-2772	196	2	simple	simple	ADJ
admet-2772	196	3	two	two	NUM
admet-2772	196	4	-	-	PUNCT
admet-2772	196	5	descriptor	descriptor	NOUN
admet-2772	196	6	model	model	NOUN
admet-2772	196	7	using	use	VERB
admet-2772	196	8	molecular	molecular	ADJ
admet-2772	196	9	volume	volume	NOUN
admet-2772	196	10	and	and	CCONJ
admet-2772	196	11	polar	polar	ADJ
admet-2772	196	12	surface	surface	NOUN
admet-2772	196	13	area	area	NOUN
admet-2772	196	14	has	have	AUX
admet-2772	196	15	been	be	AUX
admet-2772	196	16	proposed	propose	VERB
admet-2772	196	17	for	for	ADP
admet-2772	196	18	predicting	predict	VERB
admet-2772	196	19	bbb	bbb	PROPN
admet-2772	196	20	penetration	penetration	NOUN
admet-2772	196	21	[	[	X
admet-2772	196	22	67	67	NUM
admet-2772	196	23	]	]	PUNCT
admet-2772	196	24	.	.	PUNCT
admet-2772	197	1	overall	overall	ADJ
admet-2772	197	2	,	,	PUNCT
admet-2772	197	3	current	current	ADJ
admet-2772	197	4	methods	method	NOUN
admet-2772	197	5	predict	predict	VERB
admet-2772	197	6	drug	drug	NOUN
admet-2772	197	7	volume	volume	NOUN
admet-2772	197	8	of	of	ADP
admet-2772	197	9	distribution	distribution	NOUN
admet-2772	197	10	with	with	ADP
admet-2772	197	11	an	an	DET
admet-2772	197	12	average	average	ADJ
admet-2772	197	13	2	2	NUM
admet-2772	197	14	-	-	ADJ
admet-2772	197	15	fold	fold	ADJ
admet-2772	197	16	error	error	NOUN
admet-2772	197	17	[	[	X
admet-2772	197	18	66	66	NUM
admet-2772	197	19	]	]	PUNCT
admet-2772	197	20	.	.	PUNCT
admet-2772	198	1	rapid	rapid	ADJ
admet-2772	198	2	brain	brain	NOUN
admet-2772	198	3	equilibration	equilibration	NOUN
admet-2772	198	4	requires	require	VERB
admet-2772	198	5	high	high	ADJ
admet-2772	198	6	bbb	bbb	NOUN
admet-2772	198	7	permeability	permeability	NOUN
admet-2772	198	8	and	and	CCONJ
admet-2772	198	9	low	low	ADJ
admet-2772	198	10	brain	brain	NOUN
admet-2772	198	11	tissue	tissue	NOUN
admet-2772	198	12	binding	bind	VERB
admet-2772	199	1	[	[	X
admet-2772	199	2	67	67	NUM
admet-2772	199	3	]	]	PUNCT
admet-2772	199	4	,	,	PUNCT
admet-2772	199	5	highlighting	highlight	VERB
admet-2772	199	6	the	the	DET
admet-2772	199	7	importance	importance	NOUN
admet-2772	199	8	of	of	ADP
admet-2772	199	9	considering	consider	VERB
admet-2772	199	10	multiple	multiple	ADJ
admet-2772	199	11	drug	drug	NOUN
admet-2772	199	12	design	design	NOUN
admet-2772	199	13	and	and	CCONJ
admet-2772	199	14	selection	selection	NOUN
admet-2772	199	15	factors	factor	NOUN
admet-2772	199	16	.	.	PUNCT
admet-2772	200	1	iwata	iwata	PROPN
admet-2772	200	2	et	et	PROPN
admet-2772	200	3	al	al	PROPN
admet-2772	200	4	.	.	PUNCT
admet-2772	201	1	[	[	X
admet-2772	201	2	76	76	NUM
admet-2772	201	3	]	]	PUNCT
admet-2772	201	4	developed	develop	VERB
admet-2772	201	5	ml	ml	NOUN
admet-2772	201	6	models	model	NOUN
admet-2772	201	7	for	for	ADP
admet-2772	201	8	total	total	ADJ
admet-2772	201	9	body	body	NOUN
admet-2772	201	10	clearance	clearance	NOUN
admet-2772	201	11	and	and	CCONJ
admet-2772	201	12	steady	steady	ADJ
admet-2772	201	13	-	-	PUNCT
admet-2772	201	14	state	state	NOUN
admet-2772	201	15	volume	volume	NOUN
admet-2772	201	16	of	of	ADP
admet-2772	201	17	distribution	distribution	NOUN
admet-2772	201	18	(	(	PUNCT
admet-2772	201	19	vd	vd	NOUN
admet-2772	201	20	using	use	VERB
admet-2772	201	21	imputed	impute	VERB
admet-2772	201	22	admet	admet	PROPN
admet-2772	201	23	&	&	CCONJ
admet-2772	201	24	dmpk	dmpk	PROPN
admet-2772	201	25	13(3	13(3	NUM
admet-2772	201	26	)	)	PUNCT
admet-2772	201	27	(	(	PUNCT
admet-2772	201	28	2025	2025	NUM
admet-2772	201	29	)	)	PUNCT
admet-2772	201	30	2772	2772	NUM
admet-2772	201	31	machine	machine	NOUN
admet-2772	201	32	learning	learning	NOUN
admet-2772	201	33	models	model	NOUN
admet-2772	201	34	for	for	ADP
admet-2772	201	35	admet	admet	ADJ
admet-2772	201	36	prediction	prediction	NOUN
admet-2772	201	37	in	in	ADP
admet-2772	201	38	drug	drug	NOUN
admet-2772	201	39	development	development	NOUN
admet-2772	201	40	doi	doi	PROPN
admet-2772	201	41	:	:	PUNCT
admet-2772	201	42	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	201	43	9	9	NUM
admet-2772	201	44	nonclinical	nonclinical	ADJ
admet-2772	201	45	data	datum	NOUN
admet-2772	201	46	,	,	PUNCT
admet-2772	201	47	achieving	achieve	VERB
admet-2772	201	48	accuracies	accuracy	NOUN
admet-2772	201	49	comparable	comparable	ADJ
admet-2772	201	50	to	to	ADP
admet-2772	201	51	animal	animal	NOUN
admet-2772	201	52	scale	scale	NOUN
admet-2772	201	53	-	-	PUNCT
admet-2772	201	54	up	up	ADP
admet-2772	201	55	models	model	NOUN
admet-2772	201	56	.	.	PUNCT
admet-2772	202	1	parrott	parrott	PROPN
admet-2772	202	2	et	et	PROPN
admet-2772	202	3	al	al	PROPN
admet-2772	202	4	.	.	PUNCT
admet-2772	203	1	[	[	X
admet-2772	203	2	77	77	NUM
admet-2772	203	3	]	]	X
admet-2772	203	4	integrated	integrate	VERB
admet-2772	203	5	mlpredicted	mlpredicte	VERB
admet-2772	203	6	properties	property	NOUN
admet-2772	203	7	into	into	ADP
admet-2772	203	8	physiologically	physiologically	ADV
admet-2772	203	9	-	-	PUNCT
admet-2772	203	10	based	base	VERB
admet-2772	203	11	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	203	12	(	(	PUNCT
admet-2772	203	13	pbpk	pbpk	NOUN
admet-2772	203	14	)	)	PUNCT
admet-2772	203	15	models	model	NOUN
admet-2772	203	16	for	for	ADP
admet-2772	203	17	highly	highly	ADV
admet-2772	203	18	lipophilic	lipophilic	ADJ
admet-2772	203	19	compounds	compound	NOUN
admet-2772	203	20	,	,	PUNCT
admet-2772	203	21	showing	show	VERB
admet-2772	203	22	promising	promising	ADJ
admet-2772	203	23	results	result	NOUN
admet-2772	203	24	for	for	ADP
admet-2772	203	25	vd	vd	NOUN
admet-2772	203	26	predictions	prediction	NOUN
admet-2772	203	27	.	.	PUNCT
admet-2772	204	1	antontsev	antontsev	PROPN
admet-2772	204	2	et	et	PROPN
admet-2772	204	3	al	al	PROPN
admet-2772	204	4	.	.	PUNCT
admet-2772	205	1	[	[	X
admet-2772	205	2	71	71	NUM
admet-2772	205	3	]	]	PUNCT
admet-2772	205	4	demonstrated	demonstrate	VERB
admet-2772	205	5	a	a	DET
admet-2772	205	6	hybrid	hybrid	ADJ
admet-2772	205	7	approach	approach	NOUN
admet-2772	205	8	combining	combine	VERB
admet-2772	205	9	ml	ml	ADP
admet-2772	205	10	optimization	optimization	NOUN
admet-2772	205	11	with	with	ADP
admet-2772	205	12	mechanistic	mechanistic	ADJ
admet-2772	205	13	modelling	modelling	NOUN
admet-2772	205	14	to	to	PART
admet-2772	205	15	predict	predict	VERB
admet-2772	205	16	tissue	tissue	NOUN
admet-2772	205	17	-	-	PUNCT
admet-2772	205	18	plasma	plasma	NOUN
admet-2772	205	19	partition	partition	NOUN
admet-2772	205	20	coefficients	coefficient	NOUN
admet-2772	205	21	accurately	accurately	ADV
admet-2772	205	22	.	.	PUNCT
admet-2772	206	1	mulpuru	mulpuru	PROPN
admet-2772	206	2	and	and	CCONJ
admet-2772	206	3	mishra	mishra	PROPN
admet-2772	207	1	[	[	X
admet-2772	207	2	78	78	NUM
admet-2772	207	3	]	]	PUNCT
admet-2772	207	4	developed	develop	VERB
admet-2772	207	5	an	an	DET
admet-2772	207	6	automl	automl	NOUN
admet-2772	207	7	model	model	NOUN
admet-2772	207	8	for	for	ADP
admet-2772	207	9	predicting	predict	VERB
admet-2772	207	10	plasma	plasma	NOUN
admet-2772	207	11	unbound	unbound	NOUN
admet-2772	207	12	fraction	fraction	NOUN
admet-2772	207	13	,	,	PUNCT
admet-2772	207	14	achieving	achieve	VERB
admet-2772	207	15	a	a	DET
admet-2772	207	16	coefficient	coefficient	NOUN
admet-2772	207	17	of	of	ADP
admet-2772	207	18	determination	determination	NOUN
admet-2772	207	19	of	of	ADP
admet-2772	207	20	0.85	0.85	NUM
admet-2772	207	21	.	.	PUNCT
admet-2772	208	1	cao	cao	PROPN
admet-2772	208	2	et	et	PROPN
admet-2772	208	3	al	al	PROPN
admet-2772	208	4	.	.	PUNCT
admet-2772	209	1	[	[	X
admet-2772	209	2	79	79	NUM
admet-2772	209	3	]	]	PUNCT
admet-2772	209	4	created	create	VERB
admet-2772	209	5	a	a	DET
admet-2772	209	6	model	model	NOUN
admet-2772	209	7	to	to	PART
admet-2772	209	8	classify	classify	VERB
admet-2772	209	9	polyfluorinated	polyfluorinate	VERB
admet-2772	209	10	alkyl	alkyl	NOUN
admet-2772	209	11	substances	substance	NOUN
admet-2772	209	12	(	(	PUNCT
admet-2772	209	13	pfas	pfas	NOUN
admet-2772	209	14	)	)	PUNCT
admet-2772	209	15	binding	bind	VERB
admet-2772	209	16	fractions	fraction	NOUN
admet-2772	209	17	in	in	ADP
admet-2772	209	18	plasma	plasma	NOUN
admet-2772	209	19	,	,	PUNCT
admet-2772	209	20	with	with	ADP
admet-2772	209	21	92	92	NUM
admet-2772	209	22	%	%	NOUN
admet-2772	209	23	accuracy	accuracy	NOUN
admet-2772	209	24	.	.	PUNCT
admet-2772	210	1	riedl	riedl	PROPN
admet-2772	210	2	et	et	PROPN
admet-2772	210	3	al	al	PROPN
admet-2772	210	4	.	.	PUNCT
admet-2772	211	1	[	[	X
admet-2772	211	2	80	80	NUM
admet-2772	211	3	]	]	PUNCT
admet-2772	211	4	introduced	introduce	VERB
admet-2772	211	5	a	a	DET
admet-2772	211	6	descriptor	descriptor	NOUN
admet-2772	211	7	-	-	PUNCT
admet-2772	211	8	free	free	ADJ
admet-2772	211	9	deep	deep	ADJ
admet-2772	211	10	learning	learning	NOUN
admet-2772	211	11	model	model	NOUN
admet-2772	211	12	using	use	VERB
admet-2772	211	13	bidirectional	bidirectional	ADJ
admet-2772	211	14	encoder	encoder	NOUN
admet-2772	211	15	representations	representation	NOUN
admet-2772	211	16	from	from	ADP
admet-2772	211	17	transformers	transformer	NOUN
admet-2772	211	18	(	(	PUNCT
admet-2772	211	19	bert	bert	PROPN
admet-2772	211	20	)	)	PUNCT
admet-2772	211	21	for	for	ADP
admet-2772	211	22	predicting	predict	VERB
admet-2772	211	23	plasma	plasma	NOUN
admet-2772	211	24	unbound	unbound	NOUN
admet-2772	211	25	fraction	fraction	NOUN
admet-2772	211	26	,	,	PUNCT
admet-2772	211	27	offering	offer	VERB
admet-2772	211	28	flexibility	flexibility	NOUN
admet-2772	211	29	and	and	CCONJ
admet-2772	211	30	minimal	minimal	ADJ
admet-2772	211	31	domain	domain	NOUN
admet-2772	211	32	expertise	expertise	NOUN
admet-2772	211	33	requirements	requirement	NOUN
admet-2772	211	34	.	.	PUNCT
admet-2772	212	1	these	these	DET
admet-2772	212	2	studies	study	NOUN
admet-2772	212	3	demonstrate	demonstrate	VERB
admet-2772	212	4	the	the	DET
admet-2772	212	5	potential	potential	NOUN
admet-2772	212	6	of	of	ADP
admet-2772	212	7	machine	machine	NOUN
admet-2772	212	8	learning	learn	VERB
admet-2772	212	9	in	in	ADP
admet-2772	212	10	predicting	predict	VERB
admet-2772	212	11	drug	drug	NOUN
admet-2772	212	12	binding	bind	VERB
admet-2772	212	13	and	and	CCONJ
admet-2772	212	14	distribution	distribution	NOUN
admet-2772	212	15	properties	property	NOUN
admet-2772	212	16	.	.	PUNCT
admet-2772	213	1	3.3	3.3	NUM
admet-2772	213	2	.	.	PUNCT
admet-2772	213	3	metabolism	metabolism	NOUN
admet-2772	213	4	prediction	prediction	NOUN
admet-2772	213	5	machine	machine	NOUN
admet-2772	213	6	learning	learning	NOUN
admet-2772	213	7	techniques	technique	NOUN
admet-2772	213	8	have	have	AUX
admet-2772	213	9	shown	show	VERB
admet-2772	213	10	promising	promising	ADJ
admet-2772	213	11	results	result	NOUN
admet-2772	213	12	in	in	ADP
admet-2772	213	13	predicting	predict	VERB
admet-2772	213	14	drug	drug	NOUN
admet-2772	213	15	metabolism	metabolism	NOUN
admet-2772	213	16	and	and	CCONJ
admet-2772	213	17	interactions	interaction	NOUN
admet-2772	213	18	related	relate	VERB
admet-2772	213	19	to	to	ADP
admet-2772	213	20	cytochrome	cytochrome	VERB
admet-2772	213	21	p450	p450	PROPN
admet-2772	213	22	(	(	PUNCT
admet-2772	213	23	cyp	cyp	ADJ
admet-2772	213	24	)	)	PUNCT
admet-2772	213	25	enzymes	enzyme	NOUN
admet-2772	213	26	.	.	PUNCT
admet-2772	214	1	various	various	ADJ
admet-2772	214	2	approaches	approach	NOUN
admet-2772	214	3	,	,	PUNCT
admet-2772	214	4	including	include	VERB
admet-2772	214	5	k	k	NOUN
admet-2772	214	6	-	-	PUNCT
admet-2772	214	7	nearest	near	ADJ
admet-2772	214	8	neighbours	neighbour	NOUN
admet-2772	214	9	,	,	PUNCT
admet-2772	214	10	decision	decision	NOUN
admet-2772	214	11	trees	tree	NOUN
admet-2772	214	12	,	,	PUNCT
admet-2772	214	13	random	random	ADJ
admet-2772	214	14	forests	forest	NOUN
admet-2772	214	15	,	,	PUNCT
admet-2772	214	16	artificial	artificial	ADJ
admet-2772	214	17	neural	neural	ADJ
admet-2772	214	18	networks	network	NOUN
admet-2772	214	19	,	,	PUNCT
admet-2772	214	20	and	and	CCONJ
admet-2772	214	21	support	support	VERB
admet-2772	214	22	vector	vector	NOUN
admet-2772	214	23	machines	machine	NOUN
admet-2772	214	24	,	,	PUNCT
admet-2772	214	25	have	have	AUX
admet-2772	214	26	been	be	AUX
admet-2772	214	27	employed	employ	VERB
admet-2772	214	28	to	to	PART
admet-2772	214	29	classify	classify	VERB
admet-2772	214	30	cyp	cyp	ADJ
admet-2772	214	31	activities	activity	NOUN
admet-2772	214	32	and	and	CCONJ
admet-2772	214	33	predict	predict	VERB
admet-2772	214	34	interactions	interaction	NOUN
admet-2772	214	35	with	with	ADP
admet-2772	214	36	high	high	ADJ
admet-2772	214	37	accuracy	accuracy	NOUN
admet-2772	214	38	[	[	X
admet-2772	214	39	81	81	NUM
admet-2772	214	40	]	]	PUNCT
admet-2772	214	41	(	(	PUNCT
admet-2772	214	42	for	for	ADP
admet-2772	214	43	a	a	DET
admet-2772	214	44	structured	structured	ADJ
admet-2772	214	45	overview	overview	NOUN
admet-2772	214	46	of	of	ADP
admet-2772	214	47	ml	ml	NOUN
admet-2772	214	48	models	model	NOUN
admet-2772	214	49	in	in	ADP
admet-2772	214	50	drug	drug	NOUN
admet-2772	214	51	metabolism	metabolism	NOUN
admet-2772	214	52	,	,	PUNCT
admet-2772	214	53	see	see	VERB
admet-2772	214	54	table	table	NOUN
admet-2772	214	55	5	5	NUM
admet-2772	214	56	)	)	PUNCT
admet-2772	214	57	.	.	PUNCT
admet-2772	215	1	machine	machine	NOUN
admet-2772	215	2	learning	learning	NOUN
admet-2772	215	3	has	have	AUX
admet-2772	215	4	also	also	ADV
admet-2772	215	5	been	be	AUX
admet-2772	215	6	applied	apply	VERB
admet-2772	215	7	to	to	ADP
admet-2772	215	8	model	model	NOUN
admet-2772	215	9	relationships	relationship	NOUN
admet-2772	215	10	between	between	ADP
admet-2772	215	11	chemical	chemical	NOUN
admet-2772	215	12	structure	structure	NOUN
admet-2772	215	13	and	and	CCONJ
admet-2772	215	14	metabolic	metabolic	NOUN
admet-2772	215	15	fate	fate	NOUN
admet-2772	215	16	,	,	PUNCT
admet-2772	215	17	addressing	address	VERB
admet-2772	215	18	complex	complex	ADJ
admet-2772	215	19	endpoints	endpoint	NOUN
admet-2772	215	20	such	such	ADJ
admet-2772	215	21	as	as	ADP
admet-2772	215	22	metabolic	metabolic	NOUN
admet-2772	215	23	stability	stability	NOUN
admet-2772	215	24	and	and	CCONJ
admet-2772	215	25	in	in	ADP
admet-2772	215	26	vivo	vivo	ADJ
admet-2772	215	27	clearance	clearance	NOUN
admet-2772	215	28	[	[	X
admet-2772	215	29	82	82	NUM
admet-2772	215	30	]	]	PUNCT
admet-2772	215	31	.	.	PUNCT
admet-2772	216	1	table	table	NOUN
admet-2772	216	2	5	5	NUM
admet-2772	216	3	.	.	PUNCT
admet-2772	217	1	summary	summary	NOUN
admet-2772	217	2	of	of	ADP
admet-2772	217	3	machine	machine	NOUN
admet-2772	217	4	learning	learning	NOUN
admet-2772	217	5	-	-	PUNCT
admet-2772	217	6	based	base	VERB
admet-2772	217	7	models	model	NOUN
admet-2772	217	8	for	for	ADP
admet-2772	217	9	metabolism	metabolism	NOUN
admet-2772	217	10	prediction	prediction	NOUN
admet-2772	217	11	no	no	INTJ
admet-2772	217	12	.	.	PUNCT
admet-2772	217	13	of	of	ADP
admet-2772	217	14	comp	comp	PROPN
admet-2772	217	15	.	.	PUNCT
admet-2772	218	1	target	target	NOUN
admet-2772	218	2	descriptors	descriptor	NOUN
admet-2772	218	3	modelling	model	VERB
admet-2772	218	4	method	method	NOUN
admet-2772	218	5	performance	performance	NOUN
admet-2772	218	6	ref	ref	NOUN
admet-2772	218	7	.	.	PUNCT
admet-2772	219	1	4545	4545	NUM
admet-2772	219	2	metabolic	metabolic	NOUN
admet-2772	219	3	pathway	pathway	NOUN
admet-2772	219	4	molecular	molecular	ADJ
admet-2772	219	5	fingerprints	fingerprint	NOUN
admet-2772	219	6	,	,	PUNCT
admet-2772	219	7	physicochemical	physicochemical	ADJ
admet-2772	219	8	properties	property	NOUN
admet-2772	219	9	,	,	PUNCT
admet-2772	219	10	structural	structural	ADJ
admet-2772	219	11	descriptors	descriptor	NOUN
admet-2772	219	12	graph	graph	VERB
admet-2772	219	13	convolutional	convolutional	ADJ
admet-2772	219	14	network	network	NOUN
admet-2772	219	15	and	and	CCONJ
admet-2772	219	16	rf	rf	ADJ
admet-2772	219	17	single	single	ADJ
admet-2772	219	18	-	-	PUNCT
admet-2772	219	19	class	class	NOUN
admet-2772	219	20	classification	classification	NOUN
admet-2772	219	21	95.16	95.16	NUM
admet-2772	219	22	%	%	NOUN
admet-2772	219	23	multi	multi	ADJ
admet-2772	219	24	-	-	ADJ
admet-2772	219	25	class	class	ADJ
admet-2772	219	26	classification	classification	NOUN
admet-2772	219	27	97.61	97.61	NUM
admet-2772	219	28	%	%	NOUN
admet-2772	220	1	[	[	X
admet-2772	220	2	83	83	NUM
admet-2772	220	3	]	]	SYM
admet-2772	220	4	1917	1917	NUM
admet-2772	220	5	metabolic	metabolic	NOUN
admet-2772	220	6	pathway	pathway	NOUN
admet-2772	220	7	physicochemical	physicochemical	ADJ
admet-2772	220	8	properties	property	NOUN
admet-2772	220	9	and	and	CCONJ
admet-2772	220	10	others	other	NOUN
admet-2772	220	11	rf	rf	VERB
admet-2772	220	12	on	on	ADP
admet-2772	220	13	external	external	ADJ
admet-2772	220	14	test	test	NOUN
admet-2772	220	15	:	:	PUNCT
admet-2772	220	16	acc	acc	PROPN
admet-2772	220	17	0.74	0.74	NUM
admet-2772	220	18	,	,	PUNCT
admet-2772	220	19	mcc	mcc	NOUN
admet-2772	220	20	0.48	0.48	NUM
admet-2772	220	21	,	,	PUNCT
admet-2772	220	22	sensitivity	sensitivity	NOUN
admet-2772	220	23	0.70	0.70	NUM
admet-2772	220	24	,	,	PUNCT
admet-2772	220	25	specificity	specificity	NOUN
admet-2772	220	26	0.86	0.86	NUM
admet-2772	220	27	,	,	PUNCT
admet-2772	220	28	ppv	ppv	NOUN
admet-2772	220	29	0.94	0.94	NUM
admet-2772	220	30	,	,	PUNCT
admet-2772	220	31	npv	npv	NOUN
admet-2772	220	32	0.46	0.46	NUM
admet-2772	221	1	[	[	X
admet-2772	221	2	84	84	NUM
admet-2772	221	3	]	]	SYM
admet-2772	221	4	26138	26138	NUM
admet-2772	221	5	metabolic	metabolic	NOUN
admet-2772	221	6	stability	stability	NOUN
admet-2772	221	7	2d	2d	NUM
admet-2772	221	8	descriptors	descriptor	VERB
admet-2772	221	9	principal	principal	ADJ
admet-2772	221	10	component	component	NOUN
admet-2772	221	11	analysis	analysis	NOUN
admet-2772	221	12	,	,	PUNCT
admet-2772	221	13	xgboost	xgboost	X
admet-2772	221	14	test	test	NOUN
admet-2772	221	15	set	set	NOUN
admet-2772	221	16	:	:	PUNCT
admet-2772	221	17	acc	acc	PROPN
admet-2772	221	18	93.6	93.6	NUM
admet-2772	221	19	%	%	NOUN
admet-2772	222	1	[	[	X
admet-2772	222	2	85	85	NUM
admet-2772	222	3	]	]	SYM
admet-2772	222	4	16613	16613	NUM
admet-2772	222	5	cytochrome	cytochrome	NOUN
admet-2772	222	6	inhibition	inhibition	NOUN
admet-2772	222	7	2d	2d	NUM
admet-2772	222	8	descriptors	descriptor	NOUN
admet-2772	222	9	rmse	rmse	NOUN
admet-2772	222	10	,	,	PUNCT
admet-2772	222	11	xgboos	xgboos	PROPN
admet-2772	222	12	test	test	NOUN
admet-2772	222	13	set	set	NOUN
admet-2772	222	14	:	:	PUNCT
admet-2772	222	15	acc	acc	PROPN
admet-2772	222	16	97.6	97.6	NUM
admet-2772	222	17	%	%	NOUN
admet-2772	223	1	[	[	X
admet-2772	223	2	86	86	NUM
admet-2772	223	3	]	]	PUNCT
admet-2772	223	4	(	(	PUNCT
admet-2772	223	5	substrate	substrate	NOUN
admet-2772	223	6	,	,	PUNCT
admet-2772	223	7	inhibitor	inhibitor	NOUN
admet-2772	223	8	)	)	PUNCT
admet-2772	223	9	data	datum	NOUN
admet-2772	223	10	:	:	PUNCT
admet-2772	223	11	cyp1a2-(396	cyp1a2-(396	NOUN
admet-2772	223	12	,	,	PUNCT
admet-2772	223	13	13459	13459	NUM
admet-2772	223	14	)	)	PUNCT
admet-2772	223	15	cyp2c9-(518	cyp2c9-(518	NOUN
admet-2772	223	16	,	,	PUNCT
admet-2772	223	17	12677	12677	NUM
admet-2772	223	18	)	)	PUNCT
admet-2772	223	19	cyp2c19-(628	cyp2c19-(628	PROPN
admet-2772	223	20	,	,	PUNCT
admet-2772	223	21	13162	13162	NUM
admet-2772	223	22	)	)	PUNCT
admet-2772	223	23	cyp2d6-(714	cyp2d6-(714	NOUN
admet-2772	223	24	,	,	PUNCT
admet-2772	223	25	13732	13732	NUM
admet-2772	223	26	)	)	PUNCT
admet-2772	224	1	cyp3a4-(1584	cyp3a4-(1584	PROPN
admet-2772	224	2	,	,	PUNCT
admet-2772	224	3	12990	12990	NUM
admet-2772	224	4	)	)	PUNCT
admet-2772	224	5	metabolic	metabolic	NOUN
admet-2772	224	6	ddis	ddi	NOUN
admet-2772	224	7	2d	2d	NOUN
admet-2772	224	8	descriptors	descriptor	NOUN
admet-2772	224	9	,	,	PUNCT
admet-2772	224	10	cats	cat	NOUN
admet-2772	224	11	,	,	PUNCT
admet-2772	224	12	ecfp4	ecfp4	PROPN
admet-2772	224	13	and	and	CCONJ
admet-2772	224	14	maccs	maccs	PROPN
admet-2772	224	15	rf	rf	PROPN
admet-2772	224	16	,	,	PUNCT
admet-2772	224	17	xgboos	xgboos	PROPN
admet-2772	224	18	internal	internal	ADJ
admet-2772	224	19	validation	validation	NOUN
admet-2772	224	20	:	:	PUNCT
admet-2772	224	21	acc	acc	PROPN
admet-2772	224	22	0.8	0.8	NUM
admet-2772	224	23	,	,	PUNCT
admet-2772	224	24	auc	auc	VERB
admet-2772	224	25	0.9	0.9	NUM
admet-2772	224	26	external	external	ADJ
admet-2772	224	27	validation	validation	NOUN
admet-2772	224	28	:	:	PUNCT
admet-2772	224	29	acc	acc	PROPN
admet-2772	224	30	0.795	0.795	NUM
admet-2772	224	31	multi	multi	ADJ
admet-2772	224	32	-	-	ADJ
admet-2772	224	33	level	level	ADJ
admet-2772	224	34	validation	validation	NOUN
admet-2772	224	35	:	:	PUNCT
admet-2772	224	36	acc	acc	PROPN
admet-2772	224	37	0.793	0.793	NUM
admet-2772	224	38	ppv	ppv	NOUN
admet-2772	224	39	positive	positive	ADJ
admet-2772	224	40	predictive	predictive	ADJ
admet-2772	224	41	value	value	NOUN
admet-2772	224	42	;	;	PUNCT
admet-2772	224	43	npv	npv	NOUN
admet-2772	224	44	negative	negative	ADJ
admet-2772	224	45	predictive	predictive	ADJ
admet-2772	224	46	value	value	NOUN
admet-2772	224	47	;	;	PUNCT
admet-2772	224	48	acc	acc	PROPN
admet-2772	224	49	accuracy	accuracy	NOUN
admet-2772	224	50	recent	recent	ADJ
admet-2772	224	51	advancements	advancement	NOUN
admet-2772	224	52	have	have	AUX
admet-2772	224	53	led	lead	VERB
admet-2772	224	54	to	to	ADP
admet-2772	224	55	the	the	DET
admet-2772	224	56	development	development	NOUN
admet-2772	224	57	of	of	ADP
admet-2772	224	58	consensus	consensus	NOUN
admet-2772	224	59	models	model	NOUN
admet-2772	224	60	for	for	ADP
admet-2772	224	61	predicting	predict	VERB
admet-2772	224	62	metabolic	metabolic	NOUN
admet-2772	224	63	drug	drug	NOUN
admet-2772	224	64	-	-	PUNCT
admet-2772	224	65	drug	drug	NOUN
admet-2772	224	66	interactions	interaction	NOUN
admet-2772	224	67	(	(	PUNCT
admet-2772	224	68	ddis	ddi	NOUN
admet-2772	224	69	)	)	PUNCT
admet-2772	224	70	related	relate	VERB
admet-2772	224	71	to	to	ADP
admet-2772	224	72	five	five	NUM
admet-2772	224	73	important	important	ADJ
admet-2772	224	74	cyp450	cyp450	NOUN
admet-2772	224	75	isozymes	isozyme	NOUN
admet-2772	224	76	(	(	PUNCT
admet-2772	224	77	cyp1a2	cyp1a2	NOUN
admet-2772	224	78	,	,	PUNCT
admet-2772	224	79	2c9	2c9	NUM
admet-2772	224	80	,	,	PUNCT
admet-2772	224	81	2c19	2c19	NOUN
admet-2772	224	82	,	,	PUNCT
admet-2772	224	83	2d6	2d6	NUM
admet-2772	224	84	,	,	PUNCT
admet-2772	224	85	3a4	3a4	NUM
admet-2772	224	86	)	)	PUNCT
admet-2772	224	87	,	,	PUNCT
admet-2772	224	88	achieving	achieve	VERB
admet-2772	224	89	high	high	ADJ
admet-2772	224	90	accuracy	accuracy	NOUN
admet-2772	224	91	and	and	CCONJ
admet-2772	224	92	robustness	robustness	NOUN
admet-2772	224	93	in	in	ADP
admet-2772	224	94	both	both	CCONJ
admet-2772	224	95	internal	internal	ADJ
admet-2772	224	96	and	and	CCONJ
admet-2772	224	97	external	external	ADJ
admet-2772	224	98	validations	validation	NOUN
admet-2772	224	99	[	[	X
admet-2772	224	100	86	86	NUM
admet-2772	224	101	]	]	PUNCT
admet-2772	224	102	.	.	PUNCT
admet-2772	225	1	these	these	PRON
admet-2772	225	2	in	in	ADP
admet-2772	225	3	silico	silico	NOUN
admet-2772	225	4	methods	method	NOUN
admet-2772	225	5	have	have	AUX
admet-2772	225	6	become	become	VERB
admet-2772	225	7	valuable	valuable	ADJ
admet-2772	225	8	tools	tool	NOUN
admet-2772	225	9	in	in	ADP
admet-2772	225	10	drug	drug	NOUN
admet-2772	225	11	discovery	discovery	NOUN
admet-2772	225	12	and	and	CCONJ
admet-2772	225	13	development	development	NOUN
admet-2772	225	14	,	,	PUNCT
admet-2772	225	15	offering	offer	VERB
admet-2772	225	16	efficient	efficient	ADJ
admet-2772	225	17	alternatives	alternative	NOUN
admet-2772	225	18	to	to	ADP
admet-2772	225	19	time	time	NOUN
admet-2772	225	20	-	-	PUNCT
admet-2772	225	21	consuming	consume	VERB
admet-2772	225	22	and	and	CCONJ
admet-2772	225	23	costly	costly	ADJ
admet-2772	225	24	experimental	experimental	ADJ
admet-2772	225	25	assessments	assessment	NOUN
admet-2772	225	26	.	.	PUNCT
admet-2772	226	1	mamada	mamada	PROPN
admet-2772	226	2	et	et	PROPN
admet-2772	226	3	al	al	PROPN
admet-2772	226	4	.	.	PUNCT
admet-2772	227	1	[	[	X
admet-2772	227	2	87	87	NUM
admet-2772	227	3	]	]	PUNCT
admet-2772	227	4	developed	develop	VERB
admet-2772	227	5	a	a	DET
admet-2772	227	6	novel	novel	ADJ
admet-2772	227	7	combination	combination	NOUN
admet-2772	227	8	model	model	NOUN
admet-2772	227	9	using	use	VERB
admet-2772	227	10	deepsnap	deepsnap	NOUN
admet-2772	227	11	-	-	PUNCT
admet-2772	227	12	deep	deep	ADJ
admet-2772	227	13	learning	learning	NOUN
admet-2772	227	14	and	and	CCONJ
admet-2772	227	15	conventional	conventional	ADJ
admet-2772	227	16	ml	ml	NOUN
admet-2772	227	17	,	,	PUNCT
admet-2772	227	18	achieving	achieve	VERB
admet-2772	227	19	high	high	ADJ
admet-2772	227	20	accuracy	accuracy	NOUN
admet-2772	227	21	in	in	ADP
admet-2772	227	22	predicting	predict	VERB
admet-2772	227	23	rat	rat	NOUN
admet-2772	227	24	clearance	clearance	NOUN
admet-2772	227	25	.	.	PUNCT
admet-2772	228	1	keefer	keefer	PROPN
admet-2772	228	2	et	et	PROPN
admet-2772	228	3	al	al	PROPN
admet-2772	228	4	.	.	PUNCT
admet-2772	229	1	[	[	X
admet-2772	229	2	88	88	NUM
admet-2772	229	3	]	]	PUNCT
admet-2772	229	4	compared	compare	VERB
admet-2772	229	5	ml	ml	PROPN
admet-2772	229	6	and	and	CCONJ
admet-2772	229	7	mechanistic	mechanistic	ADJ
admet-2772	229	8	in	in	ADP
admet-2772	229	9	vitro	vitro	NOUN
admet-2772	229	10	-	-	PUNCT
admet-2772	229	11	in	in	ADP
admet-2772	229	12	vivo	vivo	ADJ
admet-2772	229	13	extrapolation	extrapolation	NOUN
admet-2772	229	14	(	(	PUNCT
admet-2772	229	15	ivive	ivive	ADJ
admet-2772	229	16	)	)	PUNCT
admet-2772	229	17	models	model	NOUN
admet-2772	229	18	,	,	PUNCT
admet-2772	229	19	finding	find	VERB
admet-2772	229	20	that	that	SCONJ
admet-2772	229	21	ml	ml	AUX
admet-2772	229	22	ivive	ivive	ADJ
admet-2772	229	23	models	model	NOUN
admet-2772	229	24	performed	perform	VERB
admet-2772	229	25	comparably	comparably	ADV
admet-2772	229	26	or	or	CCONJ
admet-2772	229	27	better	well	ADJ
admet-2772	229	28	than	than	ADP
admet-2772	229	29	mechanistic	mechanistic	ADJ
admet-2772	229	30	counterparts	counterpart	NOUN
admet-2772	229	31	for	for	ADP
admet-2772	229	32	human	human	ADJ
admet-2772	229	33	intrinsic	intrinsic	ADJ
admet-2772	229	34	clearance	clearance	NOUN
admet-2772	229	35	prediction	prediction	NOUN
admet-2772	229	36	.	.	PUNCT
admet-2772	230	1	rodríguez	rodríguez	NOUN
admet-2772	230	2	-	-	PUNCT
admet-2772	230	3	pérez	pérez	NOUN
admet-2772	230	4	et	et	PROPN
admet-2772	230	5	al	al	PROPN
admet-2772	230	6	.	.	PUNCT
admet-2772	231	1	[	[	X
admet-2772	231	2	89	89	NUM
admet-2772	231	3	]	]	PUNCT
admet-2772	231	4	introduced	introduce	VERB
admet-2772	231	5	a	a	DET
admet-2772	231	6	multitask	multitask	ADJ
admet-2772	231	7	graph	graph	NOUN
admet-2772	231	8	neural	neural	ADJ
admet-2772	231	9	network	network	NOUN
admet-2772	231	10	architecture	architecture	NOUN
admet-2772	231	11	for	for	ADP
admet-2772	231	12	multispecies	multispecie	NOUN
admet-2772	231	13	intrinsic	intrinsic	ADJ
admet-2772	231	14	clearance	clearance	NOUN
admet-2772	231	15	prediction	prediction	NOUN
admet-2772	231	16	,	,	PUNCT
admet-2772	231	17	approaching	approach	VERB
admet-2772	231	18	experimental	experimental	ADJ
admet-2772	231	19	variability	variability	NOUN
admet-2772	231	20	in	in	ADP
admet-2772	231	21	performance	performance	NOUN
admet-2772	231	22	.	.	PUNCT
admet-2772	232	1	andrews	andrews	PROPN
admet-2772	232	2	-	-	PUNCT
admet-2772	232	3	morger	morger	PROPN
admet-2772	232	4	et	et	PROPN
admet-2772	232	5	al	al	PROPN
admet-2772	232	6	.	.	PUNCT
admet-2772	233	1	[	[	X
admet-2772	233	2	90	90	NUM
admet-2772	233	3	]	]	PUNCT
admet-2772	233	4	explored	explore	VERB
admet-2772	233	5	ml	ml	NOUN
admet-2772	233	6	strategies	strategy	NOUN
admet-2772	233	7	to	to	PART
admet-2772	233	8	improve	improve	VERB
admet-2772	233	9	rat	rat	NOUN
admet-2772	233	10	clearance	clearance	NOUN
admet-2772	233	11	predictions	prediction	NOUN
admet-2772	233	12	for	for	ADP
admet-2772	233	13	physiologically	physiologically	ADV
admet-2772	233	14	based	base	VERB
admet-2772	233	15	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	233	16	modelling	modelling	NOUN
admet-2772	233	17	,	,	PUNCT
admet-2772	233	18	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	233	19	m.	m.	NOUN
admet-2772	233	20	venkataraman	venkataraman	PROPN
admet-2772	233	21	et	et	PROPN
admet-2772	233	22	al	al	PROPN
admet-2772	233	23	.	.	PROPN
admet-2772	233	24	admet	admet	PROPN
admet-2772	233	25	&	&	CCONJ
admet-2772	233	26	dmpk	dmpk	PROPN
admet-2772	233	27	13(3	13(3	NUM
admet-2772	233	28	)	)	PUNCT
admet-2772	233	29	(	(	PUNCT
admet-2772	233	30	2025	2025	NUM
admet-2772	233	31	)	)	PUNCT
admet-2772	233	32	2772	2772	NUM
admet-2772	233	33	10	10	NUM
admet-2772	233	34	demonstrating	demonstrate	VERB
admet-2772	233	35	enhanced	enhance	VERB
admet-2772	233	36	accuracy	accuracy	NOUN
admet-2772	233	37	compared	compare	VERB
admet-2772	233	38	to	to	ADP
admet-2772	233	39	standard	standard	NOUN
admet-2772	233	40	in	in	ADP
admet-2772	233	41	vitro	vitro	X
admet-2772	233	42	bottom	bottom	ADJ
admet-2772	233	43	-	-	PUNCT
admet-2772	233	44	up	up	ADP
admet-2772	233	45	approaches	approach	NOUN
admet-2772	233	46	.	.	PUNCT
admet-2772	234	1	these	these	DET
admet-2772	234	2	studies	study	NOUN
admet-2772	234	3	highlight	highlight	VERB
admet-2772	234	4	the	the	DET
admet-2772	234	5	potential	potential	NOUN
admet-2772	234	6	of	of	ADP
admet-2772	234	7	ml	ml	NOUN
admet-2772	234	8	models	model	NOUN
admet-2772	234	9	in	in	ADP
admet-2772	234	10	improving	improve	VERB
admet-2772	234	11	clearance	clearance	NOUN
admet-2772	234	12	predictions	prediction	NOUN
admet-2772	234	13	across	across	ADP
admet-2772	234	14	species	specie	NOUN
admet-2772	234	15	,	,	PUNCT
admet-2772	234	16	contributing	contribute	VERB
admet-2772	234	17	to	to	ADP
admet-2772	234	18	more	more	ADV
admet-2772	234	19	efficient	efficient	ADJ
admet-2772	234	20	drug	drug	NOUN
admet-2772	234	21	discovery	discovery	NOUN
admet-2772	234	22	and	and	CCONJ
admet-2772	234	23	development	development	NOUN
admet-2772	234	24	processes	process	NOUN
admet-2772	234	25	.	.	PUNCT
admet-2772	235	1	3.4	3.4	NUM
admet-2772	235	2	.	.	PUNCT
admet-2772	235	3	excretion	excretion	NOUN
admet-2772	235	4	prediction	prediction	NOUN
admet-2772	235	5	machine	machine	NOUN
admet-2772	235	6	learning	learning	NOUN
admet-2772	235	7	models	model	NOUN
admet-2772	235	8	have	have	AUX
admet-2772	235	9	emerged	emerge	VERB
admet-2772	235	10	as	as	ADP
admet-2772	235	11	powerful	powerful	ADJ
admet-2772	235	12	tools	tool	NOUN
admet-2772	235	13	for	for	ADP
admet-2772	235	14	predicting	predict	VERB
admet-2772	235	15	drug	drug	NOUN
admet-2772	235	16	metabolism	metabolism	NOUN
admet-2772	235	17	and	and	CCONJ
admet-2772	235	18	excretion	excretion	NOUN
admet-2772	235	19	in	in	ADP
admet-2772	235	20	early	early	ADJ
admet-2772	235	21	drug	drug	NOUN
admet-2772	235	22	discovery	discovery	NOUN
admet-2772	235	23	and	and	CCONJ
admet-2772	235	24	development	development	NOUN
admet-2772	235	25	[	[	X
admet-2772	235	26	91	91	NUM
admet-2772	235	27	]	]	PUNCT
admet-2772	235	28	.	.	PUNCT
admet-2772	236	1	researchers	researcher	NOUN
admet-2772	236	2	have	have	AUX
admet-2772	236	3	developed	develop	VERB
admet-2772	236	4	in	in	ADP
admet-2772	236	5	-	-	PUNCT
admet-2772	236	6	silico	silico	NOUN
admet-2772	236	7	prediction	prediction	NOUN
admet-2772	236	8	systems	system	NOUN
admet-2772	236	9	for	for	ADP
admet-2772	236	10	renal	renal	ADJ
admet-2772	236	11	excretion	excretion	NOUN
admet-2772	236	12	and	and	CCONJ
admet-2772	236	13	clearance	clearance	NOUN
admet-2772	236	14	,	,	PUNCT
admet-2772	236	15	incorporating	incorporate	VERB
admet-2772	236	16	factors	factor	NOUN
admet-2772	236	17	such	such	ADJ
admet-2772	236	18	as	as	ADP
admet-2772	236	19	the	the	DET
admet-2772	236	20	fraction	fraction	NOUN
admet-2772	236	21	unbound	unbound	NOUN
admet-2772	236	22	in	in	ADP
admet-2772	236	23	plasma	plasma	NOUN
admet-2772	236	24	to	to	PART
admet-2772	236	25	improve	improve	VERB
admet-2772	236	26	accuracy	accuracy	NOUN
admet-2772	236	27	[	[	X
admet-2772	236	28	92	92	NUM
admet-2772	236	29	]	]	PUNCT
admet-2772	236	30	.	.	PUNCT
admet-2772	237	1	ml	ml	PROPN
admet-2772	237	2	models	model	NOUN
admet-2772	237	3	for	for	ADP
admet-2772	237	4	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	237	5	(	(	PUNCT
admet-2772	237	6	pk	pk	NOUN
admet-2772	237	7	)	)	PUNCT
admet-2772	237	8	prediction	prediction	NOUN
admet-2772	237	9	complement	complement	NOUN
admet-2772	237	10	established	establish	VERB
admet-2772	237	11	approaches	approach	NOUN
admet-2772	237	12	like	like	ADP
admet-2772	237	13	ivive	ivive	ADJ
admet-2772	237	14	and	and	CCONJ
admet-2772	237	15	pbpk	pbpk	NOUN
admet-2772	237	16	models	model	NOUN
admet-2772	237	17	[	[	X
admet-2772	237	18	93	93	NUM
admet-2772	237	19	]	]	PUNCT
admet-2772	237	20	.	.	PUNCT
admet-2772	238	1	ongoing	ongoing	ADJ
admet-2772	238	2	research	research	NOUN
admet-2772	238	3	focuses	focus	VERB
admet-2772	238	4	on	on	ADP
admet-2772	238	5	improving	improve	VERB
admet-2772	238	6	model	model	NOUN
admet-2772	238	7	accuracy	accuracy	NOUN
admet-2772	238	8	,	,	PUNCT
admet-2772	238	9	addressing	address	VERB
admet-2772	238	10	limitations	limitation	NOUN
admet-2772	238	11	,	,	PUNCT
admet-2772	238	12	and	and	CCONJ
admet-2772	238	13	integrating	integrate	VERB
admet-2772	238	14	ml	ml	NOUN
admet-2772	238	15	approaches	approach	NOUN
admet-2772	238	16	into	into	ADP
admet-2772	238	17	drug	drug	NOUN
admet-2772	238	18	discovery	discovery	NOUN
admet-2772	238	19	workflows	workflow	NOUN
admet-2772	238	20	to	to	PART
admet-2772	238	21	enhance	enhance	VERB
admet-2772	238	22	efficiency	efficiency	NOUN
admet-2772	238	23	and	and	CCONJ
admet-2772	238	24	clinical	clinical	ADJ
admet-2772	238	25	success	success	NOUN
admet-2772	238	26	rates	rate	NOUN
admet-2772	238	27	[	[	X
admet-2772	238	28	93	93	NUM
admet-2772	238	29	]	]	PUNCT
admet-2772	238	30	.	.	PUNCT
admet-2772	239	1	recent	recent	ADJ
admet-2772	239	2	studies	study	NOUN
admet-2772	239	3	have	have	AUX
admet-2772	239	4	explored	explore	VERB
admet-2772	239	5	machine	machine	NOUN
admet-2772	239	6	learning	learning	NOUN
admet-2772	239	7	approaches	approach	NOUN
admet-2772	239	8	for	for	ADP
admet-2772	239	9	predicting	predict	VERB
admet-2772	239	10	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	239	11	parameters	parameter	NOUN
admet-2772	239	12	,	,	PUNCT
admet-2772	239	13	including	include	VERB
admet-2772	239	14	clearance	clearance	NOUN
admet-2772	239	15	(	(	PUNCT
admet-2772	239	16	cl	cl	NOUN
admet-2772	239	17	)	)	PUNCT
admet-2772	239	18	,	,	PUNCT
admet-2772	239	19	elimination	elimination	NOUN
admet-2772	239	20	rate	rate	NOUN
admet-2772	239	21	constant	constant	ADJ
admet-2772	239	22	(	(	PUNCT
admet-2772	239	23	ke	ke	NOUN
admet-2772	239	24	)	)	PUNCT
admet-2772	239	25	,	,	PUNCT
admet-2772	239	26	and	and	CCONJ
admet-2772	239	27	half	half	ADJ
admet-2772	239	28	-	-	PUNCT
admet-2772	239	29	life	life	NOUN
admet-2772	239	30	(	(	PUNCT
admet-2772	239	31	t½	t½	NOUN
admet-2772	239	32	)	)	PUNCT
admet-2772	239	33	(	(	PUNCT
admet-2772	239	34	table	table	NOUN
admet-2772	239	35	6	6	NUM
admet-2772	239	36	outlines	outline	VERB
admet-2772	239	37	key	key	ADJ
admet-2772	239	38	machine	machine	NOUN
admet-2772	239	39	learning	learning	NOUN
admet-2772	239	40	models	model	NOUN
admet-2772	239	41	developed	develop	VERB
admet-2772	239	42	for	for	ADP
admet-2772	239	43	predicting	predict	VERB
admet-2772	239	44	drug	drug	NOUN
admet-2772	239	45	excretion	excretion	NOUN
admet-2772	239	46	parameters	parameter	NOUN
admet-2772	239	47	)	)	PUNCT
admet-2772	239	48	.	.	PUNCT
admet-2772	240	1	seal	seal	VERB
admet-2772	240	2	et	et	PROPN
admet-2772	240	3	al	al	PROPN
admet-2772	240	4	.	.	PUNCT
admet-2772	241	1	[	[	X
admet-2772	241	2	94	94	NUM
admet-2772	241	3	]	]	PUNCT
admet-2772	241	4	created	create	VERB
admet-2772	241	5	pksmart	pksmart	NOUN
admet-2772	241	6	,	,	PUNCT
admet-2772	241	7	an	an	DET
admet-2772	241	8	open	open	ADJ
admet-2772	241	9	-	-	PUNCT
admet-2772	241	10	source	source	NOUN
admet-2772	241	11	model	model	NOUN
admet-2772	241	12	for	for	ADP
admet-2772	241	13	predicting	predict	VERB
admet-2772	241	14	human	human	ADJ
admet-2772	241	15	pk	pk	NOUN
admet-2772	241	16	parameters	parameter	NOUN
admet-2772	241	17	,	,	PUNCT
admet-2772	241	18	including	include	VERB
admet-2772	241	19	volume	volume	NOUN
admet-2772	241	20	of	of	ADP
admet-2772	241	21	distribution	distribution	NOUN
admet-2772	241	22	at	at	ADP
admet-2772	241	23	steady	steady	ADJ
admet-2772	241	24	-	-	PUNCT
admet-2772	241	25	state	state	NOUN
admet-2772	241	26	(	(	PUNCT
admet-2772	241	27	vdss	vdss	ADJ
admet-2772	241	28	)	)	PUNCT
admet-2772	241	29	,	,	PUNCT
admet-2772	241	30	cl	cl	NOUN
admet-2772	241	31	,	,	PUNCT
admet-2772	241	32	and	and	CCONJ
admet-2772	241	33	t½	t½	NOUN
admet-2772	241	34	,	,	PUNCT
admet-2772	241	35	using	use	VERB
admet-2772	241	36	molecular	molecular	ADJ
admet-2772	241	37	fingerprints	fingerprint	NOUN
admet-2772	241	38	and	and	CCONJ
admet-2772	241	39	animal	animal	NOUN
admet-2772	241	40	pk	pk	NOUN
admet-2772	241	41	data	datum	NOUN
admet-2772	241	42	.	.	PUNCT
admet-2772	242	1	fan	fan	PROPN
admet-2772	242	2	et	et	PROPN
admet-2772	242	3	al	al	PROPN
admet-2772	242	4	.	.	PUNCT
admet-2772	243	1	[	[	X
admet-2772	243	2	95	95	NUM
admet-2772	243	3	]	]	PUNCT
admet-2772	243	4	focused	focus	VERB
admet-2772	243	5	on	on	ADP
admet-2772	243	6	predicting	predict	VERB
admet-2772	243	7	drug	drug	NOUN
admet-2772	243	8	half	half	ADJ
admet-2772	243	9	-	-	PUNCT
admet-2772	243	10	life	life	NOUN
admet-2772	243	11	using	use	VERB
admet-2772	243	12	ensemble	ensemble	ADJ
admet-2772	243	13	and	and	CCONJ
admet-2772	243	14	consensus	consensus	NOUN
admet-2772	243	15	machine	machine	NOUN
admet-2772	243	16	learning	learning	NOUN
admet-2772	243	17	methods	method	NOUN
admet-2772	243	18	,	,	PUNCT
admet-2772	243	19	with	with	ADP
admet-2772	243	20	xgboost	xgboost	ADV
admet-2772	243	21	outperforming	outperform	VERB
admet-2772	243	22	other	other	ADJ
admet-2772	243	23	individual	individual	ADJ
admet-2772	243	24	models	model	NOUN
admet-2772	243	25	and	and	CCONJ
admet-2772	243	26	a	a	DET
admet-2772	243	27	consensus	consensus	NOUN
admet-2772	243	28	model	model	NOUN
admet-2772	243	29	further	far	ADV
admet-2772	243	30	enhancing	enhance	VERB
admet-2772	243	31	prediction	prediction	NOUN
admet-2772	243	32	performance	performance	NOUN
admet-2772	243	33	.	.	PUNCT
admet-2772	244	1	these	these	DET
admet-2772	244	2	studies	study	NOUN
admet-2772	244	3	demonstrate	demonstrate	VERB
admet-2772	244	4	the	the	DET
admet-2772	244	5	potential	potential	NOUN
admet-2772	244	6	of	of	ADP
admet-2772	244	7	machine	machine	NOUN
admet-2772	244	8	learning	learn	VERB
admet-2772	244	9	approaches	approach	NOUN
admet-2772	244	10	in	in	ADP
admet-2772	244	11	improving	improve	VERB
admet-2772	244	12	the	the	DET
admet-2772	244	13	accuracy	accuracy	NOUN
admet-2772	244	14	and	and	CCONJ
admet-2772	244	15	efficiency	efficiency	NOUN
admet-2772	244	16	of	of	ADP
admet-2772	244	17	pk	pk	NOUN
admet-2772	244	18	parameter	parameter	NOUN
admet-2772	244	19	prediction	prediction	NOUN
admet-2772	244	20	in	in	ADP
admet-2772	244	21	drug	drug	NOUN
admet-2772	244	22	discovery	discovery	NOUN
admet-2772	244	23	and	and	CCONJ
admet-2772	244	24	development	development	NOUN
admet-2772	244	25	.	.	PUNCT
admet-2772	245	1	table	table	NOUN
admet-2772	245	2	6	6	NUM
admet-2772	245	3	.	.	PUNCT
admet-2772	246	1	summary	summary	NOUN
admet-2772	246	2	of	of	ADP
admet-2772	246	3	machine	machine	NOUN
admet-2772	246	4	learning	learning	NOUN
admet-2772	246	5	-	-	PUNCT
admet-2772	246	6	based	base	VERB
admet-2772	246	7	models	model	NOUN
admet-2772	246	8	for	for	ADP
admet-2772	246	9	excretion	excretion	NOUN
admet-2772	246	10	prediction	prediction	NOUN
admet-2772	246	11	no	no	INTJ
admet-2772	246	12	.	.	PUNCT
admet-2772	246	13	of	of	ADP
admet-2772	246	14	comp	comp	PROPN
admet-2772	246	15	.	.	PUNCT
admet-2772	247	1	target	target	NOUN
admet-2772	247	2	descriptors	descriptor	NOUN
admet-2772	247	3	modelling	model	VERB
admet-2772	247	4	method	method	NOUN
admet-2772	247	5	performance	performance	NOUN
admet-2772	247	6	ref	ref	NOUN
admet-2772	247	7	.	.	PUNCT
admet-2772	248	1	244	244	NUM
admet-2772	248	2	intrinsic	intrinsic	ADJ
admet-2772	248	3	clearance	clearance	NOUN
admet-2772	248	4	molecular	molecular	ADJ
admet-2772	248	5	fingerprints	fingerprint	NOUN
admet-2772	248	6	,	,	PUNCT
admet-2772	248	7	physicochemical	physicochemical	ADJ
admet-2772	248	8	properties	property	NOUN
admet-2772	248	9	,	,	PUNCT
admet-2772	248	10	and	and	CCONJ
admet-2772	248	11	3d	3d	NUM
admet-2772	248	12	quantum	quantum	ADJ
admet-2772	248	13	chemical	chemical	NOUN
admet-2772	248	14	descriptors	descriptor	NOUN
admet-2772	248	15	partial	partial	ADJ
admet-2772	248	16	least	least	ADJ
admet-2772	248	17	squares	square	NOUN
admet-2772	248	18	,	,	PUNCT
admet-2772	248	19	rf	rf	NOUN
admet-2772	248	20	,	,	PUNCT
admet-2772	248	21	multilabel	multilabel	NOUN
admet-2772	248	22	classification	classification	NOUN
admet-2772	248	23	,	,	PUNCT
admet-2772	248	24	principal	principal	ADJ
admet-2772	248	25	component	component	NOUN
admet-2772	248	26	analysis	analysis	NOUN
admet-2772	248	27	r2	r2	NOUN
admet-2772	248	28	=	=	SYM
admet-2772	248	29	0.96	0.96	NUM
admet-2772	248	30	,	,	PUNCT
admet-2772	248	31	q	q	X
admet-2772	249	1	=	=	SYM
admet-2772	250	1	48	48	NUM
admet-2772	251	1	[	[	X
admet-2772	251	2	96	96	NUM
admet-2772	251	3	]	]	SYM
admet-2772	251	4	748	748	NUM
admet-2772	251	5	total	total	ADJ
admet-2772	251	6	clearance	clearance	NOUN
admet-2772	251	7	the	the	DET
admet-2772	251	8	chemical	chemical	NOUN
admet-2772	251	9	structure	structure	NOUN
admet-2772	251	10	was	be	AUX
admet-2772	251	11	represented	represent	VERB
admet-2772	251	12	as	as	ADP
admet-2772	251	13	graph	graph	NOUN
admet-2772	251	14	deep	deep	ADJ
admet-2772	251	15	learning	learning	NOUN
admet-2772	251	16	test	test	NOUN
admet-2772	251	17	data	datum	NOUN
admet-2772	251	18	set	set	VERB
admet-2772	251	19	:	:	PUNCT
admet-2772	251	20	geometric	geometric	ADJ
admet-2772	251	21	mean	mean	NOUN
admet-2772	251	22	fold	fold	NOUN
admet-2772	251	23	error	error	NOUN
admet-2772	251	24	=	=	NOUN
admet-2772	251	25	2.68	2.68	NUM
admet-2772	251	26	[	[	X
admet-2772	251	27	97	97	NUM
admet-2772	251	28	]	]	SYM
admet-2772	251	29	1114	1114	NUM
admet-2772	251	30	total	total	ADJ
admet-2772	251	31	clearance	clearance	NOUN
admet-2772	251	32	2d	2d	NUM
admet-2772	251	33	smarts	smart	NOUN
admet-2772	251	34	-	-	PUNCT
admet-2772	251	35	based	base	VERB
admet-2772	251	36	descriptors	descriptor	NOUN
admet-2772	251	37	model	model	NOUN
admet-2772	251	38	building	building	NOUN
admet-2772	251	39	using	use	VERB
admet-2772	251	40	stardrop	stardrop	NOUN
admet-2772	251	41	rf	rf	ADJ
admet-2772	251	42	,	,	PUNCT
admet-2772	251	43	radial	radial	ADJ
admet-2772	251	44	basis	basis	NOUN
admet-2772	251	45	function	function	NOUN
admet-2772	251	46	whole	whole	ADJ
admet-2772	251	47	data	datum	NOUN
admet-2772	251	48	set	set	VERB
admet-2772	251	49	:	:	PUNCT
admet-2772	251	50	r2	r2	PROPN
admet-2772	251	51	=	=	PUNCT
admet-2772	251	52	0.55	0.55	NUM
admet-2772	251	53	,	,	PUNCT
admet-2772	251	54	rmse=0.332	rmse=0.332	VERB
admet-2772	252	1	[	[	X
admet-2772	252	2	98	98	NUM
admet-2772	252	3	]	]	SYM
admet-2772	252	4	112	112	NUM
admet-2772	252	5	intrinsic	intrinsic	ADJ
admet-2772	252	6	clearance	clearance	NOUN
admet-2772	252	7	233	233	NUM
admet-2772	252	8	molecular	molecular	ADJ
admet-2772	252	9	descriptors	descriptor	NOUN
admet-2772	252	10	artificial	artificial	ADJ
admet-2772	252	11	neural	neural	ADJ
admet-2772	252	12	network	network	NOUN
admet-2772	252	13	training	training	NOUN
admet-2772	252	14	set	set	NOUN
admet-2772	252	15	:	:	PUNCT
admet-2772	252	16	r2	r2	PROPN
admet-2772	252	17	=	=	SYM
admet-2772	252	18	0.953	0.953	NUM
admet-2772	252	19	,	,	PUNCT
admet-2772	252	20	rmse	rmse	NOUN
admet-2772	252	21	=	=	NOUN
admet-2772	252	22	0.236	0.236	NUM
admet-2772	252	23	test	test	NOUN
admet-2772	252	24	set	set	NOUN
admet-2772	252	25	:	:	PUNCT
admet-2772	252	26	r2	r2	PROPN
admet-2772	252	27	=	=	PUNCT
admet-2772	252	28	0.804	0.804	NUM
admet-2772	252	29	,	,	PUNCT
admet-2772	252	30	rmse	rmse	NOUN
admet-2772	253	1	=	=	NOUN
admet-2772	253	2	0.544	0.544	NUM
admet-2772	254	1	[	[	X
admet-2772	254	2	99	99	NUM
admet-2772	254	3	]	]	SYM
admet-2772	254	4	349	349	NUM
admet-2772	254	5	renal	renal	ADJ
admet-2772	254	6	clearance	clearance	NOUN
admet-2772	254	7	195	195	NUM
admet-2772	254	8	descriptors	descriptor	NOUN
admet-2772	254	9	partial	partial	ADJ
admet-2772	254	10	least	least	ADJ
admet-2772	254	11	squares	square	NOUN
admet-2772	254	12	,	,	PUNCT
admet-2772	254	13	rf	rf	NOUN
admet-2772	254	14	training	training	NOUN
admet-2772	254	15	data	datum	NOUN
admet-2772	254	16	:	:	PUNCT
admet-2772	254	17	r2	r2	PROPN
admet-2772	254	18	=	=	PROPN
admet-2772	254	19	0.93	0.93	NUM
admet-2772	254	20	,	,	PUNCT
admet-2772	254	21	rmse	rmse	NOUN
admet-2772	254	22	=	=	SYM
admet-2772	254	23	0.32	0.32	NUM
admet-2772	254	24	test	test	NOUN
admet-2772	254	25	data	datum	NOUN
admet-2772	254	26	:	:	PUNCT
admet-2772	254	27	r2	r2	PROPN
admet-2772	254	28	=	=	SYM
admet-2772	254	29	0.63	0.63	NUM
admet-2772	254	30	,	,	PUNCT
admet-2772	254	31	rmse	rmse	NOUN
admet-2772	254	32	=	=	PUNCT
admet-2772	255	1	0.63	0.63	NUM
admet-2772	256	1	[	[	X
admet-2772	256	2	100	100	NUM
admet-2772	256	3	]	]	SYM
admet-2772	256	4	1352	1352	NUM
admet-2772	256	5	renal	renal	ADJ
admet-2772	256	6	clearance	clearance	NOUN
admet-2772	256	7	2d	2d	NOUN
admet-2772	256	8	and	and	CCONJ
admet-2772	256	9	3d	3d	NUM
admet-2772	256	10	descriptors	descriptor	NOUN
admet-2772	256	11	and	and	CCONJ
admet-2772	256	12	49	49	NUM
admet-2772	256	13	fingerprints	fingerprint	NOUN
admet-2772	256	14	svm	svm	ADJ
admet-2772	256	15	,	,	PUNCT
admet-2772	256	16	gradient	gradient	ADJ
admet-2772	256	17	boosting	boost	VERB
admet-2772	256	18	machine	machine	NOUN
admet-2772	256	19	,	,	PUNCT
admet-2772	256	20	xgboost	xgboost	ADV
admet-2772	256	21	,	,	PUNCT
admet-2772	256	22	rf	rf	ADJ
admet-2772	256	23	training	training	NOUN
admet-2772	256	24	set	set	NOUN
admet-2772	256	25	:	:	PUNCT
admet-2772	256	26	r2	r2	PROPN
admet-2772	256	27	=	=	PUNCT
admet-2772	256	28	0.882	0.882	NUM
admet-2772	256	29	,	,	PUNCT
admet-2772	256	30	rmse	rmse	NOUN
admet-2772	256	31	=	=	PROPN
admet-2772	256	32	0.239	0.239	NUM
admet-2772	256	33	test	test	NOUN
admet-2772	256	34	set	set	NOUN
admet-2772	256	35	:	:	PUNCT
admet-2772	256	36	r2	r2	PROPN
admet-2772	256	37	=	=	PUNCT
admet-2772	256	38	0.875	0.875	NUM
admet-2772	256	39	,	,	PUNCT
admet-2772	256	40	rmse	rmse	NOUN
admet-2772	256	41	=	=	NOUN
admet-2772	256	42	0.103	0.103	NUM
admet-2772	257	1	[	[	X
admet-2772	257	2	101	101	NUM
admet-2772	257	3	]	]	SYM
admet-2772	257	4	4	4	NUM
admet-2772	257	5	.	.	X
admet-2772	257	6	machine	machine	NOUN
admet-2772	257	7	learning	learning	NOUN
admet-2772	257	8	approaches	approach	NOUN
admet-2772	257	9	in	in	ADP
admet-2772	257	10	toxicity	toxicity	NOUN
admet-2772	257	11	prediction	prediction	NOUN
admet-2772	257	12	4.1	4.1	NUM
admet-2772	257	13	.	.	PUNCT
admet-2772	258	1	in	in	ADP
admet-2772	258	2	silico	silico	NOUN
admet-2772	258	3	toxicity	toxicity	NOUN
admet-2772	258	4	models	model	NOUN
admet-2772	258	5	machine	machine	NOUN
admet-2772	258	6	learning	learning	NOUN
admet-2772	258	7	models	model	NOUN
admet-2772	258	8	have	have	AUX
admet-2772	258	9	become	become	VERB
admet-2772	258	10	increasingly	increasingly	ADV
admet-2772	258	11	popular	popular	ADJ
admet-2772	258	12	for	for	ADP
admet-2772	258	13	predicting	predict	VERB
admet-2772	258	14	various	various	ADJ
admet-2772	258	15	toxicity	toxicity	NOUN
admet-2772	258	16	endpoints	endpoint	NOUN
admet-2772	258	17	,	,	PUNCT
admet-2772	258	18	including	include	VERB
admet-2772	258	19	hepatotoxicity	hepatotoxicity	NOUN
admet-2772	258	20	,	,	PUNCT
admet-2772	258	21	nephrotoxicity	nephrotoxicity	NOUN
admet-2772	258	22	,	,	PUNCT
admet-2772	258	23	cardiotoxicity	cardiotoxicity	NOUN
admet-2772	258	24	,	,	PUNCT
admet-2772	258	25	and	and	CCONJ
admet-2772	258	26	genotoxicity	genotoxicity	NOUN
admet-2772	258	27	[	[	X
admet-2772	258	28	102	102	NUM
admet-2772	258	29	]	]	PUNCT
admet-2772	258	30	.	.	PUNCT
admet-2772	259	1	various	various	ADJ
admet-2772	259	2	ml	ml	NOUN
admet-2772	259	3	models	model	NOUN
admet-2772	259	4	for	for	ADP
admet-2772	259	5	predicting	predict	VERB
admet-2772	259	6	drug	drug	NOUN
admet-2772	259	7	toxicity	toxicity	NOUN
admet-2772	259	8	are	be	AUX
admet-2772	259	9	summarized	summarize	VERB
admet-2772	259	10	in	in	ADP
admet-2772	259	11	table	table	NOUN
admet-2772	259	12	7	7	NUM
admet-2772	259	13	.	.	PUNCT
admet-2772	260	1	these	these	DET
admet-2772	260	2	models	model	NOUN
admet-2772	260	3	utilize	utilize	VERB
admet-2772	260	4	physicochemical	physicochemical	ADJ
admet-2772	260	5	properties	property	NOUN
admet-2772	260	6	and	and	CCONJ
admet-2772	260	7	in	in	ADP
admet-2772	260	8	vitro	vitro	X
admet-2772	260	9	assays	assay	NOUN
admet-2772	260	10	to	to	PART
admet-2772	260	11	predict	predict	VERB
admet-2772	260	12	drug	drug	NOUN
admet-2772	260	13	-	-	PUNCT
admet-2772	260	14	induced	induce	VERB
admet-2772	260	15	liver	liver	NOUN
admet-2772	260	16	injuries	injury	NOUN
admet-2772	260	17	(	(	PUNCT
admet-2772	260	18	dili	dili	PROPN
admet-2772	260	19	)	)	PUNCT
admet-2772	260	20	,	,	PUNCT
admet-2772	260	21	which	which	PRON
admet-2772	260	22	are	be	AUX
admet-2772	260	23	major	major	ADJ
admet-2772	260	24	causes	cause	NOUN
admet-2772	260	25	of	of	ADP
admet-2772	260	26	drug	drug	NOUN
admet-2772	260	27	attrition	attrition	NOUN
admet-2772	260	28	[	[	X
admet-2772	260	29	103	103	NUM
admet-2772	260	30	]	]	PUNCT
admet-2772	260	31	.	.	PUNCT
admet-2772	261	1	support	support	NOUN
admet-2772	261	2	vector	vector	NOUN
admet-2772	261	3	machines	machine	NOUN
admet-2772	261	4	and	and	CCONJ
admet-2772	261	5	random	random	ADJ
admet-2772	261	6	forests	forest	NOUN
admet-2772	261	7	are	be	AUX
admet-2772	261	8	among	among	ADP
admet-2772	261	9	the	the	DET
admet-2772	261	10	most	most	ADV
admet-2772	261	11	commonly	commonly	ADV
admet-2772	261	12	used	use	VERB
admet-2772	261	13	algorithms	algorithm	NOUN
admet-2772	261	14	for	for	ADP
admet-2772	261	15	toxicity	toxicity	NOUN
admet-2772	261	16	prediction	prediction	NOUN
admet-2772	261	17	[	[	X
admet-2772	261	18	104	104	NUM
admet-2772	261	19	]	]	PUNCT
admet-2772	261	20	.	.	PUNCT
admet-2772	262	1	khan	khan	PROPN
admet-2772	262	2	et	et	PROPN
admet-2772	262	3	al	al	PROPN
admet-2772	262	4	.	.	PUNCT
admet-2772	263	1	[	[	X
admet-2772	263	2	104	104	NUM
admet-2772	263	3	]	]	PUNCT
admet-2772	263	4	developed	develop	VERB
admet-2772	263	5	an	an	DET
admet-2772	263	6	ensemble	ensemble	ADJ
admet-2772	263	7	model	model	NOUN
admet-2772	263	8	integrating	integrate	VERB
admet-2772	263	9	ml	ml	NOUN
admet-2772	263	10	and	and	CCONJ
admet-2772	263	11	deep	deep	ADJ
admet-2772	263	12	learning	learning	NOUN
admet-2772	263	13	algorithms	algorithm	NOUN
admet-2772	263	14	,	,	PUNCT
admet-2772	263	15	achieving	achieve	VERB
admet-2772	263	16	80.26	80.26	NUM
admet-2772	263	17	%	%	NOUN
admet-2772	263	18	accuracy	accuracy	NOUN
admet-2772	263	19	in	in	ADP
admet-2772	263	20	predicting	predict	VERB
admet-2772	263	21	hepatotoxicity	hepatotoxicity	NOUN
admet-2772	263	22	.	.	PUNCT
admet-2772	264	1	ancuceanu	ancuceanu	PROPN
admet-2772	264	2	et	et	PROPN
admet-2772	264	3	al	al	PROPN
admet-2772	264	4	.	.	PUNCT
admet-2772	265	1	[	[	X
admet-2772	265	2	105	105	NUM
admet-2772	265	3	]	]	PUNCT
admet-2772	265	4	used	use	VERB
admet-2772	265	5	the	the	DET
admet-2772	265	6	dilirank	dilirank	NOUN
admet-2772	265	7	dataset	dataset	NOUN
admet-2772	265	8	to	to	PART
admet-2772	265	9	create	create	VERB
admet-2772	265	10	78	78	NUM
admet-2772	265	11	models	model	NOUN
admet-2772	265	12	,	,	PUNCT
admet-2772	265	13	which	which	PRON
admet-2772	265	14	were	be	AUX
admet-2772	265	15	then	then	ADV
admet-2772	265	16	stacked	stack	VERB
admet-2772	265	17	for	for	ADP
admet-2772	265	18	improved	improved	ADJ
admet-2772	265	19	performance	performance	NOUN
admet-2772	265	20	.	.	PUNCT
admet-2772	266	1	lu	lu	PROPN
admet-2772	266	2	et	et	PROPN
admet-2772	266	3	al	al	PROPN
admet-2772	266	4	.	.	PUNCT
admet-2772	267	1	[	[	X
admet-2772	267	2	106	106	NUM
admet-2772	267	3	]	]	PUNCT
admet-2772	267	4	focused	focus	VERB
admet-2772	267	5	on	on	ADP
admet-2772	267	6	predicting	predict	VERB
admet-2772	267	7	hepatotoxicity	hepatotoxicity	NOUN
admet-2772	267	8	of	of	ADP
admet-2772	267	9	drug	drug	NOUN
admet-2772	267	10	metabolites	metabolite	NOUN
admet-2772	267	11	using	use	VERB
admet-2772	267	12	an	an	DET
admet-2772	267	13	ensemble	ensemble	ADJ
admet-2772	267	14	approach	approach	NOUN
admet-2772	267	15	based	base	VERB
admet-2772	267	16	on	on	ADP
admet-2772	267	17	support	support	NOUN
admet-2772	267	18	vector	vector	NOUN
admet-2772	267	19	machines	machine	NOUN
admet-2772	267	20	,	,	PUNCT
admet-2772	267	21	achieving	achieve	VERB
admet-2772	267	22	78.47	78.47	NUM
admet-2772	267	23	%	%	NOUN
admet-2772	267	24	balanced	balanced	ADJ
admet-2772	267	25	accuracy	accuracy	NOUN
admet-2772	267	26	.	.	PUNCT
admet-2772	268	1	for	for	ADP
admet-2772	268	2	specific	specific	ADJ
admet-2772	268	3	drugs	drug	NOUN
admet-2772	268	4	like	like	ADP
admet-2772	268	5	colistin	colistin	NOUN
admet-2772	268	6	,	,	PUNCT
admet-2772	268	7	machine	machine	NOUN
admet-2772	268	8	learning	learning	NOUN
admet-2772	268	9	models	model	NOUN
admet-2772	268	10	using	use	VERB
admet-2772	268	11	electronic	electronic	ADJ
admet-2772	268	12	health	health	NOUN
admet-2772	268	13	records	record	NOUN
admet-2772	268	14	have	have	AUX
admet-2772	268	15	been	be	AUX
admet-2772	268	16	developed	develop	VERB
admet-2772	268	17	to	to	PART
admet-2772	268	18	predict	predict	VERB
admet-2772	268	19	nephrotoxicity	nephrotoxicity	NOUN
admet-2772	268	20	,	,	PUNCT
admet-2772	268	21	identifying	identify	VERB
admet-2772	268	22	key	key	ADJ
admet-2772	268	23	risk	risk	NOUN
admet-2772	268	24	factors	factor	NOUN
admet-2772	268	25	and	and	CCONJ
admet-2772	268	26	dose	dose	NOUN
admet-2772	268	27	thresholds	threshold	NOUN
admet-2772	268	28	[	[	X
admet-2772	268	29	107	107	NUM
admet-2772	268	30	]	]	PUNCT
admet-2772	268	31	.	.	PUNCT
admet-2772	269	1	admet	admet	PROPN
admet-2772	269	2	&	&	CCONJ
admet-2772	269	3	dmpk	dmpk	PROPN
admet-2772	269	4	13(3	13(3	NUM
admet-2772	269	5	)	)	PUNCT
admet-2772	269	6	(	(	PUNCT
admet-2772	269	7	2025	2025	NUM
admet-2772	269	8	)	)	PUNCT
admet-2772	269	9	2772	2772	NUM
admet-2772	269	10	machine	machine	NOUN
admet-2772	269	11	learning	learning	NOUN
admet-2772	269	12	models	model	NOUN
admet-2772	269	13	for	for	ADP
admet-2772	269	14	admet	admet	ADJ
admet-2772	269	15	prediction	prediction	NOUN
admet-2772	269	16	in	in	ADP
admet-2772	269	17	drug	drug	NOUN
admet-2772	269	18	development	development	NOUN
admet-2772	269	19	doi	doi	PROPN
admet-2772	269	20	:	:	PUNCT
admet-2772	269	21	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	269	22	11	11	NUM
admet-2772	269	23	table	table	NOUN
admet-2772	269	24	7	7	NUM
admet-2772	269	25	.	.	PUNCT
admet-2772	269	26	summary	summary	NOUN
admet-2772	269	27	of	of	ADP
admet-2772	269	28	machine	machine	NOUN
admet-2772	269	29	learning	learning	NOUN
admet-2772	269	30	-	-	PUNCT
admet-2772	269	31	based	base	VERB
admet-2772	269	32	models	model	NOUN
admet-2772	269	33	for	for	ADP
admet-2772	269	34	toxicity	toxicity	NOUN
admet-2772	269	35	prediction	prediction	NOUN
admet-2772	269	36	no	no	INTJ
admet-2772	269	37	.	.	PUNCT
admet-2772	269	38	of	of	ADP
admet-2772	269	39	comp	comp	PROPN
admet-2772	269	40	.	.	PUNCT
admet-2772	270	1	target	target	NOUN
admet-2772	270	2	descriptors	descriptor	NOUN
admet-2772	270	3	modelling	model	VERB
admet-2772	270	4	method	method	NOUN
admet-2772	270	5	performance	performance	NOUN
admet-2772	270	6	ref	ref	NOUN
admet-2772	270	7	.	.	PUNCT
admet-2772	271	1	mice	mouse	NOUN
admet-2772	271	2	=	=	SYM
admet-2772	271	3	6,226	6,226	NUM
admet-2772	271	4	rat	rat	NOUN
admet-2772	271	5	=	=	SYM
admet-2772	271	6	6,238	6,238	NUM
admet-2772	271	7	acute	acute	ADJ
admet-2772	271	8	oral	oral	ADJ
admet-2772	271	9	toxicity	toxicity	NOUN
admet-2772	271	10	molecular	molecular	ADJ
admet-2772	271	11	fingerprints	fingerprint	NOUN
admet-2772	271	12	,	,	PUNCT
admet-2772	271	13	molecular	molecular	ADJ
admet-2772	271	14	descriptors	descriptor	NOUN
admet-2772	271	15	graph	graph	VERB
admet-2772	271	16	neural	neural	ADJ
admet-2772	271	17	network	network	NOUN
admet-2772	271	18	,	,	PUNCT
admet-2772	271	19	rf	rf	NOUN
admet-2772	271	20	,	,	PUNCT
admet-2772	271	21	svm	svm	ADJ
admet-2772	271	22	,	,	PUNCT
admet-2772	271	23	artificial	artificial	ADJ
admet-2772	271	24	neural	neural	ADJ
admet-2772	271	25	network	network	NOUN
admet-2772	271	26	accuracy	accuracy	NOUN
admet-2772	271	27	:	:	PUNCT
admet-2772	271	28	mice	mouse	NOUN
admet-2772	271	29	=	=	SYM
admet-2772	271	30	0.9586	0.9586	NUM
admet-2772	271	31	;	;	PUNCT
admet-2772	271	32	rat	rat	NOUN
admet-2772	271	33	=	=	PROPN
admet-2772	271	34	0.9335	0.9335	NUM
admet-2772	271	35	mcc	mcc	NOUN
admet-2772	271	36	:	:	PUNCT
admet-2772	271	37	mice	mouse	NOUN
admet-2772	271	38	=	=	SYM
admet-2772	271	39	0.5514	0.5514	NUM
admet-2772	271	40	;	;	PUNCT
admet-2772	271	41	rat	rat	NOUN
admet-2772	271	42	=	=	PROPN
admet-2772	271	43	0.4929	0.4929	NUM
admet-2772	271	44	auroc	auroc	NOUN
admet-2772	271	45	:	:	PUNCT
admet-2772	271	46	mice	mouse	NOUN
admet-2772	271	47	=	=	SYM
admet-2772	271	48	0.7778	0.7778	NUM
admet-2772	271	49	;	;	PUNCT
admet-2772	271	50	rat	rat	NOUN
admet-2772	271	51	=	=	NUM
admet-2772	271	52	0.7442	0.7442	NUM
admet-2772	271	53	[	[	X
admet-2772	271	54	108	108	NUM
admet-2772	271	55	]	]	SYM
admet-2772	271	56	575	575	NUM
admet-2772	271	57	hepatotoxicity	hepatotoxicity	NOUN
admet-2772	271	58	1d	1d	NUM
admet-2772	271	59	and	and	CCONJ
admet-2772	271	60	2d	2d	NUM
admet-2772	271	61	molecular	molecular	ADJ
admet-2772	271	62	descriptors	descriptor	NOUN
admet-2772	271	63	rf	rf	PRON
admet-2772	271	64	accuracy=	accuracy=	NUM
admet-2772	271	65	0.631	0.631	NUM
admet-2772	271	66	[	[	X
admet-2772	271	67	109	109	NUM
admet-2772	271	68	]	]	SYM
admet-2772	271	69	7889	7889	NUM
admet-2772	271	70	cardiotoxicity	cardiotoxicity	NOUN
admet-2772	271	71	moe	moe	NOUN
admet-2772	271	72	and	and	CCONJ
admet-2772	271	73	mol2vec	mol2vec	NOUN
admet-2772	271	74	descriptors	descriptor	NOUN
admet-2772	271	75	multitask	multitask	VERB
admet-2772	271	76	a	a	DET
admet-2772	271	77	auc	auc	NOUN
admet-2772	271	78	:	:	PUNCT
admet-2772	271	79	training	training	NOUN
admet-2772	271	80	set	set	NOUN
admet-2772	271	81	=	=	PROPN
admet-2772	271	82	0.944	0.944	NUM
admet-2772	271	83	;	;	PUNCT
admet-2772	272	1	validation	validation	NOUN
admet-2772	272	2	set=	set=	NOUN
admet-2772	272	3	0967	0967	NUM
admet-2772	272	4	[	[	X
admet-2772	272	5	110	110	NUM
admet-2772	272	6	]	]	SYM
admet-2772	272	7	641	641	NUM
admet-2772	272	8	genotoxicity	genotoxicity	NOUN
admet-2772	272	9	molecular	molecular	ADJ
admet-2772	272	10	fingerprints	fingerprint	NOUN
admet-2772	272	11	,	,	PUNCT
admet-2772	272	12	molecular	molecular	ADJ
admet-2772	272	13	descriptors	descriptor	NOUN
admet-2772	272	14	svm	svm	VERB
admet-2772	272	15	,	,	PUNCT
admet-2772	272	16	rf	rf	ADJ
admet-2772	272	17	accuracy	accuracy	NOUN
admet-2772	272	18	=	=	SYM
admet-2772	272	19	0.937	0.937	NUM
admet-2772	273	1	[	[	X
admet-2772	273	2	111	111	NUM
admet-2772	273	3	]	]	SYM
admet-2772	273	4	6512	6512	NUM
admet-2772	273	5	mutagenicity	mutagenicity	NOUN
admet-2772	273	6	molecular	molecular	ADJ
admet-2772	273	7	fingerprints	fingerprint	NOUN
admet-2772	273	8	,	,	PUNCT
admet-2772	273	9	molecular	molecular	ADJ
admet-2772	273	10	descriptors	descriptor	NOUN
admet-2772	273	11	svm	svm	VERB
admet-2772	273	12	auc=	auc=	PROPN
admet-2772	273	13	0.93	0.93	NUM
admet-2772	273	14	[	[	X
admet-2772	273	15	112	112	NUM
admet-2772	273	16	]	]	SYM
admet-2772	273	17	863	863	NUM
admet-2772	273	18	carcinogenicity	carcinogenicity	NOUN
admet-2772	273	19	mol2vec	mol2vec	NOUN
admet-2772	273	20	,	,	PUNCT
admet-2772	273	21	mold2	mold2	PROPN
admet-2772	273	22	,	,	PUNCT
admet-2772	273	23	maccs	maccs	PROPN
admet-2772	273	24	deep	deep	ADJ
admet-2772	273	25	learning	learn	VERB
admet-2772	273	26	mcc=	mcc=	NUM
admet-2772	273	27	0.432	0.432	NUM
admet-2772	274	1	[	[	X
admet-2772	274	2	113	113	NUM
admet-2772	274	3	]	]	PUNCT
admet-2772	274	4	auroc	auroc	NOUN
admet-2772	274	5	area	area	NOUN
admet-2772	274	6	under	under	ADP
admet-2772	274	7	the	the	DET
admet-2772	274	8	receiver	receiver	NOUN
admet-2772	274	9	operating	operate	VERB
admet-2772	274	10	characteristic	characteristic	ADJ
admet-2772	274	11	curve	curve	NOUN
admet-2772	274	12	a	a	DET
admet-2772	274	13	radiomics	radiomic	NOUN
admet-2772	274	14	-	-	PUNCT
admet-2772	274	15	based	base	VERB
admet-2772	274	16	ml	ml	NOUN
admet-2772	274	17	model	model	NOUN
admet-2772	274	18	for	for	ADP
admet-2772	274	19	predicting	predict	VERB
admet-2772	274	20	radiotherapy	radiotherapy	NOUN
admet-2772	274	21	-	-	PUNCT
admet-2772	274	22	induced	induce	VERB
admet-2772	274	23	cardiotoxicity	cardiotoxicity	NOUN
admet-2772	274	24	in	in	ADP
admet-2772	274	25	breast	breast	NOUN
admet-2772	274	26	cancer	cancer	NOUN
admet-2772	274	27	patients	patient	NOUN
admet-2772	274	28	demonstrated	demonstrate	VERB
admet-2772	274	29	high	high	ADJ
admet-2772	274	30	performance	performance	NOUN
admet-2772	274	31	,	,	PUNCT
admet-2772	274	32	with	with	ADP
admet-2772	274	33	auc	auc	NOUN
admet-2772	274	34	up	up	ADP
admet-2772	274	35	to	to	PART
admet-2772	274	36	97	97	NUM
admet-2772	274	37	%	%	NOUN
admet-2772	274	38	when	when	SCONJ
admet-2772	274	39	combining	combine	VERB
admet-2772	274	40	dosimetric	dosimetric	NOUN
admet-2772	274	41	,	,	PUNCT
admet-2772	274	42	demographic	demographic	ADJ
admet-2772	274	43	,	,	PUNCT
admet-2772	274	44	clinical	clinical	ADJ
admet-2772	274	45	,	,	PUNCT
admet-2772	274	46	and	and	CCONJ
admet-2772	274	47	imaging	imaging	NOUN
admet-2772	274	48	features	feature	VERB
admet-2772	274	49	[	[	X
admet-2772	274	50	114	114	NUM
admet-2772	274	51	]	]	PUNCT
admet-2772	274	52	.	.	PUNCT
admet-2772	275	1	another	another	DET
admet-2772	275	2	study	study	NOUN
admet-2772	275	3	introduced	introduce	VERB
admet-2772	275	4	cardiotoxcsm	cardiotoxcsm	NOUN
admet-2772	275	5	,	,	PUNCT
admet-2772	275	6	a	a	DET
admet-2772	275	7	web	web	NOUN
admet-2772	275	8	-	-	PUNCT
admet-2772	275	9	based	base	VERB
admet-2772	275	10	tool	tool	NOUN
admet-2772	275	11	that	that	PRON
admet-2772	275	12	predicts	predict	VERB
admet-2772	275	13	six	six	NUM
admet-2772	275	14	types	type	NOUN
admet-2772	275	15	of	of	ADP
admet-2772	275	16	cardiac	cardiac	ADJ
admet-2772	275	17	toxicity	toxicity	NOUN
admet-2772	275	18	outcomes	outcome	NOUN
admet-2772	275	19	for	for	ADP
admet-2772	275	20	small	small	ADJ
admet-2772	275	21	molecules	molecule	NOUN
admet-2772	275	22	,	,	PUNCT
admet-2772	275	23	achieving	achieve	VERB
admet-2772	275	24	auc	auc	ADJ
admet-2772	275	25	values	value	NOUN
admet-2772	275	26	up	up	ADP
admet-2772	275	27	to	to	ADP
admet-2772	275	28	0.898	0.898	NUM
admet-2772	275	29	[	[	X
admet-2772	275	30	115	115	NUM
admet-2772	275	31	]	]	PUNCT
admet-2772	275	32	.	.	PUNCT
admet-2772	276	1	the	the	DET
admet-2772	276	2	multiflow	multiflow	PROPN
admet-2772	276	3	®	®	PROPN
admet-2772	276	4	dna	dna	PROPN
admet-2772	276	5	damage	damage	NOUN
admet-2772	276	6	assay	assay	PROPN
admet-2772	276	7	(	(	PUNCT
admet-2772	276	8	mfa	mfa	PROPN
admet-2772	276	9	)	)	PUNCT
admet-2772	276	10	,	,	PUNCT
admet-2772	276	11	which	which	PRON
admet-2772	276	12	measures	measure	VERB
admet-2772	276	13	four	four	NUM
admet-2772	276	14	mechanistic	mechanistic	ADJ
admet-2772	276	15	markers	marker	NOUN
admet-2772	276	16	at	at	ADP
admet-2772	276	17	two	two	NUM
admet-2772	276	18	time	time	NOUN
admet-2772	276	19	points	point	NOUN
admet-2772	276	20	,	,	PUNCT
admet-2772	276	21	has	have	AUX
admet-2772	276	22	been	be	AUX
admet-2772	276	23	combined	combine	VERB
admet-2772	276	24	with	with	ADP
admet-2772	276	25	ml	ml	NOUN
admet-2772	276	26	to	to	PART
admet-2772	276	27	enhance	enhance	VERB
admet-2772	276	28	genotoxicity	genotoxicity	NOUN
admet-2772	276	29	assessment	assessment	NOUN
admet-2772	276	30	and	and	CCONJ
admet-2772	276	31	predict	predict	VERB
admet-2772	276	32	the	the	DET
admet-2772	276	33	mode	mode	NOUN
admet-2772	276	34	of	of	ADP
admet-2772	276	35	action	action	NOUN
admet-2772	276	36	of	of	ADP
admet-2772	276	37	dna	dna	NOUN
admet-2772	276	38	-	-	PUNCT
admet-2772	276	39	damaging	damaging	ADJ
admet-2772	276	40	agents	agent	NOUN
admet-2772	277	1	[	[	X
admet-2772	277	2	116	116	NUM
admet-2772	277	3	]	]	PUNCT
admet-2772	277	4	.	.	PUNCT
admet-2772	278	1	recent	recent	ADJ
admet-2772	278	2	studies	study	NOUN
admet-2772	278	3	have	have	AUX
admet-2772	278	4	achieved	achieve	VERB
admet-2772	278	5	high	high	ADJ
admet-2772	278	6	accuracies	accuracy	NOUN
admet-2772	278	7	in	in	ADP
admet-2772	278	8	predicting	predict	VERB
admet-2772	278	9	genotoxicity	genotoxicity	NOUN
admet-2772	278	10	,	,	PUNCT
admet-2772	278	11	with	with	ADP
admet-2772	278	12	models	model	NOUN
admet-2772	278	13	reaching	reach	VERB
admet-2772	278	14	up	up	ADP
admet-2772	278	15	to	to	PART
admet-2772	278	16	95	95	NUM
admet-2772	278	17	%	%	NOUN
admet-2772	278	18	accuracy	accuracy	NOUN
admet-2772	278	19	on	on	ADP
admet-2772	278	20	training	training	NOUN
admet-2772	278	21	data	datum	NOUN
admet-2772	278	22	and	and	CCONJ
admet-2772	278	23	92	92	NUM
admet-2772	278	24	%	%	NOUN
admet-2772	278	25	on	on	ADP
admet-2772	278	26	external	external	ADJ
admet-2772	278	27	test	test	NOUN
admet-2772	278	28	sets	set	NOUN
admet-2772	278	29	[	[	X
admet-2772	278	30	116	116	NUM
admet-2772	278	31	]	]	PUNCT
admet-2772	278	32	.	.	PUNCT
admet-2772	279	1	these	these	DET
admet-2772	279	2	studies	study	NOUN
admet-2772	279	3	demonstrate	demonstrate	VERB
admet-2772	279	4	the	the	DET
admet-2772	279	5	potential	potential	NOUN
admet-2772	279	6	of	of	ADP
admet-2772	279	7	ml	ml	NOUN
admet-2772	279	8	in	in	ADP
admet-2772	279	9	toxicity	toxicity	NOUN
admet-2772	279	10	prediction	prediction	NOUN
admet-2772	279	11	.	.	PUNCT
admet-2772	280	1	the	the	DET
admet-2772	280	2	availability	availability	NOUN
admet-2772	280	3	of	of	ADP
admet-2772	280	4	large	large	ADJ
admet-2772	280	5	toxicology	toxicology	NOUN
admet-2772	280	6	databases	database	NOUN
admet-2772	280	7	has	have	AUX
admet-2772	280	8	facilitated	facilitate	VERB
admet-2772	280	9	the	the	DET
admet-2772	280	10	development	development	NOUN
admet-2772	280	11	of	of	ADP
admet-2772	280	12	more	more	ADV
admet-2772	280	13	accurate	accurate	ADJ
admet-2772	280	14	models	model	NOUN
admet-2772	280	15	[	[	X
admet-2772	280	16	117	117	NUM
admet-2772	280	17	]	]	PUNCT
admet-2772	280	18	.	.	PUNCT
admet-2772	281	1	however	however	ADV
admet-2772	281	2	,	,	PUNCT
admet-2772	281	3	challenges	challenge	NOUN
admet-2772	281	4	remain	remain	VERB
admet-2772	281	5	,	,	PUNCT
admet-2772	281	6	such	such	ADJ
admet-2772	281	7	as	as	ADP
admet-2772	281	8	the	the	DET
admet-2772	281	9	need	need	NOUN
admet-2772	281	10	for	for	ADP
admet-2772	281	11	benchmarking	benchmarke	VERB
admet-2772	281	12	datasets	dataset	NOUN
admet-2772	281	13	due	due	ADJ
admet-2772	281	14	to	to	ADP
admet-2772	281	15	inconsistencies	inconsistency	NOUN
admet-2772	281	16	in	in	ADP
admet-2772	281	17	toxicity	toxicity	NOUN
admet-2772	281	18	assignments	assignment	NOUN
admet-2772	281	19	across	across	ADP
admet-2772	281	20	different	different	ADJ
admet-2772	281	21	sources	source	NOUN
admet-2772	281	22	[	[	X
admet-2772	281	23	102	102	NUM
admet-2772	281	24	]	]	PUNCT
admet-2772	281	25	.	.	PUNCT
admet-2772	282	1	despite	despite	SCONJ
admet-2772	282	2	these	these	DET
admet-2772	282	3	challenges	challenge	NOUN
admet-2772	282	4	,	,	PUNCT
admet-2772	282	5	computational	computational	ADJ
admet-2772	282	6	toxicology	toxicology	NOUN
admet-2772	282	7	has	have	AUX
admet-2772	282	8	made	make	VERB
admet-2772	282	9	significant	significant	ADJ
admet-2772	282	10	progress	progress	NOUN
admet-2772	282	11	over	over	ADP
admet-2772	282	12	the	the	DET
admet-2772	282	13	past	past	ADJ
admet-2772	282	14	decade	decade	NOUN
admet-2772	282	15	,	,	PUNCT
admet-2772	282	16	with	with	ADP
admet-2772	282	17	machine	machine	NOUN
admet-2772	282	18	learning	learning	NOUN
admet-2772	282	19	models	model	NOUN
admet-2772	282	20	showing	show	VERB
admet-2772	282	21	promise	promise	NOUN
admet-2772	282	22	in	in	ADP
admet-2772	282	23	predicting	predict	VERB
admet-2772	282	24	various	various	ADJ
admet-2772	282	25	toxicity	toxicity	NOUN
admet-2772	282	26	endpoints	endpoint	NOUN
admet-2772	282	27	and	and	CCONJ
admet-2772	282	28	potentially	potentially	ADV
admet-2772	282	29	reducing	reduce	VERB
admet-2772	282	30	the	the	DET
admet-2772	282	31	need	need	NOUN
admet-2772	282	32	for	for	ADP
admet-2772	282	33	costly	costly	ADJ
admet-2772	282	34	and	and	CCONJ
admet-2772	282	35	time	time	NOUN
admet-2772	282	36	-	-	PUNCT
admet-2772	282	37	consuming	consume	VERB
admet-2772	282	38	in	in	ADP
admet-2772	282	39	vivo	vivo	ADJ
admet-2772	282	40	studies	study	NOUN
admet-2772	282	41	[	[	X
admet-2772	282	42	102	102	NUM
admet-2772	282	43	]	]	PUNCT
admet-2772	282	44	.	.	PUNCT
admet-2772	283	1	4.2	4.2	NUM
admet-2772	283	2	.	.	PUNCT
admet-2772	283	3	adverse	adverse	ADJ
admet-2772	283	4	drug	drug	NOUN
admet-2772	283	5	reactions	reaction	NOUN
admet-2772	283	6	machine	machine	NOUN
admet-2772	283	7	learning	learning	NOUN
admet-2772	283	8	approaches	approach	NOUN
admet-2772	283	9	have	have	AUX
admet-2772	283	10	shown	show	VERB
admet-2772	283	11	promising	promising	ADJ
admet-2772	283	12	potential	potential	NOUN
admet-2772	283	13	in	in	ADP
admet-2772	283	14	predicting	predict	VERB
admet-2772	283	15	toxicological	toxicological	ADJ
admet-2772	283	16	properties	property	NOUN
admet-2772	283	17	and	and	CCONJ
admet-2772	283	18	adverse	adverse	ADJ
admet-2772	283	19	drug	drug	NOUN
admet-2772	283	20	reactions	reaction	NOUN
admet-2772	283	21	(	(	PUNCT
admet-2772	283	22	adrs	adrs	PROPN
admet-2772	283	23	)	)	PUNCT
admet-2772	283	24	of	of	ADP
admet-2772	283	25	pharmaceutical	pharmaceutical	ADJ
admet-2772	283	26	agents	agent	NOUN
admet-2772	283	27	[	[	X
admet-2772	283	28	118	118	NUM
admet-2772	283	29	]	]	PUNCT
admet-2772	283	30	.	.	PUNCT
admet-2772	284	1	recent	recent	ADJ
admet-2772	284	2	advancements	advancement	NOUN
admet-2772	284	3	include	include	VERB
admet-2772	284	4	the	the	DET
admet-2772	284	5	development	development	NOUN
admet-2772	284	6	of	of	ADP
admet-2772	284	7	ai	ai	PROPN
admet-2772	284	8	models	model	NOUN
admet-2772	284	9	for	for	ADP
admet-2772	284	10	precise	precise	ADJ
admet-2772	284	11	prediction	prediction	NOUN
admet-2772	284	12	of	of	ADP
admet-2772	284	13	compound	compound	NOUN
admet-2772	284	14	off	off	ADP
admet-2772	284	15	-	-	PUNCT
admet-2772	284	16	target	target	NOUN
admet-2772	284	17	interactions	interaction	NOUN
admet-2772	284	18	,	,	PUNCT
admet-2772	284	19	which	which	PRON
admet-2772	284	20	can	can	AUX
admet-2772	284	21	be	be	AUX
admet-2772	284	22	used	use	VERB
admet-2772	284	23	to	to	PART
admet-2772	284	24	differentiate	differentiate	VERB
admet-2772	284	25	drugs	drug	NOUN
admet-2772	284	26	and	and	CCONJ
admet-2772	284	27	classify	classify	VERB
admet-2772	284	28	compound	compound	NOUN
admet-2772	284	29	toxicity	toxicity	NOUN
admet-2772	284	30	[	[	X
admet-2772	284	31	102	102	NUM
admet-2772	284	32	]	]	PUNCT
admet-2772	284	33	.	.	PUNCT
admet-2772	285	1	the	the	DET
admet-2772	285	2	maester	maester	PROPN
admet-2772	285	3	framework	framework	NOUN
admet-2772	285	4	integrates	integrate	VERB
admet-2772	285	5	diverse	diverse	ADJ
admet-2772	285	6	features	feature	NOUN
admet-2772	285	7	to	to	PART
admet-2772	285	8	predict	predict	VERB
admet-2772	285	9	tissue	tissue	NOUN
admet-2772	285	10	-	-	PUNCT
admet-2772	285	11	specific	specific	ADJ
admet-2772	285	12	adverse	adverse	ADJ
admet-2772	285	13	events	event	NOUN
admet-2772	285	14	with	with	ADP
admet-2772	285	15	high	high	ADJ
admet-2772	285	16	accuracy	accuracy	NOUN
admet-2772	285	17	,	,	PUNCT
admet-2772	285	18	sensitivity	sensitivity	NOUN
admet-2772	285	19	,	,	PUNCT
admet-2772	285	20	and	and	CCONJ
admet-2772	285	21	specificity	specificity	NOUN
admet-2772	285	22	[	[	X
admet-2772	285	23	119	119	NUM
admet-2772	285	24	]	]	PUNCT
admet-2772	285	25	.	.	PUNCT
admet-2772	286	1	similarly	similarly	ADV
admet-2772	286	2	,	,	PUNCT
admet-2772	286	3	the	the	DET
admet-2772	286	4	off	off	ADV
admet-2772	286	5	-	-	PUNCT
admet-2772	286	6	targetp	targetp	NOUN
admet-2772	286	7	ml	ml	X
admet-2772	286	8	framework	framework	NOUN
admet-2772	286	9	uses	use	VERB
admet-2772	286	10	deep	deep	ADJ
admet-2772	286	11	learning	learning	NOUN
admet-2772	286	12	and	and	CCONJ
admet-2772	286	13	automated	automate	VERB
admet-2772	286	14	machine	machine	NOUN
admet-2772	286	15	learning	learn	VERB
admet-2772	286	16	to	to	PART
admet-2772	286	17	predict	predict	VERB
admet-2772	286	18	off	off	ADP
admet-2772	286	19	-	-	PUNCT
admet-2772	286	20	target	target	NOUN
admet-2772	286	21	panel	panel	NOUN
admet-2772	286	22	activities	activity	NOUN
admet-2772	286	23	directly	directly	ADV
admet-2772	286	24	from	from	ADP
admet-2772	286	25	compound	compound	NOUN
admet-2772	286	26	structures	structure	NOUN
admet-2772	286	27	,	,	PUNCT
admet-2772	286	28	aiding	aid	VERB
admet-2772	286	29	in	in	ADP
admet-2772	286	30	drug	drug	NOUN
admet-2772	286	31	design	design	NOUN
admet-2772	286	32	and	and	CCONJ
admet-2772	286	33	discovery	discovery	NOUN
admet-2772	286	34	[	[	X
admet-2772	286	35	120	120	NUM
admet-2772	286	36	]	]	PUNCT
admet-2772	286	37	.	.	PUNCT
admet-2772	287	1	these	these	DET
admet-2772	287	2	computational	computational	ADJ
admet-2772	287	3	methods	method	NOUN
admet-2772	287	4	offer	offer	VERB
admet-2772	287	5	efficient	efficient	ADJ
admet-2772	287	6	,	,	PUNCT
admet-2772	287	7	low	low	ADJ
admet-2772	287	8	-	-	PUNCT
admet-2772	287	9	cost	cost	NOUN
admet-2772	287	10	tools	tool	NOUN
admet-2772	287	11	for	for	ADP
admet-2772	287	12	early	early	ADJ
admet-2772	287	13	assessment	assessment	NOUN
admet-2772	287	14	of	of	ADP
admet-2772	287	15	compound	compound	NOUN
admet-2772	287	16	safety	safety	NOUN
admet-2772	287	17	and	and	CCONJ
admet-2772	287	18	toxicity	toxicity	NOUN
admet-2772	287	19	,	,	PUNCT
admet-2772	287	20	potentially	potentially	ADV
admet-2772	287	21	reducing	reduce	VERB
admet-2772	287	22	costly	costly	ADJ
admet-2772	287	23	failures	failure	NOUN
admet-2772	287	24	in	in	ADP
admet-2772	287	25	drug	drug	NOUN
admet-2772	287	26	development	development	NOUN
admet-2772	287	27	and	and	CCONJ
admet-2772	287	28	identifying	identify	VERB
admet-2772	287	29	toxic	toxic	ADJ
admet-2772	287	30	[	[	X
admet-2772	287	31	102	102	NUM
admet-2772	287	32	]	]	PUNCT
admet-2772	287	33	.	.	PUNCT
admet-2772	288	1	4.3	4.3	NUM
admet-2772	288	2	.	.	PUNCT
admet-2772	288	3	machine	machine	NOUN
admet-2772	288	4	learning	learn	VERB
admet-2772	288	5	for	for	ADP
admet-2772	288	6	predicting	predict	VERB
admet-2772	288	7	dose	dose	NOUN
admet-2772	288	8	-	-	PUNCT
admet-2772	288	9	dependent	dependent	ADJ
admet-2772	288	10	toxicity	toxicity	NOUN
admet-2772	288	11	machine	machine	NOUN
admet-2772	288	12	learning	learning	NOUN
admet-2772	288	13	is	be	AUX
admet-2772	288	14	revolutionizing	revolutionize	VERB
admet-2772	288	15	toxicology	toxicology	NOUN
admet-2772	288	16	by	by	ADP
admet-2772	288	17	enhancing	enhance	VERB
admet-2772	288	18	predictive	predictive	ADJ
admet-2772	288	19	capabilities	capability	NOUN
admet-2772	288	20	across	across	ADP
admet-2772	288	21	various	various	ADJ
admet-2772	288	22	dosing	dosing	NOUN
admet-2772	288	23	ranges	range	NOUN
admet-2772	288	24	and	and	CCONJ
admet-2772	288	25	improving	improve	VERB
admet-2772	288	26	safety	safety	NOUN
admet-2772	288	27	assessments	assessment	NOUN
admet-2772	288	28	.	.	PUNCT
admet-2772	289	1	ml	ml	NOUN
admet-2772	289	2	models	model	NOUN
admet-2772	289	3	can	can	AUX
admet-2772	289	4	analyse	analyse	VERB
admet-2772	289	5	large	large	ADJ
admet-2772	289	6	datasets	dataset	NOUN
admet-2772	289	7	to	to	PART
admet-2772	289	8	predict	predict	VERB
admet-2772	289	9	drug	drug	NOUN
admet-2772	289	10	toxicity	toxicity	NOUN
admet-2772	289	11	,	,	PUNCT
admet-2772	289	12	environmental	environmental	ADJ
admet-2772	289	13	hazards	hazard	NOUN
admet-2772	289	14	,	,	PUNCT
admet-2772	289	15	and	and	CCONJ
admet-2772	289	16	off	off	ADP
admet-2772	289	17	-	-	PUNCT
admet-2772	289	18	target	target	NOUN
admet-2772	289	19	effects	effect	NOUN
admet-2772	289	20	,	,	PUNCT
admet-2772	289	21	offering	offer	VERB
admet-2772	289	22	more	more	ADV
admet-2772	289	23	efficient	efficient	ADJ
admet-2772	289	24	and	and	CCONJ
admet-2772	289	25	accurate	accurate	ADJ
admet-2772	289	26	risk	risk	NOUN
admet-2772	289	27	evaluations	evaluation	NOUN
admet-2772	289	28	[	[	X
admet-2772	289	29	121	121	NUM
admet-2772	289	30	-	-	SYM
admet-2772	289	31	123	123	NUM
admet-2772	289	32	-	-	NUM
admet-2772	289	33	87	87	NUM
admet-2772	289	34	]	]	PUNCT
admet-2772	289	35	.	.	PUNCT
admet-2772	290	1	these	these	DET
admet-2772	290	2	models	model	NOUN
admet-2772	290	3	can	can	AUX
admet-2772	290	4	be	be	AUX
admet-2772	290	5	applied	apply	VERB
admet-2772	290	6	early	early	ADV
admet-2772	290	7	in	in	ADP
admet-2772	290	8	drug	drug	NOUN
admet-2772	290	9	discovery	discovery	NOUN
admet-2772	290	10	to	to	PART
admet-2772	290	11	identify	identify	VERB
admet-2772	290	12	potential	potential	ADJ
admet-2772	290	13	safety	safety	NOUN
admet-2772	290	14	liabilities	liability	NOUN
admet-2772	290	15	and	and	CCONJ
admet-2772	290	16	filter	filter	VERB
admet-2772	290	17	out	out	ADP
admet-2772	290	18	problematic	problematic	ADJ
admet-2772	290	19	compounds	compound	NOUN
admet-2772	290	20	[	[	X
admet-2772	290	21	117	117	NUM
admet-2772	290	22	]	]	PUNCT
admet-2772	290	23	.	.	PUNCT
admet-2772	291	1	the	the	DET
admet-2772	291	2	integration	integration	NOUN
admet-2772	291	3	of	of	ADP
admet-2772	291	4	ml	ml	NOUN
admet-2772	291	5	with	with	ADP
admet-2772	291	6	dna	dna	PROPN
admet-2772	291	7	-	-	PUNCT
admet-2772	291	8	encoded	encode	VERB
admet-2772	291	9	libraries	library	NOUN
admet-2772	291	10	(	(	PUNCT
admet-2772	291	11	dels	del	NOUN
admet-2772	291	12	)	)	PUNCT
admet-2772	291	13	shows	show	VERB
admet-2772	291	14	promise	promise	NOUN
admet-2772	291	15	for	for	ADP
admet-2772	291	16	modelling	model	VERB
admet-2772	291	17	binding	bind	VERB
admet-2772	291	18	to	to	ADP
admet-2772	291	19	off	off	ADP
admet-2772	291	20	-	-	PUNCT
admet-2772	291	21	targets	target	NOUN
admet-2772	291	22	and	and	CCONJ
admet-2772	291	23	improving	improve	VERB
admet-2772	291	24	predictive	predictive	ADJ
admet-2772	291	25	toxicology	toxicology	NOUN
admet-2772	291	26	[	[	X
admet-2772	291	27	123	123	NUM
admet-2772	291	28	]	]	PUNCT
admet-2772	291	29	.	.	PUNCT
admet-2772	292	1	various	various	ADJ
admet-2772	292	2	toxic	toxic	ADJ
admet-2772	292	3	endpoints	endpoint	NOUN
admet-2772	292	4	,	,	PUNCT
admet-2772	292	5	including	include	VERB
admet-2772	292	6	acute	acute	ADJ
admet-2772	292	7	oral	oral	ADJ
admet-2772	292	8	toxicity	toxicity	NOUN
admet-2772	292	9	,	,	PUNCT
admet-2772	292	10	hepatotoxicity	hepatotoxicity	NOUN
admet-2772	292	11	,	,	PUNCT
admet-2772	292	12	and	and	CCONJ
admet-2772	292	13	cardiotoxicity	cardiotoxicity	NOUN
admet-2772	292	14	,	,	PUNCT
admet-2772	292	15	can	can	AUX
admet-2772	292	16	be	be	AUX
admet-2772	292	17	predicted	predict	VERB
admet-2772	292	18	using	use	VERB
admet-2772	292	19	ml	ml	NOUN
admet-2772	292	20	methods	method	NOUN
admet-2772	292	21	,	,	PUNCT
admet-2772	292	22	although	although	SCONJ
admet-2772	292	23	performance	performance	NOUN
admet-2772	292	24	varies	vary	VERB
admet-2772	292	25	depending	depend	VERB
admet-2772	292	26	on	on	ADP
admet-2772	292	27	the	the	DET
admet-2772	292	28	dataset	dataset	NOUN
admet-2772	292	29	and	and	CCONJ
admet-2772	292	30	chemical	chemical	NOUN
admet-2772	292	31	space	space	NOUN
admet-2772	292	32	covered	cover	VERB
admet-2772	292	33	[	[	PUNCT
admet-2772	292	34	117	117	NUM
admet-2772	292	35	]	]	PUNCT
admet-2772	292	36	.	.	PUNCT
admet-2772	293	1	despite	despite	SCONJ
admet-2772	293	2	challenges	challenge	NOUN
admet-2772	293	3	,	,	PUNCT
admet-2772	293	4	ml	ml	X
admet-2772	293	5	in	in	ADP
admet-2772	293	6	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	293	7	m.	m.	NOUN
admet-2772	293	8	venkataraman	venkataraman	PROPN
admet-2772	293	9	et	et	PROPN
admet-2772	293	10	al	al	PROPN
admet-2772	293	11	.	.	PROPN
admet-2772	293	12	admet	admet	PROPN
admet-2772	293	13	&	&	CCONJ
admet-2772	293	14	dmpk	dmpk	PROPN
admet-2772	293	15	13(3	13(3	NUM
admet-2772	293	16	)	)	PUNCT
admet-2772	293	17	(	(	PUNCT
admet-2772	293	18	2025	2025	NUM
admet-2772	293	19	)	)	PUNCT
admet-2772	293	20	2772	2772	NUM
admet-2772	293	21	12	12	NUM
admet-2772	293	22	toxicology	toxicology	NOUN
admet-2772	293	23	offers	offer	VERB
admet-2772	293	24	significant	significant	ADJ
admet-2772	293	25	potential	potential	NOUN
admet-2772	293	26	for	for	ADP
admet-2772	293	27	enhancing	enhance	VERB
admet-2772	293	28	risk	risk	NOUN
admet-2772	293	29	assessment	assessment	NOUN
admet-2772	293	30	,	,	PUNCT
admet-2772	293	31	determining	determine	VERB
admet-2772	293	32	clinical	clinical	ADJ
admet-2772	293	33	toxicities	toxicity	NOUN
admet-2772	293	34	,	,	PUNCT
admet-2772	293	35	and	and	CCONJ
admet-2772	293	36	detecting	detect	VERB
admet-2772	293	37	harmful	harmful	ADJ
admet-2772	293	38	side	side	ADJ
admet-2772	293	39	effects	effect	NOUN
admet-2772	293	40	of	of	ADP
admet-2772	293	41	medications	medication	NOUN
admet-2772	293	42	[	[	X
admet-2772	293	43	121	121	NUM
admet-2772	293	44	]	]	PUNCT
admet-2772	293	45	.	.	PUNCT
admet-2772	294	1	5	5	X
admet-2772	294	2	.	.	X
admet-2772	294	3	overview	overview	NOUN
admet-2772	294	4	of	of	ADP
admet-2772	294	5	common	common	ADJ
admet-2772	294	6	machine	machine	NOUN
admet-2772	294	7	learning	learn	VERB
admet-2772	294	8	techniques	technique	NOUN
admet-2772	294	9	in	in	ADP
admet-2772	294	10	adme	adme	NOUN
admet-2772	294	11	-	-	PUNCT
admet-2772	294	12	tox	tox	NOUN
admet-2772	294	13	prediction	prediction	NOUN
admet-2772	294	14	ml	ml	VERB
admet-2772	294	15	is	be	AUX
admet-2772	294	16	a	a	DET
admet-2772	294	17	method	method	NOUN
admet-2772	294	18	of	of	ADP
admet-2772	294	19	data	datum	NOUN
admet-2772	294	20	analysis	analysis	NOUN
admet-2772	294	21	involving	involve	VERB
admet-2772	294	22	the	the	DET
admet-2772	294	23	development	development	NOUN
admet-2772	294	24	of	of	ADP
admet-2772	294	25	new	new	ADJ
admet-2772	294	26	algorithms	algorithm	NOUN
admet-2772	294	27	and	and	CCONJ
admet-2772	294	28	models	model	NOUN
admet-2772	294	29	capable	capable	ADJ
admet-2772	294	30	of	of	ADP
admet-2772	294	31	interpreting	interpret	VERB
admet-2772	294	32	a	a	DET
admet-2772	294	33	multitude	multitude	NOUN
admet-2772	294	34	of	of	ADP
admet-2772	294	35	data	datum	NOUN
admet-2772	294	36	[	[	X
admet-2772	294	37	14	14	NUM
admet-2772	294	38	]	]	PUNCT
admet-2772	294	39	.	.	PUNCT
admet-2772	295	1	the	the	DET
admet-2772	295	2	algorithms	algorithm	NOUN
admet-2772	295	3	used	use	VERB
admet-2772	295	4	in	in	ADP
admet-2772	295	5	recent	recent	ADJ
admet-2772	295	6	years	year	NOUN
admet-2772	295	7	have	have	AUX
admet-2772	295	8	successively	successively	ADV
admet-2772	295	9	improved	improve	VERB
admet-2772	295	10	their	their	PRON
admet-2772	295	11	performance	performance	NOUN
admet-2772	295	12	with	with	ADP
admet-2772	295	13	the	the	DET
admet-2772	295	14	increase	increase	NOUN
admet-2772	295	15	in	in	ADP
admet-2772	295	16	both	both	CCONJ
admet-2772	295	17	the	the	DET
admet-2772	295	18	quantitative	quantitative	ADJ
admet-2772	295	19	and	and	CCONJ
admet-2772	295	20	qualitative	qualitative	ADJ
admet-2772	295	21	aspects	aspect	NOUN
admet-2772	295	22	of	of	ADP
admet-2772	295	23	data	datum	NOUN
admet-2772	295	24	available	available	ADJ
admet-2772	295	25	for	for	ADP
admet-2772	295	26	learning	learn	VERB
admet-2772	295	27	[	[	X
admet-2772	295	28	124	124	NUM
admet-2772	295	29	]	]	PUNCT
admet-2772	295	30	.	.	PUNCT
admet-2772	296	1	figure	figure	NOUN
admet-2772	296	2	2	2	NUM
admet-2772	296	3	illustrates	illustrate	VERB
admet-2772	296	4	commonly	commonly	ADV
admet-2772	296	5	used	use	VERB
admet-2772	296	6	ai	ai	NOUN
admet-2772	296	7	/	/	SYM
admet-2772	296	8	ml	ml	NOUN
admet-2772	296	9	algorithms	algorithm	NOUN
admet-2772	296	10	for	for	ADP
admet-2772	296	11	developing	develop	VERB
admet-2772	296	12	admet	admet	NOUN
admet-2772	296	13	prediction	prediction	NOUN
admet-2772	296	14	models	model	NOUN
admet-2772	296	15	.	.	PUNCT
admet-2772	297	1	ml	ml	X
admet-2772	297	2	is	be	AUX
admet-2772	297	3	considered	consider	VERB
admet-2772	297	4	one	one	NUM
admet-2772	297	5	of	of	ADP
admet-2772	297	6	the	the	DET
admet-2772	297	7	best	good	ADJ
admet-2772	297	8	options	option	NOUN
admet-2772	297	9	available	available	ADJ
admet-2772	297	10	when	when	SCONJ
admet-2772	297	11	applied	apply	VERB
admet-2772	297	12	to	to	PART
admet-2772	297	13	solve	solve	VERB
admet-2772	297	14	problems	problem	NOUN
admet-2772	297	15	for	for	ADP
admet-2772	297	16	which	which	PRON
admet-2772	297	17	a	a	DET
admet-2772	297	18	big	big	ADJ
admet-2772	297	19	amount	amount	NOUN
admet-2772	297	20	of	of	ADP
admet-2772	297	21	data	datum	NOUN
admet-2772	297	22	and	and	CCONJ
admet-2772	297	23	various	various	ADJ
admet-2772	297	24	variables	variable	NOUN
admet-2772	297	25	are	be	AUX
admet-2772	297	26	available	available	ADJ
admet-2772	297	27	to	to	ADP
admet-2772	297	28	the	the	DET
admet-2772	297	29	individual	individual	NOUN
admet-2772	297	30	,	,	PUNCT
admet-2772	297	31	but	but	CCONJ
admet-2772	297	32	a	a	DET
admet-2772	297	33	model	model	NOUN
admet-2772	297	34	or	or	CCONJ
admet-2772	297	35	formula	formula	NOUN
admet-2772	297	36	relating	relate	VERB
admet-2772	297	37	these	these	DET
admet-2772	297	38	various	various	ADJ
admet-2772	297	39	variables	variable	NOUN
admet-2772	297	40	amongst	amongst	ADP
admet-2772	297	41	themselves	themselves	PRON
admet-2772	297	42	,	,	PUNCT
admet-2772	297	43	along	along	ADP
admet-2772	297	44	with	with	ADP
admet-2772	297	45	the	the	DET
admet-2772	297	46	expected	expect	VERB
admet-2772	297	47	result	result	NOUN
admet-2772	297	48	,	,	PUNCT
admet-2772	297	49	is	be	AUX
admet-2772	297	50	not	not	PART
admet-2772	297	51	known	know	VERB
admet-2772	297	52	[	[	PUNCT
admet-2772	297	53	3,4	3,4	NUM
admet-2772	297	54	]	]	PUNCT
admet-2772	297	55	.	.	PUNCT
admet-2772	298	1	however	however	ADV
admet-2772	298	2	,	,	PUNCT
admet-2772	298	3	when	when	SCONJ
admet-2772	298	4	drug	drug	NOUN
admet-2772	298	5	discovery	discovery	NOUN
admet-2772	298	6	moved	move	VERB
admet-2772	298	7	into	into	ADP
admet-2772	298	8	an	an	DET
admet-2772	298	9	era	era	NOUN
admet-2772	298	10	of	of	ADP
admet-2772	298	11	a	a	DET
admet-2772	298	12	large	large	ADJ
admet-2772	298	13	amount	amount	NOUN
admet-2772	298	14	of	of	ADP
admet-2772	298	15	data	datum	NOUN
admet-2772	298	16	,	,	PUNCT
admet-2772	298	17	ml	ml	ADP
admet-2772	298	18	approaches	approach	NOUN
admet-2772	298	19	evolved	evolve	VERB
admet-2772	298	20	into	into	ADP
admet-2772	298	21	dl	dl	PROPN
admet-2772	298	22	approaches	approach	NOUN
admet-2772	298	23	,	,	PUNCT
admet-2772	298	24	which	which	PRON
admet-2772	298	25	are	be	AUX
admet-2772	298	26	more	more	ADV
admet-2772	298	27	powerful	powerful	ADJ
admet-2772	298	28	and	and	CCONJ
admet-2772	298	29	efficient	efficient	ADJ
admet-2772	298	30	in	in	ADP
admet-2772	298	31	dealing	deal	VERB
admet-2772	298	32	with	with	ADP
admet-2772	298	33	the	the	DET
admet-2772	298	34	massive	massive	ADJ
admet-2772	298	35	amounts	amount	NOUN
admet-2772	298	36	of	of	ADP
admet-2772	298	37	data	datum	NOUN
admet-2772	298	38	generated	generate	VERB
admet-2772	298	39	from	from	ADP
admet-2772	298	40	modern	modern	ADJ
admet-2772	298	41	drug	drug	NOUN
admet-2772	298	42	discovery	discovery	NOUN
admet-2772	298	43	approaches	approach	VERB
admet-2772	298	44	[	[	X
admet-2772	298	45	125	125	NUM
admet-2772	298	46	]	]	PUNCT
admet-2772	298	47	.	.	PUNCT
admet-2772	299	1	dl	dl	PROPN
admet-2772	299	2	is	be	AUX
admet-2772	299	3	a	a	DET
admet-2772	299	4	subset	subset	NOUN
admet-2772	299	5	of	of	ADP
admet-2772	299	6	ml	ml	NOUN
admet-2772	299	7	based	base	VERB
admet-2772	299	8	on	on	ADP
admet-2772	299	9	artificial	artificial	ADJ
admet-2772	299	10	neural	neural	ADJ
admet-2772	299	11	networks	network	NOUN
admet-2772	299	12	that	that	PRON
admet-2772	299	13	use	use	VERB
admet-2772	299	14	multiple	multiple	ADJ
admet-2772	299	15	layers	layer	NOUN
admet-2772	299	16	to	to	PART
admet-2772	299	17	progressively	progressively	ADV
admet-2772	299	18	extract	extract	VERB
admet-2772	299	19	higher	high	ADJ
admet-2772	299	20	-	-	PUNCT
admet-2772	299	21	level	level	NOUN
admet-2772	299	22	features	feature	NOUN
admet-2772	299	23	from	from	ADP
admet-2772	299	24	raw	raw	ADJ
admet-2772	299	25	input	input	NOUN
admet-2772	299	26	.	.	PUNCT
admet-2772	300	1	due	due	ADP
admet-2772	300	2	to	to	ADP
admet-2772	300	3	its	its	PRON
admet-2772	300	4	ability	ability	NOUN
admet-2772	300	5	to	to	PART
admet-2772	300	6	learn	learn	VERB
admet-2772	300	7	from	from	ADP
admet-2772	300	8	data	datum	NOUN
admet-2772	300	9	and	and	CCONJ
admet-2772	300	10	the	the	DET
admet-2772	300	11	environment	environment	NOUN
admet-2772	300	12	,	,	PUNCT
admet-2772	300	13	dl	dl	PROPN
admet-2772	300	14	and	and	CCONJ
admet-2772	300	15	neural	neural	ADJ
admet-2772	300	16	network	network	NOUN
admet-2772	300	17	(	(	PUNCT
admet-2772	300	18	nn	nn	PROPN
admet-2772	300	19	)	)	PUNCT
admet-2772	300	20	,	,	PUNCT
admet-2772	300	21	also	also	ADV
admet-2772	300	22	known	know	VERB
admet-2772	300	23	as	as	ADP
admet-2772	300	24	artificial	artificial	ADJ
admet-2772	300	25	neural	neural	ADJ
admet-2772	300	26	networks	network	NOUN
admet-2772	300	27	(	(	PUNCT
admet-2772	300	28	ann	ann	PROPN
admet-2772	300	29	)	)	PUNCT
admet-2772	300	30	named	name	VERB
admet-2772	300	31	after	after	ADP
admet-2772	300	32	its	its	PRON
admet-2772	300	33	artificial	artificial	ADJ
admet-2772	300	34	representation	representation	NOUN
admet-2772	300	35	of	of	ADP
admet-2772	300	36	the	the	DET
admet-2772	300	37	working	working	NOUN
admet-2772	300	38	of	of	ADP
admet-2772	300	39	a	a	DET
admet-2772	300	40	human	human	ADJ
admet-2772	300	41	nervous	nervous	ADJ
admet-2772	300	42	system	system	NOUN
admet-2772	300	43	,	,	PUNCT
admet-2772	300	44	have	have	AUX
admet-2772	300	45	become	become	VERB
admet-2772	300	46	one	one	NUM
admet-2772	300	47	of	of	ADP
admet-2772	300	48	the	the	DET
admet-2772	300	49	most	most	ADV
admet-2772	300	50	successful	successful	ADJ
admet-2772	300	51	techniques	technique	NOUN
admet-2772	300	52	in	in	ADP
admet-2772	300	53	various	various	ADJ
admet-2772	300	54	ai	ai	ADJ
admet-2772	300	55	research	research	NOUN
admet-2772	300	56	areas	area	NOUN
admet-2772	300	57	[	[	X
admet-2772	300	58	126	126	NUM
admet-2772	300	59	]	]	PUNCT
admet-2772	300	60	.	.	PUNCT
admet-2772	301	1	different	different	ADJ
admet-2772	301	2	types	type	NOUN
admet-2772	301	3	of	of	ADP
admet-2772	301	4	machine	machine	NOUN
admet-2772	301	5	learning	learning	NOUN
admet-2772	301	6	models	model	NOUN
admet-2772	301	7	with	with	ADP
admet-2772	301	8	varying	vary	VERB
admet-2772	301	9	degrees	degree	NOUN
admet-2772	301	10	of	of	ADP
admet-2772	301	11	complexity	complexity	NOUN
admet-2772	301	12	can	can	AUX
admet-2772	301	13	predict	predict	VERB
admet-2772	301	14	molecular	molecular	ADJ
admet-2772	301	15	properties	property	NOUN
admet-2772	301	16	,	,	PUNCT
admet-2772	301	17	such	such	ADJ
admet-2772	301	18	as	as	ADP
admet-2772	301	19	similarity	similarity	NOUN
admet-2772	301	20	-	-	PUNCT
admet-2772	301	21	based	base	VERB
admet-2772	301	22	models	model	NOUN
admet-2772	301	23	,	,	PUNCT
admet-2772	301	24	linear	linear	NOUN
admet-2772	301	25	models	model	NOUN
admet-2772	301	26	,	,	PUNCT
admet-2772	301	27	kernel	kernel	NOUN
admet-2772	301	28	-	-	PUNCT
admet-2772	301	29	based	base	VERB
admet-2772	301	30	models	model	NOUN
admet-2772	301	31	,	,	PUNCT
admet-2772	301	32	bayesian	bayesian	NOUN
admet-2772	301	33	models	model	NOUN
admet-2772	301	34	,	,	PUNCT
admet-2772	301	35	treebased	treebased	ADJ
admet-2772	301	36	models	model	NOUN
admet-2772	301	37	,	,	PUNCT
admet-2772	301	38	and	and	CCONJ
admet-2772	301	39	neural	neural	ADJ
admet-2772	301	40	networks	network	NOUN
admet-2772	301	41	.	.	PUNCT
admet-2772	302	1	5.1	5.1	NUM
admet-2772	302	2	.	.	PUNCT
admet-2772	303	1	traditional	traditional	ADJ
admet-2772	303	2	machine	machine	NOUN
admet-2772	303	3	learning	learning	NOUN
admet-2772	303	4	approaches	approach	VERB
admet-2772	303	5	5.1.1	5.1.1	NUM
admet-2772	303	6	.	.	PUNCT
admet-2772	304	1	random	random	ADJ
admet-2772	304	2	forest	forest	NOUN
admet-2772	304	3	random	random	ADJ
admet-2772	304	4	forest	forest	NOUN
admet-2772	304	5	(	(	PUNCT
admet-2772	304	6	rf	rf	NOUN
admet-2772	304	7	)	)	PUNCT
admet-2772	304	8	is	be	AUX
admet-2772	304	9	widely	widely	ADV
admet-2772	304	10	used	use	VERB
admet-2772	304	11	for	for	ADP
admet-2772	304	12	admet	admet	PROPN
admet-2772	304	13	due	due	ADP
admet-2772	304	14	to	to	ADP
admet-2772	304	15	its	its	PRON
admet-2772	304	16	ability	ability	NOUN
admet-2772	304	17	to	to	PART
admet-2772	304	18	handle	handle	VERB
admet-2772	304	19	high	high	ADJ
admet-2772	304	20	-	-	PUNCT
admet-2772	304	21	dimensional	dimensional	ADJ
admet-2772	304	22	data	datum	NOUN
admet-2772	304	23	and	and	CCONJ
admet-2772	304	24	complex	complex	ADJ
admet-2772	304	25	,	,	PUNCT
admet-2772	304	26	non	non	ADJ
admet-2772	304	27	-	-	ADJ
admet-2772	304	28	linear	linear	ADJ
admet-2772	304	29	relationships	relationship	NOUN
admet-2772	304	30	.	.	PUNCT
admet-2772	305	1	random	random	ADJ
admet-2772	305	2	forest	forest	NOUN
admet-2772	305	3	is	be	AUX
admet-2772	305	4	an	an	DET
admet-2772	305	5	ensemble	ensemble	ADJ
admet-2772	305	6	learning	learning	NOUN
admet-2772	305	7	method	method	NOUN
admet-2772	305	8	that	that	PRON
admet-2772	305	9	utilizes	utilize	VERB
admet-2772	305	10	multiple	multiple	ADJ
admet-2772	305	11	decision	decision	NOUN
admet-2772	305	12	trees	tree	NOUN
admet-2772	305	13	to	to	PART
admet-2772	305	14	make	make	VERB
admet-2772	305	15	predictions	prediction	NOUN
admet-2772	305	16	.	.	PUNCT
admet-2772	306	1	it	it	PRON
admet-2772	306	2	operates	operate	VERB
admet-2772	306	3	by	by	ADP
admet-2772	306	4	constructing	construct	VERB
admet-2772	306	5	a	a	DET
admet-2772	306	6	multitude	multitude	NOUN
admet-2772	306	7	of	of	ADP
admet-2772	306	8	decision	decision	NOUN
admet-2772	306	9	trees	tree	NOUN
admet-2772	306	10	during	during	ADP
admet-2772	306	11	training	training	NOUN
admet-2772	306	12	and	and	CCONJ
admet-2772	306	13	outputting	output	VERB
admet-2772	306	14	the	the	DET
admet-2772	306	15	mode	mode	NOUN
admet-2772	306	16	of	of	ADP
admet-2772	306	17	the	the	DET
admet-2772	306	18	classes	class	NOUN
admet-2772	306	19	(	(	PUNCT
admet-2772	306	20	classification	classification	NOUN
admet-2772	306	21	)	)	PUNCT
admet-2772	306	22	or	or	CCONJ
admet-2772	306	23	the	the	DET
admet-2772	306	24	mean	mean	ADJ
admet-2772	306	25	prediction	prediction	NOUN
admet-2772	306	26	(	(	PUNCT
admet-2772	306	27	regression	regression	NOUN
admet-2772	306	28	)	)	PUNCT
admet-2772	306	29	of	of	ADP
admet-2772	306	30	the	the	DET
admet-2772	306	31	individual	individual	ADJ
admet-2772	306	32	trees	tree	NOUN
admet-2772	307	1	[	[	X
admet-2772	307	2	127	127	NUM
admet-2772	307	3	]	]	PUNCT
admet-2772	307	4	.	.	PUNCT
admet-2772	308	1	rf	rf	NOUN
admet-2772	308	2	introduces	introduce	NOUN
admet-2772	308	3	randomness	randomness	VERB
admet-2772	308	4	both	both	PRON
admet-2772	308	5	in	in	ADP
admet-2772	308	6	the	the	DET
admet-2772	308	7	selection	selection	NOUN
admet-2772	308	8	of	of	ADP
admet-2772	308	9	data	datum	NOUN
admet-2772	308	10	points	point	NOUN
admet-2772	308	11	used	use	VERB
admet-2772	308	12	to	to	PART
admet-2772	308	13	build	build	VERB
admet-2772	308	14	each	each	DET
admet-2772	308	15	tree	tree	NOUN
admet-2772	308	16	and	and	CCONJ
admet-2772	308	17	in	in	ADP
admet-2772	308	18	the	the	DET
admet-2772	308	19	selection	selection	NOUN
admet-2772	308	20	of	of	ADP
admet-2772	308	21	features	feature	NOUN
admet-2772	308	22	used	use	VERB
admet-2772	308	23	at	at	ADP
admet-2772	308	24	each	each	DET
admet-2772	308	25	split	split	ADJ
admet-2772	308	26	point	point	NOUN
admet-2772	308	27	.	.	PUNCT
admet-2772	309	1	this	this	DET
admet-2772	309	2	randomness	randomness	NOUN
admet-2772	309	3	helps	help	VERB
admet-2772	309	4	to	to	PART
admet-2772	309	5	decorrelate	decorrelate	VERB
admet-2772	309	6	the	the	DET
admet-2772	309	7	trees	tree	NOUN
admet-2772	309	8	,	,	PUNCT
admet-2772	309	9	making	make	VERB
admet-2772	309	10	the	the	DET
admet-2772	309	11	ensemble	ensemble	ADJ
admet-2772	309	12	more	more	ADV
admet-2772	309	13	robust	robust	ADJ
admet-2772	309	14	and	and	CCONJ
admet-2772	309	15	less	less	ADV
admet-2772	309	16	prone	prone	ADJ
admet-2772	309	17	to	to	ADP
admet-2772	309	18	overfitting	overfitte	VERB
admet-2772	309	19	[	[	X
admet-2772	309	20	128	128	NUM
admet-2772	309	21	]	]	PUNCT
admet-2772	309	22	.	.	PUNCT
admet-2772	310	1	it	it	PRON
admet-2772	310	2	has	have	AUX
admet-2772	310	3	been	be	AUX
admet-2772	310	4	used	use	VERB
admet-2772	310	5	to	to	PART
admet-2772	310	6	predict	predict	VERB
admet-2772	310	7	toxicity	toxicity	NOUN
admet-2772	310	8	endpoints	endpoint	NOUN
admet-2772	310	9	[	[	X
admet-2772	310	10	109	109	NUM
admet-2772	310	11	]	]	PUNCT
admet-2772	310	12	,	,	PUNCT
admet-2772	310	13	metabolic	metabolic	NOUN
admet-2772	310	14	stability	stability	NOUN
admet-2772	310	15	[	[	X
admet-2772	310	16	84	84	NUM
admet-2772	310	17	]	]	PUNCT
admet-2772	310	18	,	,	PUNCT
admet-2772	310	19	and	and	CCONJ
admet-2772	310	20	solubility	solubility	NOUN
admet-2772	310	21	[	[	X
admet-2772	310	22	129	129	NUM
admet-2772	310	23	]	]	PUNCT
admet-2772	310	24	.	.	PUNCT
admet-2772	311	1	rf	rf	PRON
admet-2772	311	2	has	have	AUX
admet-2772	311	3	emerged	emerge	VERB
admet-2772	311	4	as	as	ADP
admet-2772	311	5	a	a	DET
admet-2772	311	6	powerful	powerful	ADJ
admet-2772	311	7	machine	machine	NOUN
admet-2772	311	8	learning	learning	NOUN
admet-2772	311	9	technique	technique	NOUN
admet-2772	311	10	for	for	ADP
admet-2772	311	11	predicting	predict	VERB
admet-2772	311	12	absorption	absorption	NOUN
admet-2772	311	13	,	,	PUNCT
admet-2772	311	14	distribution	distribution	NOUN
admet-2772	311	15	,	,	PUNCT
admet-2772	311	16	metabolism	metabolism	NOUN
admet-2772	311	17	,	,	PUNCT
admet-2772	311	18	excretion	excretion	NOUN
admet-2772	311	19	,	,	PUNCT
admet-2772	311	20	and	and	CCONJ
admet-2772	311	21	toxicity	toxicity	NOUN
admet-2772	311	22	(	(	PUNCT
admet-2772	311	23	admet	admet	ADJ
admet-2772	311	24	)	)	PUNCT
admet-2772	311	25	properties	property	NOUN
admet-2772	311	26	of	of	ADP
admet-2772	311	27	compounds	compound	NOUN
admet-2772	311	28	.	.	PUNCT
admet-2772	312	1	rf	rf	NOUN
admet-2772	312	2	models	model	NOUN
admet-2772	312	3	have	have	AUX
admet-2772	312	4	been	be	AUX
admet-2772	312	5	successfully	successfully	ADV
admet-2772	312	6	applied	apply	VERB
admet-2772	312	7	to	to	PART
admet-2772	312	8	classify	classify	VERB
admet-2772	312	9	toxicity	toxicity	NOUN
admet-2772	312	10	datasets	dataset	NOUN
admet-2772	312	11	[	[	X
admet-2772	312	12	130	130	NUM
admet-2772	312	13	]	]	PUNCT
admet-2772	312	14	and	and	CCONJ
admet-2772	312	15	predict	predict	VERB
admet-2772	312	16	maximum	maximum	ADJ
admet-2772	312	17	recommended	recommend	VERB
admet-2772	312	18	daily	daily	ADJ
admet-2772	312	19	pharmaceutical	pharmaceutical	ADJ
admet-2772	312	20	doses	dose	NOUN
admet-2772	313	1	[	[	X
admet-2772	313	2	131	131	NUM
admet-2772	313	3	]	]	PUNCT
admet-2772	313	4	.	.	PUNCT
admet-2772	314	1	these	these	DET
admet-2772	314	2	models	model	NOUN
admet-2772	314	3	utilize	utilize	VERB
admet-2772	314	4	substructure	substructure	NOUN
admet-2772	314	5	fingerprints	fingerprint	NOUN
admet-2772	314	6	as	as	ADP
admet-2772	314	7	descriptors	descriptor	NOUN
admet-2772	314	8	,	,	PUNCT
admet-2772	314	9	which	which	PRON
admet-2772	314	10	encode	encode	VERB
admet-2772	314	11	the	the	DET
admet-2772	314	12	presence	presence	NOUN
admet-2772	314	13	or	or	CCONJ
admet-2772	314	14	absence	absence	NOUN
admet-2772	314	15	of	of	ADP
admet-2772	314	16	specific	specific	ADJ
admet-2772	314	17	molecular	molecular	ADJ
admet-2772	314	18	substructures	substructure	NOUN
admet-2772	314	19	.	.	PUNCT
admet-2772	315	1	rf	rf	NOUN
admet-2772	315	2	's	's	PART
admet-2772	315	3	ability	ability	NOUN
admet-2772	315	4	to	to	PART
admet-2772	315	5	identify	identify	VERB
admet-2772	315	6	important	important	ADJ
admet-2772	315	7	substructure	substructure	NOUN
admet-2772	315	8	features	feature	NOUN
admet-2772	315	9	provides	provide	VERB
admet-2772	315	10	insights	insight	NOUN
admet-2772	315	11	into	into	ADP
admet-2772	315	12	structure	structure	NOUN
admet-2772	315	13	-	-	PUNCT
admet-2772	315	14	toxicity	toxicity	NOUN
admet-2772	315	15	relationships	relationship	NOUN
admet-2772	315	16	[	[	X
admet-2772	315	17	130	130	NUM
admet-2772	315	18	]	]	PUNCT
admet-2772	315	19	.	.	PUNCT
admet-2772	316	1	the	the	DET
admet-2772	316	2	predictive	predictive	ADJ
admet-2772	316	3	performance	performance	NOUN
admet-2772	316	4	of	of	ADP
admet-2772	316	5	rf	rf	NOUN
admet-2772	316	6	models	model	NOUN
admet-2772	316	7	can	can	AUX
admet-2772	316	8	be	be	AUX
admet-2772	316	9	further	far	ADV
admet-2772	316	10	improved	improve	VERB
admet-2772	316	11	through	through	ADP
admet-2772	316	12	rigorous	rigorous	ADJ
admet-2772	316	13	model	model	NOUN
admet-2772	316	14	selection	selection	NOUN
admet-2772	316	15	processes	process	NOUN
admet-2772	316	16	,	,	PUNCT
admet-2772	316	17	as	as	SCONJ
admet-2772	316	18	demonstrated	demonstrate	VERB
admet-2772	316	19	in	in	ADP
admet-2772	316	20	the	the	DET
admet-2772	316	21	tox21	tox21	PROPN
admet-2772	316	22	challenge	challenge	NOUN
admet-2772	316	23	[	[	X
admet-2772	316	24	132	132	NUM
admet-2772	316	25	]	]	PUNCT
admet-2772	316	26	.	.	PUNCT
admet-2772	317	1	rf	rf	PRON
admet-2772	317	2	has	have	AUX
admet-2772	317	3	also	also	ADV
admet-2772	317	4	been	be	AUX
admet-2772	317	5	employed	employ	VERB
admet-2772	317	6	in	in	ADP
admet-2772	317	7	computational	computational	ADJ
admet-2772	317	8	studies	study	NOUN
admet-2772	317	9	to	to	PART
admet-2772	317	10	evaluate	evaluate	VERB
admet-2772	317	11	admet	admet	NOUN
admet-2772	317	12	properties	property	NOUN
admet-2772	317	13	of	of	ADP
admet-2772	317	14	natural	natural	ADJ
admet-2772	317	15	products	product	NOUN
admet-2772	317	16	,	,	PUNCT
admet-2772	317	17	such	such	ADJ
admet-2772	317	18	as	as	ADP
admet-2772	317	19	papua	papua	PROPN
admet-2772	317	20	red	red	ADJ
admet-2772	317	21	fruit	fruit	NOUN
admet-2772	317	22	flavonoids	flavonoid	NOUN
admet-2772	317	23	,	,	PUNCT
admet-2772	317	24	aiding	aid	VERB
admet-2772	317	25	in	in	ADP
admet-2772	317	26	the	the	DET
admet-2772	317	27	assessment	assessment	NOUN
admet-2772	317	28	of	of	ADP
admet-2772	317	29	their	their	PRON
admet-2772	317	30	potential	potential	NOUN
admet-2772	317	31	as	as	ADP
admet-2772	317	32	bioactive	bioactive	ADJ
admet-2772	317	33	compounds	compound	NOUN
admet-2772	317	34	in	in	ADP
admet-2772	317	35	functional	functional	ADJ
admet-2772	317	36	foods	food	NOUN
admet-2772	317	37	[	[	X
admet-2772	317	38	133	133	NUM
admet-2772	317	39	]	]	PUNCT
admet-2772	317	40	.	.	PUNCT
admet-2772	318	1	these	these	DET
admet-2772	318	2	applications	application	NOUN
admet-2772	318	3	highlight	highlight	VERB
admet-2772	318	4	rf	rf	NOUN
admet-2772	318	5	's	's	PART
admet-2772	318	6	versatility	versatility	NOUN
admet-2772	318	7	and	and	CCONJ
admet-2772	318	8	effectiveness	effectiveness	NOUN
admet-2772	318	9	in	in	ADP
admet-2772	318	10	admet	admet	PROPN
admet-2772	318	11	prediction	prediction	NOUN
admet-2772	318	12	and	and	CCONJ
admet-2772	318	13	toxicity	toxicity	NOUN
admet-2772	318	14	evaluation	evaluation	NOUN
admet-2772	318	15	.	.	PUNCT
admet-2772	319	1	admet	admet	PROPN
admet-2772	319	2	&	&	CCONJ
admet-2772	319	3	dmpk	dmpk	PROPN
admet-2772	319	4	13(3	13(3	NUM
admet-2772	319	5	)	)	PUNCT
admet-2772	319	6	(	(	PUNCT
admet-2772	319	7	2025	2025	NUM
admet-2772	319	8	)	)	PUNCT
admet-2772	319	9	2772	2772	NUM
admet-2772	319	10	machine	machine	NOUN
admet-2772	319	11	learning	learning	NOUN
admet-2772	319	12	models	model	NOUN
admet-2772	319	13	for	for	ADP
admet-2772	319	14	admet	admet	ADJ
admet-2772	319	15	prediction	prediction	NOUN
admet-2772	319	16	in	in	ADP
admet-2772	319	17	drug	drug	NOUN
admet-2772	319	18	development	development	NOUN
admet-2772	319	19	doi	doi	PROPN
admet-2772	319	20	:	:	PUNCT
admet-2772	319	21	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	319	22	13	13	NUM
admet-2772	319	23	5.1.2	5.1.2	NUM
admet-2772	319	24	.	.	PUNCT
admet-2772	320	1	support	support	NOUN
admet-2772	320	2	vector	vector	NOUN
admet-2772	320	3	machines	machine	NOUN
admet-2772	320	4	support	support	VERB
admet-2772	320	5	vector	vector	NOUN
admet-2772	320	6	machines	machine	NOUN
admet-2772	320	7	(	(	PUNCT
admet-2772	320	8	svms	svms	NOUN
admet-2772	320	9	)	)	PUNCT
admet-2772	320	10	are	be	AUX
admet-2772	320	11	effective	effective	ADJ
admet-2772	320	12	for	for	ADP
admet-2772	320	13	binary	binary	ADJ
admet-2772	320	14	classification	classification	NOUN
admet-2772	320	15	tasks	task	NOUN
admet-2772	320	16	in	in	ADP
admet-2772	320	17	admet	admet	PROPN
admet-2772	320	18	modelling	modelling	PROPN
admet-2772	320	19	,	,	PUNCT
admet-2772	320	20	especially	especially	ADV
admet-2772	320	21	for	for	ADP
admet-2772	320	22	toxicology	toxicology	NOUN
admet-2772	320	23	studies	study	NOUN
admet-2772	320	24	(	(	PUNCT
admet-2772	320	25	like	like	ADP
admet-2772	320	26	classifying	classify	VERB
admet-2772	320	27	compounds	compound	NOUN
admet-2772	320	28	as	as	ADP
admet-2772	320	29	toxic	toxic	ADJ
admet-2772	320	30	or	or	CCONJ
admet-2772	320	31	non	non	ADJ
admet-2772	320	32	-	-	ADJ
admet-2772	320	33	toxic	toxic	ADJ
admet-2772	320	34	)	)	PUNCT
admet-2772	320	35	.	.	PUNCT
admet-2772	321	1	svms	svms	NOUN
admet-2772	321	2	have	have	AUX
admet-2772	321	3	emerged	emerge	VERB
admet-2772	321	4	as	as	ADP
admet-2772	321	5	a	a	DET
admet-2772	321	6	powerful	powerful	ADJ
admet-2772	321	7	tool	tool	NOUN
admet-2772	321	8	in	in	ADP
admet-2772	321	9	predicting	predict	VERB
admet-2772	321	10	admet	admet	NOUN
admet-2772	321	11	properties	property	NOUN
admet-2772	321	12	in	in	ADP
admet-2772	321	13	drug	drug	NOUN
admet-2772	321	14	discovery	discovery	NOUN
admet-2772	321	15	.	.	PUNCT
admet-2772	322	1	it	it	PRON
admet-2772	322	2	works	work	VERB
admet-2772	322	3	by	by	ADP
admet-2772	322	4	finding	find	VERB
admet-2772	322	5	the	the	DET
admet-2772	322	6	optimal	optimal	ADJ
admet-2772	322	7	hyperplane	hyperplane	NOUN
admet-2772	322	8	that	that	PRON
admet-2772	322	9	best	well	ADV
admet-2772	322	10	separates	separate	VERB
admet-2772	322	11	different	different	ADJ
admet-2772	322	12	classes	class	NOUN
admet-2772	322	13	or	or	CCONJ
admet-2772	322	14	predicts	predict	VERB
admet-2772	322	15	the	the	DET
admet-2772	322	16	continuous	continuous	ADJ
admet-2772	322	17	target	target	NOUN
admet-2772	322	18	variable	variable	NOUN
admet-2772	322	19	by	by	ADP
admet-2772	322	20	maximizing	maximize	VERB
admet-2772	322	21	the	the	DET
admet-2772	322	22	margin	margin	NOUN
admet-2772	322	23	between	between	ADP
admet-2772	322	24	the	the	DET
admet-2772	322	25	classes	class	NOUN
admet-2772	322	26	[	[	X
admet-2772	322	27	121	121	NUM
admet-2772	322	28	]	]	PUNCT
admet-2772	322	29	.	.	PUNCT
admet-2772	323	1	svms	svms	NOUN
admet-2772	323	2	can	can	AUX
admet-2772	323	3	handle	handle	VERB
admet-2772	323	4	both	both	CCONJ
admet-2772	323	5	linear	linear	ADJ
admet-2772	323	6	and	and	CCONJ
admet-2772	323	7	nonlinear	nonlinear	ADJ
admet-2772	323	8	data	datum	NOUN
admet-2772	323	9	by	by	ADP
admet-2772	323	10	using	use	VERB
admet-2772	323	11	appropriate	appropriate	ADJ
admet-2772	323	12	kernel	kernel	NOUN
admet-2772	323	13	functions	function	NOUN
admet-2772	323	14	.	.	PUNCT
admet-2772	324	1	svm	svm	PROPN
admet-2772	324	2	can	can	AUX
admet-2772	324	3	be	be	AUX
admet-2772	324	4	extended	extend	VERB
admet-2772	324	5	to	to	PART
admet-2772	324	6	handle	handle	VERB
admet-2772	324	7	nonlinear	nonlinear	ADJ
admet-2772	324	8	data	datum	NOUN
admet-2772	324	9	by	by	ADP
admet-2772	324	10	mapping	map	VERB
admet-2772	324	11	the	the	DET
admet-2772	324	12	input	input	NOUN
admet-2772	324	13	features	feature	VERB
admet-2772	324	14	into	into	ADP
admet-2772	324	15	a	a	DET
admet-2772	324	16	higherdimensional	higherdimensional	ADJ
admet-2772	324	17	space	space	NOUN
admet-2772	324	18	using	use	VERB
admet-2772	324	19	a	a	DET
admet-2772	324	20	kernel	kernel	NOUN
admet-2772	324	21	function	function	NOUN
admet-2772	324	22	[	[	X
admet-2772	324	23	134	134	NUM
admet-2772	324	24	]	]	PUNCT
admet-2772	324	25	.	.	PUNCT
admet-2772	325	1	the	the	DET
admet-2772	325	2	kernel	kernel	PROPN
admet-2772	325	3	function	function	PROPN
admet-2772	325	4	computes	compute	VERB
admet-2772	325	5	the	the	DET
admet-2772	325	6	dot	dot	NOUN
admet-2772	325	7	product	product	NOUN
admet-2772	325	8	between	between	ADP
admet-2772	325	9	the	the	DET
admet-2772	325	10	feature	feature	NOUN
admet-2772	325	11	vectors	vector	NOUN
admet-2772	325	12	in	in	ADP
admet-2772	325	13	the	the	DET
admet-2772	325	14	higher	higher	ADV
admet-2772	325	15	-	-	PUNCT
admet-2772	325	16	dimensional	dimensional	ADJ
admet-2772	325	17	space	space	NOUN
admet-2772	325	18	without	without	ADP
admet-2772	325	19	explicitly	explicitly	ADV
admet-2772	325	20	transforming	transform	VERB
admet-2772	325	21	the	the	DET
admet-2772	325	22	data	datum	NOUN
admet-2772	325	23	.	.	PUNCT
admet-2772	326	1	common	common	ADJ
admet-2772	326	2	kernel	kernel	NOUN
admet-2772	326	3	functions	function	NOUN
admet-2772	326	4	include	include	VERB
admet-2772	326	5	linear	linear	PROPN
admet-2772	326	6	,	,	PUNCT
admet-2772	326	7	polynomial	polynomial	ADJ
admet-2772	326	8	,	,	PUNCT
admet-2772	326	9	radial	radial	ADJ
admet-2772	326	10	basis	basis	NOUN
admet-2772	326	11	function	function	NOUN
admet-2772	326	12	(	(	PUNCT
admet-2772	326	13	rbf	rbf	PROPN
admet-2772	326	14	)	)	PUNCT
admet-2772	326	15	,	,	PUNCT
admet-2772	326	16	and	and	CCONJ
admet-2772	326	17	sigmoid	sigmoid	NOUN
admet-2772	326	18	kernels	kernel	NOUN
admet-2772	326	19	,	,	PUNCT
admet-2772	326	20	which	which	PRON
admet-2772	326	21	allow	allow	VERB
admet-2772	326	22	svm	svm	PROPN
admet-2772	326	23	to	to	PART
admet-2772	326	24	capture	capture	VERB
admet-2772	326	25	complex	complex	ADJ
admet-2772	326	26	nonlinear	nonlinear	ADJ
admet-2772	326	27	relationships	relationship	NOUN
admet-2772	326	28	in	in	ADP
admet-2772	326	29	the	the	DET
admet-2772	326	30	data	datum	NOUN
admet-2772	326	31	.	.	PUNCT
admet-2772	327	1	svms	svms	NOUN
admet-2772	327	2	,	,	PUNCT
admet-2772	327	3	along	along	ADP
admet-2772	327	4	with	with	ADP
admet-2772	327	5	other	other	ADJ
admet-2772	327	6	machine	machine	NOUN
admet-2772	327	7	learning	learn	VERB
admet-2772	327	8	techniques	technique	NOUN
admet-2772	327	9	like	like	ADP
admet-2772	327	10	random	random	ADJ
admet-2772	327	11	forests	forest	NOUN
admet-2772	327	12	and	and	CCONJ
admet-2772	327	13	decision	decision	NOUN
admet-2772	327	14	trees	tree	NOUN
admet-2772	327	15	,	,	PUNCT
admet-2772	327	16	have	have	AUX
admet-2772	327	17	become	become	VERB
admet-2772	327	18	dominant	dominant	ADJ
admet-2772	327	19	methods	method	NOUN
admet-2772	327	20	in	in	ADP
admet-2772	327	21	predictive	predictive	ADJ
admet-2772	327	22	toxicology	toxicology	NOUN
admet-2772	327	23	due	due	ADP
admet-2772	327	24	to	to	ADP
admet-2772	327	25	their	their	PRON
admet-2772	327	26	ability	ability	NOUN
admet-2772	327	27	to	to	PART
admet-2772	327	28	handle	handle	VERB
admet-2772	327	29	complex	complex	ADJ
admet-2772	327	30	datasets	dataset	NOUN
admet-2772	327	31	[	[	X
admet-2772	327	32	121	121	NUM
admet-2772	327	33	]	]	PUNCT
admet-2772	327	34	.	.	PUNCT
admet-2772	328	1	studies	study	NOUN
admet-2772	328	2	have	have	AUX
admet-2772	328	3	shown	show	VERB
admet-2772	328	4	that	that	DET
admet-2772	328	5	svms	svms	NOUN
admet-2772	328	6	can	can	AUX
admet-2772	328	7	accurately	accurately	ADV
admet-2772	328	8	classify	classify	VERB
admet-2772	328	9	compounds	compound	NOUN
admet-2772	328	10	based	base	VERB
admet-2772	328	11	on	on	ADP
admet-2772	328	12	human	human	ADJ
admet-2772	328	13	intestinal	intestinal	ADJ
admet-2772	328	14	absorption	absorption	NOUN
admet-2772	328	15	,	,	PUNCT
admet-2772	328	16	using	use	VERB
admet-2772	328	17	molecular	molecular	ADJ
admet-2772	328	18	descriptors	descriptor	NOUN
admet-2772	328	19	such	such	ADJ
admet-2772	328	20	as	as	ADP
admet-2772	328	21	topological	topological	ADJ
admet-2772	328	22	polar	polar	ADJ
admet-2772	328	23	surface	surface	NOUN
admet-2772	328	24	area	area	NOUN
admet-2772	328	25	and	and	CCONJ
admet-2772	328	26	predicted	predict	VERB
admet-2772	328	27	octanol	octanol	NOUN
admet-2772	328	28	-	-	PUNCT
admet-2772	328	29	water	water	NOUN
admet-2772	328	30	distribution	distribution	NOUN
admet-2772	328	31	coefficient	coefficient	NOUN
admet-2772	328	32	.	.	PUNCT
admet-2772	329	1	svms	svms	NOUN
admet-2772	329	2	have	have	AUX
admet-2772	329	3	demonstrated	demonstrate	VERB
admet-2772	329	4	competitive	competitive	ADJ
admet-2772	329	5	performance	performance	NOUN
admet-2772	329	6	compared	compare	VERB
admet-2772	329	7	to	to	ADP
admet-2772	329	8	other	other	ADJ
admet-2772	329	9	state	state	NOUN
admet-2772	329	10	-	-	PUNCT
admet-2772	329	11	of	of	ADP
admet-2772	329	12	-	-	PUNCT
admet-2772	329	13	the	the	DET
admet-2772	329	14	-	-	PUNCT
admet-2772	329	15	art	art	NOUN
admet-2772	329	16	techniques	technique	NOUN
admet-2772	329	17	in	in	ADP
admet-2772	329	18	pharmaceutical	pharmaceutical	ADJ
admet-2772	329	19	classification	classification	NOUN
admet-2772	329	20	tasks	task	NOUN
admet-2772	329	21	[	[	X
admet-2772	329	22	135	135	NUM
admet-2772	329	23	]	]	PUNCT
admet-2772	329	24	.	.	PUNCT
admet-2772	330	1	however	however	ADV
admet-2772	330	2	,	,	PUNCT
admet-2772	330	3	challenges	challenge	NOUN
admet-2772	330	4	remain	remain	VERB
admet-2772	330	5	in	in	ADP
admet-2772	330	6	fully	fully	ADV
admet-2772	330	7	integrating	integrate	VERB
admet-2772	330	8	predictive	predictive	ADJ
admet-2772	330	9	admet	admet	NOUN
admet-2772	330	10	modelling	modelling	NOUN
admet-2772	330	11	into	into	ADP
admet-2772	330	12	drug	drug	NOUN
admet-2772	330	13	discovery	discovery	NOUN
admet-2772	330	14	processes	process	NOUN
admet-2772	330	15	,	,	PUNCT
admet-2772	330	16	and	and	CCONJ
admet-2772	330	17	there	there	PRON
admet-2772	330	18	is	be	VERB
admet-2772	330	19	a	a	DET
admet-2772	330	20	need	need	NOUN
admet-2772	330	21	for	for	ADP
admet-2772	330	22	larger	large	ADJ
admet-2772	330	23	,	,	PUNCT
admet-2772	330	24	high	high	ADJ
admet-2772	330	25	-	-	PUNCT
admet-2772	330	26	quality	quality	NOUN
admet-2772	330	27	datasets	dataset	NOUN
admet-2772	330	28	and	and	CCONJ
admet-2772	330	29	improved	improve	VERB
admet-2772	330	30	molecular	molecular	ADJ
admet-2772	330	31	descriptors	descriptor	NOUN
admet-2772	330	32	to	to	PART
admet-2772	330	33	fully	fully	ADV
admet-2772	330	34	realize	realize	VERB
admet-2772	330	35	the	the	DET
admet-2772	330	36	potential	potential	NOUN
admet-2772	330	37	of	of	ADP
admet-2772	330	38	machine	machine	NOUN
admet-2772	330	39	learning	learn	VERB
admet-2772	330	40	techniques	technique	NOUN
admet-2772	330	41	in	in	ADP
admet-2772	330	42	this	this	DET
admet-2772	330	43	field	field	NOUN
admet-2772	331	1	[	[	X
admet-2772	331	2	136	136	NUM
admet-2772	331	3	]	]	PUNCT
admet-2772	331	4	.	.	PUNCT
admet-2772	332	1	5.1.3	5.1.3	NUM
admet-2772	332	2	.	.	PUNCT
admet-2772	333	1	k	k	X
admet-2772	333	2	-	-	PUNCT
admet-2772	333	3	nearest	near	ADJ
admet-2772	333	4	neighbours	neighbour	NOUN
admet-2772	333	5	the	the	DET
admet-2772	333	6	k	k	NOUN
admet-2772	333	7	-	-	PUNCT
admet-2772	333	8	nearest	near	ADJ
admet-2772	333	9	neighbours	neighbour	NOUN
admet-2772	333	10	(	(	PUNCT
admet-2772	333	11	k	k	NOUN
admet-2772	333	12	-	-	PUNCT
admet-2772	333	13	nn	nn	NOUN
admet-2772	333	14	)	)	PUNCT
admet-2772	333	15	algorithm	algorithm	NOUN
admet-2772	333	16	has	have	AUX
admet-2772	333	17	shown	show	VERB
admet-2772	333	18	promise	promise	NOUN
admet-2772	333	19	in	in	ADP
admet-2772	333	20	predicting	predict	VERB
admet-2772	333	21	various	various	ADJ
admet-2772	333	22	aspects	aspect	NOUN
admet-2772	333	23	of	of	ADP
admet-2772	333	24	absorption	absorption	NOUN
admet-2772	333	25	,	,	PUNCT
admet-2772	333	26	distribution	distribution	NOUN
admet-2772	333	27	,	,	PUNCT
admet-2772	333	28	metabolism	metabolism	NOUN
admet-2772	333	29	,	,	PUNCT
admet-2772	333	30	excretion	excretion	NOUN
admet-2772	333	31	,	,	PUNCT
admet-2772	333	32	and	and	CCONJ
admet-2772	333	33	toxicity	toxicity	NOUN
admet-2772	333	34	(	(	PUNCT
admet-2772	333	35	admet	admet	ADJ
admet-2772	333	36	)	)	PUNCT
admet-2772	333	37	properties	property	NOUN
admet-2772	333	38	of	of	ADP
admet-2772	333	39	chemicals	chemical	NOUN
admet-2772	333	40	.	.	PUNCT
admet-2772	334	1	k	k	X
admet-2772	334	2	-	-	PUNCT
admet-2772	334	3	nearest	near	ADJ
admet-2772	334	4	neighbour	neighbour	NOUN
admet-2772	334	5	is	be	AUX
admet-2772	334	6	a	a	DET
admet-2772	334	7	simple	simple	ADJ
admet-2772	334	8	and	and	CCONJ
admet-2772	334	9	intuitive	intuitive	ADJ
admet-2772	334	10	supervised	supervised	ADJ
admet-2772	334	11	learning	learning	NOUN
admet-2772	334	12	method	method	NOUN
admet-2772	334	13	used	use	VERB
admet-2772	334	14	for	for	ADP
admet-2772	334	15	classification	classification	NOUN
admet-2772	334	16	and	and	CCONJ
admet-2772	334	17	regression	regression	NOUN
admet-2772	334	18	tasks	task	NOUN
admet-2772	334	19	.	.	PUNCT
admet-2772	335	1	it	it	PRON
admet-2772	335	2	operates	operate	VERB
admet-2772	335	3	on	on	ADP
admet-2772	335	4	the	the	DET
admet-2772	335	5	principle	principle	NOUN
admet-2772	335	6	that	that	SCONJ
admet-2772	335	7	objects	object	VERB
admet-2772	335	8	(	(	PUNCT
admet-2772	335	9	e.g.	e.g.	ADV
admet-2772	335	10	data	data	NOUN
admet-2772	335	11	points	point	NOUN
admet-2772	335	12	)	)	PUNCT
admet-2772	335	13	with	with	ADP
admet-2772	335	14	similar	similar	ADJ
admet-2772	335	15	characteristics	characteristic	NOUN
admet-2772	335	16	are	be	AUX
admet-2772	335	17	often	often	ADV
admet-2772	335	18	found	find	VERB
admet-2772	335	19	near	near	ADP
admet-2772	335	20	each	each	DET
admet-2772	335	21	other	other	ADJ
admet-2772	335	22	in	in	ADP
admet-2772	335	23	the	the	DET
admet-2772	335	24	feature	feature	NOUN
admet-2772	335	25	space	space	NOUN
admet-2772	335	26	.	.	PUNCT
admet-2772	336	1	the	the	DET
admet-2772	336	2	k	k	PROPN
admet-2772	336	3	-	-	PUNCT
admet-2772	336	4	nn	nn	PROPN
admet-2772	336	5	algorithm	algorithm	NOUN
admet-2772	336	6	classifies	classify	VERB
admet-2772	336	7	or	or	CCONJ
admet-2772	336	8	predicts	predict	VERB
admet-2772	336	9	the	the	DET
admet-2772	336	10	label	label	NOUN
admet-2772	336	11	of	of	ADP
admet-2772	336	12	a	a	DET
admet-2772	336	13	new	new	ADJ
admet-2772	336	14	data	data	NOUN
admet-2772	336	15	point	point	NOUN
admet-2772	336	16	by	by	ADP
admet-2772	336	17	considering	consider	VERB
admet-2772	336	18	the	the	DET
admet-2772	336	19	labels	label	NOUN
admet-2772	336	20	of	of	ADP
admet-2772	336	21	its	its	PRON
admet-2772	336	22	k	k	ADV
admet-2772	336	23	-	-	PUNCT
admet-2772	336	24	nearest	near	ADJ
admet-2772	336	25	neighbours	neighbour	NOUN
admet-2772	336	26	,	,	PUNCT
admet-2772	336	27	where	where	SCONJ
admet-2772	336	28	k	k	PROPN
admet-2772	336	29	is	be	AUX
admet-2772	336	30	a	a	DET
admet-2772	336	31	user	user	NOUN
admet-2772	336	32	-	-	PUNCT
admet-2772	336	33	defined	define	VERB
admet-2772	336	34	parameter	parameter	NOUN
admet-2772	336	35	[	[	X
admet-2772	336	36	137	137	NUM
admet-2772	336	37	]	]	PUNCT
admet-2772	336	38	.	.	PUNCT
admet-2772	337	1	studies	study	NOUN
admet-2772	337	2	have	have	AUX
admet-2772	337	3	demonstrated	demonstrate	VERB
admet-2772	337	4	its	its	PRON
admet-2772	337	5	effectiveness	effectiveness	NOUN
admet-2772	337	6	in	in	ADP
admet-2772	337	7	predicting	predict	VERB
admet-2772	337	8	sub	sub	ADJ
admet-2772	337	9	-	-	ADJ
admet-2772	337	10	chronic	chronic	ADJ
admet-2772	337	11	oral	oral	ADJ
admet-2772	337	12	toxicity	toxicity	NOUN
admet-2772	337	13	in	in	ADP
admet-2772	337	14	rats	rat	NOUN
admet-2772	337	15	[	[	X
admet-2772	337	16	138	138	NUM
admet-2772	337	17	]	]	PUNCT
admet-2772	337	18	,	,	PUNCT
admet-2772	337	19	acute	acute	ADJ
admet-2772	337	20	contact	contact	NOUN
admet-2772	337	21	toxicity	toxicity	NOUN
admet-2772	337	22	of	of	ADP
admet-2772	337	23	pesticides	pesticide	NOUN
admet-2772	337	24	in	in	ADP
admet-2772	337	25	honeybees	honeybee	NOUN
admet-2772	337	26	[	[	X
admet-2772	337	27	139	139	NUM
admet-2772	337	28	]	]	PUNCT
admet-2772	337	29	,	,	PUNCT
admet-2772	337	30	and	and	CCONJ
admet-2772	337	31	chronic	chronic	ADJ
admet-2772	337	32	toxicity	toxicity	NOUN
admet-2772	337	33	based	base	VERB
admet-2772	337	34	on	on	ADP
admet-2772	337	35	acute	acute	ADJ
admet-2772	337	36	toxicity	toxicity	NOUN
admet-2772	337	37	data	datum	NOUN
admet-2772	337	38	[	[	X
admet-2772	337	39	140	140	NUM
admet-2772	337	40	]	]	PUNCT
admet-2772	337	41	.	.	PUNCT
admet-2772	338	1	these	these	DET
admet-2772	338	2	k	k	PROPN
admet-2772	338	3	-	-	PUNCT
admet-2772	338	4	nn	nn	ADJ
admet-2772	338	5	models	model	NOUN
admet-2772	338	6	have	have	AUX
admet-2772	338	7	achieved	achieve	VERB
admet-2772	338	8	reasonnable	reasonnable	ADJ
admet-2772	338	9	accuracy	accuracy	NOUN
admet-2772	338	10	,	,	PUNCT
admet-2772	338	11	with	with	ADP
admet-2772	338	12	external	external	ADJ
admet-2772	338	13	validation	validation	NOUN
admet-2772	338	14	results	result	NOUN
admet-2772	338	15	ranging	range	VERB
admet-2772	338	16	from	from	ADP
admet-2772	338	17	65	65	NUM
admet-2772	338	18	to	to	PART
admet-2772	338	19	77	77	NUM
admet-2772	338	20	%	%	NOUN
admet-2772	338	21	for	for	ADP
admet-2772	338	22	different	different	ADJ
admet-2772	338	23	endpoints	endpoint	NOUN
admet-2772	338	24	.	.	PUNCT
admet-2772	339	1	the	the	DET
admet-2772	339	2	approach	approach	NOUN
admet-2772	339	3	has	have	AUX
admet-2772	339	4	been	be	AUX
admet-2772	339	5	valuable	valuable	ADJ
admet-2772	339	6	in	in	ADP
admet-2772	339	7	prioritizing	prioritize	VERB
admet-2772	339	8	chemical	chemical	NOUN
admet-2772	339	9	safety	safety	NOUN
admet-2772	339	10	assessments	assessment	NOUN
admet-2772	339	11	and	and	CCONJ
admet-2772	339	12	potentially	potentially	ADV
admet-2772	339	13	reducing	reduce	VERB
admet-2772	339	14	animal	animal	NOUN
admet-2772	339	15	testing	testing	NOUN
admet-2772	339	16	[	[	X
admet-2772	339	17	139	139	NUM
admet-2772	339	18	]	]	PUNCT
admet-2772	339	19	.	.	PUNCT
admet-2772	340	1	incorporating	incorporate	VERB
admet-2772	340	2	admet	admet	NOUN
admet-2772	340	3	screening	screening	NOUN
admet-2772	340	4	earlier	early	ADV
admet-2772	340	5	in	in	ADP
admet-2772	340	6	the	the	DET
admet-2772	340	7	drug	drug	NOUN
admet-2772	340	8	discovery	discovery	NOUN
admet-2772	340	9	process	process	NOUN
admet-2772	340	10	has	have	AUX
admet-2772	340	11	become	become	VERB
admet-2772	340	12	crucial	crucial	ADJ
admet-2772	340	13	for	for	ADP
admet-2772	340	14	identifying	identify	VERB
admet-2772	340	15	poorly	poorly	ADV
admet-2772	340	16	behaved	behave	VERB
admet-2772	340	17	compounds	compound	NOUN
admet-2772	340	18	and	and	CCONJ
admet-2772	340	19	improving	improve	VERB
admet-2772	340	20	the	the	DET
admet-2772	340	21	success	success	NOUN
admet-2772	340	22	rate	rate	NOUN
admet-2772	340	23	of	of	ADP
admet-2772	340	24	new	new	ADJ
admet-2772	340	25	chemical	chemical	NOUN
admet-2772	340	26	entities	entity	NOUN
admet-2772	340	27	reaching	reach	VERB
admet-2772	340	28	the	the	DET
admet-2772	340	29	market	market	NOUN
admet-2772	340	30	.	.	PUNCT
admet-2772	341	1	these	these	DET
admet-2772	341	2	computational	computational	ADJ
admet-2772	341	3	models	model	NOUN
admet-2772	341	4	can	can	AUX
admet-2772	341	5	play	play	VERB
admet-2772	341	6	a	a	DET
admet-2772	341	7	significant	significant	ADJ
admet-2772	341	8	role	role	NOUN
admet-2772	341	9	in	in	ADP
admet-2772	341	10	predicting	predict	VERB
admet-2772	341	11	toxicity	toxicity	NOUN
admet-2772	341	12	and	and	CCONJ
admet-2772	341	13	supporting	support	VERB
admet-2772	341	14	future	future	ADJ
admet-2772	341	15	risk	risk	NOUN
admet-2772	341	16	assessments	assessment	NOUN
admet-2772	341	17	.	.	PUNCT
admet-2772	342	1	5.1.4	5.1.4	X
admet-2772	342	2	.	.	PUNCT
admet-2772	342	3	gradient	gradient	ADJ
admet-2772	342	4	boosting	boost	VERB
admet-2772	342	5	machines	machine	NOUN
admet-2772	342	6	and	and	CCONJ
admet-2772	342	7	extreme	extreme	ADJ
admet-2772	342	8	gradient	gradient	NOUN
admet-2772	342	9	boosting	boost	VERB
admet-2772	342	10	recent	recent	ADJ
admet-2772	342	11	studies	study	NOUN
admet-2772	342	12	have	have	AUX
admet-2772	342	13	demonstrated	demonstrate	VERB
admet-2772	342	14	the	the	DET
admet-2772	342	15	effectiveness	effectiveness	NOUN
admet-2772	342	16	of	of	ADP
admet-2772	342	17	gradient	gradient	ADJ
admet-2772	342	18	boosting	boost	VERB
admet-2772	342	19	algorithms	algorithm	NOUN
admet-2772	342	20	in	in	ADP
admet-2772	342	21	predicting	predict	VERB
admet-2772	342	22	absorption	absorption	NOUN
admet-2772	342	23	,	,	PUNCT
admet-2772	342	24	distribution	distribution	NOUN
admet-2772	342	25	,	,	PUNCT
admet-2772	342	26	metabolism	metabolism	NOUN
admet-2772	342	27	,	,	PUNCT
admet-2772	342	28	excretion	excretion	NOUN
admet-2772	342	29	,	,	PUNCT
admet-2772	342	30	and	and	CCONJ
admet-2772	342	31	toxicity	toxicity	NOUN
admet-2772	342	32	(	(	PUNCT
admet-2772	342	33	admet	admet	ADJ
admet-2772	342	34	)	)	PUNCT
admet-2772	342	35	properties	property	NOUN
admet-2772	342	36	of	of	ADP
admet-2772	342	37	drug	drug	NOUN
admet-2772	342	38	compounds	compound	NOUN
admet-2772	342	39	.	.	PUNCT
admet-2772	343	1	tian	tian	PROPN
admet-2772	343	2	et	et	PROPN
admet-2772	343	3	al	al	PROPN
admet-2772	343	4	.	.	PUNCT
admet-2772	344	1	[	[	X
admet-2772	344	2	141	141	NUM
admet-2772	344	3	]	]	PUNCT
admet-2772	344	4	developed	develop	VERB
admet-2772	344	5	admet	admet	PROPN
admet-2772	344	6	boost	boost	NOUN
admet-2772	344	7	,	,	PUNCT
admet-2772	344	8	a	a	DET
admet-2772	344	9	web	web	NOUN
admet-2772	344	10	server	server	NOUN
admet-2772	344	11	utilizing	utilize	VERB
admet-2772	344	12	extreme	extreme	ADJ
admet-2772	344	13	gradient	gradient	NOUN
admet-2772	344	14	boosting	boost	VERB
admet-2772	344	15	(	(	PUNCT
admet-2772	344	16	xgboost	xgboost	ADV
admet-2772	344	17	)	)	PUNCT
admet-2772	344	18	for	for	ADP
admet-2772	344	19	accurate	accurate	ADJ
admet-2772	344	20	admet	admet	PROPN
admet-2772	344	21	prediction	prediction	NOUN
admet-2772	344	22	,	,	PUNCT
admet-2772	344	23	achieving	achieve	VERB
admet-2772	344	24	top	top	ADJ
admet-2772	344	25	rankings	ranking	NOUN
admet-2772	344	26	in	in	ADP
admet-2772	344	27	multiple	multiple	ADJ
admet-2772	344	28	benchmark	benchmark	NOUN
admet-2772	344	29	tasks	task	NOUN
admet-2772	344	30	.	.	PUNCT
admet-2772	345	1	an	an	DET
admet-2772	345	2	et	et	NOUN
admet-2772	345	3	al	al	PROPN
admet-2772	345	4	.	.	PUNCT
admet-2772	346	1	[	[	X
admet-2772	346	2	142	142	NUM
admet-2772	346	3	]	]	PUNCT
admet-2772	346	4	compared	compare	VERB
admet-2772	346	5	various	various	ADJ
admet-2772	346	6	machine	machine	NOUN
admet-2772	346	7	learning	learning	NOUN
admet-2772	346	8	models	model	NOUN
admet-2772	346	9	,	,	PUNCT
admet-2772	346	10	including	include	VERB
admet-2772	346	11	xgboost	xgboost	ADV
admet-2772	346	12	and	and	CCONJ
admet-2772	346	13	light	light	ADJ
admet-2772	346	14	gradient	gradient	NOUN
admet-2772	346	15	boosting	boost	VERB
admet-2772	346	16	machines	machine	NOUN
admet-2772	346	17	(	(	PUNCT
admet-2772	346	18	lgbm	lgbm	NOUN
admet-2772	346	19	)	)	PUNCT
admet-2772	346	20	,	,	PUNCT
admet-2772	346	21	for	for	ADP
admet-2772	346	22	predicting	predict	VERB
admet-2772	346	23	estrogen	estrogen	NOUN
admet-2772	346	24	receptor	receptor	NOUN
admet-2772	346	25	alpha	alpha	NOUN
admet-2772	346	26	(	(	PUNCT
admet-2772	346	27	erα	erα	NOUN
admet-2772	346	28	)	)	PUNCT
admet-2772	346	29	bioactivity	bioactivity	NOUN
admet-2772	346	30	and	and	CCONJ
admet-2772	346	31	admet	admet	PROPN
admet-2772	346	32	properties	property	NOUN
admet-2772	346	33	,	,	PUNCT
admet-2772	346	34	finding	find	VERB
admet-2772	346	35	high	high	ADJ
admet-2772	346	36	accuracy	accuracy	NOUN
admet-2772	346	37	and	and	CCONJ
admet-2772	346	38	robustness	robustness	NOUN
admet-2772	346	39	in	in	ADP
admet-2772	346	40	their	their	PRON
admet-2772	346	41	approach	approach	NOUN
admet-2772	346	42	.	.	PUNCT
admet-2772	347	1	li	li	PROPN
admet-2772	347	2	et	et	PROPN
admet-2772	347	3	al	al	PROPN
admet-2772	347	4	.	.	PUNCT
admet-2772	348	1	[	[	X
admet-2772	348	2	143	143	NUM
admet-2772	348	3	]	]	PUNCT
admet-2772	348	4	applied	apply	VERB
admet-2772	348	5	lgbm	lgbm	NOUN
admet-2772	348	6	to	to	PART
admet-2772	348	7	predict	predict	VERB
admet-2772	348	8	admet	admet	NOUN
admet-2772	348	9	properties	property	NOUN
admet-2772	348	10	of	of	ADP
admet-2772	348	11	anti	anti	ADJ
admet-2772	348	12	-	-	ADJ
admet-2772	348	13	breast	breast	ADJ
admet-2772	348	14	cancer	cancer	NOUN
admet-2772	348	15	compounds	compound	NOUN
admet-2772	348	16	,	,	PUNCT
admet-2772	348	17	reporting	report	VERB
admet-2772	348	18	superior	superior	ADJ
admet-2772	348	19	performance	performance	NOUN
admet-2772	348	20	compared	compare	VERB
admet-2772	348	21	to	to	ADP
admet-2772	348	22	other	other	ADJ
admet-2772	348	23	algorithms	algorithm	NOUN
admet-2772	348	24	.	.	PUNCT
admet-2772	349	1	these	these	DET
admet-2772	349	2	studies	study	NOUN
admet-2772	349	3	highlight	highlight	VERB
admet-2772	349	4	the	the	DET
admet-2772	349	5	potential	potential	NOUN
admet-2772	349	6	of	of	ADP
admet-2772	349	7	gradient	gradient	ADJ
admet-2772	349	8	boosting	boost	VERB
admet-2772	349	9	techniques	technique	NOUN
admet-2772	349	10	in	in	ADP
admet-2772	349	11	drug	drug	NOUN
admet-2772	349	12	discovery	discovery	NOUN
admet-2772	349	13	and	and	CCONJ
admet-2772	349	14	development	development	NOUN
admet-2772	349	15	,	,	PUNCT
admet-2772	349	16	offering	offer	VERB
admet-2772	349	17	accurate	accurate	ADJ
admet-2772	349	18	predictions	prediction	NOUN
admet-2772	349	19	of	of	ADP
admet-2772	349	20	crucial	crucial	ADJ
admet-2772	349	21	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	349	22	m.	m.	NOUN
admet-2772	349	23	venkataraman	venkataraman	PROPN
admet-2772	349	24	et	et	PROPN
admet-2772	349	25	al	al	PROPN
admet-2772	349	26	.	.	PROPN
admet-2772	349	27	admet	admet	PROPN
admet-2772	349	28	&	&	CCONJ
admet-2772	349	29	dmpk	dmpk	PROPN
admet-2772	349	30	13(3	13(3	NUM
admet-2772	349	31	)	)	PUNCT
admet-2772	349	32	(	(	PUNCT
admet-2772	349	33	2025	2025	NUM
admet-2772	349	34	)	)	PUNCT
admet-2772	349	35	2772	2772	NUM
admet-2772	349	36	14	14	NUM
admet-2772	349	37	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	349	38	and	and	CCONJ
admet-2772	349	39	toxicological	toxicological	ADJ
admet-2772	349	40	properties	property	NOUN
admet-2772	349	41	.	.	PUNCT
admet-2772	350	1	the	the	DET
admet-2772	350	2	integration	integration	NOUN
admet-2772	350	3	of	of	ADP
admet-2772	350	4	such	such	ADJ
admet-2772	350	5	models	model	NOUN
admet-2772	350	6	into	into	ADP
admet-2772	350	7	web	web	NOUN
admet-2772	350	8	-	-	PUNCT
admet-2772	350	9	based	base	VERB
admet-2772	350	10	tools	tool	NOUN
admet-2772	350	11	further	far	ADV
admet-2772	350	12	enhances	enhance	VERB
admet-2772	350	13	their	their	PRON
admet-2772	350	14	accessibility	accessibility	NOUN
admet-2772	350	15	and	and	CCONJ
admet-2772	350	16	utility	utility	NOUN
admet-2772	350	17	in	in	ADP
admet-2772	350	18	the	the	DET
admet-2772	350	19	biopharmaceutical	biopharmaceutical	ADJ
admet-2772	350	20	field	field	NOUN
admet-2772	350	21	.	.	PUNCT
admet-2772	351	1	5.2	5.2	NUM
admet-2772	351	2	.	.	PUNCT
admet-2772	352	1	deep	deep	ADJ
admet-2772	352	2	learning	learning	NOUN
admet-2772	352	3	approaches	approach	VERB
admet-2772	352	4	5.2.1	5.2.1	NUM
admet-2772	352	5	.	.	PUNCT
admet-2772	353	1	fully	fully	ADV
admet-2772	353	2	connected	connect	VERB
admet-2772	353	3	neural	neural	ADJ
admet-2772	353	4	networks	network	NOUN
admet-2772	353	5	fully	fully	ADV
admet-2772	353	6	connected	connect	VERB
admet-2772	353	7	neural	neural	ADJ
admet-2772	353	8	networks	network	NOUN
admet-2772	353	9	(	(	PUNCT
admet-2772	353	10	fcnns	fcnn	NOUN
admet-2772	353	11	)	)	PUNCT
admet-2772	353	12	and	and	CCONJ
admet-2772	353	13	other	other	ADJ
admet-2772	353	14	artificial	artificial	ADJ
admet-2772	353	15	neural	neural	ADJ
admet-2772	353	16	network	network	NOUN
admet-2772	353	17	architectures	architecture	NOUN
admet-2772	353	18	have	have	AUX
admet-2772	353	19	shown	show	VERB
admet-2772	353	20	significant	significant	ADJ
admet-2772	353	21	potential	potential	NOUN
admet-2772	353	22	in	in	ADP
admet-2772	353	23	predicting	predict	VERB
admet-2772	353	24	admet	admet	NOUN
admet-2772	353	25	properties	property	NOUN
admet-2772	353	26	of	of	ADP
admet-2772	353	27	chemical	chemical	NOUN
admet-2772	353	28	compounds	compound	NOUN
admet-2772	353	29	.	.	PUNCT
admet-2772	354	1	these	these	DET
admet-2772	354	2	models	model	NOUN
admet-2772	354	3	can	can	AUX
admet-2772	354	4	achieve	achieve	VERB
admet-2772	354	5	high	high	ADJ
admet-2772	354	6	accuracy	accuracy	NOUN
admet-2772	354	7	in	in	ADP
admet-2772	354	8	predicting	predict	VERB
admet-2772	354	9	various	various	ADJ
admet-2772	354	10	toxicological	toxicological	ADJ
admet-2772	354	11	parameters	parameter	NOUN
admet-2772	354	12	,	,	PUNCT
admet-2772	354	13	with	with	ADP
admet-2772	354	14	some	some	DET
admet-2772	354	15	studies	study	NOUN
admet-2772	354	16	reporting	report	VERB
admet-2772	354	17	accuracies	accuracy	NOUN
admet-2772	354	18	between	between	ADP
admet-2772	354	19	74	74	NUM
admet-2772	354	20	and	and	CCONJ
admet-2772	354	21	98	98	NUM
admet-2772	354	22	%	%	NOUN
admet-2772	355	1	[	[	X
admet-2772	355	2	144	144	NUM
admet-2772	355	3	]	]	PUNCT
admet-2772	355	4	.	.	PUNCT
admet-2772	356	1	fcnns	fcnn	NOUN
admet-2772	356	2	have	have	AUX
admet-2772	356	3	demonstrated	demonstrate	VERB
admet-2772	356	4	superior	superior	ADJ
admet-2772	356	5	performance	performance	NOUN
admet-2772	356	6	in	in	ADP
admet-2772	356	7	multitask	multitask	ADJ
admet-2772	356	8	learning	learning	NOUN
admet-2772	356	9	approaches	approach	NOUN
admet-2772	356	10	,	,	PUNCT
admet-2772	356	11	improving	improve	VERB
admet-2772	356	12	predictive	predictive	ADJ
admet-2772	356	13	quality	quality	NOUN
admet-2772	356	14	for	for	ADP
admet-2772	356	15	properties	property	NOUN
admet-2772	356	16	like	like	ADP
admet-2772	356	17	human	human	ADJ
admet-2772	356	18	metabolic	metabolic	NOUN
admet-2772	356	19	stability	stability	NOUN
admet-2772	356	20	[	[	X
admet-2772	356	21	145	145	NUM
admet-2772	356	22	]	]	PUNCT
admet-2772	356	23	.	.	PUNCT
admet-2772	357	1	neural	neural	ADJ
admet-2772	357	2	networks	network	NOUN
admet-2772	357	3	outperform	outperform	VERB
admet-2772	357	4	traditional	traditional	ADJ
admet-2772	357	5	methods	method	NOUN
admet-2772	357	6	in	in	ADP
admet-2772	357	7	predicting	predict	VERB
admet-2772	357	8	several	several	ADJ
admet-2772	357	9	admet	admet	NOUN
admet-2772	357	10	properties	property	NOUN
admet-2772	357	11	,	,	PUNCT
admet-2772	357	12	including	include	VERB
admet-2772	357	13	acute	acute	ADJ
admet-2772	357	14	toxicity	toxicity	NOUN
admet-2772	357	15	,	,	PUNCT
admet-2772	357	16	carcinogenicity	carcinogenicity	NOUN
admet-2772	357	17	,	,	PUNCT
admet-2772	357	18	and	and	CCONJ
admet-2772	357	19	hepatic	hepatic	ADJ
admet-2772	357	20	clearance	clearance	NOUN
admet-2772	357	21	[	[	X
admet-2772	357	22	144	144	NUM
admet-2772	357	23	]	]	PUNCT
admet-2772	357	24	.	.	PUNCT
admet-2772	358	1	the	the	DET
admet-2772	358	2	application	application	NOUN
admet-2772	358	3	of	of	ADP
admet-2772	358	4	neural	neural	ADJ
admet-2772	358	5	networks	network	NOUN
admet-2772	358	6	in	in	ADP
admet-2772	358	7	admet	admet	PROPN
admet-2772	358	8	prediction	prediction	NOUN
admet-2772	358	9	allows	allow	VERB
admet-2772	358	10	for	for	ADP
admet-2772	358	11	early	early	ADJ
admet-2772	358	12	consideration	consideration	NOUN
admet-2772	358	13	of	of	ADP
admet-2772	358	14	these	these	DET
admet-2772	358	15	properties	property	NOUN
admet-2772	358	16	in	in	ADP
admet-2772	358	17	drug	drug	NOUN
admet-2772	358	18	development	development	NOUN
admet-2772	358	19	,	,	PUNCT
admet-2772	358	20	potentially	potentially	ADV
admet-2772	358	21	reducing	reduce	VERB
admet-2772	358	22	late	late	ADJ
admet-2772	358	23	-	-	PUNCT
admet-2772	358	24	stage	stage	NOUN
admet-2772	358	25	failures	failure	NOUN
admet-2772	358	26	and	and	CCONJ
admet-2772	358	27	improving	improve	VERB
admet-2772	358	28	pharmaceutical	pharmaceutical	ADJ
admet-2772	358	29	industry	industry	NOUN
admet-2772	358	30	efficiency	efficiency	NOUN
admet-2772	358	31	[	[	X
admet-2772	358	32	146	146	NUM
admet-2772	358	33	]	]	PUNCT
admet-2772	358	34	.	.	PUNCT
admet-2772	359	1	as	as	SCONJ
admet-2772	359	2	artificial	artificial	ADJ
admet-2772	359	3	intelligence	intelligence	NOUN
admet-2772	359	4	continues	continue	VERB
admet-2772	359	5	to	to	PART
admet-2772	359	6	advance	advance	VERB
admet-2772	359	7	,	,	PUNCT
admet-2772	359	8	neural	neural	ADJ
admet-2772	359	9	networks	network	NOUN
admet-2772	359	10	are	be	AUX
admet-2772	359	11	expected	expect	VERB
admet-2772	359	12	to	to	PART
admet-2772	359	13	play	play	VERB
admet-2772	359	14	an	an	DET
admet-2772	359	15	increasingly	increasingly	ADV
admet-2772	359	16	important	important	ADJ
admet-2772	359	17	role	role	NOUN
admet-2772	359	18	in	in	ADP
admet-2772	359	19	toxicology	toxicology	NOUN
admet-2772	359	20	research	research	NOUN
admet-2772	359	21	and	and	CCONJ
admet-2772	359	22	drug	drug	NOUN
admet-2772	359	23	discovery	discovery	NOUN
admet-2772	360	1	[	[	X
admet-2772	360	2	147	147	NUM
admet-2772	360	3	]	]	PUNCT
admet-2772	360	4	.	.	PUNCT
admet-2772	361	1	5.2.2	5.2.2	NUM
admet-2772	361	2	.	.	PUNCT
admet-2772	361	3	convolutional	convolutional	ADJ
admet-2772	361	4	neural	neural	ADJ
admet-2772	361	5	networks	network	NOUN
admet-2772	361	6	convolutional	convolutional	ADJ
admet-2772	361	7	neural	neural	ADJ
admet-2772	361	8	networks	network	NOUN
admet-2772	361	9	(	(	PUNCT
admet-2772	361	10	cnns	cnns	PROPN
admet-2772	361	11	)	)	PUNCT
admet-2772	361	12	and	and	CCONJ
admet-2772	361	13	other	other	ADJ
admet-2772	361	14	deep	deep	ADJ
admet-2772	361	15	learning	learning	NOUN
admet-2772	361	16	models	model	NOUN
admet-2772	361	17	have	have	AUX
admet-2772	361	18	shown	show	VERB
admet-2772	361	19	promising	promising	ADJ
admet-2772	361	20	results	result	NOUN
admet-2772	361	21	in	in	ADP
admet-2772	361	22	predicting	predict	VERB
admet-2772	361	23	absorption	absorption	NOUN
admet-2772	361	24	,	,	PUNCT
admet-2772	361	25	distribution	distribution	NOUN
admet-2772	361	26	,	,	PUNCT
admet-2772	361	27	metabolism	metabolism	NOUN
admet-2772	361	28	,	,	PUNCT
admet-2772	361	29	excretion	excretion	NOUN
admet-2772	361	30	,	,	PUNCT
admet-2772	361	31	and	and	CCONJ
admet-2772	361	32	toxicity	toxicity	NOUN
admet-2772	361	33	(	(	PUNCT
admet-2772	361	34	admet	admet	ADJ
admet-2772	361	35	)	)	PUNCT
admet-2772	361	36	properties	property	NOUN
admet-2772	361	37	of	of	ADP
admet-2772	361	38	drug	drug	NOUN
admet-2772	361	39	candidates	candidate	NOUN
admet-2772	361	40	.	.	PUNCT
admet-2772	362	1	these	these	DET
admet-2772	362	2	models	model	NOUN
admet-2772	362	3	can	can	AUX
admet-2772	362	4	analyse	analyse	VERB
admet-2772	362	5	large	large	ADJ
admet-2772	362	6	datasets	dataset	NOUN
admet-2772	362	7	to	to	PART
admet-2772	362	8	identify	identify	VERB
admet-2772	362	9	relevant	relevant	ADJ
admet-2772	362	10	features	feature	NOUN
admet-2772	362	11	and	and	CCONJ
admet-2772	362	12	evaluate	evaluate	VERB
admet-2772	362	13	hidden	hidden	ADJ
admet-2772	362	14	trends	trend	NOUN
admet-2772	362	15	among	among	ADP
admet-2772	362	16	multiple	multiple	ADJ
admet-2772	362	17	admet	admet	ADJ
admet-2772	362	18	parameters	parameter	NOUN
admet-2772	362	19	[	[	X
admet-2772	362	20	145	145	NUM
admet-2772	362	21	]	]	PUNCT
admet-2772	362	22	.	.	PUNCT
admet-2772	363	1	deep	deep	ADJ
admet-2772	363	2	neural	neural	ADJ
admet-2772	363	3	networks	network	NOUN
admet-2772	363	4	have	have	AUX
admet-2772	363	5	demonstrated	demonstrate	VERB
admet-2772	363	6	superior	superior	ADJ
admet-2772	363	7	performance	performance	NOUN
admet-2772	363	8	compared	compare	VERB
admet-2772	363	9	to	to	ADP
admet-2772	363	10	traditional	traditional	ADJ
admet-2772	363	11	methods	method	NOUN
admet-2772	363	12	in	in	ADP
admet-2772	363	13	predicting	predict	VERB
admet-2772	363	14	properties	property	NOUN
admet-2772	363	15	such	such	ADJ
admet-2772	363	16	as	as	ADP
admet-2772	363	17	microsomal	microsomal	ADJ
admet-2772	363	18	stability	stability	NOUN
admet-2772	363	19	,	,	PUNCT
admet-2772	363	20	passive	passive	ADJ
admet-2772	363	21	permeability	permeability	NOUN
admet-2772	363	22	,	,	PUNCT
admet-2772	363	23	and	and	CCONJ
admet-2772	363	24	log	log	VERB
admet-2772	363	25	d	d	PROPN
admet-2772	364	1	[	[	X
admet-2772	364	2	148	148	NUM
admet-2772	364	3	]	]	PUNCT
admet-2772	364	4	.	.	PUNCT
admet-2772	365	1	various	various	ADJ
admet-2772	365	2	admet	admet	PROPN
admet-2772	365	3	prediction	prediction	NOUN
admet-2772	365	4	models	model	NOUN
admet-2772	365	5	have	have	AUX
admet-2772	365	6	been	be	AUX
admet-2772	365	7	developed	develop	VERB
admet-2772	365	8	and	and	CCONJ
admet-2772	365	9	made	make	VERB
admet-2772	365	10	publicly	publicly	ADV
admet-2772	365	11	available	available	ADJ
admet-2772	365	12	,	,	PUNCT
admet-2772	365	13	offering	offer	VERB
admet-2772	365	14	rapid	rapid	ADJ
admet-2772	365	15	assessments	assessment	NOUN
admet-2772	365	16	of	of	ADP
admet-2772	365	17	important	important	ADJ
admet-2772	365	18	drug	drug	NOUN
admet-2772	365	19	properties	property	NOUN
admet-2772	365	20	like	like	ADP
admet-2772	365	21	cytotoxicity	cytotoxicity	NOUN
admet-2772	365	22	,	,	PUNCT
admet-2772	365	23	mutagenicity	mutagenicity	NOUN
admet-2772	365	24	,	,	PUNCT
admet-2772	365	25	and	and	CCONJ
admet-2772	365	26	drug	drug	NOUN
admet-2772	365	27	-	-	PUNCT
admet-2772	365	28	drug	drug	NOUN
admet-2772	365	29	interactions	interaction	NOUN
admet-2772	365	30	[	[	X
admet-2772	365	31	149	149	NUM
admet-2772	365	32	]	]	PUNCT
admet-2772	365	33	.	.	PUNCT
admet-2772	366	1	the	the	DET
admet-2772	366	2	integration	integration	NOUN
admet-2772	366	3	of	of	ADP
admet-2772	366	4	admet	admet	PROPN
admet-2772	366	5	screening	screen	VERB
admet-2772	366	6	earlier	early	ADV
admet-2772	366	7	in	in	ADP
admet-2772	366	8	the	the	DET
admet-2772	366	9	drug	drug	NOUN
admet-2772	366	10	discovery	discovery	NOUN
admet-2772	366	11	process	process	NOUN
admet-2772	366	12	helps	help	VERB
admet-2772	366	13	eliminate	eliminate	VERB
admet-2772	366	14	poorly	poorly	ADV
admet-2772	366	15	behaved	behave	VERB
admet-2772	366	16	compounds	compound	NOUN
admet-2772	366	17	,	,	PUNCT
admet-2772	366	18	reducing	reduce	VERB
admet-2772	366	19	costly	costly	ADJ
admet-2772	366	20	failures	failure	NOUN
admet-2772	366	21	in	in	ADP
admet-2772	366	22	later	later	ADJ
admet-2772	366	23	stages[5	stages[5	NOUN
admet-2772	366	24	]	]	PUNCT
admet-2772	366	25	.	.	PUNCT
admet-2772	367	1	as	as	SCONJ
admet-2772	367	2	artificial	artificial	ADJ
admet-2772	367	3	intelligence	intelligence	NOUN
admet-2772	367	4	continues	continue	VERB
admet-2772	367	5	to	to	PART
admet-2772	367	6	advance	advance	VERB
admet-2772	367	7	,	,	PUNCT
admet-2772	367	8	neural	neural	ADJ
admet-2772	367	9	networks	network	NOUN
admet-2772	367	10	are	be	AUX
admet-2772	367	11	expected	expect	VERB
admet-2772	367	12	to	to	PART
admet-2772	367	13	play	play	VERB
admet-2772	367	14	an	an	DET
admet-2772	367	15	increasingly	increasingly	ADV
admet-2772	367	16	important	important	ADJ
admet-2772	367	17	role	role	NOUN
admet-2772	367	18	in	in	ADP
admet-2772	367	19	toxicology	toxicology	NOUN
admet-2772	367	20	research	research	NOUN
admet-2772	367	21	and	and	CCONJ
admet-2772	367	22	the	the	DET
admet-2772	367	23	development	development	NOUN
admet-2772	367	24	of	of	ADP
admet-2772	367	25	accurate	accurate	ADJ
admet-2772	367	26	biosensors	biosensor	NOUN
admet-2772	367	27	for	for	ADP
admet-2772	367	28	toxic	toxic	ADJ
admet-2772	367	29	substance	substance	NOUN
admet-2772	367	30	detection	detection	NOUN
admet-2772	368	1	[	[	X
admet-2772	368	2	147	147	NUM
admet-2772	368	3	]	]	PUNCT
admet-2772	368	4	.	.	PUNCT
admet-2772	369	1	5.2.3	5.2.3	NUM
admet-2772	369	2	.	.	PUNCT
admet-2772	369	3	recurrent	recurrent	ADJ
admet-2772	369	4	neural	neural	ADJ
admet-2772	369	5	networks	network	NOUN
admet-2772	369	6	and	and	CCONJ
admet-2772	369	7	long	long	ADJ
admet-2772	369	8	short	short	ADJ
admet-2772	369	9	-	-	PUNCT
admet-2772	369	10	term	term	NOUN
admet-2772	369	11	memory	memory	NOUN
admet-2772	369	12	recent	recent	ADJ
admet-2772	369	13	research	research	NOUN
admet-2772	369	14	has	have	AUX
admet-2772	369	15	explored	explore	VERB
admet-2772	369	16	the	the	DET
admet-2772	369	17	application	application	NOUN
admet-2772	369	18	of	of	ADP
admet-2772	369	19	recurrent	recurrent	ADJ
admet-2772	369	20	neural	neural	ADJ
admet-2772	369	21	networks	network	NOUN
admet-2772	369	22	(	(	PUNCT
admet-2772	369	23	rnns	rnns	PROPN
admet-2772	369	24	)	)	PUNCT
admet-2772	369	25	and	and	CCONJ
admet-2772	369	26	long	long	ADJ
admet-2772	369	27	short	short	ADJ
admet-2772	369	28	-	-	PUNCT
admet-2772	369	29	term	term	NOUN
admet-2772	369	30	memory	memory	NOUN
admet-2772	369	31	(	(	PUNCT
admet-2772	369	32	lstm	lstm	NOUN
admet-2772	369	33	)	)	PUNCT
admet-2772	369	34	models	model	NOUN
admet-2772	369	35	in	in	ADP
admet-2772	369	36	predicting	predict	VERB
admet-2772	369	37	and	and	CCONJ
admet-2772	369	38	analysing	analyse	VERB
admet-2772	369	39	admet	admet	NOUN
admet-2772	369	40	properties	property	NOUN
admet-2772	369	41	of	of	ADP
admet-2772	369	42	drugs	drug	NOUN
admet-2772	369	43	and	and	CCONJ
admet-2772	369	44	peptides	peptide	NOUN
admet-2772	369	45	.	.	PUNCT
admet-2772	370	1	wang	wang	PROPN
admet-2772	370	2	et	et	PROPN
admet-2772	370	3	al	al	PROPN
admet-2772	370	4	.	.	PUNCT
admet-2772	371	1	[	[	X
admet-2772	371	2	15	15	NUM
admet-2772	371	3	]	]	PUNCT
admet-2772	371	4	demonstrated	demonstrate	VERB
admet-2772	371	5	that	that	SCONJ
admet-2772	371	6	lstm	lstm	PROPN
admet-2772	371	7	networks	network	NOUN
admet-2772	371	8	can	can	AUX
admet-2772	371	9	accurately	accurately	ADV
admet-2772	371	10	model	model	VERB
admet-2772	371	11	complex	complex	ADJ
admet-2772	371	12	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	371	13	-	-	PUNCT
admet-2772	371	14	pharmacodynamics	pharmacodynamic	NOUN
admet-2772	371	15	relationships	relationship	NOUN
admet-2772	371	16	.	.	PUNCT
admet-2772	372	1	wenzel	wenzel	PROPN
admet-2772	372	2	et	et	PROPN
admet-2772	372	3	al	al	PROPN
admet-2772	372	4	.	.	PUNCT
admet-2772	373	1	[	[	X
admet-2772	373	2	145	145	NUM
admet-2772	373	3	]	]	PUNCT
admet-2772	373	4	developed	develop	VERB
admet-2772	373	5	multitask	multitask	ADJ
admet-2772	373	6	deep	deep	ADJ
admet-2772	373	7	neural	neural	ADJ
admet-2772	373	8	networks	network	NOUN
admet-2772	373	9	for	for	ADP
admet-2772	373	10	predicting	predict	VERB
admet-2772	373	11	multiple	multiple	ADJ
admet-2772	373	12	adme	adme	NOUN
admet-2772	373	13	-	-	PUNCT
admet-2772	373	14	tox	tox	NOUN
admet-2772	373	15	properties	property	NOUN
admet-2772	373	16	simultaneously	simultaneously	ADV
admet-2772	373	17	,	,	PUNCT
admet-2772	373	18	showing	show	VERB
admet-2772	373	19	improved	improved	ADJ
admet-2772	373	20	performance	performance	NOUN
admet-2772	373	21	over	over	ADP
admet-2772	373	22	single	single	ADJ
admet-2772	373	23	-	-	PUNCT
admet-2772	373	24	task	task	NOUN
admet-2772	373	25	models	model	NOUN
admet-2772	373	26	.	.	PUNCT
admet-2772	374	1	gonzález	gonzález	PROPN
admet-2772	374	2	-	-	PUNCT
admet-2772	374	3	díaz	díaz	NOUN
admet-2772	375	1	[	[	X
admet-2772	375	2	150	150	NUM
admet-2772	375	3	]	]	PUNCT
admet-2772	375	4	reviewed	review	VERB
admet-2772	375	5	multi	multi	ADJ
admet-2772	375	6	-	-	ADJ
admet-2772	375	7	output	output	ADJ
admet-2772	375	8	qspr	qspr	NOUN
admet-2772	375	9	models	model	NOUN
admet-2772	375	10	for	for	ADP
admet-2772	375	11	predicting	predict	VERB
admet-2772	375	12	admet	admet	NOUN
admet-2772	375	13	processes	process	NOUN
admet-2772	375	14	,	,	PUNCT
admet-2772	375	15	including	include	VERB
admet-2772	375	16	drug	drug	NOUN
admet-2772	375	17	-	-	PUNCT
admet-2772	375	18	target	target	NOUN
admet-2772	375	19	interactions	interaction	NOUN
admet-2772	375	20	and	and	CCONJ
admet-2772	375	21	nanoparticle	nanoparticle	NOUN
admet-2772	375	22	toxicity	toxicity	NOUN
admet-2772	375	23	.	.	PUNCT
admet-2772	376	1	in	in	ADP
admet-2772	376	2	the	the	DET
admet-2772	376	3	realm	realm	NOUN
admet-2772	376	4	of	of	ADP
admet-2772	376	5	peptide	peptide	ADJ
admet-2772	376	6	design	design	NOUN
admet-2772	376	7	,	,	PUNCT
admet-2772	376	8	müller	müller	PROPN
admet-2772	376	9	et	et	PROPN
admet-2772	376	10	al	al	PROPN
admet-2772	376	11	.	.	PUNCT
admet-2772	377	1	[	[	X
admet-2772	377	2	151	151	NUM
admet-2772	377	3	]	]	PUNCT
admet-2772	377	4	utilized	utilize	VERB
admet-2772	377	5	lstm	lstm	PROPN
admet-2772	377	6	rnns	rnn	NOUN
admet-2772	377	7	to	to	PART
admet-2772	377	8	generate	generate	VERB
admet-2772	377	9	novel	novel	ADJ
admet-2772	377	10	antimicrobial	antimicrobial	ADJ
admet-2772	377	11	peptide	peptide	NOUN
admet-2772	377	12	sequences	sequence	NOUN
admet-2772	377	13	with	with	ADP
admet-2772	377	14	a	a	DET
admet-2772	377	15	higher	high	ADJ
admet-2772	377	16	predicted	predict	VERB
admet-2772	377	17	activity	activity	NOUN
admet-2772	377	18	rate	rate	NOUN
admet-2772	377	19	compared	compare	VERB
admet-2772	377	20	to	to	PART
admet-2772	377	21	randomly	randomly	ADV
admet-2772	377	22	sampled	sample	VERB
admet-2772	377	23	sequences	sequence	NOUN
admet-2772	377	24	.	.	PUNCT
admet-2772	378	1	these	these	DET
admet-2772	378	2	studies	study	NOUN
admet-2772	378	3	highlight	highlight	VERB
admet-2772	378	4	the	the	DET
admet-2772	378	5	potential	potential	NOUN
admet-2772	378	6	of	of	ADP
admet-2772	378	7	rnn	rnn	PROPN
admet-2772	378	8	and	and	CCONJ
admet-2772	378	9	lstm	lstm	NOUN
admet-2772	378	10	models	model	NOUN
admet-2772	378	11	in	in	ADP
admet-2772	378	12	drug	drug	NOUN
admet-2772	378	13	discovery	discovery	NOUN
admet-2772	378	14	,	,	PUNCT
admet-2772	378	15	admet	admet	PROPN
admet-2772	378	16	prediction	prediction	NOUN
admet-2772	378	17	,	,	PUNCT
admet-2772	378	18	and	and	CCONJ
admet-2772	378	19	peptide	peptide	NOUN
admet-2772	378	20	design	design	NOUN
admet-2772	378	21	,	,	PUNCT
admet-2772	378	22	offering	offer	VERB
admet-2772	378	23	promising	promising	ADJ
admet-2772	378	24	tools	tool	NOUN
admet-2772	378	25	for	for	ADP
admet-2772	378	26	pharmaceutical	pharmaceutical	ADJ
admet-2772	378	27	research	research	NOUN
admet-2772	378	28	and	and	CCONJ
admet-2772	378	29	development	development	NOUN
admet-2772	378	30	.	.	PUNCT
admet-2772	379	1	5.2.4	5.2.4	NUM
admet-2772	379	2	.	.	PUNCT
admet-2772	380	1	graph	graph	NOUN
admet-2772	380	2	neural	neural	ADJ
admet-2772	380	3	networks	network	NOUN
admet-2772	380	4	recent	recent	ADJ
admet-2772	380	5	advancements	advancement	NOUN
admet-2772	380	6	in	in	ADP
admet-2772	380	7	graph	graph	NOUN
admet-2772	380	8	neural	neural	ADJ
admet-2772	380	9	networks	network	NOUN
admet-2772	380	10	(	(	PUNCT
admet-2772	380	11	gnns	gnns	NOUN
admet-2772	380	12	)	)	PUNCT
admet-2772	380	13	have	have	AUX
admet-2772	380	14	significantly	significantly	ADV
admet-2772	380	15	improved	improve	VERB
admet-2772	380	16	the	the	DET
admet-2772	380	17	prediction	prediction	NOUN
admet-2772	380	18	of	of	ADP
admet-2772	380	19	admet	admet	NOUN
admet-2772	380	20	properties	property	NOUN
admet-2772	380	21	in	in	ADP
admet-2772	380	22	drug	drug	NOUN
admet-2772	380	23	discovery	discovery	NOUN
admet-2772	380	24	.	.	PUNCT
admet-2772	381	1	de	de	PROPN
admet-2772	381	2	carlo	carlo	PROPN
admet-2772	381	3	et	et	PROPN
admet-2772	381	4	al	al	PROPN
admet-2772	381	5	.	.	PUNCT
admet-2772	382	1	[	[	X
admet-2772	382	2	152	152	NUM
admet-2772	382	3	]	]	PUNCT
admet-2772	382	4	developed	develop	VERB
admet-2772	382	5	an	an	DET
admet-2772	382	6	attention	attention	NOUN
admet-2772	382	7	-	-	PUNCT
admet-2772	382	8	based	base	VERB
admet-2772	382	9	gnn	gnn	NOUN
admet-2772	382	10	that	that	PRON
admet-2772	382	11	processes	process	VERB
admet-2772	382	12	molecular	molecular	ADJ
admet-2772	382	13	information	information	NOUN
admet-2772	382	14	from	from	ADP
admet-2772	382	15	substructures	substructure	NOUN
admet-2772	382	16	to	to	ADP
admet-2772	382	17	whole	whole	ADJ
admet-2772	382	18	molecules	molecule	NOUN
admet-2772	382	19	,	,	PUNCT
admet-2772	382	20	effectively	effectively	ADV
admet-2772	382	21	predicting	predict	VERB
admet-2772	382	22	admet	admet	NOUN
admet-2772	382	23	properties	property	NOUN
admet-2772	382	24	without	without	ADP
admet-2772	382	25	relying	rely	VERB
admet-2772	382	26	on	on	ADP
admet-2772	382	27	molecular	molecular	ADJ
admet-2772	382	28	descriptors	descriptor	NOUN
admet-2772	382	29	.	.	PUNCT
admet-2772	383	1	aburidi	aburidi	NOUN
admet-2772	383	2	and	and	CCONJ
admet-2772	383	3	marcia	marcia	PROPN
admet-2772	384	1	[	[	X
admet-2772	384	2	153	153	NUM
admet-2772	384	3	]	]	PUNCT
admet-2772	384	4	introduced	introduce	VERB
admet-2772	384	5	an	an	DET
admet-2772	384	6	optimal	optimal	ADJ
admet-2772	384	7	transport	transport	NOUN
admet-2772	384	8	-	-	PUNCT
admet-2772	384	9	based	base	VERB
admet-2772	384	10	admet	admet	PROPN
admet-2772	384	11	&	&	CCONJ
admet-2772	384	12	dmpk	dmpk	PROPN
admet-2772	384	13	13(3	13(3	NUM
admet-2772	384	14	)	)	PUNCT
admet-2772	384	15	(	(	PUNCT
admet-2772	384	16	2025	2025	NUM
admet-2772	384	17	)	)	PUNCT
admet-2772	384	18	2772	2772	NUM
admet-2772	384	19	machine	machine	NOUN
admet-2772	384	20	learning	learning	NOUN
admet-2772	384	21	models	model	NOUN
admet-2772	384	22	for	for	ADP
admet-2772	384	23	admet	admet	ADJ
admet-2772	384	24	prediction	prediction	NOUN
admet-2772	384	25	in	in	ADP
admet-2772	384	26	drug	drug	NOUN
admet-2772	384	27	development	development	NOUN
admet-2772	384	28	doi	doi	PROPN
admet-2772	384	29	:	:	PUNCT
admet-2772	384	30	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	384	31	15	15	NUM
admet-2772	384	32	graph	graph	NOUN
admet-2772	384	33	kernel	kernel	NOUN
admet-2772	384	34	approach	approach	NOUN
admet-2772	384	35	that	that	PRON
admet-2772	384	36	outperformed	outperform	VERB
admet-2772	384	37	state	state	NOUN
admet-2772	384	38	-	-	PUNCT
admet-2772	384	39	of	of	ADP
admet-2772	384	40	-	-	PUNCT
admet-2772	384	41	the	the	DET
admet-2772	384	42	-	-	PUNCT
admet-2772	384	43	art	art	NOUN
admet-2772	384	44	gnns	gnns	NOUN
admet-2772	384	45	on	on	ADP
admet-2772	384	46	multiple	multiple	ADJ
admet-2772	384	47	admet	admet	NOUN
admet-2772	384	48	datasets	dataset	NOUN
admet-2772	384	49	.	.	PUNCT
admet-2772	385	1	feinberg	feinberg	PROPN
admet-2772	385	2	et	et	PROPN
admet-2772	385	3	al	al	PROPN
admet-2772	385	4	.	.	PUNCT
admet-2772	386	1	[	[	X
admet-2772	386	2	31	31	NUM
admet-2772	386	3	]	]	PUNCT
admet-2772	386	4	demonstrated	demonstrate	VERB
admet-2772	386	5	that	that	SCONJ
admet-2772	386	6	graph	graph	NOUN
admet-2772	386	7	convolutions	convolution	NOUN
admet-2772	386	8	applied	apply	VERB
admet-2772	386	9	to	to	AUX
admet-2772	386	10	explicit	explicit	ADJ
admet-2772	386	11	molecular	molecular	ADJ
admet-2772	386	12	representations	representation	NOUN
admet-2772	386	13	achieve	achieve	VERB
admet-2772	386	14	unprecedented	unprecedented	ADJ
admet-2772	386	15	accuracy	accuracy	NOUN
admet-2772	386	16	in	in	ADP
admet-2772	386	17	admet	admet	PROPN
admet-2772	386	18	prediction	prediction	NOUN
admet-2772	386	19	,	,	PUNCT
admet-2772	386	20	enabling	enable	VERB
admet-2772	386	21	both	both	CCONJ
admet-2772	386	22	interpolation	interpolation	NOUN
admet-2772	386	23	and	and	CCONJ
admet-2772	386	24	extrapolation	extrapolation	NOUN
admet-2772	386	25	to	to	ADP
admet-2772	386	26	new	new	ADJ
admet-2772	386	27	chemical	chemical	NOUN
admet-2772	386	28	spaces	space	NOUN
admet-2772	386	29	.	.	PUNCT
admet-2772	387	1	wenzel	wenzel	PROPN
admet-2772	387	2	et	et	PROPN
admet-2772	387	3	al	al	PROPN
admet-2772	387	4	.	.	PUNCT
admet-2772	388	1	[	[	X
admet-2772	388	2	145	145	NUM
admet-2772	388	3	]	]	PUNCT
admet-2772	388	4	explored	explore	VERB
admet-2772	388	5	multitask	multitask	ADJ
admet-2772	388	6	deep	deep	ADJ
admet-2772	388	7	neural	neural	ADJ
admet-2772	388	8	networks	network	NOUN
admet-2772	388	9	for	for	ADP
admet-2772	388	10	adme	adme	NOUN
admet-2772	388	11	-	-	PUNCT
admet-2772	388	12	tox	tox	NOUN
admet-2772	388	13	modelling	modelling	NOUN
admet-2772	388	14	,	,	PUNCT
admet-2772	388	15	showing	show	VERB
admet-2772	388	16	improved	improved	ADJ
admet-2772	388	17	performance	performance	NOUN
admet-2772	388	18	compared	compare	VERB
admet-2772	388	19	to	to	ADP
admet-2772	388	20	single	single	ADJ
admet-2772	388	21	-	-	PUNCT
admet-2772	388	22	task	task	NOUN
admet-2772	388	23	models	model	NOUN
admet-2772	388	24	and	and	CCONJ
admet-2772	388	25	introducing	introduce	VERB
admet-2772	388	26	a	a	DET
admet-2772	388	27	"	"	PUNCT
admet-2772	388	28	response	response	NOUN
admet-2772	388	29	map	map	NOUN
admet-2772	388	30	"	"	PUNCT
admet-2772	388	31	visualization	visualization	NOUN
admet-2772	388	32	technique	technique	NOUN
admet-2772	388	33	for	for	ADP
admet-2772	388	34	interpreting	interpret	VERB
admet-2772	388	35	model	model	NOUN
admet-2772	388	36	predictions	prediction	NOUN
admet-2772	388	37	.	.	PUNCT
admet-2772	389	1	these	these	DET
admet-2772	389	2	studies	study	NOUN
admet-2772	389	3	collectively	collectively	ADV
admet-2772	389	4	highlight	highlight	VERB
admet-2772	389	5	the	the	DET
admet-2772	389	6	potential	potential	NOUN
admet-2772	389	7	of	of	ADP
admet-2772	389	8	gnns	gnns	ADJ
admet-2772	389	9	and	and	CCONJ
admet-2772	389	10	deep	deep	ADJ
admet-2772	389	11	learning	learning	NOUN
admet-2772	389	12	approaches	approach	NOUN
admet-2772	389	13	to	to	PART
admet-2772	389	14	enhance	enhance	VERB
admet-2772	389	15	admet	admet	PROPN
admet-2772	389	16	property	property	NOUN
admet-2772	389	17	prediction	prediction	NOUN
admet-2772	389	18	in	in	ADP
admet-2772	389	19	drug	drug	NOUN
admet-2772	389	20	development	development	NOUN
admet-2772	389	21	.	.	PUNCT
admet-2772	390	1	5.3	5.3	NUM
admet-2772	390	2	.	.	PUNCT
admet-2772	390	3	generative	generative	ADJ
admet-2772	390	4	models	model	NOUN
admet-2772	390	5	for	for	ADP
admet-2772	390	6	admet	admet	NOUN
admet-2772	390	7	-	-	PUNCT
admet-2772	390	8	optimized	optimize	VERB
admet-2772	390	9	molecule	molecule	NOUN
admet-2772	390	10	design	design	NOUN
admet-2772	390	11	5.3.1	5.3.1	NUM
admet-2772	390	12	.	.	PUNCT
admet-2772	390	13	variational	variational	ADJ
admet-2772	390	14	autoencoders	autoencoder	NOUN
admet-2772	390	15	and	and	CCONJ
admet-2772	390	16	generative	generative	ADJ
admet-2772	390	17	adversarial	adversarial	ADJ
admet-2772	390	18	networks	network	NOUN
admet-2772	390	19	variational	variational	ADJ
admet-2772	390	20	autoencoders	autoencoder	NOUN
admet-2772	390	21	(	(	PUNCT
admet-2772	390	22	vaes	vaes	ADJ
admet-2772	390	23	)	)	PUNCT
admet-2772	390	24	and	and	CCONJ
admet-2772	390	25	generative	generative	VERB
admet-2772	390	26	adversarial	adversarial	ADJ
admet-2772	390	27	networks	network	NOUN
admet-2772	390	28	(	(	PUNCT
admet-2772	390	29	gans	gan	NOUN
admet-2772	390	30	)	)	PUNCT
admet-2772	390	31	are	be	AUX
admet-2772	390	32	powerful	powerful	ADJ
admet-2772	390	33	machine	machine	NOUN
admet-2772	390	34	learning	learning	NOUN
admet-2772	390	35	models	model	NOUN
admet-2772	390	36	with	with	ADP
admet-2772	390	37	applications	application	NOUN
admet-2772	390	38	in	in	ADP
admet-2772	390	39	various	various	ADJ
admet-2772	390	40	fields	field	NOUN
admet-2772	390	41	.	.	PUNCT
admet-2772	391	1	adversarial	adversarial	ADJ
admet-2772	391	2	variational	variational	ADJ
admet-2772	391	3	bayes	bayes	NOUN
admet-2772	391	4	(	(	PUNCT
admet-2772	391	5	avb	avb	PROPN
admet-2772	391	6	)	)	PUNCT
admet-2772	391	7	unifies	unify	VERB
admet-2772	391	8	vaes	vaes	NOUN
admet-2772	391	9	and	and	CCONJ
admet-2772	391	10	gans	gan	NOUN
admet-2772	391	11	,	,	PUNCT
admet-2772	391	12	allowing	allow	VERB
admet-2772	391	13	for	for	ADP
admet-2772	391	14	more	more	ADJ
admet-2772	391	15	expressive	expressive	ADJ
admet-2772	391	16	inference	inference	NOUN
admet-2772	391	17	models	model	NOUN
admet-2772	391	18	[	[	X
admet-2772	391	19	154	154	NUM
admet-2772	391	20	]	]	PUNCT
admet-2772	391	21	.	.	PUNCT
admet-2772	392	1	the	the	DET
admet-2772	392	2	connection	connection	NOUN
admet-2772	392	3	between	between	ADP
admet-2772	392	4	vaes	vaes	ADJ
admet-2772	392	5	,	,	PUNCT
admet-2772	392	6	gans	gan	NOUN
admet-2772	392	7	,	,	PUNCT
admet-2772	392	8	and	and	CCONJ
admet-2772	392	9	minimum	minimum	ADJ
admet-2772	392	10	kantorovitch	kantorovitch	NOUN
admet-2772	392	11	estimators	estimator	NOUN
admet-2772	392	12	has	have	AUX
admet-2772	392	13	been	be	AUX
admet-2772	392	14	explored	explore	VERB
admet-2772	392	15	from	from	ADP
admet-2772	392	16	an	an	DET
admet-2772	392	17	optimal	optimal	ADJ
admet-2772	392	18	transport	transport	NOUN
admet-2772	392	19	perspective	perspective	NOUN
admet-2772	392	20	[	[	X
admet-2772	392	21	155	155	NUM
admet-2772	392	22	]	]	PUNCT
admet-2772	392	23	.	.	PUNCT
admet-2772	393	1	in	in	ADP
admet-2772	393	2	the	the	DET
admet-2772	393	3	field	field	NOUN
admet-2772	393	4	of	of	ADP
admet-2772	393	5	drug	drug	NOUN
admet-2772	393	6	development	development	NOUN
admet-2772	393	7	and	and	CCONJ
admet-2772	393	8	toxicology	toxicology	NOUN
admet-2772	393	9	,	,	PUNCT
admet-2772	393	10	multi	multi	ADJ
admet-2772	393	11	-	-	ADJ
admet-2772	393	12	output	output	ADJ
admet-2772	393	13	qspr	qspr	NOUN
admet-2772	393	14	models	model	NOUN
admet-2772	393	15	have	have	AUX
admet-2772	393	16	been	be	AUX
admet-2772	393	17	used	use	VERB
admet-2772	393	18	to	to	PART
admet-2772	393	19	predict	predict	VERB
admet-2772	393	20	absorption	absorption	NOUN
admet-2772	393	21	,	,	PUNCT
admet-2772	393	22	distribution	distribution	NOUN
admet-2772	393	23	,	,	PUNCT
admet-2772	393	24	metabolism	metabolism	NOUN
admet-2772	393	25	,	,	PUNCT
admet-2772	393	26	excretion	excretion	NOUN
admet-2772	393	27	and	and	CCONJ
admet-2772	393	28	toxicity	toxicity	NOUN
admet-2772	393	29	(	(	PUNCT
admet-2772	393	30	admet	admet	ADJ
admet-2772	393	31	)	)	PUNCT
admet-2772	393	32	properties	property	NOUN
admet-2772	393	33	for	for	ADP
admet-2772	393	34	drugs	drug	NOUN
admet-2772	393	35	,	,	PUNCT
admet-2772	393	36	pollutants	pollutant	NOUN
admet-2772	393	37	,	,	PUNCT
admet-2772	393	38	and	and	CCONJ
admet-2772	393	39	nanoparticles	nanoparticle	NOUN
admet-2772	393	40	[	[	X
admet-2772	393	41	150	150	NUM
admet-2772	393	42	]	]	PUNCT
admet-2772	393	43	.	.	PUNCT
admet-2772	394	1	adme	adme	NOUN
admet-2772	394	2	profiling	profiling	NOUN
admet-2772	394	3	has	have	AUX
admet-2772	394	4	significantly	significantly	ADV
admet-2772	394	5	reduced	reduce	VERB
admet-2772	394	6	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	394	7	drug	drug	NOUN
admet-2772	394	8	failures	failure	NOUN
admet-2772	394	9	in	in	ADP
admet-2772	394	10	clinical	clinical	ADJ
admet-2772	394	11	trials	trial	NOUN
admet-2772	394	12	and	and	CCONJ
admet-2772	394	13	has	have	AUX
admet-2772	394	14	become	become	VERB
admet-2772	394	15	crucial	crucial	ADJ
admet-2772	394	16	for	for	ADP
admet-2772	394	17	safety	safety	NOUN
admet-2772	394	18	and	and	CCONJ
admet-2772	394	19	toxicity	toxicity	NOUN
admet-2772	394	20	prediction	prediction	NOUN
admet-2772	394	21	across	across	ADP
admet-2772	394	22	industries	industry	NOUN
admet-2772	394	23	[	[	X
admet-2772	394	24	156	156	NUM
admet-2772	394	25	]	]	PUNCT
admet-2772	394	26	.	.	PUNCT
admet-2772	395	1	the	the	DET
admet-2772	395	2	integration	integration	NOUN
admet-2772	395	3	of	of	ADP
admet-2772	395	4	adme	adme	NOUN
admet-2772	395	5	information	information	NOUN
admet-2772	395	6	with	with	ADP
admet-2772	395	7	in	in	ADP
admet-2772	395	8	vitro	vitro	X
admet-2772	395	9	results	result	NOUN
admet-2772	395	10	and	and	CCONJ
admet-2772	395	11	computer	computer	NOUN
admet-2772	395	12	modelling	modelling	NOUN
admet-2772	395	13	is	be	AUX
admet-2772	395	14	essential	essential	ADJ
admet-2772	395	15	for	for	ADP
admet-2772	395	16	developing	develop	VERB
admet-2772	395	17	quantitative	quantitative	ADJ
admet-2772	395	18	in	in	ADP
admet-2772	395	19	vitro	vitro	X
admet-2772	395	20	to	to	ADP
admet-2772	395	21	in	in	ADP
admet-2772	395	22	vivo	vivo	ADJ
admet-2772	395	23	extrapolations	extrapolation	NOUN
admet-2772	395	24	and	and	CCONJ
admet-2772	395	25	integrated	integrated	ADJ
admet-2772	395	26	testing	testing	NOUN
admet-2772	395	27	strategies	strategy	NOUN
admet-2772	395	28	in	in	ADP
admet-2772	395	29	toxicology	toxicology	NOUN
admet-2772	395	30	[	[	X
admet-2772	395	31	156	156	NUM
admet-2772	395	32	]	]	PUNCT
admet-2772	395	33	.	.	PUNCT
admet-2772	396	1	5.3.2	5.3.2	X
admet-2772	396	2	.	.	PUNCT
admet-2772	396	3	reinforcement	reinforcement	NOUN
admet-2772	396	4	learning	learning	NOUN
admet-2772	396	5	(	(	PUNCT
admet-2772	396	6	rl	rl	NOUN
admet-2772	396	7	)	)	PUNCT
admet-2772	396	8	generative	generative	NOUN
admet-2772	396	9	ai	ai	NOUN
admet-2772	396	10	models	model	NOUN
admet-2772	396	11	combined	combine	VERB
admet-2772	396	12	with	with	ADP
admet-2772	396	13	reinforcement	reinforcement	NOUN
admet-2772	396	14	learning	learning	NOUN
admet-2772	396	15	can	can	AUX
admet-2772	396	16	efficiently	efficiently	ADV
admet-2772	396	17	design	design	VERB
admet-2772	396	18	drug	drug	NOUN
admet-2772	396	19	candidates	candidate	NOUN
admet-2772	396	20	with	with	ADP
admet-2772	396	21	suitable	suitable	ADJ
admet-2772	396	22	admet	admet	NOUN
admet-2772	396	23	properties	property	NOUN
admet-2772	396	24	[	[	X
admet-2772	396	25	157	157	NUM
admet-2772	396	26	]	]	PUNCT
admet-2772	396	27	.	.	PUNCT
admet-2772	397	1	quantum	quantum	NOUN
admet-2772	397	2	-	-	PUNCT
admet-2772	397	3	informed	inform	VERB
admet-2772	397	4	molecular	molecular	ADJ
admet-2772	397	5	representation	representation	NOUN
admet-2772	397	6	learning	learning	NOUN
admet-2772	397	7	has	have	AUX
admet-2772	397	8	improved	improve	VERB
admet-2772	397	9	admet	admet	PROPN
admet-2772	397	10	property	property	NOUN
admet-2772	397	11	prediction	prediction	NOUN
admet-2772	397	12	,	,	PUNCT
admet-2772	397	13	achieving	achieve	VERB
admet-2772	397	14	state	state	NOUN
admet-2772	397	15	-	-	PUNCT
admet-2772	397	16	of	of	ADP
admet-2772	397	17	-	-	PUNCT
admet-2772	397	18	the	the	DET
admet-2772	397	19	-	-	PUNCT
admet-2772	397	20	art	art	NOUN
admet-2772	397	21	results	result	NOUN
admet-2772	397	22	in	in	ADP
admet-2772	397	23	multiple	multiple	ADJ
admet-2772	397	24	tasks	task	NOUN
admet-2772	397	25	[	[	X
admet-2772	397	26	158	158	NUM
admet-2772	397	27	]	]	PUNCT
admet-2772	397	28	.	.	PUNCT
admet-2772	398	1	the	the	DET
admet-2772	398	2	remedi	remedi	PROPN
admet-2772	398	3	framework	framework	NOUN
admet-2772	398	4	uses	use	VERB
admet-2772	398	5	reinforcement	reinforcement	NOUN
admet-2772	398	6	learning	learning	NOUN
admet-2772	398	7	to	to	PART
admet-2772	398	8	model	model	VERB
admet-2772	398	9	bile	bile	NOUN
admet-2772	398	10	acid	acid	NOUN
admet-2772	398	11	metabolism	metabolism	NOUN
admet-2772	398	12	adaptations	adaptation	NOUN
admet-2772	398	13	in	in	ADP
admet-2772	398	14	primary	primary	ADJ
admet-2772	398	15	sclerosing	sclerose	VERB
admet-2772	398	16	cholangitis	cholangitis	NOUN
admet-2772	398	17	,	,	PUNCT
admet-2772	398	18	demonstrating	demonstrate	VERB
admet-2772	398	19	potential	potential	NOUN
admet-2772	398	20	for	for	ADP
admet-2772	398	21	exploring	explore	VERB
admet-2772	398	22	treatments	treatment	NOUN
admet-2772	398	23	[	[	X
admet-2772	398	24	159	159	NUM
admet-2772	398	25	]	]	PUNCT
admet-2772	398	26	.	.	PUNCT
admet-2772	399	1	rl	rl	PROPN
admet-2772	399	2	is	be	AUX
admet-2772	399	3	emerging	emerge	VERB
admet-2772	399	4	as	as	ADP
admet-2772	399	5	a	a	DET
admet-2772	399	6	powerful	powerful	ADJ
admet-2772	399	7	tool	tool	NOUN
admet-2772	399	8	in	in	ADP
admet-2772	399	9	drug	drug	NOUN
admet-2772	399	10	discovery	discovery	NOUN
admet-2772	399	11	and	and	CCONJ
admet-2772	399	12	development	development	NOUN
admet-2772	399	13	,	,	PUNCT
admet-2772	399	14	offering	offer	VERB
admet-2772	399	15	potential	potential	NOUN
admet-2772	399	16	to	to	PART
admet-2772	399	17	accelerate	accelerate	VERB
admet-2772	399	18	and	and	CCONJ
admet-2772	399	19	optimize	optimize	VERB
admet-2772	399	20	the	the	DET
admet-2772	399	21	process	process	NOUN
admet-2772	399	22	.	.	PUNCT
admet-2772	400	1	rl	rl	VERB
admet-2772	400	2	algorithms	algorithm	NOUN
admet-2772	400	3	can	can	AUX
admet-2772	400	4	improve	improve	VERB
admet-2772	400	5	sample	sample	NOUN
admet-2772	400	6	efficiency	efficiency	NOUN
admet-2772	400	7	and	and	CCONJ
admet-2772	400	8	policy	policy	NOUN
admet-2772	400	9	optimization	optimization	NOUN
admet-2772	400	10	for	for	ADP
admet-2772	400	11	de	de	X
admet-2772	400	12	novo	novo	PROPN
admet-2772	400	13	drug	drug	NOUN
admet-2772	400	14	design	design	NOUN
admet-2772	400	15	[	[	X
admet-2772	400	16	160	160	NUM
admet-2772	400	17	]	]	PUNCT
admet-2772	400	18	.	.	PUNCT
admet-2772	401	1	these	these	DET
admet-2772	401	2	approaches	approach	NOUN
admet-2772	401	3	enable	enable	VERB
admet-2772	401	4	simultaneous	simultaneous	ADJ
admet-2772	401	5	optimization	optimization	NOUN
admet-2772	401	6	of	of	ADP
admet-2772	401	7	molecules	molecule	NOUN
admet-2772	401	8	for	for	ADP
admet-2772	401	9	multiple	multiple	ADJ
admet-2772	401	10	goals	goal	NOUN
admet-2772	401	11	through	through	ADP
admet-2772	401	12	structure	structure	NOUN
admet-2772	401	13	-	-	PUNCT
admet-2772	401	14	based	base	VERB
admet-2772	401	15	drug	drug	NOUN
admet-2772	401	16	design	design	NOUN
admet-2772	401	17	and	and	CCONJ
admet-2772	401	18	highthroughput	highthroughput	NOUN
admet-2772	401	19	screening	screening	NOUN
admet-2772	401	20	;	;	PUNCT
admet-2772	401	21	one	one	NUM
admet-2772	401	22	such	such	ADJ
admet-2772	401	23	example	example	NOUN
admet-2772	401	24	is	be	AUX
admet-2772	401	25	where	where	SCONJ
admet-2772	401	26	rf	rf	NOUN
admet-2772	401	27	has	have	AUX
admet-2772	401	28	been	be	AUX
admet-2772	401	29	applied	apply	VERB
admet-2772	401	30	to	to	PART
admet-2772	401	31	optimize	optimize	VERB
admet-2772	401	32	failed	fail	VERB
admet-2772	401	33	anticancer	anticancer	NOUN
admet-2772	401	34	drugs	drug	NOUN
admet-2772	401	35	by	by	ADP
admet-2772	401	36	considering	consider	VERB
admet-2772	401	37	multiple	multiple	ADJ
admet-2772	401	38	properties	property	NOUN
admet-2772	401	39	simultaneously	simultaneously	ADV
admet-2772	401	40	,	,	PUNCT
admet-2772	401	41	including	include	VERB
admet-2772	401	42	binding	bind	VERB
admet-2772	401	43	affinity	affinity	NOUN
admet-2772	401	44	and	and	CCONJ
admet-2772	401	45	toxicity	toxicity	NOUN
admet-2772	401	46	profiles	profile	NOUN
admet-2772	401	47	[	[	X
admet-2772	401	48	161	161	NUM
admet-2772	401	49	]	]	PUNCT
admet-2772	401	50	.	.	PUNCT
admet-2772	402	1	6	6	X
admet-2772	402	2	.	.	X
admet-2772	402	3	recent	recent	ADJ
admet-2772	402	4	developments	development	NOUN
admet-2772	402	5	in	in	ADP
admet-2772	402	6	admet	admet	PROPN
admet-2772	402	7	modeling	model	VERB
admet-2772	402	8	6.1	6.1	NUM
admet-2772	402	9	.	.	PUNCT
admet-2772	403	1	integration	integration	NOUN
admet-2772	403	2	of	of	ADP
admet-2772	403	3	machine	machine	NOUN
admet-2772	403	4	learning	learning	NOUN
admet-2772	403	5	methods	method	NOUN
admet-2772	403	6	with	with	ADP
admet-2772	403	7	physiologically	physiologically	ADV
admet-2772	403	8	-	-	PUNCT
admet-2772	403	9	based	base	VERB
admet-2772	403	10	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	403	11	and	and	CCONJ
admet-2772	403	12	quantitative	quantitative	ADJ
admet-2772	403	13	structure	structure	NOUN
admet-2772	403	14	-	-	PUNCT
admet-2772	403	15	activity	activity	NOUN
admet-2772	403	16	relationship	relationship	NOUN
admet-2772	403	17	models	model	NOUN
admet-2772	403	18	physiologically	physiologically	ADV
admet-2772	403	19	-	-	PUNCT
admet-2772	403	20	based	base	VERB
admet-2772	403	21	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	403	22	(	(	PUNCT
admet-2772	403	23	pbpk	pbpk	NOUN
admet-2772	403	24	)	)	PUNCT
admet-2772	403	25	models	model	NOUN
admet-2772	403	26	are	be	AUX
admet-2772	403	27	mathematical	mathematical	ADJ
admet-2772	403	28	representations	representation	NOUN
admet-2772	403	29	of	of	ADP
admet-2772	403	30	how	how	SCONJ
admet-2772	403	31	chemicals	chemical	NOUN
admet-2772	403	32	enter	enter	VERB
admet-2772	403	33	the	the	DET
admet-2772	403	34	body	body	NOUN
admet-2772	403	35	through	through	ADP
admet-2772	403	36	various	various	ADJ
admet-2772	403	37	routes	route	NOUN
admet-2772	403	38	such	such	ADJ
admet-2772	403	39	as	as	ADP
admet-2772	403	40	inhalation	inhalation	NOUN
admet-2772	403	41	,	,	PUNCT
admet-2772	403	42	ingestion	ingestion	NOUN
admet-2772	403	43	,	,	PUNCT
admet-2772	403	44	or	or	CCONJ
admet-2772	403	45	dermal	dermal	ADJ
admet-2772	403	46	exposure	exposure	NOUN
admet-2772	403	47	.	.	PUNCT
admet-2772	404	1	these	these	DET
admet-2772	404	2	models	model	NOUN
admet-2772	404	3	describe	describe	VERB
admet-2772	404	4	how	how	SCONJ
admet-2772	404	5	much	much	ADJ
admet-2772	404	6	of	of	ADP
admet-2772	404	7	the	the	DET
admet-2772	404	8	chemical	chemical	NOUN
admet-2772	404	9	enters	enter	VERB
admet-2772	404	10	the	the	DET
admet-2772	404	11	bloodstream	bloodstream	NOUN
admet-2772	404	12	,	,	PUNCT
admet-2772	404	13	its	its	PRON
admet-2772	404	14	distribution	distribution	NOUN
admet-2772	404	15	among	among	ADP
admet-2772	404	16	different	different	ADJ
admet-2772	404	17	tissues	tissue	NOUN
admet-2772	404	18	,	,	PUNCT
admet-2772	404	19	and	and	CCONJ
admet-2772	404	20	how	how	SCONJ
admet-2772	404	21	the	the	DET
admet-2772	404	22	body	body	NOUN
admet-2772	404	23	metabolizes	metabolize	VERB
admet-2772	404	24	and	and	CCONJ
admet-2772	404	25	eliminates	eliminate	VERB
admet-2772	404	26	it	it	PRON
admet-2772	404	27	[	[	X
admet-2772	404	28	162	162	NUM
admet-2772	404	29	]	]	PUNCT
admet-2772	404	30	.	.	PUNCT
admet-2772	405	1	they	they	PRON
admet-2772	405	2	incorporate	incorporate	VERB
admet-2772	405	3	information	information	NOUN
admet-2772	405	4	about	about	ADP
admet-2772	405	5	the	the	DET
admet-2772	405	6	body	body	NOUN
admet-2772	405	7	's	's	PART
admet-2772	405	8	anatomy	anatomy	NOUN
admet-2772	405	9	,	,	PUNCT
admet-2772	405	10	physiology	physiology	NOUN
admet-2772	405	11	,	,	PUNCT
admet-2772	405	12	and	and	CCONJ
admet-2772	405	13	biochemical	biochemical	ADJ
admet-2772	405	14	processes	process	NOUN
admet-2772	405	15	.	.	PUNCT
admet-2772	406	1	pbpk	pbpk	NOUN
admet-2772	406	2	models	model	NOUN
admet-2772	406	3	can	can	AUX
admet-2772	406	4	range	range	VERB
admet-2772	406	5	from	from	ADP
admet-2772	406	6	simple	simple	ADJ
admet-2772	406	7	versions	version	NOUN
admet-2772	406	8	with	with	ADP
admet-2772	406	9	few	few	ADJ
admet-2772	406	10	features	feature	NOUN
admet-2772	406	11	to	to	ADP
admet-2772	406	12	complex	complex	ADJ
admet-2772	406	13	ones	one	NOUN
admet-2772	406	14	that	that	PRON
admet-2772	406	15	capture	capture	VERB
admet-2772	406	16	intricate	intricate	ADJ
admet-2772	406	17	details	detail	NOUN
admet-2772	406	18	about	about	ADP
admet-2772	406	19	chemical	chemical	NOUN
admet-2772	406	20	movement	movement	NOUN
admet-2772	406	21	and	and	CCONJ
admet-2772	406	22	fate	fate	NOUN
admet-2772	406	23	in	in	ADP
admet-2772	406	24	the	the	DET
admet-2772	406	25	body	body	NOUN
admet-2772	406	26	[	[	X
admet-2772	406	27	163	163	NUM
admet-2772	406	28	]	]	PUNCT
admet-2772	406	29	.	.	PUNCT
admet-2772	407	1	however	however	ADV
admet-2772	407	2	,	,	PUNCT
admet-2772	407	3	creating	create	VERB
admet-2772	407	4	pbpk	pbpk	ADJ
admet-2772	407	5	models	model	NOUN
admet-2772	407	6	for	for	ADP
admet-2772	407	7	new	new	ADJ
admet-2772	407	8	chemicals	chemical	NOUN
admet-2772	407	9	is	be	AUX
admet-2772	407	10	challenging	challenge	VERB
admet-2772	407	11	due	due	ADJ
admet-2772	407	12	to	to	ADP
admet-2772	407	13	their	their	PRON
admet-2772	407	14	complexity	complexity	NOUN
admet-2772	407	15	and	and	CCONJ
admet-2772	407	16	the	the	DET
admet-2772	407	17	numerous	numerous	ADJ
admet-2772	407	18	parameters	parameter	NOUN
admet-2772	407	19	involved	involve	VERB
admet-2772	407	20	[	[	PUNCT
admet-2772	407	21	163	163	NUM
admet-2772	407	22	]	]	PUNCT
admet-2772	407	23	.	.	PUNCT
admet-2772	408	1	to	to	PART
admet-2772	408	2	address	address	VERB
admet-2772	408	3	this	this	PRON
admet-2772	408	4	,	,	PUNCT
admet-2772	408	5	some	some	DET
admet-2772	408	6	researchers	researcher	NOUN
admet-2772	408	7	have	have	AUX
admet-2772	408	8	proposed	propose	VERB
admet-2772	408	9	an	an	DET
admet-2772	408	10	integrated	integrated	ADJ
admet-2772	408	11	approach	approach	NOUN
admet-2772	408	12	that	that	PRON
admet-2772	408	13	combines	combine	VERB
admet-2772	408	14	a	a	DET
admet-2772	408	15	simplified	simplified	ADJ
admet-2772	408	16	pbpk	pbpk	ADJ
admet-2772	408	17	model	model	NOUN
admet-2772	408	18	with	with	ADP
admet-2772	408	19	machine	machine	NOUN
admet-2772	408	20	learning	learning	NOUN
admet-2772	408	21	based	base	VERB
admet-2772	408	22	quantitative	quantitative	ADJ
admet-2772	408	23	structure	structure	NOUN
admet-2772	408	24	-	-	PUNCT
admet-2772	408	25	activity	activity	NOUN
admet-2772	408	26	relationship	relationship	NOUN
admet-2772	408	27	(	(	PUNCT
admet-2772	408	28	qsar	qsar	NOUN
admet-2772	408	29	)	)	PUNCT
admet-2772	408	30	models	model	NOUN
admet-2772	409	1	[	[	X
admet-2772	409	2	164	164	NUM
admet-2772	409	3	]	]	PUNCT
admet-2772	409	4	.	.	PUNCT
admet-2772	410	1	this	this	DET
admet-2772	410	2	integrated	integrate	VERB
admet-2772	410	3	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	410	4	m.	m.	NOUN
admet-2772	410	5	venkataraman	venkataraman	PROPN
admet-2772	410	6	et	et	PROPN
admet-2772	410	7	al	al	PROPN
admet-2772	410	8	.	.	PROPN
admet-2772	410	9	admet	admet	PROPN
admet-2772	410	10	&	&	CCONJ
admet-2772	410	11	dmpk	dmpk	PROPN
admet-2772	410	12	13(3	13(3	NUM
admet-2772	410	13	)	)	PUNCT
admet-2772	410	14	(	(	PUNCT
admet-2772	410	15	2025	2025	NUM
admet-2772	410	16	)	)	PUNCT
admet-2772	410	17	2772	2772	NUM
admet-2772	410	18	16	16	NUM
admet-2772	410	19	approach	approach	NOUN
admet-2772	410	20	aims	aim	VERB
admet-2772	410	21	to	to	PART
admet-2772	410	22	estimate	estimate	VERB
admet-2772	410	23	plasma	plasma	NOUN
admet-2772	410	24	and	and	CCONJ
admet-2772	410	25	tissue	tissue	NOUN
admet-2772	410	26	concentrations	concentration	NOUN
admet-2772	410	27	,	,	PUNCT
admet-2772	410	28	as	as	ADV
admet-2772	410	29	well	well	ADV
admet-2772	410	30	as	as	ADP
admet-2772	410	31	various	various	ADJ
admet-2772	410	32	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	410	33	(	(	PUNCT
admet-2772	410	34	pk	pk	NOUN
admet-2772	410	35	)	)	PUNCT
admet-2772	410	36	parameters	parameter	NOUN
admet-2772	410	37	,	,	PUNCT
admet-2772	410	38	by	by	ADP
admet-2772	410	39	leveraging	leverage	VERB
admet-2772	410	40	databases	database	NOUN
admet-2772	410	41	containing	contain	VERB
admet-2772	410	42	in	in	ADP
admet-2772	410	43	vivo	vivo	NOUN
admet-2772	410	44	and	and	CCONJ
admet-2772	410	45	in	in	ADP
admet-2772	410	46	vitro	vitro	X
admet-2772	410	47	data	datum	NOUN
admet-2772	410	48	along	along	ADP
admet-2772	410	49	with	with	ADP
admet-2772	410	50	the	the	DET
admet-2772	410	51	structural	structural	ADJ
admet-2772	410	52	and	and	CCONJ
admet-2772	410	53	physicochemical	physicochemical	ADJ
admet-2772	410	54	properties	property	NOUN
admet-2772	410	55	of	of	ADP
admet-2772	410	56	selected	select	VERB
admet-2772	410	57	compounds	compound	NOUN
admet-2772	410	58	.	.	PUNCT
admet-2772	411	1	ml	ml	NOUN
admet-2772	411	2	models	model	NOUN
admet-2772	411	3	are	be	AUX
admet-2772	411	4	trained	train	VERB
admet-2772	411	5	using	use	VERB
admet-2772	411	6	these	these	DET
admet-2772	411	7	databases	database	NOUN
admet-2772	411	8	to	to	PART
admet-2772	411	9	predict	predict	VERB
admet-2772	411	10	adme	adme	NOUN
admet-2772	411	11	parameters	parameter	NOUN
admet-2772	411	12	,	,	PUNCT
admet-2772	411	13	which	which	PRON
admet-2772	411	14	are	be	AUX
admet-2772	411	15	then	then	ADV
admet-2772	411	16	incorporated	incorporate	VERB
admet-2772	411	17	into	into	ADP
admet-2772	411	18	the	the	DET
admet-2772	411	19	pbpk	pbpk	ADJ
admet-2772	411	20	model	model	NOUN
admet-2772	411	21	to	to	PART
admet-2772	411	22	simulate	simulate	VERB
admet-2772	411	23	time	time	NOUN
admet-2772	411	24	-	-	PUNCT
admet-2772	411	25	concentration	concentration	NOUN
admet-2772	411	26	profiles	profile	NOUN
admet-2772	411	27	and	and	CCONJ
admet-2772	411	28	calculate	calculate	VERB
admet-2772	411	29	pk	pk	NOUN
admet-2772	411	30	parameters	parameter	NOUN
admet-2772	411	31	such	such	ADJ
admet-2772	411	32	as	as	ADP
admet-2772	411	33	area	area	NOUN
admet-2772	411	34	under	under	ADP
admet-2772	411	35	the	the	DET
admet-2772	411	36	curve	curve	NOUN
admet-2772	411	37	(	(	PUNCT
admet-2772	411	38	auc	auc	NOUN
admet-2772	411	39	)	)	PUNCT
admet-2772	411	40	and	and	CCONJ
admet-2772	411	41	maximum	maximum	ADJ
admet-2772	411	42	concentration	concentration	NOUN
admet-2772	411	43	(	(	PUNCT
admet-2772	411	44	cmax	cmax	NOUN
admet-2772	411	45	)	)	PUNCT
admet-2772	411	46	.	.	PUNCT
admet-2772	412	1	the	the	DET
admet-2772	412	2	performance	performance	NOUN
admet-2772	412	3	of	of	ADP
admet-2772	412	4	the	the	DET
admet-2772	412	5	integrated	integrate	VERB
admet-2772	412	6	ml	ml	NOUN
admet-2772	412	7	-	-	PUNCT
admet-2772	412	8	based	base	VERB
admet-2772	412	9	pbpk	pbpk	NOUN
admet-2772	412	10	model	model	NOUN
admet-2772	412	11	is	be	AUX
admet-2772	412	12	assessed	assess	VERB
admet-2772	412	13	against	against	ADP
admet-2772	412	14	in	in	ADP
admet-2772	412	15	vivo	vivo	ADJ
admet-2772	412	16	pk	pk	NOUN
admet-2772	412	17	data	datum	NOUN
admet-2772	412	18	,	,	PUNCT
admet-2772	412	19	and	and	CCONJ
admet-2772	412	20	if	if	SCONJ
admet-2772	412	21	satisfactory	satisfactory	ADJ
admet-2772	412	22	,	,	PUNCT
admet-2772	412	23	the	the	DET
admet-2772	412	24	model	model	NOUN
admet-2772	412	25	can	can	AUX
admet-2772	412	26	be	be	AUX
admet-2772	412	27	used	use	VERB
admet-2772	412	28	to	to	PART
admet-2772	412	29	generate	generate	VERB
admet-2772	412	30	simulation	simulation	NOUN
admet-2772	412	31	data	datum	NOUN
admet-2772	412	32	for	for	ADP
admet-2772	412	33	further	further	ADJ
admet-2772	412	34	refinement	refinement	NOUN
admet-2772	412	35	and	and	CCONJ
admet-2772	412	36	validation	validation	NOUN
admet-2772	413	1	[	[	X
admet-2772	413	2	165	165	NUM
admet-2772	413	3	]	]	PUNCT
admet-2772	413	4	.	.	PUNCT
admet-2772	414	1	this	this	DET
admet-2772	414	2	approach	approach	NOUN
admet-2772	414	3	aims	aim	VERB
admet-2772	414	4	to	to	PART
admet-2772	414	5	enhance	enhance	VERB
admet-2772	414	6	efficiency	efficiency	NOUN
admet-2772	414	7	in	in	ADP
admet-2772	414	8	drug	drug	NOUN
admet-2772	414	9	development	development	NOUN
admet-2772	414	10	and	and	CCONJ
admet-2772	414	11	reduce	reduce	VERB
admet-2772	414	12	animal	animal	NOUN
admet-2772	414	13	testing	testing	NOUN
admet-2772	414	14	[	[	X
admet-2772	414	15	166	166	NUM
admet-2772	414	16	]	]	PUNCT
admet-2772	414	17	.	.	PUNCT
admet-2772	415	1	a	a	DET
admet-2772	415	2	novel	novel	ADJ
admet-2772	415	3	computational	computational	ADJ
admet-2772	415	4	platform	platform	NOUN
admet-2772	415	5	combining	combine	VERB
admet-2772	415	6	ml	ml	NOUN
admet-2772	415	7	and	and	CCONJ
admet-2772	415	8	pbpk	pbpk	NOUN
admet-2772	415	9	models	model	NOUN
admet-2772	415	10	has	have	AUX
admet-2772	415	11	demonstrated	demonstrate	VERB
admet-2772	415	12	improved	improved	ADJ
admet-2772	415	13	accuracy	accuracy	NOUN
admet-2772	415	14	in	in	ADP
admet-2772	415	15	predicting	predict	VERB
admet-2772	415	16	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	415	17	profiles	profile	NOUN
admet-2772	415	18	without	without	ADP
admet-2772	415	19	experimental	experimental	ADJ
admet-2772	415	20	data	datum	NOUN
admet-2772	415	21	,	,	PUNCT
admet-2772	415	22	potentially	potentially	ADV
admet-2772	415	23	accelerating	accelerate	VERB
admet-2772	415	24	early	early	ADJ
admet-2772	415	25	drug	drug	NOUN
admet-2772	415	26	discovery	discovery	NOUN
admet-2772	416	1	[	[	X
admet-2772	416	2	167	167	NUM
admet-2772	416	3	]	]	PUNCT
admet-2772	416	4	.	.	PUNCT
admet-2772	417	1	additionally	additionally	ADV
admet-2772	417	2	,	,	PUNCT
admet-2772	417	3	adapting	adapt	VERB
admet-2772	417	4	pbpk	pbpk	NOUN
admet-2772	417	5	models	model	NOUN
admet-2772	417	6	for	for	ADP
admet-2772	417	7	ml	ml	NOUN
admet-2772	417	8	applications	application	NOUN
admet-2772	417	9	has	have	AUX
admet-2772	417	10	shown	show	VERB
admet-2772	417	11	promise	promise	NOUN
admet-2772	417	12	in	in	ADP
admet-2772	417	13	recapitulating	recapitulate	VERB
admet-2772	417	14	summary	summary	NOUN
admet-2772	417	15	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	417	16	parameters	parameter	NOUN
admet-2772	417	17	,	,	PUNCT
admet-2772	417	18	although	although	SCONJ
admet-2772	417	19	limitations	limitation	NOUN
admet-2772	417	20	in	in	ADP
admet-2772	417	21	the	the	DET
admet-2772	417	22	underlying	underlying	ADJ
admet-2772	417	23	pbpk	pbpk	ADJ
admet-2772	417	24	models	model	NOUN
admet-2772	417	25	may	may	AUX
admet-2772	417	26	affect	affect	VERB
admet-2772	417	27	prediction	prediction	NOUN
admet-2772	417	28	accuracy	accuracy	NOUN
admet-2772	418	1	[	[	X
admet-2772	418	2	169	169	NUM
admet-2772	418	3	]	]	PUNCT
admet-2772	418	4	.	.	PUNCT
admet-2772	419	1	despite	despite	SCONJ
admet-2772	419	2	challenges	challenge	NOUN
admet-2772	419	3	such	such	ADJ
admet-2772	419	4	as	as	ADP
admet-2772	419	5	the	the	DET
admet-2772	419	6	need	need	NOUN
admet-2772	419	7	for	for	ADP
admet-2772	419	8	diverse	diverse	ADJ
admet-2772	419	9	training	training	NOUN
admet-2772	419	10	data	datum	NOUN
admet-2772	419	11	and	and	CCONJ
admet-2772	419	12	improved	improve	VERB
admet-2772	419	13	interpretability	interpretability	NOUN
admet-2772	419	14	of	of	ADP
admet-2772	419	15	ml	ml	NOUN
admet-2772	419	16	models	model	NOUN
admet-2772	419	17	,	,	PUNCT
admet-2772	419	18	the	the	DET
admet-2772	419	19	integration	integration	NOUN
admet-2772	419	20	of	of	ADP
admet-2772	419	21	ml	ml	NOUN
admet-2772	419	22	/	/	SYM
admet-2772	419	23	ai	ai	PROPN
admet-2772	419	24	approaches	approach	NOUN
admet-2772	419	25	with	with	ADP
admet-2772	419	26	pbpk	pbpk	NOUN
admet-2772	419	27	modelling	modelling	NOUN
admet-2772	419	28	is	be	AUX
admet-2772	419	29	expected	expect	VERB
admet-2772	419	30	to	to	PART
admet-2772	419	31	facilitate	facilitate	VERB
admet-2772	419	32	more	more	ADV
admet-2772	419	33	efficient	efficient	ADJ
admet-2772	419	34	and	and	CCONJ
admet-2772	419	35	robust	robust	ADJ
admet-2772	419	36	admet	admet	NOUN
admet-2772	419	37	predictions	prediction	NOUN
admet-2772	419	38	for	for	ADP
admet-2772	419	39	a	a	DET
admet-2772	419	40	wide	wide	ADJ
admet-2772	419	41	range	range	NOUN
admet-2772	419	42	of	of	ADP
admet-2772	419	43	chemicals	chemical	NOUN
admet-2772	419	44	[	[	X
admet-2772	419	45	165	165	NUM
admet-2772	419	46	]	]	PUNCT
admet-2772	419	47	.	.	PUNCT
admet-2772	420	1	6.2	6.2	NUM
admet-2772	420	2	.	.	PUNCT
admet-2772	421	1	generalization	generalization	NOUN
admet-2772	421	2	6.2.1	6.2.1	NOUN
admet-2772	421	3	.	.	PUNCT
admet-2772	422	1	multi	multi	ADJ
admet-2772	422	2	-	-	NOUN
admet-2772	422	3	task	task	ADJ
admet-2772	422	4	learning	learning	NOUN
admet-2772	422	5	while	while	SCONJ
admet-2772	422	6	each	each	DET
admet-2772	422	7	admet	admet	NOUN
admet-2772	422	8	parameter	parameter	NOUN
admet-2772	422	9	can	can	AUX
admet-2772	422	10	be	be	AUX
admet-2772	422	11	studied	study	VERB
admet-2772	422	12	independently	independently	ADV
admet-2772	422	13	,	,	PUNCT
admet-2772	422	14	they	they	PRON
admet-2772	422	15	are	be	AUX
admet-2772	422	16	interconnected	interconnected	ADJ
admet-2772	422	17	and	and	CCONJ
admet-2772	422	18	influence	influence	VERB
admet-2772	422	19	each	each	DET
admet-2772	422	20	other	other	ADJ
admet-2772	422	21	throughout	throughout	ADP
admet-2772	422	22	the	the	DET
admet-2772	422	23	drug	drug	NOUN
admet-2772	422	24	development	development	NOUN
admet-2772	422	25	process	process	NOUN
admet-2772	422	26	.	.	PUNCT
admet-2772	423	1	therefore	therefore	ADV
admet-2772	423	2	,	,	PUNCT
admet-2772	423	3	admet	admet	PROPN
admet-2772	423	4	is	be	AUX
admet-2772	423	5	not	not	PART
admet-2772	423	6	a	a	DET
admet-2772	423	7	sequential	sequential	ADJ
admet-2772	423	8	process	process	NOUN
admet-2772	423	9	but	but	CCONJ
admet-2772	423	10	rather	rather	ADV
admet-2772	423	11	a	a	DET
admet-2772	423	12	holistic	holistic	ADJ
admet-2772	423	13	approach	approach	NOUN
admet-2772	423	14	that	that	PRON
admet-2772	423	15	considers	consider	VERB
admet-2772	423	16	the	the	DET
admet-2772	423	17	interplay	interplay	NOUN
admet-2772	423	18	between	between	ADP
admet-2772	423	19	absorption	absorption	NOUN
admet-2772	423	20	,	,	PUNCT
admet-2772	423	21	distribution	distribution	NOUN
admet-2772	423	22	,	,	PUNCT
admet-2772	423	23	metabolism	metabolism	NOUN
admet-2772	423	24	,	,	PUNCT
admet-2772	423	25	excretion	excretion	NOUN
admet-2772	423	26	,	,	PUNCT
admet-2772	423	27	and	and	CCONJ
admet-2772	423	28	toxicity	toxicity	NOUN
admet-2772	423	29	to	to	PART
admet-2772	423	30	predict	predict	VERB
admet-2772	423	31	drug	drug	NOUN
admet-2772	423	32	behaviour	behaviour	NOUN
admet-2772	423	33	accurately	accurately	ADV
admet-2772	423	34	[	[	X
admet-2772	423	35	14	14	NUM
admet-2772	423	36	]	]	PUNCT
admet-2772	423	37	.	.	PUNCT
admet-2772	424	1	considering	consider	VERB
admet-2772	424	2	this	this	PRON
admet-2772	424	3	,	,	PUNCT
admet-2772	424	4	it	it	PRON
admet-2772	424	5	would	would	AUX
admet-2772	424	6	be	be	AUX
admet-2772	424	7	practical	practical	ADJ
admet-2772	424	8	to	to	PART
admet-2772	424	9	develop	develop	VERB
admet-2772	424	10	a	a	DET
admet-2772	424	11	reliable	reliable	ADJ
admet-2772	424	12	multitask	multitask	ADJ
admet-2772	424	13	model	model	NOUN
admet-2772	424	14	that	that	PRON
admet-2772	424	15	could	could	AUX
admet-2772	424	16	simultaneously	simultaneously	ADV
admet-2772	424	17	predict	predict	VERB
admet-2772	424	18	multiple	multiple	ADJ
admet-2772	424	19	adme	adme	NOUN
admet-2772	424	20	endpoints	endpoint	NOUN
admet-2772	424	21	.	.	PUNCT
admet-2772	425	1	despite	despite	SCONJ
admet-2772	425	2	the	the	DET
admet-2772	425	3	advancements	advancement	NOUN
admet-2772	425	4	made	make	VERB
admet-2772	425	5	by	by	ADP
admet-2772	425	6	classical	classical	ADJ
admet-2772	425	7	single	single	ADJ
admet-2772	425	8	-	-	PUNCT
admet-2772	425	9	task	task	NOUN
admet-2772	425	10	learning	learning	NOUN
admet-2772	425	11	in	in	ADP
admet-2772	425	12	predicting	predict	VERB
admet-2772	425	13	individual	individual	ADJ
admet-2772	425	14	admet	admet	PROPN
admet-2772	425	15	endpoints	endpoint	NOUN
admet-2772	425	16	using	use	VERB
admet-2772	425	17	abundant	abundant	ADJ
admet-2772	425	18	labelled	label	VERB
admet-2772	425	19	data	datum	NOUN
admet-2772	425	20	,	,	PUNCT
admet-2772	425	21	multi	multi	ADJ
admet-2772	425	22	-	-	ADJ
admet-2772	425	23	task	task	ADJ
admet-2772	425	24	learning	learning	NOUN
admet-2772	425	25	(	(	PUNCT
admet-2772	425	26	mtl	mtl	PROPN
admet-2772	425	27	)	)	PUNCT
admet-2772	425	28	emerges	emerge	VERB
admet-2772	425	29	as	as	ADP
admet-2772	425	30	a	a	DET
admet-2772	425	31	promising	promising	ADJ
admet-2772	425	32	paradigm	paradigm	NOUN
admet-2772	425	33	,	,	PUNCT
admet-2772	425	34	offering	offer	VERB
admet-2772	425	35	a	a	DET
admet-2772	425	36	solution	solution	NOUN
admet-2772	425	37	that	that	PRON
admet-2772	425	38	reduces	reduce	VERB
admet-2772	425	39	reliance	reliance	NOUN
admet-2772	425	40	on	on	ADP
admet-2772	425	41	endpoint	endpoint	NOUN
admet-2772	425	42	labels	label	NOUN
admet-2772	425	43	while	while	SCONJ
admet-2772	425	44	simultaneously	simultaneously	ADV
admet-2772	425	45	predicting	predict	VERB
admet-2772	425	46	multiple	multiple	ADJ
admet-2772	425	47	admet	admet	X
admet-2772	425	48	endpoints	endpoint	NOUN
admet-2772	425	49	[	[	X
admet-2772	425	50	169	169	NUM
admet-2772	425	51	]	]	PUNCT
admet-2772	425	52	.	.	PUNCT
admet-2772	426	1	by	by	ADP
admet-2772	426	2	leveraging	leverage	VERB
admet-2772	426	3	shared	share	VERB
admet-2772	426	4	information	information	NOUN
admet-2772	426	5	and	and	CCONJ
admet-2772	426	6	underlying	underlying	ADJ
admet-2772	426	7	correlations	correlation	NOUN
admet-2772	426	8	between	between	ADP
admet-2772	426	9	different	different	ADJ
admet-2772	426	10	admet	admet	NOUN
admet-2772	426	11	properties	property	NOUN
admet-2772	426	12	,	,	PUNCT
admet-2772	426	13	mtl	mtl	PROPN
admet-2772	426	14	provides	provide	VERB
admet-2772	426	15	a	a	DET
admet-2772	426	16	more	more	ADV
admet-2772	426	17	comprehensive	comprehensive	ADJ
admet-2772	426	18	and	and	CCONJ
admet-2772	426	19	efficient	efficient	ADJ
admet-2772	426	20	framework	framework	NOUN
admet-2772	426	21	for	for	ADP
admet-2772	426	22	predictive	predictive	ADJ
admet-2772	426	23	modelling	modelling	NOUN
admet-2772	426	24	in	in	ADP
admet-2772	426	25	admet	admet	PROPN
admet-2772	426	26	studies	study	NOUN
admet-2772	426	27	.	.	PUNCT
admet-2772	427	1	for	for	ADP
admet-2772	427	2	example	example	NOUN
admet-2772	427	3	,	,	PUNCT
admet-2772	427	4	wenzel	wenzel	PROPN
admet-2772	427	5	et	et	PROPN
admet-2772	427	6	al	al	PROPN
admet-2772	427	7	.	.	PUNCT
admet-2772	428	1	[	[	X
admet-2772	428	2	145	145	NUM
admet-2772	428	3	]	]	PUNCT
admet-2772	428	4	introduced	introduce	VERB
admet-2772	428	5	an	an	DET
admet-2772	428	6	industrialized	industrialized	ADJ
admet-2772	428	7	approach	approach	NOUN
admet-2772	428	8	for	for	ADP
admet-2772	428	9	optimizing	optimize	VERB
admet-2772	428	10	deep	deep	ADJ
admet-2772	428	11	neural	neural	ADJ
admet-2772	428	12	network	network	NOUN
admet-2772	428	13	(	(	PUNCT
admet-2772	428	14	dnn	dnn	PROPN
admet-2772	428	15	)	)	PUNCT
admet-2772	428	16	models	model	NOUN
admet-2772	428	17	to	to	PART
admet-2772	428	18	predict	predict	VERB
admet-2772	428	19	adme	adme	NOUN
admet-2772	428	20	-	-	PUNCT
admet-2772	428	21	tox	tox	NOUN
admet-2772	428	22	properties	property	NOUN
admet-2772	428	23	,	,	PUNCT
admet-2772	428	24	utilizing	utilize	VERB
admet-2772	428	25	up	up	ADP
admet-2772	428	26	to	to	PART
admet-2772	428	27	50,000	50,000	NUM
admet-2772	428	28	compounds	compound	NOUN
admet-2772	428	29	from	from	ADP
admet-2772	428	30	diverse	diverse	ADJ
admet-2772	428	31	databases	database	NOUN
admet-2772	428	32	.	.	PUNCT
admet-2772	429	1	the	the	DET
admet-2772	429	2	study	study	NOUN
admet-2772	429	3	highlights	highlight	VERB
admet-2772	429	4	the	the	DET
admet-2772	429	5	significance	significance	NOUN
admet-2772	429	6	of	of	ADP
admet-2772	429	7	dnn	dnn	PROPN
admet-2772	429	8	hyperparameters	hyperparameter	NOUN
admet-2772	429	9	and	and	CCONJ
admet-2772	429	10	molecular	molecular	ADJ
admet-2772	429	11	descriptors	descriptor	NOUN
admet-2772	429	12	in	in	ADP
admet-2772	429	13	model	model	NOUN
admet-2772	429	14	success	success	NOUN
admet-2772	429	15	,	,	PUNCT
admet-2772	429	16	demonstrating	demonstrate	VERB
admet-2772	429	17	the	the	DET
admet-2772	429	18	superiority	superiority	NOUN
admet-2772	429	19	of	of	ADP
admet-2772	429	20	multitask	multitask	ADJ
admet-2772	429	21	dnns	dnn	NOUN
admet-2772	429	22	in	in	ADP
admet-2772	429	23	predictive	predictive	ADJ
admet-2772	429	24	performance	performance	NOUN
admet-2772	429	25	across	across	ADP
admet-2772	429	26	various	various	ADJ
admet-2772	429	27	datasets	dataset	NOUN
admet-2772	429	28	.	.	PUNCT
admet-2772	430	1	for	for	ADP
admet-2772	430	2	instance	instance	NOUN
admet-2772	430	3	,	,	PUNCT
admet-2772	430	4	multitask	multitask	ADJ
admet-2772	430	5	dnns	dnn	NOUN
admet-2772	430	6	showed	show	VERB
admet-2772	430	7	improved	improve	VERB
admet-2772	430	8	predictive	predictive	ADJ
admet-2772	430	9	quality	quality	NOUN
admet-2772	430	10	compared	compare	VERB
admet-2772	430	11	to	to	ADP
admet-2772	430	12	single	single	ADJ
admet-2772	430	13	-	-	PUNCT
admet-2772	430	14	task	task	NOUN
admet-2772	430	15	models	model	NOUN
admet-2772	430	16	,	,	PUNCT
admet-2772	430	17	with	with	ADP
admet-2772	430	18	an	an	DET
admet-2772	430	19	increase	increase	NOUN
admet-2772	430	20	in	in	ADP
admet-2772	430	21	r2	r2	PROPN
admet-2772	430	22	from	from	ADP
admet-2772	430	23	0.6	0.6	NUM
admet-2772	430	24	to	to	ADP
admet-2772	430	25	0.7	0.7	NUM
admet-2772	430	26	for	for	ADP
admet-2772	430	27	human	human	ADJ
admet-2772	430	28	metabolic	metabolic	NOUN
admet-2772	430	29	stability	stability	NOUN
admet-2772	430	30	data	datum	NOUN
admet-2772	430	31	in	in	ADP
admet-2772	430	32	external	external	ADJ
admet-2772	430	33	validation	validation	NOUN
admet-2772	430	34	sets	set	NOUN
admet-2772	430	35	.	.	PUNCT
admet-2772	431	1	in	in	ADP
admet-2772	431	2	another	another	DET
admet-2772	431	3	study	study	NOUN
admet-2772	431	4	,	,	PUNCT
admet-2772	431	5	s.	s.	PROPN
admet-2772	431	6	zhang	zhang	PROPN
admet-2772	431	7	et	et	PROPN
admet-2772	431	8	al	al	PROPN
admet-2772	431	9	.	.	PUNCT
admet-2772	432	1	[	[	X
admet-2772	432	2	170	170	NUM
admet-2772	432	3	]	]	PUNCT
admet-2772	432	4	employ	employ	NOUN
admet-2772	432	5	machine	machine	NOUN
admet-2772	432	6	learning	learn	VERB
admet-2772	432	7	techniques	technique	NOUN
admet-2772	432	8	,	,	PUNCT
admet-2772	432	9	including	include	VERB
admet-2772	432	10	random	random	ADJ
admet-2772	432	11	forest	forest	NOUN
admet-2772	432	12	(	(	PUNCT
admet-2772	432	13	rf	rf	NOUN
admet-2772	432	14	)	)	PUNCT
admet-2772	432	15	and	and	CCONJ
admet-2772	432	16	artificial	artificial	ADJ
admet-2772	432	17	neural	neural	ADJ
admet-2772	432	18	network	network	NOUN
admet-2772	432	19	(	(	PUNCT
admet-2772	432	20	ann	ann	PROPN
admet-2772	432	21	)	)	PUNCT
admet-2772	432	22	,	,	PUNCT
admet-2772	432	23	to	to	PART
admet-2772	432	24	develop	develop	VERB
admet-2772	432	25	multi	multi	ADJ
admet-2772	432	26	-	-	NOUN
admet-2772	432	27	task	task	ADJ
admet-2772	432	28	(	(	PUNCT
admet-2772	432	29	mt	mt	PROPN
admet-2772	432	30	)	)	PUNCT
admet-2772	432	31	models	model	NOUN
admet-2772	432	32	for	for	ADP
admet-2772	432	33	predicting	predict	VERB
admet-2772	432	34	tissue	tissue	NOUN
admet-2772	432	35	-	-	PUNCT
admet-2772	432	36	to	to	ADP
admet-2772	432	37	-	-	PUNCT
admet-2772	432	38	blood	blood	NOUN
admet-2772	432	39	partition	partition	NOUN
admet-2772	432	40	coefficient	coefficient	NOUN
admet-2772	432	41	(	(	PUNCT
admet-2772	432	42	ptb	ptb	PROPN
admet-2772	432	43	)	)	PUNCT
admet-2772	432	44	values	value	NOUN
admet-2772	432	45	across	across	ADP
admet-2772	432	46	various	various	ADJ
admet-2772	432	47	mammalian	mammalian	ADJ
admet-2772	432	48	tissues	tissue	NOUN
admet-2772	432	49	.	.	PUNCT
admet-2772	433	1	compared	compare	VERB
admet-2772	433	2	to	to	ADP
admet-2772	433	3	single	single	ADJ
admet-2772	433	4	-	-	PUNCT
admet-2772	433	5	task	task	NOUN
admet-2772	433	6	(	(	PUNCT
admet-2772	433	7	st	st	NOUN
admet-2772	433	8	)	)	PUNCT
admet-2772	433	9	models	model	NOUN
admet-2772	433	10	,	,	PUNCT
admet-2772	433	11	the	the	DET
admet-2772	433	12	mt	mt	PROPN
admet-2772	433	13	approach	approach	NOUN
admet-2772	433	14	consistently	consistently	ADV
admet-2772	433	15	outperforms	outperform	NOUN
admet-2772	433	16	,	,	PUNCT
admet-2772	433	17	with	with	ADP
admet-2772	433	18	ann	ann	PROPN
admet-2772	433	19	-	-	PUNCT
admet-2772	433	20	based	base	VERB
admet-2772	433	21	mt	mt	PROPN
admet-2772	433	22	models	model	NOUN
admet-2772	433	23	exhibiting	exhibit	VERB
admet-2772	433	24	the	the	DET
admet-2772	433	25	highest	high	ADJ
admet-2772	433	26	prediction	prediction	NOUN
admet-2772	433	27	accuracy	accuracy	NOUN
admet-2772	433	28	,	,	PUNCT
admet-2772	433	29	showcasing	showcase	VERB
admet-2772	433	30	determination	determination	NOUN
admet-2772	433	31	coefficients	coefficient	NOUN
admet-2772	433	32	ranging	range	VERB
admet-2772	433	33	from	from	ADP
admet-2772	433	34	0.704	0.704	NUM
admet-2772	433	35	to	to	ADP
admet-2772	433	36	0.886	0.886	NUM
admet-2772	433	37	and	and	CCONJ
admet-2772	433	38	low	low	ADJ
admet-2772	433	39	root	root	NOUN
admet-2772	433	40	mean	mean	ADJ
admet-2772	433	41	square	square	ADJ
admet-2772	433	42	errors	error	NOUN
admet-2772	433	43	and	and	CCONJ
admet-2772	433	44	mean	mean	VERB
admet-2772	433	45	absolute	absolute	ADJ
admet-2772	433	46	errors	error	NOUN
admet-2772	433	47	across	across	ADP
admet-2772	433	48	multiple	multiple	ADJ
admet-2772	433	49	endpoints	endpoint	NOUN
admet-2772	433	50	.	.	PUNCT
admet-2772	434	1	the	the	DET
admet-2772	434	2	study	study	NOUN
admet-2772	434	3	by	by	ADP
admet-2772	434	4	walter	walter	PROPN
admet-2772	434	5	et	et	PROPN
admet-2772	434	6	al	al	PROPN
admet-2772	434	7	.	.	PUNCT
admet-2772	435	1	[	[	X
admet-2772	435	2	171	171	NUM
admet-2772	435	3	]	]	PUNCT
admet-2772	435	4	investigates	investigate	VERB
admet-2772	435	5	multi	multi	ADJ
admet-2772	435	6	-	-	ADJ
admet-2772	435	7	task	task	ADJ
admet-2772	435	8	machine	machine	NOUN
admet-2772	435	9	learning	learning	NOUN
admet-2772	435	10	models	model	NOUN
admet-2772	435	11	for	for	ADP
admet-2772	435	12	predicting	predict	VERB
admet-2772	435	13	adme	adme	NOUN
admet-2772	435	14	and	and	CCONJ
admet-2772	435	15	animal	animal	NOUN
admet-2772	435	16	pk	pk	NOUN
admet-2772	435	17	endpoints	endpoint	NOUN
admet-2772	435	18	using	use	VERB
admet-2772	435	19	in	in	ADP
admet-2772	435	20	-	-	PUNCT
admet-2772	435	21	house	house	NOUN
admet-2772	435	22	data	datum	NOUN
admet-2772	435	23	of	of	ADP
admet-2772	435	24	28	28	NUM
admet-2772	435	25	endpoints	endpoint	NOUN
admet-2772	435	26	.	.	PUNCT
admet-2772	436	1	it	it	PRON
admet-2772	436	2	reveals	reveal	VERB
admet-2772	436	3	the	the	DET
admet-2772	436	4	superior	superior	ADJ
admet-2772	436	5	performance	performance	NOUN
admet-2772	436	6	of	of	ADP
admet-2772	436	7	multi	multi	ADJ
admet-2772	436	8	-	-	ADJ
admet-2772	436	9	task	task	ADJ
admet-2772	436	10	graph	graph	NOUN
admet-2772	436	11	-	-	PUNCT
admet-2772	436	12	based	base	VERB
admet-2772	436	13	neural	neural	ADJ
admet-2772	436	14	networks	network	NOUN
admet-2772	436	15	,	,	PUNCT
admet-2772	436	16	attributing	attribute	VERB
admet-2772	436	17	this	this	DET
admet-2772	436	18	success	success	NOUN
admet-2772	436	19	to	to	ADP
admet-2772	436	20	the	the	DET
admet-2772	436	21	influence	influence	NOUN
admet-2772	436	22	of	of	ADP
admet-2772	436	23	endpoints	endpoint	NOUN
admet-2772	436	24	with	with	ADP
admet-2772	436	25	larger	large	ADJ
admet-2772	436	26	data	datum	NOUN
admet-2772	436	27	sets	set	NOUN
admet-2772	436	28	,	,	PUNCT
admet-2772	436	29	such	such	ADJ
admet-2772	436	30	as	as	ADP
admet-2772	436	31	physicochemical	physicochemical	ADJ
admet-2772	436	32	endpoints	endpoint	NOUN
admet-2772	436	33	and	and	CCONJ
admet-2772	436	34	microsomal	microsomal	ADJ
admet-2772	436	35	clearance	clearance	NOUN
admet-2772	436	36	.	.	PUNCT
admet-2772	437	1	admet	admet	PROPN
admet-2772	437	2	&	&	CCONJ
admet-2772	437	3	dmpk	dmpk	PROPN
admet-2772	437	4	13(3	13(3	NUM
admet-2772	437	5	)	)	PUNCT
admet-2772	437	6	(	(	PUNCT
admet-2772	437	7	2025	2025	NUM
admet-2772	437	8	)	)	PUNCT
admet-2772	437	9	2772	2772	NUM
admet-2772	437	10	machine	machine	NOUN
admet-2772	437	11	learning	learning	NOUN
admet-2772	437	12	models	model	NOUN
admet-2772	437	13	for	for	ADP
admet-2772	437	14	admet	admet	ADJ
admet-2772	437	15	prediction	prediction	NOUN
admet-2772	437	16	in	in	ADP
admet-2772	437	17	drug	drug	NOUN
admet-2772	437	18	development	development	NOUN
admet-2772	437	19	doi	doi	PROPN
admet-2772	437	20	:	:	PUNCT
admet-2772	437	21	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	437	22	17	17	NUM
admet-2772	437	23	6.2.2	6.2.2	NUM
admet-2772	437	24	.	.	PUNCT
admet-2772	438	1	transfer	transfer	NOUN
admet-2772	438	2	learning	learn	VERB
admet-2772	438	3	developing	develop	VERB
admet-2772	438	4	highly	highly	ADV
admet-2772	438	5	accurate	accurate	ADJ
admet-2772	438	6	models	model	NOUN
admet-2772	438	7	is	be	AUX
admet-2772	438	8	essential	essential	ADJ
admet-2772	438	9	for	for	ADP
admet-2772	438	10	swiftly	swiftly	ADV
admet-2772	438	11	evaluating	evaluate	VERB
admet-2772	438	12	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	438	13	(	(	PUNCT
admet-2772	438	14	pk	pk	NOUN
admet-2772	438	15	)	)	PUNCT
admet-2772	438	16	properties	property	NOUN
admet-2772	438	17	during	during	ADP
admet-2772	438	18	the	the	DET
admet-2772	438	19	drug	drug	NOUN
admet-2772	438	20	development	development	NOUN
admet-2772	438	21	process	process	NOUN
admet-2772	438	22	.	.	PUNCT
admet-2772	439	1	traditional	traditional	ADJ
admet-2772	439	2	models	model	NOUN
admet-2772	439	3	,	,	PUNCT
admet-2772	439	4	which	which	PRON
admet-2772	439	5	rely	rely	VERB
admet-2772	439	6	on	on	ADP
admet-2772	439	7	a	a	DET
admet-2772	439	8	substantial	substantial	ADJ
admet-2772	439	9	amount	amount	NOUN
admet-2772	439	10	of	of	ADP
admet-2772	439	11	existing	exist	VERB
admet-2772	439	12	domain	domain	NOUN
admet-2772	439	13	knowledge	knowledge	NOUN
admet-2772	439	14	and	and	CCONJ
admet-2772	439	15	constructing	construct	VERB
admet-2772	439	16	these	these	DET
admet-2772	439	17	models	model	NOUN
admet-2772	439	18	is	be	AUX
admet-2772	439	19	rather	rather	ADV
admet-2772	439	20	time	time	NOUN
admet-2772	439	21	-	-	PUNCT
admet-2772	439	22	consuming	consume	VERB
admet-2772	439	23	;	;	PUNCT
admet-2772	439	24	thus	thus	ADV
admet-2772	439	25	,	,	PUNCT
admet-2772	439	26	with	with	ADP
admet-2772	439	27	transfer	transfer	NOUN
admet-2772	439	28	learning	learning	NOUN
admet-2772	439	29	,	,	PUNCT
admet-2772	439	30	which	which	PRON
admet-2772	439	31	aims	aim	VERB
admet-2772	439	32	to	to	PART
admet-2772	439	33	generalize	generalize	VERB
admet-2772	439	34	the	the	DET
admet-2772	439	35	knowledge	knowledge	NOUN
admet-2772	439	36	gained	gain	VERB
admet-2772	439	37	from	from	ADP
admet-2772	439	38	one	one	NUM
admet-2772	439	39	task	task	NOUN
admet-2772	439	40	to	to	ADP
admet-2772	439	41	another	another	DET
admet-2772	439	42	task	task	NOUN
admet-2772	439	43	to	to	PART
admet-2772	439	44	enhance	enhance	VERB
admet-2772	439	45	its	its	PRON
admet-2772	439	46	applicability	applicability	NOUN
admet-2772	439	47	and	and	CCONJ
admet-2772	439	48	decisionmaking	decisionmaking	NOUN
admet-2772	439	49	.	.	PUNCT
admet-2772	440	1	leveraging	leverage	VERB
admet-2772	440	2	the	the	DET
admet-2772	440	3	common	common	ADJ
admet-2772	440	4	features	feature	NOUN
admet-2772	440	5	learned	learn	VERB
admet-2772	440	6	from	from	ADP
admet-2772	440	7	a	a	DET
admet-2772	440	8	similar	similar	ADJ
admet-2772	440	9	source	source	NOUN
admet-2772	440	10	domain	domain	NOUN
admet-2772	440	11	,	,	PUNCT
admet-2772	440	12	transfer	transfer	NOUN
admet-2772	440	13	learning	learning	NOUN
admet-2772	440	14	has	have	AUX
admet-2772	440	15	been	be	AUX
admet-2772	440	16	demonstrated	demonstrate	VERB
admet-2772	440	17	to	to	PART
admet-2772	440	18	be	be	AUX
admet-2772	440	19	able	able	ADJ
admet-2772	440	20	to	to	PART
admet-2772	440	21	develop	develop	VERB
admet-2772	440	22	the	the	DET
admet-2772	440	23	models	model	NOUN
admet-2772	440	24	without	without	ADP
admet-2772	440	25	learning	learn	VERB
admet-2772	440	26	from	from	ADP
admet-2772	440	27	scratch	scratch	NOUN
admet-2772	440	28	[	[	X
admet-2772	440	29	172	172	NUM
admet-2772	440	30	]	]	PUNCT
admet-2772	440	31	.	.	PUNCT
admet-2772	441	1	ye	ye	INTJ
admet-2772	441	2	et	et	PROPN
admet-2772	441	3	al	al	PROPN
admet-2772	441	4	.	.	PUNCT
admet-2772	442	1	[	[	X
admet-2772	442	2	173	173	NUM
admet-2772	442	3	]	]	PUNCT
admet-2772	442	4	introduced	introduce	VERB
admet-2772	442	5	an	an	DET
admet-2772	442	6	integrated	integrate	VERB
admet-2772	442	7	transfer	transfer	NOUN
admet-2772	442	8	learning	learning	NOUN
admet-2772	442	9	and	and	CCONJ
admet-2772	442	10	multitask	multitask	PROPN
admet-2772	442	11	learning	learn	VERB
admet-2772	442	12	approach	approach	NOUN
admet-2772	442	13	utilizing	utilize	VERB
admet-2772	442	14	three	three	NUM
admet-2772	442	15	deep	deep	ADJ
admet-2772	442	16	neural	neural	ADJ
admet-2772	442	17	networks	network	NOUN
admet-2772	442	18	to	to	PART
admet-2772	442	19	predict	predict	VERB
admet-2772	442	20	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	442	21	parameters	parameter	NOUN
admet-2772	442	22	.	.	PUNCT
admet-2772	443	1	the	the	DET
admet-2772	443	2	consensus	consensus	NOUN
admet-2772	443	3	model	model	NOUN
admet-2772	443	4	,	,	PUNCT
admet-2772	443	5	deeppharm	deeppharm	ADJ
admet-2772	443	6	utilized	utilize	VERB
admet-2772	443	7	transfer	transfer	NOUN
admet-2772	443	8	learning	learn	VERB
admet-2772	443	9	from	from	ADP
admet-2772	443	10	three	three	NUM
admet-2772	443	11	pretrained	pretraine	VERB
admet-2772	443	12	deep	deep	ADJ
admet-2772	443	13	neural	neural	ADJ
admet-2772	443	14	networks	network	NOUN
admet-2772	443	15	:	:	PUNCT
admet-2772	443	16	deeppharm	deeppharm	PROPN
admet-2772	443	17	-	-	PUNCT
admet-2772	443	18	ba	ba	PROPN
admet-2772	443	19	,	,	PUNCT
admet-2772	443	20	deeppharm	deeppharm	NOUN
admet-2772	443	21	-	-	PUNCT
admet-2772	443	22	ppbr	ppbr	NOUN
admet-2772	443	23	,	,	PUNCT
admet-2772	443	24	and	and	CCONJ
admet-2772	443	25	deeppharm	deeppharm	NOUN
admet-2772	443	26	-	-	PUNCT
admet-2772	443	27	vdss&hl	vdss&hl	PROPN
admet-2772	443	28	and	and	CCONJ
admet-2772	443	29	achieved	achieve	VERB
admet-2772	443	30	the	the	DET
admet-2772	443	31	highest	high	ADJ
admet-2772	443	32	accuracies	accuracy	NOUN
admet-2772	443	33	of	of	ADP
admet-2772	443	34	27.78	27.78	NUM
admet-2772	443	35	,	,	PUNCT
admet-2772	443	36	44.22	44.22	NUM
admet-2772	443	37	,	,	PUNCT
admet-2772	443	38	63.33	63.33	NUM
admet-2772	443	39	and	and	CCONJ
admet-2772	443	40	68.39	68.39	NUM
admet-2772	443	41	%	%	NOUN
admet-2772	443	42	in	in	ADP
admet-2772	443	43	predicting	predict	VERB
admet-2772	443	44	oral	oral	ADJ
admet-2772	443	45	bioavailability	bioavailability	NOUN
admet-2772	443	46	(	(	PUNCT
admet-2772	443	47	ba	ba	NOUN
admet-2772	443	48	)	)	PUNCT
admet-2772	443	49	,	,	PUNCT
admet-2772	443	50	plasma	plasma	NOUN
admet-2772	443	51	protein	protein	NOUN
admet-2772	443	52	binding	bind	VERB
admet-2772	443	53	rate	rate	NOUN
admet-2772	443	54	(	(	PUNCT
admet-2772	443	55	ppbr	ppbr	PROPN
admet-2772	443	56	)	)	PUNCT
admet-2772	443	57	,	,	PUNCT
admet-2772	443	58	apparent	apparent	ADJ
admet-2772	443	59	vdss	vdss	ADV
admet-2772	443	60	and	and	CCONJ
admet-2772	443	61	elimination	elimination	NOUN
admet-2772	443	62	half	half	ADJ
admet-2772	443	63	-	-	PUNCT
admet-2772	443	64	life	life	NOUN
admet-2772	443	65	(	(	PUNCT
admet-2772	443	66	hl	hl	NOUN
admet-2772	443	67	)	)	PUNCT
admet-2772	443	68	,	,	PUNCT
admet-2772	443	69	respectively	respectively	ADV
admet-2772	443	70	,	,	PUNCT
admet-2772	443	71	outperforming	outperform	VERB
admet-2772	443	72	conventional	conventional	ADJ
admet-2772	443	73	machine	machine	NOUN
admet-2772	443	74	learning	learning	NOUN
admet-2772	443	75	methods	method	NOUN
admet-2772	443	76	.	.	PUNCT
admet-2772	444	1	in	in	ADP
admet-2772	444	2	a	a	DET
admet-2772	444	3	study	study	NOUN
admet-2772	444	4	proposed	propose	VERB
admet-2772	444	5	by	by	ADP
admet-2772	444	6	abbasi	abbasi	PROPN
admet-2772	444	7	et	et	PROPN
admet-2772	444	8	al	al	PROPN
admet-2772	444	9	.	.	PUNCT
admet-2772	445	1	[	[	X
admet-2772	445	2	174	174	NUM
admet-2772	445	3	]	]	PUNCT
admet-2772	445	4	explores	explore	VERB
admet-2772	445	5	the	the	DET
admet-2772	445	6	transfer	transfer	NOUN
admet-2772	445	7	of	of	ADP
admet-2772	445	8	knowledge	knowledge	NOUN
admet-2772	445	9	across	across	ADP
admet-2772	445	10	different	different	ADJ
admet-2772	445	11	physiological	physiological	ADJ
admet-2772	445	12	and	and	CCONJ
admet-2772	445	13	biophysical	biophysical	ADJ
admet-2772	445	14	domains	domain	NOUN
admet-2772	445	15	,	,	PUNCT
admet-2772	445	16	evaluating	evaluate	VERB
admet-2772	445	17	its	its	PRON
admet-2772	445	18	effectiveness	effectiveness	NOUN
admet-2772	445	19	in	in	ADP
admet-2772	445	20	predicting	predict	VERB
admet-2772	445	21	compound	compound	NOUN
admet-2772	445	22	activity	activity	NOUN
admet-2772	445	23	with	with	ADP
admet-2772	445	24	limited	limited	ADJ
admet-2772	445	25	labelled	label	VERB
admet-2772	445	26	data	datum	NOUN
admet-2772	445	27	.	.	PUNCT
admet-2772	446	1	by	by	ADP
admet-2772	446	2	leveraging	leverage	VERB
admet-2772	446	3	source	source	NOUN
admet-2772	446	4	datasets	dataset	NOUN
admet-2772	446	5	such	such	ADJ
admet-2772	446	6	as	as	ADP
admet-2772	446	7	tox21	tox21	PROPN
admet-2772	446	8	,	,	PUNCT
admet-2772	446	9	toxcast	toxcast	NOUN
admet-2772	446	10	,	,	PUNCT
admet-2772	446	11	sider	sider	NOUN
admet-2772	446	12	,	,	PUNCT
admet-2772	446	13	hiv	hiv	PROPN
admet-2772	446	14	,	,	PUNCT
admet-2772	446	15	and	and	CCONJ
admet-2772	446	16	bace	bace	PROPN
admet-2772	446	17	,	,	PUNCT
admet-2772	446	18	the	the	DET
admet-2772	446	19	proposed	propose	VERB
admet-2772	446	20	approach	approach	NOUN
admet-2772	446	21	transfers	transfer	NOUN
admet-2772	446	22	knowledge	knowledge	NOUN
admet-2772	446	23	between	between	ADP
admet-2772	446	24	related	related	ADJ
admet-2772	446	25	or	or	CCONJ
admet-2772	446	26	semi	semi	ADJ
admet-2772	446	27	-	-	ADJ
admet-2772	446	28	related	related	ADJ
admet-2772	446	29	tasks	task	NOUN
admet-2772	446	30	,	,	PUNCT
admet-2772	446	31	demonstrating	demonstrate	VERB
admet-2772	446	32	improved	improved	ADJ
admet-2772	446	33	performance	performance	NOUN
admet-2772	446	34	in	in	ADP
admet-2772	446	35	target	target	NOUN
admet-2772	446	36	tasks	task	NOUN
admet-2772	446	37	.	.	PUNCT
admet-2772	447	1	additionally	additionally	ADV
admet-2772	447	2	,	,	PUNCT
admet-2772	447	3	the	the	DET
admet-2772	447	4	study	study	NOUN
admet-2772	447	5	highlighted	highlight	VERB
admet-2772	447	6	the	the	DET
admet-2772	447	7	importance	importance	NOUN
admet-2772	447	8	of	of	ADP
admet-2772	447	9	selecting	select	VERB
admet-2772	447	10	appropriate	appropriate	ADJ
admet-2772	447	11	source	source	NOUN
admet-2772	447	12	datasets	dataset	NOUN
admet-2772	447	13	and	and	CCONJ
admet-2772	447	14	revealed	reveal	VERB
admet-2772	447	15	that	that	SCONJ
admet-2772	447	16	knowledge	knowledge	NOUN
admet-2772	447	17	transfer	transfer	NOUN
admet-2772	447	18	between	between	ADP
admet-2772	447	19	tasks	task	NOUN
admet-2772	447	20	within	within	ADP
admet-2772	447	21	the	the	DET
admet-2772	447	22	same	same	ADJ
admet-2772	447	23	category	category	NOUN
admet-2772	447	24	yields	yield	VERB
admet-2772	447	25	better	well	ADJ
admet-2772	447	26	results	result	NOUN
admet-2772	447	27	compared	compare	VERB
admet-2772	447	28	to	to	ADP
admet-2772	447	29	tasks	task	NOUN
admet-2772	447	30	from	from	ADP
admet-2772	447	31	different	different	ADJ
admet-2772	447	32	categories	category	NOUN
admet-2772	447	33	.	.	PUNCT
admet-2772	448	1	in	in	ADP
admet-2772	448	2	another	another	DET
admet-2772	448	3	study	study	NOUN
admet-2772	448	4	s.	s.	PROPN
admet-2772	448	5	wang	wang	PROPN
admet-2772	448	6	et	et	PROPN
admet-2772	448	7	al	al	PROPN
admet-2772	448	8	.	.	PUNCT
admet-2772	449	1	[	[	X
admet-2772	449	2	175	175	NUM
admet-2772	449	3	]	]	PUNCT
admet-2772	449	4	introduced	introduce	VERB
admet-2772	449	5	a	a	DET
admet-2772	449	6	semi	semi	ADJ
admet-2772	449	7	-	-	ADJ
admet-2772	449	8	supervised	supervised	ADJ
admet-2772	449	9	model	model	NOUN
admet-2772	449	10	named	name	VERB
admet-2772	449	11	smiles	smile	NOUN
admet-2772	449	12	-	-	PUNCT
admet-2772	449	13	bert	bert	NOUN
admet-2772	449	14	for	for	ADP
admet-2772	449	15	molecular	molecular	ADJ
admet-2772	449	16	property	property	NOUN
admet-2772	449	17	prediction	prediction	NOUN
admet-2772	449	18	,	,	PUNCT
admet-2772	449	19	utilizing	utilize	VERB
admet-2772	449	20	deep	deep	ADJ
admet-2772	449	21	learning	learning	NOUN
admet-2772	449	22	techniques	technique	NOUN
admet-2772	449	23	and	and	CCONJ
admet-2772	449	24	a	a	DET
admet-2772	449	25	largescale	largescale	NOUN
admet-2772	449	26	of	of	ADP
admet-2772	449	27	unlabelled	unlabelled	ADJ
admet-2772	449	28	data	datum	NOUN
admet-2772	449	29	.	.	PUNCT
admet-2772	450	1	the	the	DET
admet-2772	450	2	model	model	NOUN
admet-2772	450	3	utilized	utilize	VERB
admet-2772	450	4	an	an	DET
admet-2772	450	5	attention	attention	NOUN
admet-2772	450	6	mechanism	mechanism	NOUN
admet-2772	450	7	-	-	PUNCT
admet-2772	450	8	based	base	VERB
admet-2772	450	9	transformer	transformer	NOUN
admet-2772	450	10	layer	layer	NOUN
admet-2772	450	11	and	and	CCONJ
admet-2772	450	12	underwent	undergo	VERB
admet-2772	450	13	pre	pre	NOUN
admet-2772	450	14	-	-	NOUN
admet-2772	450	15	training	training	NOUN
admet-2772	450	16	via	via	ADP
admet-2772	450	17	a	a	DET
admet-2772	450	18	masked	mask	VERB
admet-2772	450	19	smiles	smile	NOUN
admet-2772	450	20	recovery	recovery	NOUN
admet-2772	450	21	task	task	NOUN
admet-2772	450	22	on	on	ADP
admet-2772	450	23	the	the	DET
admet-2772	450	24	zinc	zinc	NOUN
admet-2772	450	25	dataset	dataset	NOUN
admet-2772	450	26	.	.	PUNCT
admet-2772	451	1	this	this	DET
admet-2772	451	2	pre	pre	ADJ
admet-2772	451	3	-	-	ADJ
admet-2772	451	4	training	training	ADJ
admet-2772	451	5	process	process	NOUN
admet-2772	451	6	significantly	significantly	ADV
admet-2772	451	7	improved	improve	VERB
admet-2772	451	8	the	the	DET
admet-2772	451	9	model	model	NOUN
admet-2772	451	10	's	's	PART
admet-2772	451	11	generalization	generalization	NOUN
admet-2772	451	12	capability	capability	NOUN
admet-2772	451	13	,	,	PUNCT
admet-2772	451	14	as	as	SCONJ
admet-2772	451	15	evidenced	evidence	VERB
admet-2772	451	16	by	by	ADP
admet-2772	451	17	achieving	achieve	VERB
admet-2772	451	18	an	an	DET
admet-2772	451	19	exact	exact	ADJ
admet-2772	451	20	recovery	recovery	NOUN
admet-2772	451	21	rate	rate	NOUN
admet-2772	451	22	of	of	ADP
admet-2772	451	23	82.85	82.85	NUM
admet-2772	451	24	%	%	NOUN
admet-2772	451	25	on	on	ADP
admet-2772	451	26	the	the	DET
admet-2772	451	27	validation	validation	NOUN
admet-2772	451	28	dataset	dataset	NOUN
admet-2772	451	29	.	.	PUNCT
admet-2772	452	1	during	during	ADP
admet-2772	452	2	fine	fine	ADV
admet-2772	452	3	-	-	PUNCT
admet-2772	452	4	tuning	tuning	NOUN
admet-2772	452	5	,	,	PUNCT
admet-2772	452	6	the	the	DET
admet-2772	452	7	model	model	NOUN
admet-2772	452	8	was	be	AUX
admet-2772	452	9	trained	train	VERB
admet-2772	452	10	using	use	VERB
admet-2772	452	11	various	various	ADJ
admet-2772	452	12	learning	learning	NOUN
admet-2772	452	13	rates	rate	NOUN
admet-2772	452	14	and	and	CCONJ
admet-2772	452	15	optimization	optimization	NOUN
admet-2772	452	16	strategies	strategy	NOUN
admet-2772	452	17	,	,	PUNCT
admet-2772	452	18	resulting	result	VERB
admet-2772	452	19	in	in	ADP
admet-2772	452	20	high	high	ADJ
admet-2772	452	21	prediction	prediction	NOUN
admet-2772	452	22	performance	performance	NOUN
admet-2772	452	23	across	across	ADP
admet-2772	452	24	three	three	NUM
admet-2772	452	25	datasets	dataset	NOUN
admet-2772	452	26	:	:	PUNCT
admet-2772	452	27	log	log	VERB
admet-2772	452	28	p	p	NOUN
admet-2772	452	29	,	,	PUNCT
admet-2772	452	30	pm2	pm2	NOUN
admet-2772	452	31	,	,	PUNCT
admet-2772	452	32	and	and	CCONJ
admet-2772	452	33	pcba-686978	pcba-686978	NOUN
admet-2772	452	34	.	.	PUNCT
admet-2772	453	1	smiles	smile	NOUN
admet-2772	453	2	-	-	PUNCT
admet-2772	453	3	bert	bert	NOUN
admet-2772	453	4	surpassed	surpass	VERB
admet-2772	453	5	state	state	NOUN
admet-2772	453	6	-	-	PUNCT
admet-2772	453	7	of	of	ADP
admet-2772	453	8	-	-	PUNCT
admet-2772	453	9	the	the	DET
admet-2772	453	10	-	-	PUNCT
admet-2772	453	11	art	art	NOUN
admet-2772	453	12	methods	method	NOUN
admet-2772	453	13	,	,	PUNCT
admet-2772	453	14	highlighting	highlight	VERB
admet-2772	453	15	its	its	PRON
admet-2772	453	16	ability	ability	NOUN
admet-2772	453	17	to	to	PART
admet-2772	453	18	effectively	effectively	ADV
admet-2772	453	19	leverage	leverage	VERB
admet-2772	453	20	unlabelled	unlabelled	ADJ
admet-2772	453	21	data	datum	NOUN
admet-2772	453	22	and	and	CCONJ
admet-2772	453	23	its	its	PRON
admet-2772	453	24	potential	potential	NOUN
admet-2772	453	25	for	for	ADP
admet-2772	453	26	molecular	molecular	ADJ
admet-2772	453	27	property	property	NOUN
admet-2772	453	28	prediction	prediction	NOUN
admet-2772	453	29	tasks	task	NOUN
admet-2772	453	30	with	with	ADP
admet-2772	453	31	varying	vary	VERB
admet-2772	453	32	dataset	dataset	ADJ
admet-2772	453	33	sizes	size	NOUN
admet-2772	453	34	and	and	CCONJ
admet-2772	453	35	properties	property	NOUN
admet-2772	453	36	.	.	PUNCT
admet-2772	454	1	similarly	similarly	ADV
admet-2772	454	2	,	,	PUNCT
admet-2772	454	3	x.	x.	PROPN
admet-2772	454	4	li	li	PROPN
admet-2772	454	5	and	and	CCONJ
admet-2772	454	6	fourches	fourche	VERB
admet-2772	454	7	[	[	X
admet-2772	454	8	176	176	NUM
admet-2772	454	9	]	]	PUNCT
admet-2772	454	10	introduced	introduce	VERB
admet-2772	454	11	molpmofit	molpmofit	NOUN
admet-2772	454	12	,	,	PUNCT
admet-2772	454	13	an	an	DET
admet-2772	454	14	inductive	inductive	ADJ
admet-2772	454	15	transfer	transfer	NOUN
admet-2772	454	16	learning	learning	NOUN
admet-2772	454	17	method	method	NOUN
admet-2772	454	18	for	for	ADP
admet-2772	454	19	molecular	molecular	ADJ
admet-2772	454	20	activity	activity	NOUN
admet-2772	454	21	prediction	prediction	NOUN
admet-2772	454	22	in	in	ADP
admet-2772	454	23	quantitative	quantitative	ADJ
admet-2772	454	24	structure	structure	NOUN
admet-2772	454	25	-	-	PUNCT
admet-2772	454	26	activity	activity	NOUN
admet-2772	454	27	relationship	relationship	NOUN
admet-2772	454	28	(	(	PUNCT
admet-2772	454	29	qsar	qsar	NOUN
admet-2772	454	30	)	)	PUNCT
admet-2772	454	31	modelling	modelling	NOUN
admet-2772	454	32	.	.	PUNCT
admet-2772	455	1	the	the	DET
admet-2772	455	2	approach	approach	NOUN
admet-2772	455	3	utilized	utilize	VERB
admet-2772	455	4	a	a	DET
admet-2772	455	5	pre	pre	ADJ
admet-2772	455	6	-	-	ADJ
admet-2772	455	7	trained	train	VERB
admet-2772	455	8	molecular	molecular	ADJ
admet-2772	455	9	structure	structure	NOUN
admet-2772	455	10	prediction	prediction	NOUN
admet-2772	455	11	model	model	NOUN
admet-2772	455	12	(	(	PUNCT
admet-2772	455	13	mspm	mspm	NOUN
admet-2772	455	14	)	)	PUNCT
admet-2772	455	15	using	use	VERB
admet-2772	455	16	one	one	NUM
admet-2772	455	17	million	million	NUM
admet-2772	455	18	unlabelled	unlabelled	ADJ
admet-2772	455	19	molecules	molecule	NOUN
admet-2772	455	20	from	from	ADP
admet-2772	455	21	chembl	chembl	NOUN
admet-2772	455	22	,	,	PUNCT
admet-2772	455	23	finetuning	finetune	VERB
admet-2772	455	24	it	it	PRON
admet-2772	455	25	for	for	ADP
admet-2772	455	26	specific	specific	ADJ
admet-2772	455	27	qsar	qsar	NOUN
admet-2772	455	28	tasks	task	NOUN
admet-2772	455	29	.	.	PUNCT
admet-2772	456	1	this	this	DET
admet-2772	456	2	method	method	NOUN
admet-2772	456	3	achieved	achieve	VERB
admet-2772	456	4	strong	strong	ADJ
admet-2772	456	5	performance	performance	NOUN
admet-2772	456	6	across	across	ADP
admet-2772	456	7	four	four	NUM
admet-2772	456	8	benchmark	benchmark	NOUN
admet-2772	456	9	datasets	dataset	NOUN
admet-2772	456	10	(	(	PUNCT
admet-2772	456	11	lipophilicity	lipophilicity	NOUN
admet-2772	456	12	,	,	PUNCT
admet-2772	456	13	freesolv	freesolv	ADJ
admet-2772	456	14	,	,	PUNCT
admet-2772	456	15	hiv	hiv	PROPN
admet-2772	456	16	,	,	PUNCT
admet-2772	456	17	and	and	CCONJ
admet-2772	456	18	blood	blood	NOUN
admet-2772	456	19	-	-	PUNCT
admet-2772	456	20	brain	brain	NOUN
admet-2772	456	21	barrier	barrier	NOUN
admet-2772	456	22	penetration	penetration	NOUN
admet-2772	456	23	)	)	PUNCT
admet-2772	456	24	,	,	PUNCT
admet-2772	456	25	when	when	SCONJ
admet-2772	456	26	compared	compare	VERB
admet-2772	456	27	to	to	ADP
admet-2772	456	28	state	state	NOUN
admet-2772	456	29	-	-	PUNCT
admet-2772	456	30	of	of	ADP
admet-2772	456	31	-	-	PUNCT
admet-2772	456	32	the	the	DET
admet-2772	456	33	-	-	PUNCT
admet-2772	456	34	art	art	NOUN
admet-2772	456	35	techniques	technique	NOUN
admet-2772	456	36	reported	report	VERB
admet-2772	456	37	in	in	ADP
admet-2772	456	38	the	the	DET
admet-2772	456	39	literature	literature	NOUN
admet-2772	456	40	.	.	PUNCT
admet-2772	457	1	the	the	DET
admet-2772	457	2	approach	approach	NOUN
admet-2772	457	3	showcased	showcase	VERB
admet-2772	457	4	its	its	PRON
admet-2772	457	5	potential	potential	NOUN
admet-2772	457	6	for	for	ADP
admet-2772	457	7	improving	improve	VERB
admet-2772	457	8	next	next	ADJ
admet-2772	457	9	-	-	PUNCT
admet-2772	457	10	generation	generation	NOUN
admet-2772	457	11	qsar	qsar	NOUN
admet-2772	457	12	models	model	NOUN
admet-2772	457	13	,	,	PUNCT
admet-2772	457	14	particularly	particularly	ADV
admet-2772	457	15	for	for	ADP
admet-2772	457	16	smaller	small	ADJ
admet-2772	457	17	datasets	dataset	NOUN
admet-2772	457	18	with	with	ADP
admet-2772	457	19	challenging	challenging	ADJ
admet-2772	457	20	endpoints	endpoint	NOUN
admet-2772	457	21	.	.	PUNCT
admet-2772	458	1	6.2.3	6.2.3	X
admet-2772	458	2	.	.	PUNCT
admet-2772	458	3	pretrained	pretraine	VERB
admet-2772	458	4	models	model	NOUN
admet-2772	458	5	recent	recent	ADJ
admet-2772	458	6	advancements	advancement	NOUN
admet-2772	458	7	in	in	ADP
admet-2772	458	8	machine	machine	NOUN
admet-2772	458	9	learning	learning	NOUN
admet-2772	458	10	have	have	AUX
admet-2772	458	11	significantly	significantly	ADV
admet-2772	458	12	improved	improve	VERB
admet-2772	458	13	the	the	DET
admet-2772	458	14	prediction	prediction	NOUN
admet-2772	458	15	of	of	ADP
admet-2772	458	16	absorption	absorption	NOUN
admet-2772	458	17	,	,	PUNCT
admet-2772	458	18	distribution	distribution	NOUN
admet-2772	458	19	,	,	PUNCT
admet-2772	458	20	metabolism	metabolism	NOUN
admet-2772	458	21	,	,	PUNCT
admet-2772	458	22	excretion	excretion	NOUN
admet-2772	458	23	,	,	PUNCT
admet-2772	458	24	and	and	CCONJ
admet-2772	458	25	toxicity	toxicity	NOUN
admet-2772	458	26	(	(	PUNCT
admet-2772	458	27	admet	admet	NOUN
admet-2772	458	28	)	)	PUNCT
admet-2772	458	29	properties	property	NOUN
admet-2772	458	30	in	in	ADP
admet-2772	458	31	drug	drug	NOUN
admet-2772	458	32	discovery	discovery	NOUN
admet-2772	458	33	.	.	PUNCT
admet-2772	459	1	pretrained	pretraine	VERB
admet-2772	459	2	models	model	NOUN
admet-2772	459	3	and	and	CCONJ
admet-2772	459	4	self	self	NOUN
admet-2772	459	5	-	-	PUNCT
admet-2772	459	6	supervised	supervise	VERB
admet-2772	459	7	learning	learning	NOUN
admet-2772	459	8	approaches	approach	NOUN
admet-2772	459	9	have	have	AUX
admet-2772	459	10	shown	show	VERB
admet-2772	459	11	promising	promising	ADJ
admet-2772	459	12	results	result	NOUN
admet-2772	459	13	in	in	ADP
admet-2772	459	14	this	this	DET
admet-2772	459	15	field	field	NOUN
admet-2772	459	16	.	.	PUNCT
admet-2772	460	1	zhang	zhang	PROPN
admet-2772	460	2	et	et	PROPN
admet-2772	460	3	al	al	PROPN
admet-2772	460	4	.	.	PUNCT
admet-2772	461	1	[	[	X
admet-2772	461	2	177	177	NUM
admet-2772	461	3	]	]	PUNCT
admet-2772	461	4	developed	develop	VERB
admet-2772	461	5	helixadmet	helixadmet	ADJ
admet-2772	461	6	,	,	PUNCT
admet-2772	461	7	a	a	DET
admet-2772	461	8	system	system	NOUN
admet-2772	461	9	incorporating	incorporate	VERB
admet-2772	461	10	self	self	NOUN
admet-2772	461	11	-	-	PUNCT
admet-2772	461	12	supervised	supervise	VERB
admet-2772	461	13	learning	learning	NOUN
admet-2772	461	14	that	that	PRON
admet-2772	461	15	achieved	achieve	VERB
admet-2772	461	16	a	a	DET
admet-2772	461	17	4	4	NUM
admet-2772	461	18	%	%	NOUN
admet-2772	461	19	improvement	improvement	NOUN
admet-2772	461	20	over	over	ADP
admet-2772	461	21	existing	exist	VERB
admet-2772	461	22	admet	admet	NOUN
admet-2772	461	23	systems	system	NOUN
admet-2772	461	24	.	.	PUNCT
admet-2772	462	1	jung	jung	PROPN
admet-2772	462	2	et	et	PROPN
admet-2772	462	3	al	al	PROPN
admet-2772	462	4	.	.	PUNCT
admet-2772	463	1	[	[	X
admet-2772	463	2	178	178	NUM
admet-2772	463	3	]	]	PUNCT
admet-2772	463	4	utilized	utilize	VERB
admet-2772	463	5	the	the	DET
admet-2772	463	6	pretrained	pretraine	VERB
admet-2772	463	7	chemberta	chemberta	NOUN
admet-2772	463	8	model	model	NOUN
admet-2772	463	9	for	for	ADP
admet-2772	463	10	admet	admet	PROPN
admet-2772	463	11	prediction	prediction	NOUN
admet-2772	463	12	,	,	PUNCT
admet-2772	463	13	exploring	explore	VERB
admet-2772	463	14	various	various	ADJ
admet-2772	463	15	architectures	architecture	NOUN
admet-2772	463	16	.	.	PUNCT
admet-2772	464	1	wenzel	wenzel	PROPN
admet-2772	464	2	et	et	PROPN
admet-2772	464	3	al	al	PROPN
admet-2772	464	4	.	.	PUNCT
admet-2772	465	1	[	[	X
admet-2772	465	2	179	179	NUM
admet-2772	465	3	]	]	PUNCT
admet-2772	465	4	demonstrated	demonstrate	VERB
admet-2772	465	5	the	the	DET
admet-2772	465	6	effectiveness	effectiveness	NOUN
admet-2772	465	7	of	of	ADP
admet-2772	465	8	multitask	multitask	ADJ
admet-2772	465	9	deep	deep	ADJ
admet-2772	465	10	neural	neural	ADJ
admet-2772	465	11	networks	network	NOUN
admet-2772	465	12	in	in	ADP
admet-2772	465	13	predicting	predict	VERB
admet-2772	465	14	adme	adme	NOUN
admet-2772	465	15	-	-	PUNCT
admet-2772	465	16	tox	tox	NOUN
admet-2772	465	17	properties	property	NOUN
admet-2772	465	18	,	,	PUNCT
admet-2772	465	19	showing	show	VERB
admet-2772	465	20	improved	improved	ADJ
admet-2772	465	21	performance	performance	NOUN
admet-2772	465	22	compared	compare	VERB
admet-2772	465	23	to	to	ADP
admet-2772	465	24	single	single	ADJ
admet-2772	465	25	-	-	PUNCT
admet-2772	465	26	task	task	NOUN
admet-2772	465	27	models	model	NOUN
admet-2772	465	28	.	.	PUNCT
admet-2772	466	1	kumar	kumar	PROPN
admet-2772	466	2	et	et	PROPN
admet-2772	466	3	al	al	PROPN
admet-2772	466	4	.	.	PUNCT
admet-2772	467	1	[	[	X
admet-2772	467	2	62	62	NUM
admet-2772	467	3	]	]	PUNCT
admet-2772	467	4	implemented	implement	VERB
admet-2772	467	5	an	an	DET
admet-2772	467	6	enterprise	enterprise	NOUN
admet-2772	467	7	-	-	PUNCT
admet-2772	467	8	wide	wide	ADJ
admet-2772	467	9	predictive	predictive	ADJ
admet-2772	467	10	model	model	NOUN
admet-2772	467	11	,	,	PUNCT
admet-2772	467	12	gtpp	gtpp	NOUN
admet-2772	467	13	,	,	PUNCT
admet-2772	467	14	which	which	PRON
admet-2772	467	15	outperformed	outperform	VERB
admet-2772	467	16	commercial	commercial	ADJ
admet-2772	467	17	adme	adme	NOUN
admet-2772	467	18	models	model	NOUN
admet-2772	467	19	and	and	CCONJ
admet-2772	467	20	automatic	automatic	ADJ
admet-2772	467	21	model	model	NOUN
admet-2772	467	22	builders	builder	NOUN
admet-2772	467	23	.	.	PUNCT
admet-2772	468	1	these	these	DET
admet-2772	468	2	studies	study	NOUN
admet-2772	468	3	highlight	highlight	VERB
admet-2772	468	4	the	the	DET
admet-2772	468	5	potential	potential	ADJ
admet-2772	468	6	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	468	7	m.	m.	NOUN
admet-2772	468	8	venkataraman	venkataraman	PROPN
admet-2772	468	9	et	et	PROPN
admet-2772	468	10	al	al	PROPN
admet-2772	468	11	.	.	PROPN
admet-2772	468	12	admet	admet	PROPN
admet-2772	468	13	&	&	CCONJ
admet-2772	468	14	dmpk	dmpk	PROPN
admet-2772	468	15	13(3	13(3	NUM
admet-2772	468	16	)	)	PUNCT
admet-2772	468	17	(	(	PUNCT
admet-2772	468	18	2025	2025	NUM
admet-2772	468	19	)	)	PUNCT
admet-2772	468	20	2772	2772	NUM
admet-2772	468	21	18	18	NUM
admet-2772	468	22	of	of	ADP
admet-2772	468	23	advanced	advanced	ADJ
admet-2772	468	24	machine	machine	NOUN
admet-2772	468	25	learning	learn	VERB
admet-2772	468	26	techniques	technique	NOUN
admet-2772	468	27	,	,	PUNCT
admet-2772	468	28	particularly	particularly	ADV
admet-2772	468	29	pretrained	pretraine	VERB
admet-2772	468	30	models	model	NOUN
admet-2772	468	31	and	and	CCONJ
admet-2772	468	32	self	self	NOUN
admet-2772	468	33	-	-	PUNCT
admet-2772	468	34	supervised	supervise	VERB
admet-2772	468	35	learning	learning	NOUN
admet-2772	468	36	,	,	PUNCT
admet-2772	468	37	in	in	ADP
admet-2772	468	38	enhancing	enhance	VERB
admet-2772	468	39	admet	admet	NOUN
admet-2772	468	40	property	property	NOUN
admet-2772	468	41	prediction	prediction	NOUN
admet-2772	468	42	and	and	CCONJ
admet-2772	468	43	facilitating	facilitate	VERB
admet-2772	468	44	early	early	ADJ
admet-2772	468	45	-	-	PUNCT
admet-2772	468	46	stage	stage	NOUN
admet-2772	468	47	drug	drug	NOUN
admet-2772	468	48	development	development	NOUN
admet-2772	468	49	.	.	PUNCT
admet-2772	469	1	6.3	6.3	NUM
admet-2772	469	2	.	.	PUNCT
admet-2772	470	1	interpretable	interpretable	ADJ
admet-2772	470	2	and	and	CCONJ
admet-2772	470	3	explainable	explainable	ADJ
admet-2772	470	4	admet	admet	NOUN
admet-2772	470	5	models	model	NOUN
admet-2772	470	6	as	as	SCONJ
admet-2772	470	7	artificial	artificial	ADJ
admet-2772	470	8	intelligence	intelligence	NOUN
admet-2772	470	9	and	and	CCONJ
admet-2772	470	10	machine	machine	NOUN
admet-2772	470	11	learning	learning	NOUN
admet-2772	470	12	models	model	NOUN
admet-2772	470	13	grow	grow	VERB
admet-2772	470	14	in	in	ADP
admet-2772	470	15	complexity	complexity	NOUN
admet-2772	470	16	,	,	PUNCT
admet-2772	470	17	a	a	DET
admet-2772	470	18	significant	significant	ADJ
admet-2772	470	19	challenge	challenge	NOUN
admet-2772	470	20	has	have	AUX
admet-2772	470	21	surfaced	surface	VERB
admet-2772	470	22	within	within	ADP
admet-2772	470	23	the	the	DET
admet-2772	470	24	field	field	NOUN
admet-2772	470	25	:	:	PUNCT
admet-2772	470	26	the	the	DET
admet-2772	470	27	absence	absence	NOUN
admet-2772	470	28	of	of	ADP
admet-2772	470	29	transparency	transparency	NOUN
admet-2772	470	30	and	and	CCONJ
admet-2772	470	31	interpretability	interpretability	NOUN
admet-2772	470	32	[	[	X
admet-2772	470	33	180	180	NUM
admet-2772	470	34	]	]	PUNCT
admet-2772	470	35	.	.	PUNCT
admet-2772	471	1	while	while	SCONJ
admet-2772	471	2	these	these	DET
admet-2772	471	3	models	model	NOUN
admet-2772	471	4	demonstrate	demonstrate	VERB
admet-2772	471	5	remarkable	remarkable	ADJ
admet-2772	471	6	predictive	predictive	ADJ
admet-2772	471	7	capabilities	capability	NOUN
admet-2772	471	8	,	,	PUNCT
admet-2772	471	9	elucidating	elucidate	VERB
admet-2772	471	10	the	the	DET
admet-2772	471	11	rationale	rationale	NOUN
admet-2772	471	12	behind	behind	ADP
admet-2772	471	13	their	their	PRON
admet-2772	471	14	predictions	prediction	NOUN
admet-2772	471	15	remains	remain	VERB
admet-2772	471	16	difficult	difficult	ADJ
admet-2772	471	17	.	.	PUNCT
admet-2772	472	1	this	this	DET
admet-2772	472	2	absence	absence	NOUN
admet-2772	472	3	of	of	ADP
admet-2772	472	4	interpretability	interpretability	NOUN
admet-2772	472	5	can	can	AUX
admet-2772	472	6	pose	pose	VERB
admet-2772	472	7	challenges	challenge	NOUN
admet-2772	472	8	for	for	ADP
admet-2772	472	9	researchers	researcher	NOUN
admet-2772	472	10	and	and	CCONJ
admet-2772	472	11	regulatory	regulatory	ADJ
admet-2772	472	12	authorities	authority	NOUN
admet-2772	472	13	in	in	ADP
admet-2772	472	14	relying	rely	VERB
admet-2772	472	15	on	on	ADP
admet-2772	472	16	ai	ai	ADP
admet-2772	472	17	and	and	CCONJ
admet-2772	472	18	ml	ml	NOUN
admet-2772	472	19	-	-	PUNCT
admet-2772	472	20	driven	drive	VERB
admet-2772	472	21	predictions	prediction	NOUN
admet-2772	472	22	,	,	PUNCT
admet-2772	472	23	particularly	particularly	ADV
admet-2772	472	24	in	in	ADP
admet-2772	472	25	drug	drug	NOUN
admet-2772	472	26	discovery	discovery	NOUN
admet-2772	473	1	[	[	X
admet-2772	473	2	157	157	NUM
admet-2772	473	3	]	]	PUNCT
admet-2772	473	4	.	.	PUNCT
admet-2772	474	1	moreover	moreover	ADV
admet-2772	474	2	,	,	PUNCT
admet-2772	474	3	assessing	assess	VERB
admet-2772	474	4	and	and	CCONJ
admet-2772	474	5	prioritizing	prioritize	VERB
admet-2772	474	6	discovered	discover	VERB
admet-2772	474	7	targets	target	NOUN
admet-2772	474	8	or	or	CCONJ
admet-2772	474	9	compounds	compound	NOUN
admet-2772	474	10	becomes	become	VERB
admet-2772	474	11	cumbersome	cumbersome	ADJ
admet-2772	474	12	without	without	ADP
admet-2772	474	13	understanding	understand	VERB
admet-2772	474	14	the	the	DET
admet-2772	474	15	decisionmaking	decisionmake	VERB
admet-2772	474	16	process	process	NOUN
admet-2772	474	17	of	of	ADP
admet-2772	474	18	ai	ai	ADJ
admet-2772	474	19	algorithms	algorithm	NOUN
admet-2772	474	20	.	.	PUNCT
admet-2772	475	1	in	in	ADP
admet-2772	475	2	order	order	NOUN
admet-2772	475	3	to	to	PART
admet-2772	475	4	foster	foster	VERB
admet-2772	475	5	trust	trust	NOUN
admet-2772	475	6	in	in	ADP
admet-2772	475	7	ai	ai	NOUN
admet-2772	475	8	/	/	SYM
admet-2772	475	9	ml	ml	NOUN
admet-2772	475	10	systems	system	NOUN
admet-2772	475	11	,	,	PUNCT
admet-2772	475	12	it	it	PRON
admet-2772	475	13	is	be	AUX
admet-2772	475	14	imperative	imperative	ADJ
admet-2772	475	15	that	that	SCONJ
admet-2772	475	16	models	model	NOUN
admet-2772	475	17	are	be	AUX
admet-2772	475	18	transparent	transparent	ADJ
admet-2772	475	19	and	and	CCONJ
admet-2772	475	20	understandable	understandable	ADJ
admet-2772	475	21	to	to	ADP
admet-2772	475	22	users	user	NOUN
admet-2772	475	23	thus	thus	ADV
admet-2772	475	24	efforts	effort	NOUN
admet-2772	475	25	are	be	AUX
admet-2772	475	26	being	be	AUX
admet-2772	475	27	made	make	VERB
admet-2772	475	28	to	to	PART
admet-2772	475	29	enhance	enhance	VERB
admet-2772	475	30	the	the	DET
admet-2772	475	31	interpretability	interpretability	NOUN
admet-2772	475	32	by	by	ADP
admet-2772	475	33	embracing	embrace	VERB
admet-2772	475	34	explainable	explainable	ADJ
admet-2772	475	35	artificial	artificial	ADJ
admet-2772	475	36	intelligence	intelligence	NOUN
admet-2772	475	37	(	(	PUNCT
admet-2772	475	38	xai	xai	PROPN
admet-2772	475	39	)	)	PUNCT
admet-2772	475	40	,	,	PUNCT
admet-2772	475	41	which	which	PRON
admet-2772	475	42	tries	try	VERB
admet-2772	475	43	to	to	PART
admet-2772	475	44	offer	offer	VERB
admet-2772	475	45	clear	clear	ADJ
admet-2772	475	46	and	and	CCONJ
admet-2772	475	47	intelligible	intelligible	ADJ
admet-2772	475	48	justifications	justification	NOUN
admet-2772	475	49	for	for	ADP
admet-2772	475	50	the	the	DET
admet-2772	475	51	predictions	prediction	NOUN
admet-2772	475	52	made	make	VERB
admet-2772	475	53	by	by	ADP
admet-2772	475	54	ai	ai	NOUN
admet-2772	475	55	and	and	CCONJ
admet-2772	475	56	ml	ml	NOUN
admet-2772	475	57	models	model	NOUN
admet-2772	475	58	of	of	ADP
admet-2772	475	59	machine	machine	NOUN
admet-2772	475	60	learning	learning	NOUN
admet-2772	475	61	models	model	NOUN
admet-2772	475	62	in	in	ADP
admet-2772	475	63	adme	adme	NOUN
admet-2772	475	64	studies	study	NOUN
admet-2772	475	65	[	[	X
admet-2772	475	66	181	181	NUM
admet-2772	475	67	]	]	PUNCT
admet-2772	475	68	.	.	PUNCT
admet-2772	476	1	interpretability	interpretability	NOUN
admet-2772	476	2	in	in	ADP
admet-2772	476	3	ai	ai	ADJ
admet-2772	476	4	exposes	expose	NOUN
admet-2772	476	5	the	the	DET
admet-2772	476	6	inner	inner	ADJ
admet-2772	476	7	workings	working	NOUN
admet-2772	476	8	of	of	ADP
admet-2772	476	9	these	these	DET
admet-2772	476	10	systems	system	NOUN
admet-2772	476	11	,	,	PUNCT
admet-2772	476	12	allowing	allow	VERB
admet-2772	476	13	for	for	ADP
admet-2772	476	14	the	the	DET
admet-2772	476	15	detection	detection	NOUN
admet-2772	476	16	of	of	ADP
admet-2772	476	17	issues	issue	NOUN
admet-2772	476	18	like	like	ADP
admet-2772	476	19	information	information	NOUN
admet-2772	476	20	leakage	leakage	NOUN
admet-2772	476	21	,	,	PUNCT
admet-2772	476	22	model	model	NOUN
admet-2772	476	23	bias	bias	NOUN
admet-2772	476	24	,	,	PUNCT
admet-2772	476	25	robustness	robustness	NOUN
admet-2772	476	26	,	,	PUNCT
admet-2772	476	27	and	and	CCONJ
admet-2772	476	28	causality	causality	NOUN
admet-2772	476	29	[	[	X
admet-2772	476	30	182	182	NUM
admet-2772	476	31	]	]	PUNCT
admet-2772	476	32	.	.	PUNCT
admet-2772	477	1	6.3.1	6.3.1	NUM
admet-2772	477	2	.	.	PUNCT
admet-2772	477	3	local	local	ADJ
admet-2772	477	4	interpretable	interpretable	ADJ
admet-2772	477	5	model	model	ADJ
admet-2772	477	6	-	-	ADJ
admet-2772	477	7	agnostic	agnostic	ADJ
admet-2772	477	8	explanations	explanation	NOUN
admet-2772	477	9	and	and	CCONJ
admet-2772	477	10	shapley	shapley	ADJ
admet-2772	477	11	additive	additive	ADJ
admet-2772	477	12	explanations	explanation	NOUN
admet-2772	477	13	recent	recent	ADJ
admet-2772	477	14	research	research	NOUN
admet-2772	477	15	has	have	AUX
admet-2772	477	16	explored	explore	VERB
admet-2772	477	17	the	the	DET
admet-2772	477	18	application	application	NOUN
admet-2772	477	19	of	of	ADP
admet-2772	477	20	explainable	explainable	ADJ
admet-2772	477	21	artificial	artificial	ADJ
admet-2772	477	22	intelligence	intelligence	NOUN
admet-2772	477	23	(	(	PUNCT
admet-2772	477	24	xai	xai	PROPN
admet-2772	477	25	)	)	PUNCT
admet-2772	477	26	techniques	technique	NOUN
admet-2772	477	27	,	,	PUNCT
admet-2772	477	28	particularly	particularly	ADV
admet-2772	477	29	lime	lime	NOUN
admet-2772	477	30	(	(	PUNCT
admet-2772	477	31	local	local	ADJ
admet-2772	477	32	interpretable	interpretable	ADJ
admet-2772	477	33	model	model	ADJ
admet-2772	477	34	-	-	ADJ
admet-2772	477	35	agnostic	agnostic	ADJ
admet-2772	477	36	explanations	explanation	NOUN
admet-2772	477	37	)	)	PUNCT
admet-2772	477	38	and	and	CCONJ
admet-2772	477	39	shap	shap	PROPN
admet-2772	477	40	(	(	PUNCT
admet-2772	477	41	shapley	shapley	ADJ
admet-2772	477	42	additive	additive	ADJ
admet-2772	477	43	explanations	explanation	NOUN
admet-2772	477	44	)	)	PUNCT
admet-2772	477	45	,	,	PUNCT
admet-2772	477	46	in	in	ADP
admet-2772	477	47	interpreting	interpret	VERB
admet-2772	477	48	complex	complex	ADJ
admet-2772	477	49	machine	machine	NOUN
admet-2772	477	50	learning	learning	NOUN
admet-2772	477	51	models	model	NOUN
admet-2772	477	52	for	for	ADP
admet-2772	477	53	medical	medical	ADJ
admet-2772	477	54	applications	application	NOUN
admet-2772	477	55	such	such	ADJ
admet-2772	477	56	as	as	ADP
admet-2772	477	57	alzheimer	alzheimer	PROPN
admet-2772	477	58	's	's	PART
admet-2772	477	59	disease	disease	NOUN
admet-2772	477	60	detection	detection	NOUN
admet-2772	477	61	[	[	X
admet-2772	477	62	183	183	NUM
admet-2772	477	63	]	]	PUNCT
admet-2772	477	64	.	.	PUNCT
admet-2772	478	1	the	the	DET
admet-2772	478	2	paper	paper	NOUN
admet-2772	478	3	introduced	introduce	VERB
admet-2772	478	4	lime	lime	NOUN
admet-2772	478	5	,	,	PUNCT
admet-2772	478	6	a	a	DET
admet-2772	478	7	method	method	NOUN
admet-2772	478	8	designed	design	VERB
admet-2772	478	9	to	to	PART
admet-2772	478	10	provide	provide	VERB
admet-2772	478	11	interpretable	interpretable	ADJ
admet-2772	478	12	explanations	explanation	NOUN
admet-2772	478	13	for	for	ADP
admet-2772	478	14	complex	complex	ADJ
admet-2772	478	15	machine	machine	NOUN
admet-2772	478	16	learning	learning	NOUN
admet-2772	478	17	models	model	NOUN
admet-2772	478	18	by	by	ADP
admet-2772	478	19	approximating	approximate	VERB
admet-2772	478	20	their	their	PRON
admet-2772	478	21	behaviour	behaviour	NOUN
admet-2772	478	22	locally	locally	ADV
admet-2772	478	23	.	.	PUNCT
admet-2772	479	1	lime	lime	NOUN
admet-2772	479	2	achieves	achieve	VERB
admet-2772	479	3	this	this	PRON
admet-2772	479	4	by	by	ADP
admet-2772	479	5	generating	generate	VERB
admet-2772	479	6	local	local	ADJ
admet-2772	479	7	surrogate	surrogate	ADJ
admet-2772	479	8	models	model	NOUN
admet-2772	479	9	around	around	ADP
admet-2772	479	10	specific	specific	ADJ
admet-2772	479	11	instances	instance	NOUN
admet-2772	479	12	,	,	PUNCT
admet-2772	479	13	enabling	enable	VERB
admet-2772	479	14	users	user	NOUN
admet-2772	479	15	to	to	PART
admet-2772	479	16	understand	understand	VERB
admet-2772	479	17	model	model	NOUN
admet-2772	479	18	predictions	prediction	NOUN
admet-2772	479	19	on	on	ADP
admet-2772	479	20	individual	individual	ADJ
admet-2772	479	21	data	datum	NOUN
admet-2772	479	22	points	point	NOUN
admet-2772	479	23	.	.	PUNCT
admet-2772	480	1	a	a	DET
admet-2772	480	2	novel	novel	ADJ
admet-2772	480	3	extension	extension	NOUN
admet-2772	480	4	,	,	PUNCT
admet-2772	480	5	kg	kg	NOUN
admet-2772	480	6	-	-	PUNCT
admet-2772	480	7	lime	lime	NOUN
admet-2772	480	8	,	,	PUNCT
admet-2772	480	9	has	have	AUX
admet-2772	480	10	been	be	AUX
admet-2772	480	11	developed	develop	VERB
admet-2772	480	12	to	to	PART
admet-2772	480	13	predict	predict	VERB
admet-2772	480	14	individualized	individualized	ADJ
admet-2772	480	15	risk	risk	NOUN
admet-2772	480	16	of	of	ADP
admet-2772	480	17	adverse	adverse	ADJ
admet-2772	480	18	drug	drug	NOUN
admet-2772	480	19	events	event	NOUN
admet-2772	480	20	in	in	ADP
admet-2772	480	21	multiple	multiple	ADJ
admet-2772	480	22	sclerosis	sclerosis	NOUN
admet-2772	480	23	therapy	therapy	NOUN
admet-2772	480	24	,	,	PUNCT
admet-2772	480	25	leveraging	leverage	VERB
admet-2772	480	26	knowledge	knowledge	NOUN
admet-2772	480	27	graphs	graph	NOUN
admet-2772	480	28	for	for	ADP
admet-2772	480	29	more	more	ADV
admet-2772	480	30	interpretable	interpretable	ADJ
admet-2772	480	31	explanations	explanation	NOUN
admet-2772	481	1	[	[	X
admet-2772	481	2	184	184	NUM
admet-2772	481	3	]	]	PUNCT
admet-2772	481	4	.	.	PUNCT
admet-2772	482	1	another	another	DET
admet-2772	482	2	study	study	NOUN
admet-2772	482	3	by	by	ADP
admet-2772	482	4	gabbay	gabbay	PROPN
admet-2772	482	5	et	et	PROPN
admet-2772	482	6	al	al	PROPN
admet-2772	482	7	.	.	PUNCT
admet-2772	483	1	[	[	X
admet-2772	483	2	185	185	NUM
admet-2772	483	3	]	]	PUNCT
admet-2772	483	4	presents	present	VERB
admet-2772	483	5	a	a	DET
admet-2772	483	6	lime	lime	NOUN
admet-2772	483	7	-	-	PUNCT
admet-2772	483	8	based	base	VERB
admet-2772	483	9	explainable	explainable	ADJ
admet-2772	483	10	machine	machine	NOUN
admet-2772	483	11	learning	learning	NOUN
admet-2772	483	12	model	model	NOUN
admet-2772	483	13	for	for	ADP
admet-2772	483	14	predicting	predict	VERB
admet-2772	483	15	the	the	DET
admet-2772	483	16	severity	severity	NOUN
admet-2772	483	17	level	level	NOUN
admet-2772	483	18	of	of	ADP
admet-2772	483	19	covid-19	covid-19	PROPN
admet-2772	483	20	diagnosed	diagnose	VERB
admet-2772	483	21	patients	patient	NOUN
admet-2772	483	22	.	.	PUNCT
admet-2772	484	1	by	by	ADP
admet-2772	484	2	employing	employ	VERB
admet-2772	484	3	lime	lime	NOUN
admet-2772	484	4	,	,	PUNCT
admet-2772	484	5	the	the	DET
admet-2772	484	6	model	model	NOUN
admet-2772	484	7	provides	provide	VERB
admet-2772	484	8	interpretable	interpretable	ADJ
admet-2772	484	9	insights	insight	NOUN
admet-2772	484	10	into	into	ADP
admet-2772	484	11	the	the	DET
admet-2772	484	12	factors	factor	NOUN
admet-2772	484	13	influencing	influence	VERB
admet-2772	484	14	severity	severity	NOUN
admet-2772	484	15	prediction	prediction	NOUN
admet-2772	484	16	,	,	PUNCT
admet-2772	484	17	aiding	aid	VERB
admet-2772	484	18	in	in	ADP
admet-2772	484	19	understanding	understanding	NOUN
admet-2772	484	20	and	and	CCONJ
admet-2772	484	21	decision	decision	NOUN
admet-2772	484	22	-	-	PUNCT
admet-2772	484	23	making	making	NOUN
admet-2772	484	24	in	in	ADP
admet-2772	484	25	covid-19	covid-19	PROPN
admet-2772	484	26	management	management	NOUN
admet-2772	484	27	.	.	PUNCT
admet-2772	485	1	another	another	DET
admet-2772	485	2	explainable	explainable	ADJ
admet-2772	485	3	technique	technique	NOUN
admet-2772	485	4	called	call	VERB
admet-2772	485	5	shap	shap	NOUN
admet-2772	485	6	(	(	PUNCT
admet-2772	485	7	shapley	shapley	ADJ
admet-2772	485	8	additive	additive	ADJ
admet-2772	485	9	explanations	explanation	NOUN
admet-2772	485	10	)	)	PUNCT
admet-2772	485	11	methodology	methodology	NOUN
admet-2772	485	12	has	have	AUX
admet-2772	485	13	emerged	emerge	VERB
admet-2772	485	14	as	as	ADP
admet-2772	485	15	a	a	DET
admet-2772	485	16	powerful	powerful	ADJ
admet-2772	485	17	tool	tool	NOUN
admet-2772	485	18	for	for	ADP
admet-2772	485	19	interpreting	interpret	VERB
admet-2772	485	20	machine	machine	NOUN
admet-2772	485	21	learning	learning	NOUN
admet-2772	485	22	models	model	NOUN
admet-2772	485	23	in	in	ADP
admet-2772	485	24	admet	admet	PROPN
admet-2772	485	25	prediction	prediction	NOUN
admet-2772	485	26	and	and	CCONJ
admet-2772	485	27	drug	drug	NOUN
admet-2772	485	28	design	design	NOUN
admet-2772	485	29	.	.	PUNCT
admet-2772	486	1	shap	shap	PROPN
admet-2772	486	2	enables	enable	VERB
admet-2772	486	3	the	the	DET
admet-2772	486	4	identification	identification	NOUN
admet-2772	486	5	and	and	CCONJ
admet-2772	486	6	prioritization	prioritization	NOUN
admet-2772	486	7	of	of	ADP
admet-2772	486	8	molecular	molecular	ADJ
admet-2772	486	9	features	feature	NOUN
admet-2772	486	10	that	that	PRON
admet-2772	486	11	influence	influence	NOUN
admet-2772	486	12	compound	compound	NOUN
admet-2772	486	13	activity	activity	NOUN
admet-2772	486	14	and	and	CCONJ
admet-2772	486	15	potency	potency	NOUN
admet-2772	486	16	predictions	prediction	NOUN
admet-2772	486	17	,	,	PUNCT
admet-2772	486	18	regardless	regardless	ADV
admet-2772	486	19	of	of	ADP
admet-2772	486	20	model	model	NOUN
admet-2772	486	21	complexity	complexity	NOUN
admet-2772	486	22	[	[	X
admet-2772	486	23	186	186	NUM
admet-2772	486	24	]	]	PUNCT
admet-2772	486	25	.	.	PUNCT
admet-2772	487	1	this	this	DET
admet-2772	487	2	approach	approach	NOUN
admet-2772	487	3	has	have	AUX
admet-2772	487	4	been	be	AUX
admet-2772	487	5	applied	apply	VERB
admet-2772	487	6	to	to	ADP
admet-2772	487	7	various	various	ADJ
admet-2772	487	8	admet	admet	NOUN
admet-2772	487	9	properties	property	NOUN
admet-2772	487	10	,	,	PUNCT
admet-2772	487	11	including	include	VERB
admet-2772	487	12	metabolic	metabolic	NOUN
admet-2772	487	13	stability	stability	NOUN
admet-2772	487	14	[	[	X
admet-2772	487	15	187	187	NUM
admet-2772	487	16	]	]	PUNCT
admet-2772	487	17	and	and	CCONJ
admet-2772	487	18	general	general	ADJ
admet-2772	487	19	adme	adme	NOUN
admet-2772	487	20	profiles	profile	NOUN
admet-2772	487	21	[	[	X
admet-2772	487	22	188	188	NUM
admet-2772	487	23	]	]	PUNCT
admet-2772	487	24	.	.	PUNCT
admet-2772	488	1	shap	shap	NOUN
admet-2772	488	2	analysis	analysis	NOUN
admet-2772	488	3	can	can	AUX
admet-2772	488	4	be	be	AUX
admet-2772	488	5	used	use	VERB
admet-2772	488	6	to	to	PART
admet-2772	488	7	interpret	interpret	VERB
admet-2772	488	8	predictions	prediction	NOUN
admet-2772	488	9	from	from	ADP
admet-2772	488	10	diverse	diverse	ADJ
admet-2772	488	11	machine	machine	NOUN
admet-2772	488	12	learning	learning	NOUN
admet-2772	488	13	algorithms	algorithm	NOUN
admet-2772	488	14	,	,	PUNCT
admet-2772	488	15	such	such	ADJ
admet-2772	488	16	as	as	ADP
admet-2772	488	17	random	random	ADJ
admet-2772	488	18	forests	forest	NOUN
admet-2772	488	19	,	,	PUNCT
admet-2772	488	20	support	support	VERB
admet-2772	488	21	vector	vector	NOUN
admet-2772	488	22	machines	machine	NOUN
admet-2772	488	23	,	,	PUNCT
admet-2772	488	24	and	and	CCONJ
admet-2772	488	25	deep	deep	ADJ
admet-2772	488	26	neural	neural	ADJ
admet-2772	488	27	networks	network	NOUN
admet-2772	488	28	[	[	X
admet-2772	488	29	189	189	NUM
admet-2772	488	30	]	]	PUNCT
admet-2772	488	31	.	.	PUNCT
admet-2772	489	1	by	by	ADP
admet-2772	489	2	providing	provide	VERB
admet-2772	489	3	insights	insight	NOUN
admet-2772	489	4	into	into	ADP
admet-2772	489	5	the	the	DET
admet-2772	489	6	contribution	contribution	NOUN
admet-2772	489	7	of	of	ADP
admet-2772	489	8	specific	specific	ADJ
admet-2772	489	9	structural	structural	ADJ
admet-2772	489	10	features	feature	NOUN
admet-2772	489	11	to	to	PART
admet-2772	489	12	model	model	NOUN
admet-2772	489	13	outcomes	outcome	NOUN
admet-2772	489	14	,	,	PUNCT
admet-2772	489	15	shap	shap	PROPN
admet-2772	489	16	aids	aid	NOUN
admet-2772	489	17	in	in	ADP
admet-2772	489	18	compound	compound	NOUN
admet-2772	489	19	optimization	optimization	NOUN
admet-2772	489	20	and	and	CCONJ
admet-2772	489	21	supports	support	VERB
admet-2772	489	22	experts	expert	NOUN
admet-2772	489	23	in	in	ADP
admet-2772	489	24	drug	drug	NOUN
admet-2772	489	25	candidate	candidate	NOUN
admet-2772	489	26	selection	selection	NOUN
admet-2772	489	27	[	[	X
admet-2772	489	28	188	188	NUM
admet-2772	489	29	]	]	PUNCT
admet-2772	489	30	.	.	PUNCT
admet-2772	490	1	this	this	DET
admet-2772	490	2	interpretability	interpretability	NOUN
admet-2772	490	3	enhances	enhance	VERB
admet-2772	490	4	confidence	confidence	NOUN
admet-2772	490	5	in	in	ADP
admet-2772	490	6	machine	machine	NOUN
admet-2772	490	7	learning	learn	VERB
admet-2772	490	8	applications	application	NOUN
admet-2772	490	9	within	within	ADP
admet-2772	490	10	pharmaceutical	pharmaceutical	ADJ
admet-2772	490	11	research	research	NOUN
admet-2772	490	12	.	.	PUNCT
admet-2772	491	1	these	these	DET
admet-2772	491	2	advancements	advancement	NOUN
admet-2772	491	3	demonstrate	demonstrate	VERB
admet-2772	491	4	the	the	DET
admet-2772	491	5	growing	grow	VERB
admet-2772	491	6	importance	importance	NOUN
admet-2772	491	7	of	of	ADP
admet-2772	491	8	interpretable	interpretable	ADJ
admet-2772	491	9	machine	machine	NOUN
admet-2772	491	10	learning	learning	NOUN
admet-2772	491	11	models	model	NOUN
admet-2772	491	12	in	in	ADP
admet-2772	491	13	drug	drug	NOUN
admet-2772	491	14	discovery	discovery	NOUN
admet-2772	491	15	and	and	CCONJ
admet-2772	491	16	optimization	optimization	NOUN
admet-2772	491	17	,	,	PUNCT
admet-2772	491	18	offering	offer	VERB
admet-2772	491	19	researchers	researcher	NOUN
admet-2772	491	20	valuable	valuable	ADJ
admet-2772	491	21	tools	tool	NOUN
admet-2772	491	22	for	for	ADP
admet-2772	491	23	understanding	understanding	NOUN
admet-2772	491	24	and	and	CCONJ
admet-2772	491	25	improving	improve	VERB
admet-2772	491	26	admet	admet	NOUN
admet-2772	491	27	predictions	prediction	NOUN
admet-2772	491	28	.	.	PUNCT
admet-2772	492	1	admet	admet	PROPN
admet-2772	492	2	&	&	CCONJ
admet-2772	492	3	dmpk	dmpk	PROPN
admet-2772	492	4	13(3	13(3	NUM
admet-2772	492	5	)	)	PUNCT
admet-2772	492	6	(	(	PUNCT
admet-2772	492	7	2025	2025	NUM
admet-2772	492	8	)	)	PUNCT
admet-2772	492	9	2772	2772	NUM
admet-2772	492	10	machine	machine	NOUN
admet-2772	492	11	learning	learning	NOUN
admet-2772	492	12	models	model	NOUN
admet-2772	492	13	for	for	ADP
admet-2772	492	14	admet	admet	ADJ
admet-2772	492	15	prediction	prediction	NOUN
admet-2772	492	16	in	in	ADP
admet-2772	492	17	drug	drug	NOUN
admet-2772	492	18	development	development	NOUN
admet-2772	492	19	doi	doi	PROPN
admet-2772	492	20	:	:	PUNCT
admet-2772	492	21	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	492	22	19	19	NUM
admet-2772	492	23	7	7	NUM
admet-2772	492	24	.	.	PUNCT
admet-2772	492	25	machine	machine	NOUN
admet-2772	492	26	learning	learn	VERB
admet-2772	492	27	techniques	technique	NOUN
admet-2772	492	28	in	in	ADP
admet-2772	492	29	clinical	clinical	ADJ
admet-2772	492	30	trial	trial	NOUN
admet-2772	492	31	designs	design	NOUN
admet-2772	492	32	in	in	ADP
admet-2772	492	33	silico	silico	NOUN
admet-2772	492	34	prediction	prediction	NOUN
admet-2772	492	35	of	of	ADP
admet-2772	492	36	absorption	absorption	NOUN
admet-2772	492	37	,	,	PUNCT
admet-2772	492	38	distribution	distribution	NOUN
admet-2772	492	39	,	,	PUNCT
admet-2772	492	40	metabolism	metabolism	NOUN
admet-2772	492	41	,	,	PUNCT
admet-2772	492	42	and	and	CCONJ
admet-2772	492	43	excretion	excretion	NOUN
admet-2772	492	44	(	(	PUNCT
admet-2772	492	45	adme	adme	NOUN
admet-2772	492	46	)	)	PUNCT
admet-2772	492	47	properties	property	NOUN
admet-2772	492	48	,	,	PUNCT
admet-2772	492	49	as	as	ADV
admet-2772	492	50	well	well	ADV
admet-2772	492	51	as	as	ADP
admet-2772	492	52	model	model	NOUN
admet-2772	492	53	-	-	PUNCT
admet-2772	492	54	informed	inform	VERB
admet-2772	492	55	drug	drug	NOUN
admet-2772	492	56	discovery	discovery	NOUN
admet-2772	492	57	and	and	CCONJ
admet-2772	492	58	development	development	NOUN
admet-2772	492	59	(	(	PUNCT
admet-2772	492	60	mid3)1	mid3)1	NOUN
admet-2772	492	61	strategies	strategy	NOUN
admet-2772	492	62	.	.	PUNCT
admet-2772	493	1	mid3	mid3	PROPN
admet-2772	493	2	includes	include	VERB
admet-2772	493	3	providing	provide	VERB
admet-2772	493	4	quantitative	quantitative	ADJ
admet-2772	493	5	predictions	prediction	NOUN
admet-2772	493	6	for	for	ADP
admet-2772	493	7	aspects	aspect	NOUN
admet-2772	493	8	such	such	ADJ
admet-2772	493	9	as	as	ADP
admet-2772	493	10	pharmacokinetics	pharmacokinetic	NOUN
admet-2772	493	11	,	,	PUNCT
admet-2772	493	12	pharmacodynamics	pharmacodynamic	NOUN
admet-2772	493	13	,	,	PUNCT
admet-2772	493	14	efficacy	efficacy	NOUN
admet-2772	493	15	and	and	CCONJ
admet-2772	493	16	safety	safety	NOUN
admet-2772	493	17	end	end	NOUN
admet-2772	493	18	points	point	NOUN
admet-2772	493	19	,	,	PUNCT
admet-2772	493	20	and	and	CCONJ
admet-2772	493	21	disease	disease	NOUN
admet-2772	493	22	progression	progression	NOUN
admet-2772	494	1	[	[	X
admet-2772	494	2	190	190	NUM
admet-2772	494	3	]	]	PUNCT
admet-2772	494	4	.	.	PUNCT
admet-2772	495	1	by	by	ADP
admet-2772	495	2	leveraging	leverage	VERB
admet-2772	495	3	these	these	DET
admet-2772	495	4	models	model	NOUN
admet-2772	495	5	,	,	PUNCT
admet-2772	495	6	researchers	researcher	NOUN
admet-2772	495	7	can	can	AUX
admet-2772	495	8	optimize	optimize	VERB
admet-2772	495	9	dosing	dosing	ADJ
admet-2772	495	10	strategies	strategy	NOUN
admet-2772	495	11	,	,	PUNCT
admet-2772	495	12	inform	inform	VERB
admet-2772	495	13	clinical	clinical	ADJ
admet-2772	495	14	trial	trial	NOUN
admet-2772	495	15	designs	design	NOUN
admet-2772	495	16	,	,	PUNCT
admet-2772	495	17	and	and	CCONJ
admet-2772	495	18	obtain	obtain	VERB
admet-2772	495	19	robust	robust	ADJ
admet-2772	495	20	quantitative	quantitative	ADJ
admet-2772	495	21	assessments	assessment	NOUN
admet-2772	495	22	regarding	regard	VERB
admet-2772	495	23	drug	drug	NOUN
admet-2772	495	24	efficacy	efficacy	NOUN
admet-2772	495	25	and	and	CCONJ
admet-2772	495	26	safety	safety	NOUN
admet-2772	495	27	.	.	PUNCT
admet-2772	496	1	the	the	DET
admet-2772	496	2	mainstay	mainstay	NOUN
admet-2772	496	3	of	of	ADP
admet-2772	496	4	modelling	model	VERB
admet-2772	496	5	activities	activity	NOUN
admet-2772	496	6	for	for	ADP
admet-2772	496	7	drug	drug	NOUN
admet-2772	496	8	development	development	NOUN
admet-2772	496	9	includes	include	VERB
admet-2772	496	10	an	an	DET
admet-2772	496	11	empirical	empirical	ADJ
admet-2772	496	12	compartmental	compartmental	NOUN
admet-2772	496	13	model	model	NOUN
admet-2772	496	14	built	build	VERB
admet-2772	496	15	from	from	ADP
admet-2772	496	16	sparsely	sparsely	ADV
admet-2772	496	17	sampled	sample	VERB
admet-2772	496	18	pk	pk	NOUN
admet-2772	496	19	/	/	SYM
admet-2772	496	20	pd	pd	NOUN
admet-2772	496	21	datasets	dataset	NOUN
admet-2772	496	22	[	[	X
admet-2772	496	23	191	191	NUM
admet-2772	496	24	]	]	PUNCT
admet-2772	496	25	.	.	PUNCT
admet-2772	497	1	in	in	ADP
admet-2772	497	2	this	this	DET
admet-2772	497	3	respect	respect	NOUN
admet-2772	497	4	,	,	PUNCT
admet-2772	497	5	ai	ai	VERB
admet-2772	497	6	/	/	SYM
admet-2772	497	7	ml	ml	VERB
admet-2772	497	8	provides	provide	VERB
admet-2772	497	9	new	new	ADJ
admet-2772	497	10	ways	way	NOUN
admet-2772	497	11	for	for	SCONJ
admet-2772	497	12	pharmacometricians	pharmacometrician	NOUN
admet-2772	497	13	to	to	PART
admet-2772	497	14	think	think	VERB
admet-2772	497	15	about	about	ADP
admet-2772	497	16	their	their	PRON
admet-2772	497	17	models	model	NOUN
admet-2772	497	18	.	.	PUNCT
admet-2772	498	1	there	there	PRON
admet-2772	498	2	have	have	AUX
admet-2772	498	3	been	be	AUX
admet-2772	498	4	a	a	DET
admet-2772	498	5	number	number	NOUN
admet-2772	498	6	of	of	ADP
admet-2772	498	7	approaches	approach	NOUN
admet-2772	498	8	proposed	propose	VERB
admet-2772	498	9	in	in	ADP
admet-2772	498	10	using	use	VERB
admet-2772	498	11	feed	feed	NOUN
admet-2772	498	12	-	-	PUNCT
admet-2772	498	13	forward	forward	NOUN
admet-2772	498	14	nns	nn	NOUN
admet-2772	498	15	[	[	X
admet-2772	498	16	192	192	NUM
admet-2772	498	17	]	]	PUNCT
admet-2772	498	18	for	for	ADP
admet-2772	498	19	modelling	modelling	NOUN
admet-2772	498	20	of	of	ADP
admet-2772	498	21	pk(/pd	pk(/pd	NOUN
admet-2772	498	22	)	)	PUNCT
admet-2772	498	23	data	datum	NOUN
admet-2772	498	24	.	.	PUNCT
admet-2772	499	1	however	however	ADV
admet-2772	499	2	,	,	PUNCT
admet-2772	499	3	these	these	PRON
admet-2772	499	4	did	do	AUX
admet-2772	499	5	not	not	PART
admet-2772	499	6	tackle	tackle	VERB
admet-2772	499	7	the	the	DET
admet-2772	499	8	more	more	ADV
admet-2772	499	9	complex	complex	ADJ
admet-2772	499	10	problem	problem	NOUN
admet-2772	499	11	of	of	ADP
admet-2772	499	12	extrapolating	extrapolate	VERB
admet-2772	499	13	outside	outside	ADP
admet-2772	499	14	the	the	DET
admet-2772	499	15	range	range	NOUN
admet-2772	499	16	of	of	ADP
admet-2772	499	17	observed	observed	ADJ
admet-2772	499	18	data	datum	NOUN
admet-2772	499	19	.	.	PUNCT
admet-2772	500	1	in	in	ADP
admet-2772	500	2	fact	fact	NOUN
admet-2772	500	3	,	,	PUNCT
admet-2772	500	4	the	the	DET
admet-2772	500	5	main	main	ADJ
admet-2772	500	6	limitation	limitation	NOUN
admet-2772	500	7	of	of	ADP
admet-2772	500	8	such	such	ADJ
admet-2772	500	9	models	model	NOUN
admet-2772	500	10	is	be	AUX
admet-2772	500	11	that	that	SCONJ
admet-2772	500	12	they	they	PRON
admet-2772	500	13	do	do	AUX
admet-2772	500	14	not	not	PART
admet-2772	500	15	explicitly	explicitly	ADV
admet-2772	500	16	encode	encode	VERB
admet-2772	500	17	causality	causality	NOUN
admet-2772	500	18	relationships	relationship	NOUN
admet-2772	500	19	among	among	ADP
admet-2772	500	20	dose	dose	PROPN
admet-2772	500	21	,	,	PUNCT
admet-2772	500	22	pks	pks	NOUN
admet-2772	500	23	,	,	PUNCT
admet-2772	500	24	and	and	CCONJ
admet-2772	500	25	pds	pds	NOUN
admet-2772	500	26	and	and	CCONJ
admet-2772	500	27	,	,	PUNCT
admet-2772	500	28	hence	hence	ADV
admet-2772	500	29	,	,	PUNCT
admet-2772	500	30	can	can	AUX
admet-2772	500	31	not	not	PART
admet-2772	500	32	enable	enable	VERB
admet-2772	500	33	robust	robust	ADJ
admet-2772	500	34	predictions	prediction	NOUN
admet-2772	500	35	of	of	ADP
admet-2772	500	36	new	new	ADJ
admet-2772	500	37	dosing	dosing	ADJ
admet-2772	500	38	regimens	regimen	NOUN
admet-2772	500	39	.	.	PUNCT
admet-2772	501	1	in	in	ADP
admet-2772	501	2	the	the	DET
admet-2772	501	3	1990s	1990	NOUN
admet-2772	501	4	,	,	PUNCT
admet-2772	501	5	the	the	DET
admet-2772	501	6	availability	availability	NOUN
admet-2772	501	7	of	of	ADP
admet-2772	501	8	biological	biological	ADJ
admet-2772	501	9	reagents	reagent	NOUN
admet-2772	501	10	and	and	CCONJ
admet-2772	501	11	liquid	liquid	ADJ
admet-2772	501	12	chromatography	chromatography	NOUN
admet-2772	501	13	mass	mass	NOUN
admet-2772	501	14	spectrometry	spectrometry	NOUN
admet-2772	501	15	dramatically	dramatically	ADV
admet-2772	501	16	reduced	reduce	VERB
admet-2772	501	17	the	the	DET
admet-2772	501	18	attrition	attrition	NOUN
admet-2772	501	19	of	of	ADP
admet-2772	501	20	small	small	ADJ
admet-2772	501	21	-	-	PUNCT
admet-2772	501	22	molecule	molecule	NOUN
admet-2772	501	23	drugs	drug	NOUN
admet-2772	501	24	due	due	ADP
admet-2772	501	25	to	to	ADP
admet-2772	501	26	pk	pk	NOUN
admet-2772	501	27	considerations	consideration	NOUN
admet-2772	501	28	.	.	PUNCT
admet-2772	502	1	currently	currently	ADV
admet-2772	502	2	,	,	PUNCT
admet-2772	502	3	attrition	attrition	NOUN
admet-2772	502	4	due	due	ADP
admet-2772	502	5	to	to	ADP
admet-2772	502	6	poor	poor	ADJ
admet-2772	502	7	clinical	clinical	ADJ
admet-2772	502	8	exposure	exposure	NOUN
admet-2772	502	9	is	be	AUX
admet-2772	502	10	rare	rare	ADJ
admet-2772	502	11	,	,	PUNCT
admet-2772	502	12	with	with	ADP
admet-2772	502	13	preclinical	preclinical	ADJ
admet-2772	502	14	toxicology	toxicology	NOUN
admet-2772	502	15	,	,	PUNCT
admet-2772	502	16	clinical	clinical	ADJ
admet-2772	502	17	intolerability	intolerability	NOUN
admet-2772	502	18	,	,	PUNCT
admet-2772	502	19	or	or	CCONJ
admet-2772	502	20	insufficient	insufficient	ADJ
admet-2772	502	21	efficacy	efficacy	NOUN
admet-2772	502	22	being	be	AUX
admet-2772	502	23	the	the	DET
admet-2772	502	24	major	major	ADJ
admet-2772	502	25	sources	source	NOUN
admet-2772	502	26	of	of	ADP
admet-2772	502	27	attrition	attrition	NOUN
admet-2772	502	28	[	[	X
admet-2772	502	29	7	7	NUM
admet-2772	502	30	]	]	PUNCT
admet-2772	502	31	.	.	PUNCT
admet-2772	503	1	reagents	reagent	NOUN
admet-2772	503	2	,	,	PUNCT
admet-2772	503	3	such	such	ADJ
admet-2772	503	4	as	as	ADP
admet-2772	503	5	microsomes	microsome	NOUN
admet-2772	503	6	,	,	PUNCT
admet-2772	503	7	cryopreserved	cryopreserved	ADJ
admet-2772	503	8	hepatocytes	hepatocyte	NOUN
admet-2772	503	9	,	,	PUNCT
admet-2772	503	10	recombinant	recombinant	ADJ
admet-2772	503	11	drug	drug	NOUN
admet-2772	503	12	metabolizing	metabolize	VERB
admet-2772	503	13	enzymes	enzyme	NOUN
admet-2772	503	14	,	,	PUNCT
admet-2772	503	15	and	and	CCONJ
admet-2772	503	16	cells	cell	NOUN
admet-2772	503	17	overexpressing	overexpresse	VERB
admet-2772	503	18	specific	specific	ADJ
admet-2772	503	19	transporters	transporter	NOUN
admet-2772	503	20	,	,	PUNCT
admet-2772	503	21	have	have	AUX
admet-2772	503	22	enabled	enable	VERB
admet-2772	503	23	drug	drug	NOUN
admet-2772	503	24	metabolism	metabolism	NOUN
admet-2772	503	25	and	and	CCONJ
admet-2772	503	26	pk	pk	NOUN
admet-2772	503	27	departments	department	NOUN
admet-2772	503	28	to	to	PART
admet-2772	503	29	generate	generate	VERB
admet-2772	503	30	large	large	ADJ
admet-2772	503	31	quantities	quantity	NOUN
admet-2772	503	32	of	of	ADP
admet-2772	503	33	in	in	ADP
admet-2772	503	34	vitro	vitro	X
admet-2772	503	35	adme	adme	NOUN
admet-2772	503	36	data	datum	NOUN
admet-2772	503	37	over	over	ADP
admet-2772	503	38	the	the	DET
admet-2772	503	39	last	last	ADJ
admet-2772	503	40	15	15	NUM
admet-2772	503	41	to	to	PART
admet-2772	503	42	20	20	NUM
admet-2772	503	43	years	year	NOUN
admet-2772	503	44	.	.	PUNCT
admet-2772	504	1	these	these	DET
admet-2772	504	2	data	datum	NOUN
admet-2772	504	3	serve	serve	VERB
admet-2772	504	4	two	two	NUM
admet-2772	504	5	specific	specific	ADJ
admet-2772	504	6	functions	function	NOUN
admet-2772	504	7	:	:	PUNCT
admet-2772	504	8	first	first	ADV
admet-2772	504	9	,	,	PUNCT
admet-2772	504	10	in	in	ADP
admet-2772	504	11	vitro	vitro	X
admet-2772	504	12	data	datum	NOUN
admet-2772	504	13	related	relate	VERB
admet-2772	504	14	to	to	ADP
admet-2772	504	15	metabolic	metabolic	NOUN
admet-2772	504	16	stability	stability	NOUN
admet-2772	504	17	,	,	PUNCT
admet-2772	504	18	plasma	plasma	NOUN
admet-2772	504	19	protein	protein	NOUN
admet-2772	504	20	binding	bind	VERB
admet-2772	504	21	,	,	PUNCT
admet-2772	504	22	permeability	permeability	NOUN
admet-2772	504	23	,	,	PUNCT
admet-2772	504	24	efflux	efflux	VERB
admet-2772	504	25	,	,	PUNCT
admet-2772	504	26	and	and	CCONJ
admet-2772	504	27	cyp	cyp	ADJ
admet-2772	504	28	inhibition	inhibition	NOUN
admet-2772	504	29	can	can	AUX
admet-2772	504	30	be	be	AUX
admet-2772	504	31	used	use	VERB
admet-2772	504	32	for	for	ADP
admet-2772	504	33	the	the	DET
admet-2772	504	34	design	design	NOUN
admet-2772	504	35	(	(	PUNCT
admet-2772	504	36	i.e.	i.e.	X
admet-2772	504	37	prior	prior	ADV
admet-2772	504	38	to	to	ADP
admet-2772	504	39	synthesis	synthesis	NOUN
admet-2772	504	40	)	)	PUNCT
admet-2772	504	41	of	of	ADP
admet-2772	504	42	small	small	ADJ
admet-2772	504	43	molecules	molecule	NOUN
admet-2772	504	44	with	with	ADP
admet-2772	504	45	superior	superior	ADJ
admet-2772	504	46	adme	adme	NOUN
admet-2772	504	47	properties	property	NOUN
admet-2772	504	48	,	,	PUNCT
admet-2772	504	49	along	along	ADP
admet-2772	504	50	with	with	ADP
admet-2772	504	51	other	other	ADJ
admet-2772	504	52	parameters	parameter	NOUN
admet-2772	504	53	,	,	PUNCT
admet-2772	504	54	such	such	ADJ
admet-2772	504	55	as	as	ADP
admet-2772	504	56	biochemical	biochemical	ADJ
admet-2772	504	57	and	and	CCONJ
admet-2772	504	58	cellular	cellular	ADJ
admet-2772	504	59	potency	potency	NOUN
admet-2772	504	60	and	and	CCONJ
admet-2772	504	61	selectivity	selectivity	NOUN
admet-2772	504	62	data	datum	NOUN
admet-2772	504	63	;	;	PUNCT
admet-2772	504	64	second	second	ADJ
admet-2772	504	65	,	,	PUNCT
admet-2772	504	66	archived	archive	VERB
admet-2772	504	67	data	datum	NOUN
admet-2772	504	68	can	can	AUX
admet-2772	504	69	be	be	AUX
admet-2772	504	70	used	use	VERB
admet-2772	504	71	to	to	PART
admet-2772	504	72	build	build	VERB
admet-2772	504	73	ml	ml	NOUN
admet-2772	504	74	models	model	NOUN
admet-2772	504	75	to	to	PART
admet-2772	504	76	predict	predict	VERB
admet-2772	504	77	these	these	DET
admet-2772	504	78	properties	property	NOUN
admet-2772	504	79	(	(	PUNCT
admet-2772	504	80	in	in	ADP
admet-2772	504	81	silico	silico	NOUN
admet-2772	504	82	optimization	optimization	NOUN
admet-2772	504	83	)	)	PUNCT
admet-2772	504	84	.	.	PUNCT
admet-2772	505	1	8	8	X
admet-2772	505	2	.	.	PUNCT
admet-2772	505	3	data	datum	NOUN
admet-2772	505	4	sources	source	NOUN
admet-2772	505	5	and	and	CCONJ
admet-2772	505	6	challenges	challenge	NOUN
admet-2772	505	7	in	in	ADP
admet-2772	505	8	machine	machine	NOUN
admet-2772	505	9	learning	learning	NOUN
admet-2772	505	10	based	base	VERB
admet-2772	505	11	adme	adme	NOUN
admet-2772	505	12	-	-	PUNCT
admet-2772	505	13	tox	tox	NOUN
admet-2772	505	14	prediction	prediction	NOUN
admet-2772	505	15	8.1	8.1	NUM
admet-2772	505	16	.	.	PUNCT
admet-2772	506	1	key	key	ADJ
admet-2772	506	2	databases	database	NOUN
admet-2772	506	3	for	for	ADP
admet-2772	506	4	adme	adme	NOUN
admet-2772	506	5	-	-	PUNCT
admet-2772	506	6	tox	tox	NOUN
admet-2772	506	7	data	datum	NOUN
admet-2772	506	8	the	the	DET
admet-2772	506	9	development	development	NOUN
admet-2772	506	10	of	of	ADP
admet-2772	506	11	predictive	predictive	ADJ
admet-2772	506	12	models	model	NOUN
admet-2772	506	13	for	for	ADP
admet-2772	506	14	adme	adme	NOUN
admet-2772	506	15	-	-	PUNCT
admet-2772	506	16	tox	tox	NOUN
admet-2772	506	17	properties	property	NOUN
admet-2772	506	18	is	be	AUX
admet-2772	506	19	crucial	crucial	ADJ
admet-2772	506	20	in	in	ADP
admet-2772	506	21	drug	drug	NOUN
admet-2772	506	22	discovery	discovery	NOUN
admet-2772	506	23	,	,	PUNCT
admet-2772	506	24	but	but	CCONJ
admet-2772	506	25	it	it	PRON
admet-2772	506	26	relies	rely	VERB
admet-2772	506	27	heavily	heavily	ADV
admet-2772	506	28	on	on	ADP
admet-2772	506	29	the	the	DET
admet-2772	506	30	availability	availability	NOUN
admet-2772	506	31	and	and	CCONJ
admet-2772	506	32	quality	quality	NOUN
admet-2772	506	33	of	of	ADP
admet-2772	506	34	data	datum	NOUN
admet-2772	506	35	.	.	PUNCT
admet-2772	507	1	several	several	ADJ
admet-2772	507	2	databases	database	NOUN
admet-2772	507	3	and	and	CCONJ
admet-2772	507	4	resources	resource	NOUN
admet-2772	507	5	have	have	AUX
admet-2772	507	6	emerged	emerge	VERB
admet-2772	507	7	to	to	PART
admet-2772	507	8	address	address	VERB
admet-2772	507	9	this	this	DET
admet-2772	507	10	need	need	NOUN
admet-2772	507	11	.	.	PUNCT
admet-2772	508	1	canault	canault	VERB
admet-2772	508	2	et	et	PROPN
admet-2772	508	3	al	al	PROPN
admet-2772	508	4	.	.	PUNCT
admet-2772	509	1	[	[	X
admet-2772	509	2	193	193	NUM
admet-2772	509	3	]	]	PUNCT
admet-2772	509	4	proposed	propose	VERB
admet-2772	509	5	an	an	DET
admet-2772	509	6	interactive	interactive	ADJ
admet-2772	509	7	network	network	NOUN
admet-2772	509	8	of	of	ADP
admet-2772	509	9	databases	database	NOUN
admet-2772	509	10	to	to	PART
admet-2772	509	11	facilitate	facilitate	VERB
admet-2772	509	12	finding	find	VERB
admet-2772	509	13	relevant	relevant	ADJ
admet-2772	509	14	adme	adme	NOUN
admet-2772	509	15	-	-	PUNCT
admet-2772	509	16	tox	tox	NOUN
admet-2772	509	17	data	datum	NOUN
admet-2772	509	18	sources	source	NOUN
admet-2772	509	19	.	.	PUNCT
admet-2772	510	1	ekins	ekin	NOUN
admet-2772	510	2	and	and	CCONJ
admet-2772	510	3	williams	williams	PROPN
admet-2772	511	1	[	[	X
admet-2772	511	2	194	194	NUM
admet-2772	511	3	]	]	PUNCT
admet-2772	511	4	advocated	advocate	VERB
admet-2772	511	5	for	for	ADP
admet-2772	511	6	making	make	VERB
admet-2772	511	7	preclinical	preclinical	ADJ
admet-2772	511	8	adme	adme	NOUN
admet-2772	511	9	-	-	PUNCT
admet-2772	511	10	tox	tox	NOUN
admet-2772	511	11	data	datum	NOUN
admet-2772	511	12	freely	freely	ADV
admet-2772	511	13	available	available	ADJ
admet-2772	511	14	on	on	ADP
admet-2772	511	15	the	the	DET
admet-2772	511	16	web	web	NOUN
admet-2772	511	17	,	,	PUNCT
admet-2772	511	18	suggesting	suggest	VERB
admet-2772	511	19	the	the	DET
admet-2772	511	20	expansion	expansion	NOUN
admet-2772	511	21	of	of	ADP
admet-2772	511	22	databases	database	NOUN
admet-2772	511	23	like	like	ADP
admet-2772	511	24	chemspider	chemspider	NOUN
admet-2772	511	25	.	.	PUNCT
admet-2772	512	1	pawar	pawar	PROPN
admet-2772	512	2	et	et	PROPN
admet-2772	512	3	al	al	PROPN
admet-2772	512	4	.	.	PUNCT
admet-2772	513	1	[	[	X
admet-2772	513	2	195	195	NUM
admet-2772	513	3	]	]	PUNCT
admet-2772	513	4	conducted	conduct	VERB
admet-2772	513	5	a	a	DET
admet-2772	513	6	comprehensive	comprehensive	ADJ
admet-2772	513	7	review	review	NOUN
admet-2772	513	8	of	of	ADP
admet-2772	513	9	over	over	ADP
admet-2772	513	10	900	900	NUM
admet-2772	513	11	databases	database	NOUN
admet-2772	513	12	relevant	relevant	ADJ
admet-2772	513	13	to	to	ADP
admet-2772	513	14	in	in	ADP
admet-2772	513	15	silico	silico	NOUN
admet-2772	513	16	toxicology	toxicology	NOUN
admet-2772	513	17	,	,	PUNCT
admet-2772	513	18	categorizing	categorize	VERB
admet-2772	513	19	them	they	PRON
admet-2772	513	20	based	base	VERB
admet-2772	513	21	on	on	ADP
admet-2772	513	22	various	various	ADJ
admet-2772	513	23	criteria	criterion	NOUN
admet-2772	513	24	.	.	PUNCT
admet-2772	514	1	to	to	PART
admet-2772	514	2	assist	assist	VERB
admet-2772	514	3	in	in	ADP
admet-2772	514	4	compound	compound	NOUN
admet-2772	514	5	filtering	filtering	NOUN
admet-2772	514	6	,	,	PUNCT
admet-2772	514	7	miteva	miteva	PROPN
admet-2772	514	8	et	et	PROPN
admet-2772	514	9	al	al	PROPN
admet-2772	514	10	.	.	PUNCT
admet-2772	515	1	[	[	X
admet-2772	515	2	196	196	NUM
admet-2772	515	3	]	]	PUNCT
admet-2772	515	4	developed	develop	VERB
admet-2772	515	5	faf	faf	NUM
admet-2772	515	6	-	-	PUNCT
admet-2772	515	7	drugs	drug	NOUN
admet-2772	515	8	,	,	PUNCT
admet-2772	515	9	an	an	DET
admet-2772	515	10	online	online	ADJ
admet-2772	515	11	service	service	NOUN
admet-2772	515	12	that	that	PRON
admet-2772	515	13	allows	allow	VERB
admet-2772	515	14	users	user	NOUN
admet-2772	515	15	to	to	PART
admet-2772	515	16	process	process	VERB
admet-2772	515	17	their	their	PRON
admet-2772	515	18	compound	compound	NOUN
admet-2772	515	19	collections	collection	NOUN
admet-2772	515	20	using	use	VERB
admet-2772	515	21	simple	simple	ADJ
admet-2772	515	22	adme	adme	NOUN
admet-2772	515	23	-	-	PUNCT
admet-2772	515	24	tox	tox	NOUN
admet-2772	515	25	filtering	filtering	NOUN
admet-2772	515	26	rules	rule	NOUN
admet-2772	515	27	.	.	PUNCT
admet-2772	516	1	these	these	DET
admet-2772	516	2	resources	resource	NOUN
admet-2772	516	3	collectively	collectively	ADV
admet-2772	516	4	aim	aim	VERB
admet-2772	516	5	to	to	PART
admet-2772	516	6	improve	improve	VERB
admet-2772	516	7	drug	drug	NOUN
admet-2772	516	8	development	development	NOUN
admet-2772	516	9	processes	process	NOUN
admet-2772	516	10	by	by	ADP
admet-2772	516	11	enhancing	enhance	VERB
admet-2772	516	12	access	access	NOUN
admet-2772	516	13	to	to	ADP
admet-2772	516	14	and	and	CCONJ
admet-2772	516	15	utilization	utilization	NOUN
admet-2772	516	16	of	of	ADP
admet-2772	516	17	adme	adme	NOUN
admet-2772	516	18	-	-	PUNCT
admet-2772	516	19	tox	tox	NOUN
admet-2772	516	20	data	datum	NOUN
admet-2772	516	21	.	.	PUNCT
admet-2772	517	1	8.2	8.2	NUM
admet-2772	517	2	.	.	PUNCT
admet-2772	517	3	data	datum	NOUN
admet-2772	517	4	quality	quality	NOUN
admet-2772	517	5	and	and	CCONJ
admet-2772	517	6	availability	availability	NOUN
admet-2772	517	7	issues	issue	NOUN
admet-2772	517	8	data	datum	NOUN
admet-2772	517	9	quality	quality	NOUN
admet-2772	517	10	issues	issue	NOUN
admet-2772	517	11	have	have	AUX
admet-2772	517	12	become	become	VERB
admet-2772	517	13	increasingly	increasingly	ADV
admet-2772	517	14	critical	critical	ADJ
admet-2772	517	15	in	in	ADP
admet-2772	517	16	the	the	DET
admet-2772	517	17	era	era	NOUN
admet-2772	517	18	of	of	ADP
admet-2772	517	19	big	big	ADJ
admet-2772	517	20	data	datum	NOUN
admet-2772	517	21	,	,	PUNCT
admet-2772	517	22	affecting	affect	VERB
admet-2772	517	23	various	various	ADJ
admet-2772	517	24	domains	domain	NOUN
admet-2772	517	25	and	and	CCONJ
admet-2772	517	26	applications	application	NOUN
admet-2772	517	27	[	[	X
admet-2772	517	28	197	197	NUM
admet-2772	517	29	]	]	PUNCT
admet-2772	517	30	.	.	PUNCT
admet-2772	518	1	these	these	DET
admet-2772	518	2	issues	issue	NOUN
admet-2772	518	3	encompass	encompass	VERB
admet-2772	518	4	multiple	multiple	ADJ
admet-2772	518	5	dimensions	dimension	NOUN
admet-2772	518	6	,	,	PUNCT
admet-2772	518	7	including	include	VERB
admet-2772	518	8	accuracy	accuracy	NOUN
admet-2772	518	9	,	,	PUNCT
admet-2772	518	10	completeness	completeness	NOUN
admet-2772	518	11	,	,	PUNCT
admet-2772	518	12	consistency	consistency	NOUN
admet-2772	518	13	,	,	PUNCT
admet-2772	518	14	and	and	CCONJ
admet-2772	518	15	currency	currency	NOUN
admet-2772	519	1	[	[	X
admet-2772	519	2	198	198	NUM
admet-2772	519	3	]	]	PUNCT
admet-2772	519	4	.	.	PUNCT
admet-2772	520	1	poor	poor	ADJ
admet-2772	520	2	data	datum	NOUN
admet-2772	520	3	quality	quality	NOUN
admet-2772	520	4	can	can	AUX
admet-2772	520	5	significantly	significantly	ADV
admet-2772	520	6	impact	impact	VERB
admet-2772	520	7	organizational	organizational	ADJ
admet-2772	520	8	efficiency	efficiency	NOUN
admet-2772	520	9	and	and	CCONJ
admet-2772	520	10	decision	decision	NOUN
admet-2772	520	11	-	-	PUNCT
admet-2772	520	12	making	making	NOUN
admet-2772	520	13	,	,	PUNCT
admet-2772	520	14	leading	lead	VERB
admet-2772	520	15	to	to	ADP
admet-2772	520	16	financial	financial	ADJ
admet-2772	520	17	losses	loss	NOUN
admet-2772	520	18	and	and	CCONJ
admet-2772	520	19	credibility	credibility	NOUN
admet-2772	520	20	issues	issue	NOUN
admet-2772	520	21	[	[	X
admet-2772	520	22	198	198	NUM
admet-2772	520	23	]	]	PUNCT
admet-2772	520	24	.	.	PUNCT
admet-2772	521	1	data	datum	NOUN
admet-2772	521	2	cleaning	cleaning	NOUN
admet-2772	521	3	,	,	PUNCT
admet-2772	521	4	a	a	DET
admet-2772	521	5	crucial	crucial	ADJ
admet-2772	521	6	process	process	NOUN
admet-2772	521	7	in	in	ADP
admet-2772	521	8	addressing	address	VERB
admet-2772	521	9	these	these	DET
admet-2772	521	10	problems	problem	NOUN
admet-2772	521	11	,	,	PUNCT
admet-2772	521	12	is	be	AUX
admet-2772	521	13	particularly	particularly	ADV
admet-2772	521	14	important	important	ADJ
admet-2772	521	15	when	when	SCONJ
admet-2772	521	16	integrating	integrate	VERB
admet-2772	521	17	heterogeneous	heterogeneous	ADJ
admet-2772	521	18	data	datum	NOUN
admet-2772	521	19	sources	source	NOUN
admet-2772	521	20	and	and	CCONJ
admet-2772	521	21	in	in	ADP
admet-2772	521	22	data	data	NOUN
admet-2772	521	23	warehouse	warehouse	NOUN
admet-2772	521	24	environments	environment	NOUN
admet-2772	521	25	[	[	X
admet-2772	521	26	200	200	NUM
admet-2772	521	27	]	]	PUNCT
admet-2772	521	28	.	.	PUNCT
admet-2772	522	1	researchers	researcher	NOUN
admet-2772	522	2	have	have	AUX
admet-2772	522	3	proposed	propose	VERB
admet-2772	522	4	various	various	ADJ
admet-2772	522	5	methodologies	methodology	NOUN
admet-2772	522	6	and	and	CCONJ
admet-2772	522	7	techniques	technique	NOUN
admet-2772	522	8	to	to	PART
admet-2772	522	9	tackle	tackle	VERB
admet-2772	522	10	data	data	NOUN
admet-2772	522	11	quality	quality	NOUN
admet-2772	522	12	challenges	challenge	NOUN
admet-2772	522	13	,	,	PUNCT
admet-2772	522	14	drawing	draw	VERB
admet-2772	522	15	from	from	ADP
admet-2772	522	16	fields	field	NOUN
admet-2772	522	17	such	such	ADJ
admet-2772	522	18	as	as	ADP
admet-2772	522	19	data	datum	NOUN
admet-2772	522	20	mining	mining	NOUN
admet-2772	522	21	,	,	PUNCT
admet-2772	522	22	probability	probability	NOUN
admet-2772	522	23	theory	theory	NOUN
admet-2772	522	24	,	,	PUNCT
admet-2772	522	25	and	and	CCONJ
admet-2772	522	26	machine	machine	NOUN
admet-2772	522	27	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	522	28	m.	m.	NOUN
admet-2772	522	29	venkataraman	venkataraman	PROPN
admet-2772	522	30	et	et	PROPN
admet-2772	522	31	al	al	PROPN
admet-2772	522	32	.	.	PROPN
admet-2772	522	33	admet	admet	PROPN
admet-2772	522	34	&	&	CCONJ
admet-2772	522	35	dmpk	dmpk	PROPN
admet-2772	522	36	13(3	13(3	NUM
admet-2772	522	37	)	)	PUNCT
admet-2772	522	38	(	(	PUNCT
admet-2772	522	39	2025	2025	NUM
admet-2772	522	40	)	)	PUNCT
admet-2772	522	41	2772	2772	NUM
admet-2772	522	42	20	20	NUM
admet-2772	522	43	learning	learn	VERB
admet-2772	522	44	[	[	X
admet-2772	522	45	201	201	NUM
admet-2772	522	46	]	]	PUNCT
admet-2772	522	47	.	.	PUNCT
admet-2772	523	1	these	these	DET
admet-2772	523	2	approaches	approach	NOUN
admet-2772	523	3	often	often	ADV
admet-2772	523	4	involve	involve	VERB
admet-2772	523	5	the	the	DET
admet-2772	523	6	use	use	NOUN
admet-2772	523	7	of	of	ADP
admet-2772	523	8	data	datum	NOUN
admet-2772	523	9	quality	quality	NOUN
admet-2772	523	10	rules	rule	NOUN
admet-2772	523	11	and	and	CCONJ
admet-2772	523	12	algorithms	algorithm	NOUN
admet-2772	523	13	for	for	ADP
admet-2772	523	14	detecting	detect	VERB
admet-2772	523	15	and	and	CCONJ
admet-2772	523	16	correcting	correct	VERB
admet-2772	523	17	errors	error	NOUN
admet-2772	523	18	,	,	PUNCT
admet-2772	523	19	as	as	ADV
admet-2772	523	20	well	well	ADV
admet-2772	523	21	as	as	ADP
admet-2772	523	22	managing	manage	VERB
admet-2772	523	23	issues	issue	NOUN
admet-2772	523	24	like	like	ADP
admet-2772	523	25	data	datum	NOUN
admet-2772	523	26	deduplication	deduplication	NOUN
admet-2772	523	27	and	and	CCONJ
admet-2772	523	28	information	information	NOUN
admet-2772	523	29	completeness	completeness	NOUN
admet-2772	523	30	[	[	X
admet-2772	523	31	198	198	NUM
admet-2772	523	32	]	]	PUNCT
admet-2772	523	33	.	.	PUNCT
admet-2772	524	1	8.3	8.3	NUM
admet-2772	524	2	.	.	PUNCT
admet-2772	524	3	integration	integration	NOUN
admet-2772	524	4	of	of	ADP
admet-2772	524	5	multi	multi	ADJ
admet-2772	524	6	-	-	ADJ
admet-2772	524	7	omics	omics	ADJ
admet-2772	524	8	data	data	PROPN
admet-2772	524	9	multi	multi	ADJ
admet-2772	524	10	-	-	ADJ
admet-2772	524	11	omics	omics	ADJ
admet-2772	524	12	data	data	NOUN
admet-2772	524	13	integration	integration	NOUN
admet-2772	524	14	is	be	AUX
admet-2772	524	15	crucial	crucial	ADJ
admet-2772	524	16	for	for	ADP
admet-2772	524	17	understanding	understand	VERB
admet-2772	524	18	complex	complex	ADJ
admet-2772	524	19	biological	biological	ADJ
admet-2772	524	20	systems	system	NOUN
admet-2772	524	21	and	and	CCONJ
admet-2772	524	22	improving	improve	VERB
admet-2772	524	23	clinical	clinical	ADJ
admet-2772	524	24	outcomes	outcome	NOUN
admet-2772	524	25	.	.	PUNCT
admet-2772	525	1	various	various	ADJ
admet-2772	525	2	strategies	strategy	NOUN
admet-2772	525	3	have	have	AUX
admet-2772	525	4	been	be	AUX
admet-2772	525	5	developed	develop	VERB
admet-2772	525	6	,	,	PUNCT
admet-2772	525	7	including	include	VERB
admet-2772	525	8	early	early	ADJ
admet-2772	525	9	,	,	PUNCT
admet-2772	525	10	mixed	mixed	ADJ
admet-2772	525	11	,	,	PUNCT
admet-2772	525	12	intermediate	intermediate	ADJ
admet-2772	525	13	,	,	PUNCT
admet-2772	525	14	late	late	ADJ
admet-2772	525	15	,	,	PUNCT
admet-2772	525	16	and	and	CCONJ
admet-2772	525	17	hierarchical	hierarchical	ADJ
admet-2772	525	18	integration	integration	NOUN
admet-2772	525	19	approaches	approach	VERB
admet-2772	525	20	[	[	X
admet-2772	525	21	202	202	NUM
admet-2772	525	22	]	]	PUNCT
admet-2772	525	23	.	.	PUNCT
admet-2772	526	1	machine	machine	NOUN
admet-2772	526	2	learning	learn	VERB
admet-2772	526	3	algorithms	algorithm	NOUN
admet-2772	526	4	have	have	AUX
admet-2772	526	5	been	be	AUX
admet-2772	526	6	applied	apply	VERB
admet-2772	526	7	to	to	ADP
admet-2772	526	8	multi	multi	ADJ
admet-2772	526	9	-	-	ADJ
admet-2772	526	10	omics	omics	ADJ
admet-2772	526	11	data	datum	NOUN
admet-2772	526	12	to	to	PART
admet-2772	526	13	produce	produce	VERB
admet-2772	526	14	diagnostic	diagnostic	ADJ
admet-2772	526	15	and	and	CCONJ
admet-2772	526	16	classification	classification	NOUN
admet-2772	526	17	biomarkers	biomarker	NOUN
admet-2772	526	18	[	[	X
admet-2772	526	19	203	203	NUM
admet-2772	526	20	]	]	PUNCT
admet-2772	526	21	.	.	PUNCT
admet-2772	527	1	tools	tool	NOUN
admet-2772	527	2	like	like	SCONJ
admet-2772	527	3	omicsnet	omicsnet	NOUN
admet-2772	527	4	use	use	NOUN
admet-2772	527	5	multilayer	multilayer	ADJ
admet-2772	527	6	networks	network	NOUN
admet-2772	527	7	to	to	PART
admet-2772	527	8	integrate	integrate	VERB
admet-2772	527	9	heterogeneous	heterogeneous	ADJ
admet-2772	527	10	omics	omic	NOUN
admet-2772	527	11	data	datum	NOUN
admet-2772	527	12	,	,	PUNCT
admet-2772	527	13	facilitating	facilitate	VERB
admet-2772	527	14	functional	functional	ADJ
admet-2772	527	15	analysis	analysis	NOUN
admet-2772	527	16	,	,	PUNCT
admet-2772	527	17	biomarker	biomarker	NOUN
admet-2772	527	18	discovery	discovery	NOUN
admet-2772	527	19	,	,	PUNCT
admet-2772	527	20	and	and	CCONJ
admet-2772	527	21	drug	drug	NOUN
admet-2772	527	22	response	response	NOUN
admet-2772	527	23	prediction	prediction	NOUN
admet-2772	527	24	[	[	X
admet-2772	527	25	204	204	NUM
admet-2772	527	26	]	]	PUNCT
admet-2772	527	27	.	.	PUNCT
admet-2772	528	1	the	the	DET
admet-2772	528	2	integration	integration	NOUN
admet-2772	528	3	of	of	ADP
admet-2772	528	4	multi	multi	ADJ
admet-2772	528	5	-	-	ADJ
admet-2772	528	6	omics	omics	ADJ
admet-2772	528	7	data	datum	NOUN
admet-2772	528	8	has	have	VERB
admet-2772	528	9	applications	application	NOUN
admet-2772	528	10	in	in	ADP
admet-2772	528	11	disease	disease	NOUN
admet-2772	528	12	subtyping	subtyping	NOUN
admet-2772	528	13	,	,	PUNCT
admet-2772	528	14	biomarker	biomarker	NOUN
admet-2772	528	15	prediction	prediction	NOUN
admet-2772	528	16	,	,	PUNCT
admet-2772	528	17	and	and	CCONJ
admet-2772	528	18	deriving	derive	VERB
admet-2772	528	19	biological	biological	ADJ
admet-2772	528	20	insights	insight	NOUN
admet-2772	528	21	[	[	X
admet-2772	528	22	205	205	NUM
admet-2772	528	23	]	]	PUNCT
admet-2772	528	24	.	.	PUNCT
admet-2772	529	1	despite	despite	SCONJ
admet-2772	529	2	progress	progress	NOUN
admet-2772	529	3	in	in	ADP
admet-2772	529	4	the	the	DET
admet-2772	529	5	field	field	NOUN
admet-2772	529	6	,	,	PUNCT
admet-2772	529	7	challenges	challenge	NOUN
admet-2772	529	8	remain	remain	VERB
admet-2772	529	9	in	in	ADP
admet-2772	529	10	developing	develop	VERB
admet-2772	529	11	computational	computational	ADJ
admet-2772	529	12	methods	method	NOUN
admet-2772	529	13	for	for	ADP
admet-2772	529	14	the	the	DET
admet-2772	529	15	proper	proper	ADJ
admet-2772	529	16	integration	integration	NOUN
admet-2772	529	17	of	of	ADP
admet-2772	529	18	multi	multi	ADJ
admet-2772	529	19	-	-	ADJ
admet-2772	529	20	omics	omics	ADJ
admet-2772	529	21	datasets	dataset	NOUN
admet-2772	529	22	[	[	X
admet-2772	529	23	204	204	NUM
admet-2772	529	24	]	]	PUNCT
admet-2772	529	25	.	.	PUNCT
admet-2772	530	1	researchers	researcher	NOUN
admet-2772	530	2	have	have	AUX
admet-2772	530	3	developed	develop	VERB
admet-2772	530	4	numerous	numerous	ADJ
admet-2772	530	5	software	software	NOUN
admet-2772	530	6	tools	tool	NOUN
admet-2772	530	7	and	and	CCONJ
admet-2772	530	8	methods	method	NOUN
admet-2772	530	9	to	to	PART
admet-2772	530	10	address	address	VERB
admet-2772	530	11	these	these	DET
admet-2772	530	12	challenges	challenge	NOUN
admet-2772	530	13	and	and	CCONJ
admet-2772	530	14	improve	improve	VERB
admet-2772	530	15	clinical	clinical	ADJ
admet-2772	530	16	outcome	outcome	NOUN
admet-2772	530	17	predictions	prediction	NOUN
admet-2772	530	18	[	[	X
admet-2772	530	19	205	205	NUM
admet-2772	530	20	]	]	PUNCT
admet-2772	530	21	.	.	PUNCT
admet-2772	531	1	8.4	8.4	NUM
admet-2772	531	2	.	.	X
admet-2772	532	1	privacy	privacy	NOUN
admet-2772	532	2	and	and	CCONJ
admet-2772	532	3	ethical	ethical	ADJ
admet-2772	532	4	concerns	concern	NOUN
admet-2772	532	5	privacy	privacy	NOUN
admet-2772	532	6	and	and	CCONJ
admet-2772	532	7	ethical	ethical	ADJ
admet-2772	532	8	concerns	concern	NOUN
admet-2772	532	9	in	in	ADP
admet-2772	532	10	research	research	NOUN
admet-2772	532	11	and	and	CCONJ
admet-2772	532	12	technology	technology	NOUN
admet-2772	532	13	adoption	adoption	NOUN
admet-2772	532	14	have	have	AUX
admet-2772	532	15	gained	gain	VERB
admet-2772	532	16	significant	significant	ADJ
admet-2772	532	17	attention	attention	NOUN
admet-2772	532	18	.	.	PUNCT
admet-2772	533	1	key	key	ADJ
admet-2772	533	2	issues	issue	NOUN
admet-2772	533	3	include	include	VERB
admet-2772	533	4	ensuring	ensure	VERB
admet-2772	533	5	meaningful	meaningful	ADJ
admet-2772	533	6	user	user	NOUN
admet-2772	533	7	notice	notice	NOUN
admet-2772	533	8	,	,	PUNCT
admet-2772	533	9	access	access	NOUN
admet-2772	533	10	control	control	NOUN
admet-2772	533	11	,	,	PUNCT
admet-2772	533	12	data	data	NOUN
admet-2772	533	13	anonymization	anonymization	NOUN
admet-2772	533	14	,	,	PUNCT
admet-2772	533	15	and	and	CCONJ
admet-2772	533	16	algorithm	algorithm	NOUN
admet-2772	533	17	validation	validation	NOUN
admet-2772	533	18	to	to	PART
admet-2772	533	19	prevent	prevent	VERB
admet-2772	533	20	harm	harm	NOUN
admet-2772	533	21	[	[	X
admet-2772	533	22	206	206	NUM
admet-2772	533	23	]	]	PUNCT
admet-2772	533	24	.	.	PUNCT
admet-2772	534	1	the	the	DET
admet-2772	534	2	increasing	increase	VERB
admet-2772	534	3	use	use	NOUN
admet-2772	534	4	of	of	ADP
admet-2772	534	5	technology	technology	NOUN
admet-2772	534	6	in	in	ADP
admet-2772	534	7	learning	learn	VERB
admet-2772	534	8	processes	process	NOUN
admet-2772	534	9	raises	raise	VERB
admet-2772	534	10	concerns	concern	NOUN
admet-2772	534	11	about	about	ADP
admet-2772	534	12	learner	learner	NOUN
admet-2772	534	13	tracking	tracking	NOUN
admet-2772	534	14	,	,	PUNCT
admet-2772	534	15	necessitating	necessitate	VERB
admet-2772	534	16	principles	principle	NOUN
admet-2772	534	17	for	for	ADP
admet-2772	534	18	trust	trust	NOUN
admet-2772	534	19	,	,	PUNCT
admet-2772	534	20	accountability	accountability	NOUN
admet-2772	534	21	,	,	PUNCT
admet-2772	534	22	and	and	CCONJ
admet-2772	534	23	transparency	transparency	NOUN
admet-2772	534	24	in	in	ADP
admet-2772	534	25	learning	learn	VERB
admet-2772	534	26	analytics	analytic	NOUN
admet-2772	534	27	[	[	X
admet-2772	534	28	207	207	NUM
admet-2772	534	29	]	]	PUNCT
admet-2772	534	30	.	.	PUNCT
admet-2772	535	1	rfid	rfid	ADJ
admet-2772	535	2	technology	technology	NOUN
admet-2772	535	3	,	,	PUNCT
admet-2772	535	4	while	while	SCONJ
admet-2772	535	5	promising	promise	VERB
admet-2772	535	6	for	for	ADP
admet-2772	535	7	data	data	NOUN
admet-2772	535	8	collection	collection	NOUN
admet-2772	535	9	,	,	PUNCT
admet-2772	535	10	presents	present	VERB
admet-2772	535	11	challenges	challenge	NOUN
admet-2772	535	12	for	for	ADP
admet-2772	535	13	privacy	privacy	NOUN
admet-2772	535	14	due	due	ADP
admet-2772	535	15	to	to	ADP
admet-2772	535	16	its	its	PRON
admet-2772	535	17	ability	ability	NOUN
admet-2772	535	18	to	to	PART
admet-2772	535	19	track	track	VERB
admet-2772	535	20	individual	individual	ADJ
admet-2772	535	21	products	product	NOUN
admet-2772	535	22	[	[	X
admet-2772	535	23	208	208	NUM
admet-2772	535	24	]	]	PUNCT
admet-2772	535	25	.	.	PUNCT
admet-2772	536	1	researchers	researcher	NOUN
admet-2772	536	2	are	be	AUX
admet-2772	536	3	exploring	explore	VERB
admet-2772	536	4	situations	situation	NOUN
admet-2772	536	5	where	where	SCONJ
admet-2772	536	6	privacy	privacy	NOUN
admet-2772	536	7	may	may	AUX
admet-2772	536	8	not	not	PART
admet-2772	536	9	always	always	ADV
admet-2772	536	10	be	be	AUX
admet-2772	536	11	optimal	optimal	ADJ
admet-2772	536	12	,	,	PUNCT
admet-2772	536	13	considering	consider	VERB
admet-2772	536	14	the	the	DET
admet-2772	536	15	balance	balance	NOUN
admet-2772	536	16	between	between	ADP
admet-2772	536	17	privacy	privacy	NOUN
admet-2772	536	18	and	and	CCONJ
admet-2772	536	19	other	other	ADJ
admet-2772	536	20	competing	compete	VERB
admet-2772	536	21	values	value	NOUN
admet-2772	536	22	in	in	ADP
admet-2772	536	23	research	research	NOUN
admet-2772	536	24	and	and	CCONJ
admet-2772	536	25	design	design	NOUN
admet-2772	536	26	[	[	X
admet-2772	536	27	209	209	NUM
admet-2772	536	28	]	]	PUNCT
admet-2772	536	29	.	.	PUNCT
admet-2772	537	1	these	these	DET
admet-2772	537	2	studies	study	NOUN
admet-2772	537	3	emphasize	emphasize	VERB
admet-2772	537	4	the	the	DET
admet-2772	537	5	importance	importance	NOUN
admet-2772	537	6	of	of	ADP
admet-2772	537	7	addressing	address	VERB
admet-2772	537	8	ethical	ethical	ADJ
admet-2772	537	9	and	and	CCONJ
admet-2772	537	10	privacy	privacy	NOUN
admet-2772	537	11	concerns	concern	NOUN
admet-2772	537	12	in	in	ADP
admet-2772	537	13	various	various	ADJ
admet-2772	537	14	contexts	contexts	NOUN
admet-2772	537	15	,	,	PUNCT
admet-2772	537	16	from	from	ADP
admet-2772	537	17	social	social	ADJ
admet-2772	537	18	-	-	PUNCT
admet-2772	537	19	behavioural	behavioural	ADJ
admet-2772	537	20	research	research	NOUN
admet-2772	537	21	to	to	ADP
admet-2772	537	22	technological	technological	ADJ
admet-2772	537	23	implementations	implementation	NOUN
admet-2772	537	24	,	,	PUNCT
admet-2772	537	25	to	to	PART
admet-2772	537	26	ensure	ensure	VERB
admet-2772	537	27	responsible	responsible	ADJ
admet-2772	537	28	data	datum	NOUN
admet-2772	537	29	use	use	NOUN
admet-2772	537	30	and	and	CCONJ
admet-2772	537	31	protect	protect	VERB
admet-2772	537	32	individuals	individual	NOUN
admet-2772	537	33	'	'	PART
admet-2772	537	34	rights	right	NOUN
admet-2772	537	35	.	.	PUNCT
admet-2772	538	1	9	9	X
admet-2772	538	2	.	.	X
admet-2772	538	3	case	case	NOUN
admet-2772	538	4	studies	study	NOUN
admet-2772	538	5	of	of	ADP
admet-2772	538	6	machine	machine	NOUN
admet-2772	538	7	learning	learn	VERB
admet-2772	538	8	in	in	ADP
admet-2772	538	9	adme	adme	NOUN
admet-2772	538	10	-	-	PUNCT
admet-2772	538	11	tox	tox	NOUN
admet-2772	538	12	prediction	prediction	NOUN
admet-2772	538	13	9.1	9.1	NUM
admet-2772	538	14	.	.	PUNCT
admet-2772	539	1	successful	successful	ADJ
admet-2772	539	2	machine	machine	NOUN
admet-2772	539	3	learning	learn	VERB
admet-2772	539	4	applications	application	NOUN
admet-2772	539	5	in	in	ADP
admet-2772	539	6	drug	drug	NOUN
admet-2772	539	7	development	development	NOUN
admet-2772	539	8	machine	machine	NOUN
admet-2772	539	9	learning	learn	VERB
admet-2772	539	10	techniques	technique	NOUN
admet-2772	539	11	are	be	AUX
admet-2772	539	12	increasingly	increasingly	ADV
admet-2772	539	13	applied	apply	VERB
admet-2772	539	14	across	across	ADP
admet-2772	539	15	various	various	ADJ
admet-2772	539	16	stages	stage	NOUN
admet-2772	539	17	of	of	ADP
admet-2772	539	18	drug	drug	NOUN
admet-2772	539	19	discovery	discovery	NOUN
admet-2772	539	20	and	and	CCONJ
admet-2772	539	21	development	development	NOUN
admet-2772	539	22	to	to	PART
admet-2772	539	23	accelerate	accelerate	VERB
admet-2772	539	24	the	the	DET
admet-2772	539	25	process	process	NOUN
admet-2772	539	26	and	and	CCONJ
admet-2772	539	27	reduce	reduce	VERB
admet-2772	539	28	failure	failure	NOUN
admet-2772	539	29	rates	rate	NOUN
admet-2772	539	30	[	[	X
admet-2772	539	31	3	3	NUM
admet-2772	539	32	]	]	PUNCT
admet-2772	539	33	.	.	PUNCT
admet-2772	540	1	ml	ml	PROPN
admet-2772	540	2	approaches	approach	NOUN
admet-2772	540	3	have	have	AUX
admet-2772	540	4	shown	show	VERB
admet-2772	540	5	promise	promise	NOUN
admet-2772	540	6	in	in	ADP
admet-2772	540	7	target	target	NOUN
admet-2772	540	8	validation	validation	NOUN
admet-2772	540	9	,	,	PUNCT
admet-2772	540	10	biomarker	biomarker	NOUN
admet-2772	540	11	identification	identification	NOUN
admet-2772	540	12	,	,	PUNCT
admet-2772	540	13	and	and	CCONJ
admet-2772	540	14	digital	digital	ADJ
admet-2772	540	15	pathology	pathology	NOUN
admet-2772	540	16	analysis	analysis	NOUN
admet-2772	540	17	[	[	X
admet-2772	540	18	3	3	NUM
admet-2772	540	19	]	]	PUNCT
admet-2772	540	20	.	.	PUNCT
admet-2772	541	1	specific	specific	ADJ
admet-2772	541	2	applications	application	NOUN
admet-2772	541	3	include	include	VERB
admet-2772	541	4	snp	snp	ADJ
admet-2772	541	5	discoveries	discovery	NOUN
admet-2772	541	6	,	,	PUNCT
admet-2772	541	7	drug	drug	NOUN
admet-2772	541	8	repurposing	repurposing	NOUN
admet-2772	541	9	,	,	PUNCT
admet-2772	541	10	virtual	virtual	ADJ
admet-2772	541	11	screening	screening	NOUN
admet-2772	541	12	,	,	PUNCT
admet-2772	541	13	lead	lead	VERB
admet-2772	541	14	identification	identification	NOUN
admet-2772	541	15	,	,	PUNCT
admet-2772	541	16	qsar	qsar	NOUN
admet-2772	541	17	modelling	modelling	NOUN
admet-2772	541	18	,	,	PUNCT
admet-2772	541	19	and	and	CCONJ
admet-2772	541	20	admet	admet	VERB
admet-2772	541	21	analysis	analysis	NOUN
admet-2772	541	22	[	[	X
admet-2772	541	23	210	210	NUM
admet-2772	541	24	]	]	PUNCT
admet-2772	541	25	.	.	PUNCT
admet-2772	542	1	algorithms	algorithm	NOUN
admet-2772	542	2	such	such	ADJ
admet-2772	542	3	as	as	ADP
admet-2772	542	4	support	support	NOUN
admet-2772	542	5	vector	vector	NOUN
admet-2772	542	6	machines	machine	NOUN
admet-2772	542	7	,	,	PUNCT
admet-2772	542	8	random	random	ADJ
admet-2772	542	9	forests	forest	NOUN
admet-2772	542	10	,	,	PUNCT
admet-2772	542	11	and	and	CCONJ
admet-2772	542	12	artificial	artificial	ADJ
admet-2772	542	13	neural	neural	ADJ
admet-2772	542	14	networks	network	NOUN
admet-2772	542	15	have	have	AUX
admet-2772	542	16	demonstrated	demonstrate	VERB
admet-2772	542	17	success	success	NOUN
admet-2772	542	18	in	in	ADP
admet-2772	542	19	predicting	predict	VERB
admet-2772	542	20	human	human	ADJ
admet-2772	542	21	intestinal	intestinal	ADJ
admet-2772	542	22	absorption	absorption	NOUN
admet-2772	542	23	and	and	CCONJ
admet-2772	542	24	identifying	identify	VERB
admet-2772	542	25	novel	novel	ADJ
admet-2772	542	26	compounds	compound	NOUN
admet-2772	542	27	for	for	ADP
admet-2772	542	28	cancer	cancer	NOUN
admet-2772	542	29	treatment	treatment	NOUN
admet-2772	542	30	[	[	X
admet-2772	542	31	210	210	NUM
admet-2772	542	32	]	]	PUNCT
admet-2772	542	33	.	.	PUNCT
admet-2772	543	1	the	the	DET
admet-2772	543	2	janssen	janssen	PROPN
admet-2772	543	3	gtpp	gtpp	PROPN
admet-2772	543	4	model	model	PROPN
admet-2772	543	5	,	,	PUNCT
admet-2772	543	6	employing	employ	VERB
admet-2772	543	7	graph	graph	NOUN
admet-2772	543	8	convolutional	convolutional	ADJ
admet-2772	543	9	neural	neural	ADJ
admet-2772	543	10	networks	network	NOUN
admet-2772	543	11	,	,	PUNCT
admet-2772	543	12	has	have	AUX
admet-2772	543	13	shown	show	VERB
admet-2772	543	14	superior	superior	ADJ
admet-2772	543	15	performance	performance	NOUN
admet-2772	543	16	in	in	ADP
admet-2772	543	17	predicting	predict	VERB
admet-2772	543	18	early	early	ADJ
admet-2772	543	19	adme	adme	NOUN
admet-2772	543	20	properties	property	NOUN
admet-2772	543	21	compared	compare	VERB
admet-2772	543	22	to	to	ADP
admet-2772	543	23	commercial	commercial	ADJ
admet-2772	543	24	models	model	NOUN
admet-2772	543	25	[	[	X
admet-2772	543	26	62	62	NUM
admet-2772	543	27	]	]	PUNCT
admet-2772	543	28	.	.	PUNCT
admet-2772	544	1	however	however	ADV
admet-2772	544	2	,	,	PUNCT
admet-2772	544	3	challenges	challenge	NOUN
admet-2772	544	4	remain	remain	VERB
admet-2772	544	5	in	in	ADP
admet-2772	544	6	the	the	DET
admet-2772	544	7	interpretability	interpretability	NOUN
admet-2772	544	8	and	and	CCONJ
admet-2772	544	9	repeatability	repeatability	NOUN
admet-2772	544	10	of	of	ADP
admet-2772	544	11	ml	ml	NOUN
admet-2772	544	12	-	-	PUNCT
admet-2772	544	13	generated	generate	VERB
admet-2772	544	14	results	result	NOUN
admet-2772	544	15	,	,	PUNCT
admet-2772	544	16	necessitating	necessitate	VERB
admet-2772	544	17	systematic	systematic	ADJ
admet-2772	544	18	data	datum	NOUN
admet-2772	544	19	generation	generation	NOUN
admet-2772	544	20	and	and	CCONJ
admet-2772	544	21	validation	validation	NOUN
admet-2772	544	22	of	of	ADP
admet-2772	544	23	ml	ml	NOUN
admet-2772	544	24	approaches	approach	NOUN
admet-2772	544	25	[	[	X
admet-2772	544	26	3,4	3,4	NUM
admet-2772	544	27	]	]	PUNCT
admet-2772	544	28	.	.	PUNCT
admet-2772	545	1	9.2	9.2	NUM
admet-2772	545	2	.	.	PUNCT
admet-2772	546	1	real	real	ADJ
admet-2772	546	2	-	-	PUNCT
admet-2772	546	3	world	world	NOUN
admet-2772	546	4	use	use	NOUN
admet-2772	546	5	cases	case	NOUN
admet-2772	546	6	machine	machine	NOUN
admet-2772	546	7	learning	learn	VERB
admet-2772	546	8	techniques	technique	NOUN
admet-2772	546	9	have	have	AUX
admet-2772	546	10	been	be	AUX
admet-2772	546	11	increasingly	increasingly	ADV
admet-2772	546	12	applied	apply	VERB
admet-2772	546	13	to	to	PART
admet-2772	546	14	predict	predict	VERB
admet-2772	546	15	adme	adme	NOUN
admet-2772	546	16	-	-	PUNCT
admet-2772	546	17	tox	tox	NOUN
admet-2772	546	18	properties	property	NOUN
admet-2772	546	19	of	of	ADP
admet-2772	546	20	drug	drug	NOUN
admet-2772	546	21	candidates	candidate	NOUN
admet-2772	546	22	,	,	PUNCT
admet-2772	546	23	helping	help	VERB
admet-2772	546	24	to	to	PART
admet-2772	546	25	streamline	streamline	VERB
admet-2772	546	26	the	the	DET
admet-2772	546	27	drug	drug	NOUN
admet-2772	546	28	discovery	discovery	NOUN
admet-2772	546	29	process	process	NOUN
admet-2772	546	30	and	and	CCONJ
admet-2772	546	31	reduce	reduce	VERB
admet-2772	546	32	costs	cost	NOUN
admet-2772	546	33	[	[	X
admet-2772	546	34	211	211	NUM
admet-2772	546	35	]	]	PUNCT
admet-2772	546	36	.	.	PUNCT
admet-2772	547	1	these	these	DET
admet-2772	547	2	computational	computational	ADJ
admet-2772	547	3	methods	method	NOUN
admet-2772	547	4	rely	rely	VERB
admet-2772	547	5	heavily	heavily	ADV
admet-2772	547	6	on	on	ADP
admet-2772	547	7	high	high	ADJ
admet-2772	547	8	-	-	PUNCT
admet-2772	547	9	quality	quality	NOUN
admet-2772	547	10	experimental	experimental	ADJ
admet-2772	547	11	data	datum	NOUN
admet-2772	547	12	to	to	PART
admet-2772	547	13	generate	generate	VERB
admet-2772	547	14	accurate	accurate	ADJ
admet-2772	547	15	models	model	NOUN
admet-2772	547	16	.	.	PUNCT
admet-2772	548	1	flexible	flexible	ADJ
admet-2772	548	2	approaches	approach	NOUN
admet-2772	548	3	combining	combine	VERB
admet-2772	548	4	multiple	multiple	ADJ
admet-2772	548	5	technologies	technology	NOUN
admet-2772	548	6	,	,	PUNCT
admet-2772	548	7	such	such	ADJ
admet-2772	548	8	as	as	ADP
admet-2772	548	9	bio	bio	NOUN
admet-2772	548	10	-	-	PROPN
admet-2772	548	11	rad	rad	PROPN
admet-2772	548	12	's	's	PART
admet-2772	548	13	knowitall	knowitall	PROPN
admet-2772	548	14	adme	adme	PROPN
admet-2772	548	15	/	/	SYM
admet-2772	548	16	tox	tox	NOUN
admet-2772	548	17	system	system	NOUN
admet-2772	548	18	with	with	ADP
admet-2772	548	19	support	support	NOUN
admet-2772	548	20	vector	vector	NOUN
admet-2772	548	21	machine	machine	NOUN
admet-2772	548	22	platforms	platform	NOUN
admet-2772	548	23	,	,	PUNCT
admet-2772	548	24	have	have	AUX
admet-2772	548	25	shown	show	VERB
admet-2772	548	26	promise	promise	NOUN
admet-2772	548	27	in	in	ADP
admet-2772	548	28	improving	improve	VERB
admet-2772	548	29	prediction	prediction	NOUN
admet-2772	548	30	performance	performance	NOUN
admet-2772	548	31	and	and	CCONJ
admet-2772	548	32	overcoming	overcome	VERB
admet-2772	548	33	limitations	limitation	NOUN
admet-2772	548	34	of	of	ADP
admet-2772	548	35	individual	individual	ADJ
admet-2772	548	36	methods	method	NOUN
admet-2772	548	37	[	[	X
admet-2772	548	38	212	212	NUM
admet-2772	548	39	]	]	PUNCT
admet-2772	548	40	.	.	PUNCT
admet-2772	549	1	despite	despite	SCONJ
admet-2772	549	2	the	the	DET
admet-2772	549	3	potential	potential	NOUN
admet-2772	549	4	of	of	ADP
admet-2772	549	5	in	in	ADP
admet-2772	549	6	silico	silico	NOUN
admet-2772	549	7	approaches	approach	NOUN
admet-2772	549	8	,	,	PUNCT
admet-2772	549	9	regulatory	regulatory	ADJ
admet-2772	549	10	requirements	requirement	NOUN
admet-2772	549	11	for	for	ADP
admet-2772	549	12	adme	adme	NOUN
admet-2772	549	13	and	and	CCONJ
admet-2772	549	14	admet	admet	PROPN
admet-2772	549	15	&	&	CCONJ
admet-2772	549	16	dmpk	dmpk	PROPN
admet-2772	549	17	13(3	13(3	NUM
admet-2772	549	18	)	)	PUNCT
admet-2772	549	19	(	(	PUNCT
admet-2772	549	20	2025	2025	NUM
admet-2772	549	21	)	)	PUNCT
admet-2772	549	22	2772	2772	NUM
admet-2772	549	23	machine	machine	NOUN
admet-2772	549	24	learning	learning	NOUN
admet-2772	549	25	models	model	NOUN
admet-2772	549	26	for	for	ADP
admet-2772	549	27	admet	admet	ADJ
admet-2772	549	28	prediction	prediction	NOUN
admet-2772	549	29	in	in	ADP
admet-2772	549	30	drug	drug	NOUN
admet-2772	549	31	development	development	NOUN
admet-2772	549	32	doi	doi	PROPN
admet-2772	549	33	:	:	PUNCT
admet-2772	549	34	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	X
admet-2772	549	35	21	21	NUM
admet-2772	549	36	toxicokinetic	toxicokinetic	ADJ
admet-2772	549	37	data	datum	NOUN
admet-2772	549	38	vary	vary	VERB
admet-2772	549	39	widely	widely	ADV
admet-2772	549	40	across	across	ADP
admet-2772	549	41	different	different	ADJ
admet-2772	549	42	chemical	chemical	NOUN
admet-2772	549	43	frameworks	framework	NOUN
admet-2772	549	44	,	,	PUNCT
admet-2772	549	45	with	with	ADP
admet-2772	549	46	some	some	DET
admet-2772	549	47	areas	area	NOUN
admet-2772	549	48	having	have	VERB
admet-2772	549	49	minimal	minimal	ADJ
admet-2772	549	50	or	or	CCONJ
admet-2772	549	51	no	no	DET
admet-2772	549	52	requirements	requirement	NOUN
admet-2772	549	53	[	[	X
admet-2772	549	54	213	213	NUM
admet-2772	549	55	]	]	PUNCT
admet-2772	549	56	.	.	PUNCT
admet-2772	550	1	incorporating	incorporate	VERB
admet-2772	550	2	adme	adme	NOUN
admet-2772	550	3	/	/	SYM
admet-2772	550	4	tk	tk	PROPN
admet-2772	550	5	information	information	NOUN
admet-2772	550	6	early	early	ADV
admet-2772	550	7	in	in	ADP
admet-2772	550	8	toxicity	toxicity	NOUN
admet-2772	550	9	testing	testing	NOUN
admet-2772	550	10	can	can	AUX
admet-2772	550	11	enhance	enhance	VERB
admet-2772	550	12	study	study	NOUN
admet-2772	550	13	design	design	NOUN
admet-2772	550	14	,	,	PUNCT
admet-2772	550	15	support	support	VERB
admet-2772	550	16	4r	4r	NUM
admet-2772	550	17	goals	goal	NOUN
admet-2772	550	18	,	,	PUNCT
admet-2772	550	19	and	and	CCONJ
admet-2772	550	20	ultimately	ultimately	ADV
admet-2772	550	21	improve	improve	VERB
admet-2772	550	22	risk	risk	NOUN
admet-2772	550	23	assessment	assessment	NOUN
admet-2772	550	24	and	and	CCONJ
admet-2772	550	25	characterization	characterization	NOUN
admet-2772	550	26	of	of	ADP
admet-2772	550	27	chemical	chemical	ADJ
admet-2772	550	28	safety	safety	NOUN
admet-2772	550	29	[	[	X
admet-2772	550	30	213	213	NUM
admet-2772	550	31	]	]	SYM
admet-2772	550	32	.	.	PUNCT
admet-2772	551	1	9.3	9.3	NUM
admet-2772	551	2	.	.	PUNCT
admet-2772	551	3	drug	drug	NOUN
admet-2772	551	4	repurposing	repurpose	VERB
admet-2772	551	5	applications	application	NOUN
admet-2772	551	6	drug	drug	NOUN
admet-2772	551	7	repurposing	repurposing	NOUN
admet-2772	551	8	,	,	PUNCT
admet-2772	551	9	the	the	DET
admet-2772	551	10	process	process	NOUN
admet-2772	551	11	of	of	ADP
admet-2772	551	12	using	use	VERB
admet-2772	551	13	existing	exist	VERB
admet-2772	551	14	drugs	drug	NOUN
admet-2772	551	15	for	for	ADP
admet-2772	551	16	new	new	ADJ
admet-2772	551	17	indications	indication	NOUN
admet-2772	551	18	,	,	PUNCT
admet-2772	551	19	has	have	AUX
admet-2772	551	20	gained	gain	VERB
admet-2772	551	21	attention	attention	NOUN
admet-2772	551	22	due	due	ADP
admet-2772	551	23	to	to	ADP
admet-2772	551	24	its	its	PRON
admet-2772	551	25	potential	potential	NOUN
admet-2772	551	26	to	to	PART
admet-2772	551	27	reduce	reduce	VERB
admet-2772	551	28	costs	cost	NOUN
admet-2772	551	29	and	and	CCONJ
admet-2772	551	30	development	development	NOUN
admet-2772	551	31	time	time	NOUN
admet-2772	551	32	[	[	X
admet-2772	551	33	214	214	NUM
admet-2772	551	34	]	]	PUNCT
admet-2772	551	35	.	.	PUNCT
admet-2772	552	1	this	this	DET
admet-2772	552	2	approach	approach	NOUN
admet-2772	552	3	leverages	leverage	VERB
admet-2772	552	4	existing	exist	VERB
admet-2772	552	5	admet	admet	NOUN
admet-2772	552	6	data	datum	NOUN
admet-2772	552	7	to	to	PART
admet-2772	552	8	expedite	expedite	VERB
admet-2772	552	9	drug	drug	NOUN
admet-2772	552	10	development	development	NOUN
admet-2772	552	11	[	[	X
admet-2772	552	12	215	215	NUM
admet-2772	552	13	]	]	PUNCT
admet-2772	552	14	.	.	PUNCT
admet-2772	553	1	chemical	chemical	ADJ
admet-2772	553	2	structure	structure	NOUN
admet-2772	553	3	modifications	modification	NOUN
admet-2772	553	4	and	and	CCONJ
admet-2772	553	5	nanotechnology	nanotechnology	NOUN
admet-2772	553	6	applications	application	NOUN
admet-2772	553	7	can	can	AUX
admet-2772	553	8	improve	improve	VERB
admet-2772	553	9	adme	adme	NOUN
admet-2772	553	10	-	-	PUNCT
admet-2772	553	11	tox	tox	NOUN
admet-2772	553	12	properties	property	NOUN
admet-2772	553	13	of	of	ADP
admet-2772	553	14	drug	drug	NOUN
admet-2772	553	15	candidates	candidate	NOUN
admet-2772	553	16	,	,	PUNCT
admet-2772	553	17	enhancing	enhance	VERB
admet-2772	553	18	absorption	absorption	NOUN
admet-2772	553	19	,	,	PUNCT
admet-2772	553	20	permeability	permeability	NOUN
admet-2772	553	21	,	,	PUNCT
admet-2772	553	22	distribution	distribution	NOUN
admet-2772	553	23	,	,	PUNCT
admet-2772	553	24	and	and	CCONJ
admet-2772	553	25	stability	stability	NOUN
admet-2772	553	26	while	while	SCONJ
admet-2772	553	27	reducing	reduce	VERB
admet-2772	553	28	toxicity	toxicity	NOUN
admet-2772	553	29	[	[	X
admet-2772	553	30	216	216	NUM
admet-2772	553	31	]	]	PUNCT
admet-2772	553	32	.	.	PUNCT
admet-2772	554	1	abc	abc	PROPN
admet-2772	554	2	transporters	transporter	NOUN
admet-2772	554	3	play	play	VERB
admet-2772	554	4	a	a	DET
admet-2772	554	5	crucial	crucial	ADJ
admet-2772	554	6	role	role	NOUN
admet-2772	554	7	in	in	ADP
admet-2772	554	8	admet	admet	NOUN
admet-2772	554	9	,	,	PUNCT
admet-2772	554	10	influencing	influence	VERB
admet-2772	554	11	drug	drug	NOUN
admet-2772	554	12	resistance	resistance	NOUN
admet-2772	554	13	and	and	CCONJ
admet-2772	554	14	passage	passage	NOUN
admet-2772	554	15	through	through	ADP
admet-2772	554	16	cellular	cellular	ADJ
admet-2772	554	17	barriers	barrier	NOUN
admet-2772	554	18	[	[	X
admet-2772	554	19	217	217	NUM
admet-2772	554	20	]	]	PUNCT
admet-2772	554	21	.	.	PUNCT
admet-2772	555	1	various	various	ADJ
admet-2772	555	2	models	model	NOUN
admet-2772	555	3	and	and	CCONJ
admet-2772	555	4	assay	assay	NOUN
admet-2772	555	5	systems	system	NOUN
admet-2772	555	6	,	,	PUNCT
admet-2772	555	7	including	include	VERB
admet-2772	555	8	in	in	ADP
admet-2772	555	9	vitro	vitro	X
admet-2772	555	10	,	,	PUNCT
admet-2772	555	11	in	in	ADP
admet-2772	555	12	vivo	vivo	NOUN
admet-2772	555	13	,	,	PUNCT
admet-2772	555	14	and	and	CCONJ
admet-2772	555	15	in	in	ADP
admet-2772	555	16	silico	silico	NOUN
admet-2772	555	17	approaches	approach	NOUN
admet-2772	555	18	,	,	PUNCT
admet-2772	555	19	can	can	AUX
admet-2772	555	20	be	be	AUX
admet-2772	555	21	used	use	VERB
admet-2772	555	22	to	to	PART
admet-2772	555	23	analyze	analyze	VERB
admet-2772	555	24	drug	drug	NOUN
admet-2772	555	25	interactions	interaction	NOUN
admet-2772	555	26	with	with	ADP
admet-2772	555	27	abc	abc	PROPN
admet-2772	555	28	transporters	transporter	NOUN
admet-2772	555	29	and	and	CCONJ
admet-2772	555	30	predict	predict	VERB
admet-2772	555	31	admet	admet	PROPN
admet-2772	555	32	profiles	profile	NOUN
admet-2772	555	33	[	[	X
admet-2772	555	34	217	217	NUM
admet-2772	555	35	]	]	PUNCT
admet-2772	555	36	.	.	PUNCT
admet-2772	556	1	these	these	DET
admet-2772	556	2	strategies	strategy	NOUN
admet-2772	556	3	collectively	collectively	ADV
admet-2772	556	4	contribute	contribute	VERB
admet-2772	556	5	to	to	ADP
admet-2772	556	6	more	more	ADV
admet-2772	556	7	efficient	efficient	ADJ
admet-2772	556	8	drug	drug	NOUN
admet-2772	556	9	discovery	discovery	NOUN
admet-2772	556	10	and	and	CCONJ
admet-2772	556	11	development	development	NOUN
admet-2772	556	12	processes	process	NOUN
admet-2772	556	13	,	,	PUNCT
admet-2772	556	14	potentially	potentially	ADV
admet-2772	556	15	leading	lead	VERB
admet-2772	556	16	to	to	ADP
admet-2772	556	17	improved	improve	VERB
admet-2772	556	18	therapeutic	therapeutic	ADJ
admet-2772	556	19	outcomes	outcome	NOUN
admet-2772	556	20	.	.	PUNCT
admet-2772	557	1	10	10	NUM
admet-2772	557	2	.	.	PUNCT
admet-2772	557	3	challenges	challenge	NOUN
admet-2772	557	4	and	and	CCONJ
admet-2772	557	5	limitations	limitation	NOUN
admet-2772	557	6	in	in	ADP
admet-2772	557	7	machine	machine	NOUN
admet-2772	557	8	learning	learning	NOUN
admet-2772	557	9	based	base	VERB
admet-2772	557	10	adme	adme	NOUN
admet-2772	557	11	-	-	PUNCT
admet-2772	557	12	tox	tox	NOUN
admet-2772	557	13	prediction	prediction	NOUN
admet-2772	557	14	10.1	10.1	NUM
admet-2772	557	15	.	.	PUNCT
admet-2772	558	1	data	datum	NOUN
admet-2772	558	2	scarcity	scarcity	NOUN
admet-2772	558	3	and	and	CCONJ
admet-2772	558	4	imbalance	imbalance	NOUN
admet-2772	558	5	machine	machine	NOUN
admet-2772	558	6	learning	learning	NOUN
admet-2772	558	7	techniques	technique	NOUN
admet-2772	558	8	have	have	AUX
admet-2772	558	9	been	be	AUX
admet-2772	558	10	increasingly	increasingly	ADV
admet-2772	558	11	applied	apply	VERB
admet-2772	558	12	to	to	ADP
admet-2772	558	13	adme	adme	NOUN
admet-2772	558	14	-	-	PUNCT
admet-2772	558	15	tox	tox	NOUN
admet-2772	558	16	prediction	prediction	NOUN
admet-2772	558	17	,	,	PUNCT
admet-2772	558	18	offering	offer	VERB
admet-2772	558	19	promising	promising	ADJ
admet-2772	558	20	tools	tool	NOUN
admet-2772	558	21	for	for	ADP
admet-2772	558	22	toxicity	toxicity	NOUN
admet-2772	558	23	screening	screening	NOUN
admet-2772	558	24	and	and	CCONJ
admet-2772	558	25	compound	compound	NOUN
admet-2772	558	26	profiling	profiling	NOUN
admet-2772	558	27	[	[	X
admet-2772	558	28	211	211	NUM
admet-2772	558	29	]	]	PUNCT
admet-2772	558	30	.	.	PUNCT
admet-2772	559	1	however	however	ADV
admet-2772	559	2	,	,	PUNCT
admet-2772	559	3	data	datum	NOUN
admet-2772	559	4	scarcity	scarcity	NOUN
admet-2772	559	5	and	and	CCONJ
admet-2772	559	6	class	class	NOUN
admet-2772	559	7	imbalance	imbalance	NOUN
admet-2772	559	8	pose	pose	VERB
admet-2772	559	9	significant	significant	ADJ
admet-2772	559	10	challenges	challenge	NOUN
admet-2772	559	11	in	in	ADP
admet-2772	559	12	developing	develop	VERB
admet-2772	559	13	accurate	accurate	ADJ
admet-2772	559	14	models	model	NOUN
admet-2772	559	15	.	.	PUNCT
admet-2772	560	1	studies	study	NOUN
admet-2772	560	2	have	have	AUX
admet-2772	560	3	shown	show	VERB
admet-2772	560	4	that	that	SCONJ
admet-2772	560	5	class	class	NOUN
admet-2772	560	6	imbalance	imbalance	NOUN
admet-2772	560	7	can	can	AUX
admet-2772	560	8	significantly	significantly	ADV
admet-2772	560	9	impact	impact	VERB
admet-2772	560	10	model	model	NOUN
admet-2772	560	11	performance	performance	NOUN
admet-2772	560	12	,	,	PUNCT
admet-2772	560	13	particularly	particularly	ADV
admet-2772	560	14	affecting	affect	VERB
admet-2772	560	15	recall	recall	NOUN
admet-2772	560	16	and	and	CCONJ
admet-2772	560	17	f1	f1	NOUN
admet-2772	560	18	scores	score	NOUN
admet-2772	560	19	[	[	X
admet-2772	560	20	218	218	NUM
admet-2772	560	21	]	]	PUNCT
admet-2772	560	22	.	.	PUNCT
admet-2772	561	1	to	to	PART
admet-2772	561	2	address	address	VERB
admet-2772	561	3	these	these	DET
admet-2772	561	4	issues	issue	NOUN
admet-2772	561	5	,	,	PUNCT
admet-2772	561	6	various	various	ADJ
admet-2772	561	7	strategies	strategy	NOUN
admet-2772	561	8	have	have	AUX
admet-2772	561	9	been	be	AUX
admet-2772	561	10	explored	explore	VERB
admet-2772	561	11	,	,	PUNCT
admet-2772	561	12	including	include	VERB
admet-2772	561	13	resampling	resample	VERB
admet-2772	561	14	methods	method	NOUN
admet-2772	561	15	and	and	CCONJ
admet-2772	561	16	transfer	transfer	NOUN
admet-2772	561	17	learning	learning	NOUN
admet-2772	561	18	.	.	PUNCT
admet-2772	562	1	resampling	resample	VERB
admet-2772	562	2	techniques	technique	NOUN
admet-2772	562	3	have	have	AUX
admet-2772	562	4	demonstrated	demonstrate	VERB
admet-2772	562	5	improvements	improvement	NOUN
admet-2772	562	6	in	in	ADP
admet-2772	562	7	sensitivity	sensitivity	NOUN
admet-2772	562	8	and	and	CCONJ
admet-2772	562	9	specificity	specificity	NOUN
admet-2772	562	10	for	for	ADP
admet-2772	562	11	nuclear	nuclear	ADJ
admet-2772	562	12	receptor	receptor	NOUN
admet-2772	562	13	profiling	profiling	NOUN
admet-2772	562	14	[	[	X
admet-2772	562	15	219	219	NUM
admet-2772	562	16	]	]	PUNCT
admet-2772	562	17	.	.	PUNCT
admet-2772	563	1	additionally	additionally	ADV
admet-2772	563	2	,	,	PUNCT
admet-2772	563	3	transfer	transfer	NOUN
admet-2772	563	4	learning	learning	NOUN
admet-2772	563	5	approaches	approach	NOUN
admet-2772	563	6	have	have	AUX
admet-2772	563	7	shown	show	VERB
admet-2772	563	8	success	success	NOUN
admet-2772	563	9	in	in	ADP
admet-2772	563	10	predicting	predict	VERB
admet-2772	563	11	drug	drug	NOUN
admet-2772	563	12	activity	activity	NOUN
admet-2772	563	13	and	and	CCONJ
admet-2772	563	14	toxicity	toxicity	NOUN
admet-2772	563	15	for	for	ADP
admet-2772	563	16	targets	target	NOUN
admet-2772	563	17	with	with	ADP
admet-2772	563	18	insufficient	insufficient	ADJ
admet-2772	563	19	data	datum	NOUN
admet-2772	563	20	by	by	ADP
admet-2772	563	21	leveraging	leverage	VERB
admet-2772	563	22	information	information	NOUN
admet-2772	563	23	from	from	ADP
admet-2772	563	24	data	data	NOUN
admet-2772	563	25	-	-	PUNCT
admet-2772	563	26	rich	rich	ADJ
admet-2772	563	27	targets	target	NOUN
admet-2772	563	28	[	[	X
admet-2772	563	29	220	220	NUM
admet-2772	563	30	]	]	PUNCT
admet-2772	563	31	.	.	PUNCT
admet-2772	564	1	these	these	DET
admet-2772	564	2	methods	method	NOUN
admet-2772	564	3	,	,	PUNCT
admet-2772	564	4	along	along	ADP
admet-2772	564	5	with	with	ADP
admet-2772	564	6	appropriate	appropriate	ADJ
admet-2772	564	7	evaluation	evaluation	NOUN
admet-2772	564	8	metrics	metric	NOUN
admet-2772	564	9	and	and	CCONJ
admet-2772	564	10	hyperparameter	hyperparameter	NOUN
admet-2772	564	11	tuning	tuning	NOUN
admet-2772	564	12	,	,	PUNCT
admet-2772	564	13	can	can	AUX
admet-2772	564	14	enhance	enhance	VERB
admet-2772	564	15	the	the	DET
admet-2772	564	16	performance	performance	NOUN
admet-2772	564	17	of	of	ADP
admet-2772	564	18	toxicity	toxicity	NOUN
admet-2772	564	19	classification	classification	NOUN
admet-2772	564	20	models	model	NOUN
admet-2772	564	21	and	and	CCONJ
admet-2772	564	22	improve	improve	VERB
admet-2772	564	23	predictions	prediction	NOUN
admet-2772	564	24	for	for	ADP
admet-2772	564	25	understudied	understudied	ADJ
admet-2772	564	26	targets	target	NOUN
admet-2772	564	27	[	[	X
admet-2772	564	28	221	221	NUM
admet-2772	564	29	]	]	PUNCT
admet-2772	564	30	.	.	PUNCT
admet-2772	565	1	10.2	10.2	NUM
admet-2772	565	2	.	.	PUNCT
admet-2772	566	1	model	model	NOUN
admet-2772	566	2	interpretability	interpretability	NOUN
admet-2772	566	3	and	and	CCONJ
admet-2772	566	4	trustworthiness	trustworthiness	NOUN
admet-2772	566	5	data	datum	NOUN
admet-2772	566	6	scarcity	scarcity	NOUN
admet-2772	566	7	and	and	CCONJ
admet-2772	566	8	imbalance	imbalance	NOUN
admet-2772	566	9	pose	pose	VERB
admet-2772	566	10	significant	significant	ADJ
admet-2772	566	11	challenges	challenge	NOUN
admet-2772	566	12	for	for	ADP
admet-2772	566	13	deep	deep	ADJ
admet-2772	566	14	learning	learning	NOUN
admet-2772	566	15	models	model	NOUN
admet-2772	566	16	,	,	PUNCT
admet-2772	566	17	particularly	particularly	ADV
admet-2772	566	18	in	in	ADP
admet-2772	566	19	high	high	ADJ
admet-2772	566	20	-	-	PUNCT
admet-2772	566	21	stakes	stake	NOUN
admet-2772	566	22	domains	domain	NOUN
admet-2772	566	23	[	[	X
admet-2772	566	24	222	222	NUM
admet-2772	566	25	]	]	PUNCT
admet-2772	566	26	.	.	PUNCT
admet-2772	567	1	these	these	DET
admet-2772	567	2	issues	issue	NOUN
admet-2772	567	3	can	can	AUX
admet-2772	567	4	lead	lead	VERB
admet-2772	567	5	to	to	ADP
admet-2772	567	6	reduced	reduced	ADJ
admet-2772	567	7	model	model	NOUN
admet-2772	567	8	performance	performance	NOUN
admet-2772	567	9	and	and	CCONJ
admet-2772	567	10	trustworthiness	trustworthiness	NOUN
admet-2772	567	11	.	.	PUNCT
admet-2772	568	1	to	to	PART
admet-2772	568	2	address	address	VERB
admet-2772	568	3	data	datum	NOUN
admet-2772	568	4	scarcity	scarcity	NOUN
admet-2772	568	5	,	,	PUNCT
admet-2772	568	6	various	various	ADJ
admet-2772	568	7	techniques	technique	NOUN
admet-2772	568	8	have	have	AUX
admet-2772	568	9	been	be	AUX
admet-2772	568	10	proposed	propose	VERB
admet-2772	568	11	,	,	PUNCT
admet-2772	568	12	including	include	VERB
admet-2772	568	13	transfer	transfer	NOUN
admet-2772	568	14	learning	learning	NOUN
admet-2772	568	15	,	,	PUNCT
admet-2772	568	16	self	self	NOUN
admet-2772	568	17	-	-	PUNCT
admet-2772	568	18	supervised	supervise	VERB
admet-2772	568	19	learning	learning	NOUN
admet-2772	568	20	,	,	PUNCT
admet-2772	568	21	and	and	CCONJ
admet-2772	568	22	generative	generative	VERB
admet-2772	568	23	adversarial	adversarial	ADJ
admet-2772	568	24	networks	network	NOUN
admet-2772	568	25	[	[	X
admet-2772	568	26	222	222	NUM
admet-2772	568	27	]	]	PUNCT
admet-2772	568	28	.	.	PUNCT
admet-2772	569	1	for	for	ADP
admet-2772	569	2	imbalanced	imbalanced	ADJ
admet-2772	569	3	datasets	dataset	NOUN
admet-2772	569	4	,	,	PUNCT
admet-2772	569	5	interpretable	interpretable	ADJ
admet-2772	569	6	machine	machine	NOUN
admet-2772	569	7	learning	learning	NOUN
admet-2772	569	8	approaches	approach	NOUN
admet-2772	569	9	can	can	AUX
admet-2772	569	10	help	help	AUX
admet-2772	569	11	identify	identify	VERB
admet-2772	569	12	class	class	NOUN
admet-2772	569	13	prototypes	prototype	NOUN
admet-2772	569	14	,	,	PUNCT
admet-2772	569	15	sub	sub	NOUN
admet-2772	569	16	-	-	NOUN
admet-2772	569	17	concepts	concept	NOUN
admet-2772	569	18	,	,	PUNCT
admet-2772	569	19	and	and	CCONJ
admet-2772	569	20	outlier	outlier	NOUN
admet-2772	569	21	instances	instance	NOUN
admet-2772	569	22	[	[	X
admet-2772	569	23	223	223	NUM
admet-2772	569	24	]	]	PUNCT
admet-2772	569	25	.	.	PUNCT
admet-2772	570	1	however	however	ADV
admet-2772	570	2	,	,	PUNCT
admet-2772	570	3	class	class	NOUN
admet-2772	570	4	imbalance	imbalance	NOUN
admet-2772	570	5	can	can	AUX
admet-2772	570	6	adversely	adversely	ADV
admet-2772	570	7	affect	affect	VERB
admet-2772	570	8	the	the	DET
admet-2772	570	9	stability	stability	NOUN
admet-2772	570	10	of	of	ADP
admet-2772	570	11	interpretation	interpretation	NOUN
admet-2772	570	12	methods	method	NOUN
admet-2772	570	13	like	like	ADP
admet-2772	570	14	lime	lime	NOUN
admet-2772	570	15	and	and	CCONJ
admet-2772	570	16	shap	shap	NOUN
admet-2772	570	17	,	,	PUNCT
admet-2772	570	18	particularly	particularly	ADV
admet-2772	570	19	in	in	ADP
admet-2772	570	20	credit	credit	NOUN
admet-2772	570	21	scoring	scoring	NOUN
admet-2772	570	22	applications	application	NOUN
admet-2772	570	23	[	[	X
admet-2772	570	24	224	224	NUM
admet-2772	570	25	]	]	PUNCT
admet-2772	570	26	.	.	PUNCT
admet-2772	571	1	when	when	SCONJ
admet-2772	571	2	evaluating	evaluate	VERB
admet-2772	571	3	model	model	NOUN
admet-2772	571	4	interpretability	interpretability	NOUN
admet-2772	571	5	and	and	CCONJ
admet-2772	571	6	trustworthiness	trustworthiness	NOUN
admet-2772	571	7	,	,	PUNCT
admet-2772	571	8	it	it	PRON
admet-2772	571	9	's	be	AUX
admet-2772	571	10	crucial	crucial	ADJ
admet-2772	571	11	to	to	PART
admet-2772	571	12	consider	consider	VERB
admet-2772	571	13	the	the	DET
admet-2772	571	14	inductive	inductive	ADJ
admet-2772	571	15	bias	bias	NOUN
admet-2772	571	16	of	of	ADP
admet-2772	571	17	different	different	ADJ
admet-2772	571	18	algorithms	algorithm	NOUN
admet-2772	571	19	.	.	PUNCT
admet-2772	572	1	for	for	ADP
admet-2772	572	2	instance	instance	NOUN
admet-2772	572	3	,	,	PUNCT
admet-2772	572	4	in	in	ADP
admet-2772	572	5	generalized	generalized	ADJ
admet-2772	572	6	additive	additive	ADJ
admet-2772	572	7	models	model	NOUN
admet-2772	572	8	(	(	PUNCT
admet-2772	572	9	gams	gams	PROPN
admet-2772	572	10	)	)	PUNCT
admet-2772	572	11	,	,	PUNCT
admet-2772	572	12	tree	tree	NOUN
admet-2772	572	13	-	-	PUNCT
admet-2772	572	14	based	base	VERB
admet-2772	572	15	approaches	approach	NOUN
admet-2772	572	16	offer	offer	VERB
admet-2772	572	17	a	a	DET
admet-2772	572	18	good	good	ADJ
admet-2772	572	19	balance	balance	NOUN
admet-2772	572	20	of	of	ADP
admet-2772	572	21	sparsity	sparsity	NOUN
admet-2772	572	22	,	,	PUNCT
admet-2772	572	23	fidelity	fidelity	NOUN
admet-2772	572	24	,	,	PUNCT
admet-2772	572	25	and	and	CCONJ
admet-2772	572	26	accuracy	accuracy	NOUN
admet-2772	572	27	,	,	PUNCT
admet-2772	572	28	making	make	VERB
admet-2772	572	29	them	they	PRON
admet-2772	572	30	potentially	potentially	ADV
admet-2772	572	31	more	more	ADV
admet-2772	572	32	trustworthy	trustworthy	ADJ
admet-2772	572	33	[	[	X
admet-2772	572	34	225	225	NUM
admet-2772	572	35	]	]	PUNCT
admet-2772	572	36	.	.	PUNCT
admet-2772	573	1	10.3	10.3	NUM
admet-2772	573	2	.	.	PUNCT
admet-2772	573	3	generalization	generalization	NOUN
admet-2772	573	4	across	across	ADP
admet-2772	573	5	chemical	chemical	NOUN
admet-2772	573	6	space	space	NOUN
admet-2772	573	7	machine	machine	NOUN
admet-2772	573	8	learning	learning	NOUN
admet-2772	573	9	models	model	NOUN
admet-2772	573	10	in	in	ADP
admet-2772	573	11	chemistry	chemistry	NOUN
admet-2772	573	12	often	often	ADV
admet-2772	573	13	face	face	VERB
admet-2772	573	14	challenges	challenge	NOUN
admet-2772	573	15	due	due	ADP
admet-2772	573	16	to	to	ADP
admet-2772	573	17	data	datum	NOUN
admet-2772	573	18	scarcity	scarcity	NOUN
admet-2772	573	19	and	and	CCONJ
admet-2772	573	20	imbalance	imbalance	NOUN
admet-2772	573	21	,	,	PUNCT
admet-2772	573	22	which	which	PRON
admet-2772	573	23	can	can	AUX
admet-2772	573	24	lead	lead	VERB
admet-2772	573	25	to	to	ADP
admet-2772	573	26	overfitting	overfitte	VERB
admet-2772	573	27	and	and	CCONJ
admet-2772	573	28	poor	poor	ADJ
admet-2772	573	29	generalization	generalization	NOUN
admet-2772	573	30	.	.	PUNCT
admet-2772	574	1	several	several	ADJ
admet-2772	574	2	strategies	strategy	NOUN
admet-2772	574	3	have	have	AUX
admet-2772	574	4	been	be	AUX
admet-2772	574	5	proposed	propose	VERB
admet-2772	574	6	to	to	PART
admet-2772	574	7	address	address	VERB
admet-2772	574	8	these	these	DET
admet-2772	574	9	issues	issue	NOUN
admet-2772	574	10	.	.	PUNCT
admet-2772	575	1	farthest	farth	ADJ
admet-2772	575	2	point	point	NOUN
admet-2772	575	3	sampling	sample	VERB
admet-2772	575	4	in	in	ADP
admet-2772	575	5	chemical	chemical	ADJ
admet-2772	575	6	feature	feature	NOUN
admet-2772	575	7	spaces	space	NOUN
admet-2772	575	8	can	can	AUX
admet-2772	575	9	generate	generate	VERB
admet-2772	575	10	well	well	ADV
admet-2772	575	11	-	-	PUNCT
admet-2772	575	12	distributed	distribute	VERB
admet-2772	575	13	training	training	NOUN
admet-2772	575	14	datasets	dataset	NOUN
admet-2772	575	15	,	,	PUNCT
admet-2772	575	16	enhancing	enhance	VERB
admet-2772	575	17	model	model	NOUN
admet-2772	575	18	performance	performance	NOUN
admet-2772	575	19	across	across	ADP
admet-2772	575	20	various	various	ADJ
admet-2772	575	21	algorithms	algorithm	NOUN
admet-2772	575	22	[	[	X
admet-2772	575	23	226	226	NUM
admet-2772	575	24	]	]	PUNCT
admet-2772	575	25	.	.	PUNCT
admet-2772	576	1	latent	latent	ADJ
admet-2772	576	2	space	space	NOUN
admet-2772	576	3	enrichment	enrichment	NOUN
admet-2772	576	4	,	,	PUNCT
admet-2772	576	5	combining	combine	VERB
admet-2772	576	6	disparate	disparate	ADJ
admet-2772	576	7	data	datum	NOUN
admet-2772	576	8	sources	source	NOUN
admet-2772	576	9	in	in	ADP
admet-2772	576	10	joint	joint	ADJ
admet-2772	576	11	prediction	prediction	NOUN
admet-2772	576	12	tasks	task	NOUN
admet-2772	576	13	,	,	PUNCT
admet-2772	576	14	improves	improve	VERB
admet-2772	576	15	prediction	prediction	NOUN
admet-2772	576	16	in	in	ADP
admet-2772	576	17	data	data	NOUN
admet-2772	576	18	-	-	PUNCT
admet-2772	576	19	scarce	scarce	NOUN
admet-2772	576	20	applications	application	NOUN
admet-2772	576	21	[	[	X
admet-2772	576	22	227	227	NUM
admet-2772	576	23	]	]	PUNCT
admet-2772	576	24	.	.	PUNCT
admet-2772	577	1	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	577	2	m.	m.	PROPN
admet-2772	577	3	venkataraman	venkataraman	PROPN
admet-2772	577	4	et	et	PROPN
admet-2772	577	5	al	al	PROPN
admet-2772	577	6	.	.	PROPN
admet-2772	577	7	admet	admet	PROPN
admet-2772	577	8	&	&	CCONJ
admet-2772	577	9	dmpk	dmpk	PROPN
admet-2772	577	10	13(3	13(3	NUM
admet-2772	577	11	)	)	PUNCT
admet-2772	577	12	(	(	PUNCT
admet-2772	577	13	2025	2025	NUM
admet-2772	577	14	)	)	PUNCT
admet-2772	577	15	2772	2772	NUM
admet-2772	577	16	22	22	NUM
admet-2772	577	17	similarity	similarity	NOUN
admet-2772	577	18	-	-	PUNCT
admet-2772	577	19	based	base	VERB
admet-2772	577	20	machine	machine	NOUN
admet-2772	577	21	learning	learning	NOUN
admet-2772	577	22	enables	enable	VERB
admet-2772	577	23	on	on	ADP
admet-2772	577	24	-	-	PUNCT
admet-2772	577	25	the	the	DET
admet-2772	577	26	-	-	PUNCT
admet-2772	577	27	fly	fly	NOUN
admet-2772	577	28	data	datum	NOUN
admet-2772	577	29	selection	selection	NOUN
admet-2772	577	30	and	and	CCONJ
admet-2772	577	31	model	model	NOUN
admet-2772	577	32	training	training	NOUN
admet-2772	577	33	for	for	ADP
admet-2772	577	34	specific	specific	ADJ
admet-2772	577	35	queries	query	NOUN
admet-2772	577	36	,	,	PUNCT
admet-2772	577	37	requiring	require	VERB
admet-2772	577	38	only	only	ADV
admet-2772	577	39	a	a	DET
admet-2772	577	40	fraction	fraction	NOUN
admet-2772	577	41	of	of	ADP
admet-2772	577	42	data	datum	NOUN
admet-2772	577	43	to	to	PART
admet-2772	577	44	achieve	achieve	VERB
admet-2772	577	45	competitive	competitive	ADJ
admet-2772	577	46	performance	performance	NOUN
admet-2772	577	47	[	[	X
admet-2772	577	48	228	228	NUM
admet-2772	577	49	]	]	PUNCT
admet-2772	577	50	.	.	PUNCT
admet-2772	578	1	when	when	SCONJ
admet-2772	578	2	dealing	deal	VERB
admet-2772	578	3	with	with	ADP
admet-2772	578	4	class	class	NOUN
admet-2772	578	5	imbalance	imbalance	NOUN
admet-2772	578	6	and	and	CCONJ
admet-2772	578	7	data	datum	NOUN
admet-2772	578	8	scarcity	scarcity	NOUN
admet-2772	578	9	in	in	ADP
admet-2772	578	10	toxicity	toxicity	NOUN
admet-2772	578	11	classification	classification	NOUN
admet-2772	578	12	models	model	NOUN
admet-2772	578	13	,	,	PUNCT
admet-2772	578	14	appropriate	appropriate	ADJ
admet-2772	578	15	resampling	resample	VERB
admet-2772	578	16	algorithms	algorithm	NOUN
admet-2772	578	17	,	,	PUNCT
admet-2772	578	18	evaluation	evaluation	NOUN
admet-2772	578	19	metrics	metric	NOUN
admet-2772	578	20	,	,	PUNCT
admet-2772	578	21	and	and	CCONJ
admet-2772	578	22	hyperparameter	hyperparameter	NOUN
admet-2772	578	23	tuning	tuning	NOUN
admet-2772	578	24	are	be	AUX
admet-2772	578	25	crucial	crucial	ADJ
admet-2772	578	26	for	for	ADP
admet-2772	578	27	optimal	optimal	ADJ
admet-2772	578	28	performance	performance	NOUN
admet-2772	578	29	[	[	X
admet-2772	578	30	218	218	NUM
admet-2772	578	31	]	]	PUNCT
admet-2772	578	32	.	.	PUNCT
admet-2772	579	1	these	these	DET
admet-2772	579	2	approaches	approach	NOUN
admet-2772	579	3	collectively	collectively	ADV
admet-2772	579	4	offer	offer	VERB
admet-2772	579	5	promising	promise	VERB
admet-2772	579	6	solutions	solution	NOUN
admet-2772	579	7	to	to	PART
admet-2772	579	8	enhance	enhance	VERB
admet-2772	579	9	machine	machine	NOUN
admet-2772	579	10	learning	learning	NOUN
admet-2772	579	11	model	model	NOUN
admet-2772	579	12	performance	performance	NOUN
admet-2772	579	13	in	in	ADP
admet-2772	579	14	chemistry	chemistry	NOUN
admet-2772	579	15	,	,	PUNCT
admet-2772	579	16	particularly	particularly	ADV
admet-2772	579	17	when	when	SCONJ
admet-2772	579	18	faced	face	VERB
admet-2772	579	19	with	with	ADP
admet-2772	579	20	limited	limited	ADJ
admet-2772	579	21	or	or	CCONJ
admet-2772	579	22	imbalanced	imbalanced	ADJ
admet-2772	579	23	datasets	dataset	NOUN
admet-2772	579	24	.	.	PUNCT
admet-2772	580	1	10.4	10.4	NUM
admet-2772	580	2	.	.	PUNCT
admet-2772	580	3	model	model	NOUN
admet-2772	580	4	validation	validation	NOUN
admet-2772	580	5	and	and	CCONJ
admet-2772	580	6	regulatory	regulatory	ADJ
admet-2772	580	7	acceptance	acceptance	NOUN
admet-2772	580	8	data	datum	NOUN
admet-2772	580	9	scarcity	scarcity	NOUN
admet-2772	580	10	and	and	CCONJ
admet-2772	580	11	class	class	NOUN
admet-2772	580	12	imbalance	imbalance	NOUN
admet-2772	580	13	pose	pose	VERB
admet-2772	580	14	significant	significant	ADJ
admet-2772	580	15	challenges	challenge	NOUN
admet-2772	580	16	in	in	ADP
admet-2772	580	17	developing	develop	VERB
admet-2772	580	18	and	and	CCONJ
admet-2772	580	19	validating	validate	VERB
admet-2772	580	20	machine	machine	NOUN
admet-2772	580	21	learning	learning	NOUN
admet-2772	580	22	models	model	NOUN
admet-2772	580	23	,	,	PUNCT
admet-2772	580	24	particularly	particularly	ADV
admet-2772	580	25	for	for	ADP
admet-2772	580	26	safety	safety	NOUN
admet-2772	580	27	-	-	PUNCT
admet-2772	580	28	critical	critical	ADJ
admet-2772	580	29	applications	application	NOUN
admet-2772	580	30	.	.	PUNCT
admet-2772	581	1	these	these	DET
admet-2772	581	2	issues	issue	NOUN
admet-2772	581	3	can	can	AUX
admet-2772	581	4	affect	affect	VERB
admet-2772	581	5	model	model	NOUN
admet-2772	581	6	performance	performance	NOUN
admet-2772	581	7	metrics	metric	NOUN
admet-2772	581	8	and	and	CCONJ
admet-2772	581	9	potentially	potentially	ADV
admet-2772	581	10	invalidate	invalidate	VERB
admet-2772	581	11	underlying	underlying	ADJ
admet-2772	581	12	assumptions	assumption	NOUN
admet-2772	581	13	[	[	X
admet-2772	581	14	229	229	NUM
admet-2772	581	15	]	]	PUNCT
admet-2772	581	16	.	.	PUNCT
admet-2772	582	1	studies	study	NOUN
admet-2772	582	2	have	have	AUX
admet-2772	582	3	shown	show	VERB
admet-2772	582	4	that	that	PRON
admet-2772	582	5	class	class	NOUN
admet-2772	582	6	imbalance	imbalance	NOUN
admet-2772	582	7	significantly	significantly	ADV
admet-2772	582	8	impacts	impact	VERB
admet-2772	582	9	recall	recall	NOUN
admet-2772	582	10	and	and	CCONJ
admet-2772	582	11	f1	f1	NOUN
admet-2772	582	12	scores	score	NOUN
admet-2772	582	13	,	,	PUNCT
admet-2772	582	14	while	while	SCONJ
admet-2772	582	15	hyperparameter	hyperparameter	NOUN
admet-2772	582	16	tuning	tuning	NOUN
admet-2772	582	17	can	can	AUX
admet-2772	582	18	improve	improve	VERB
admet-2772	582	19	performance	performance	NOUN
admet-2772	582	20	on	on	ADP
admet-2772	582	21	imbalanced	imbalanced	ADJ
admet-2772	582	22	datasets	dataset	NOUN
admet-2772	582	23	[	[	X
admet-2772	582	24	218	218	NUM
admet-2772	582	25	]	]	PUNCT
admet-2772	582	26	.	.	PUNCT
admet-2772	583	1	to	to	PART
admet-2772	583	2	address	address	VERB
admet-2772	583	3	data	datum	NOUN
admet-2772	583	4	scarcity	scarcity	NOUN
admet-2772	583	5	,	,	PUNCT
admet-2772	583	6	various	various	ADJ
admet-2772	583	7	techniques	technique	NOUN
admet-2772	583	8	have	have	AUX
admet-2772	583	9	been	be	AUX
admet-2772	583	10	proposed	propose	VERB
admet-2772	583	11	,	,	PUNCT
admet-2772	583	12	including	include	VERB
admet-2772	583	13	transfer	transfer	NOUN
admet-2772	583	14	learning	learning	NOUN
admet-2772	583	15	,	,	PUNCT
admet-2772	583	16	self	self	NOUN
admet-2772	583	17	-	-	PUNCT
admet-2772	583	18	supervised	supervise	VERB
admet-2772	583	19	learning	learning	NOUN
admet-2772	583	20	,	,	PUNCT
admet-2772	583	21	and	and	CCONJ
admet-2772	583	22	generative	generative	VERB
admet-2772	583	23	adversarial	adversarial	ADJ
admet-2772	583	24	networks	network	NOUN
admet-2772	583	25	[	[	X
admet-2772	583	26	222	222	NUM
admet-2772	583	27	]	]	PUNCT
admet-2772	583	28	.	.	PUNCT
admet-2772	584	1	for	for	ADP
admet-2772	584	2	regulatory	regulatory	ADJ
admet-2772	584	3	acceptance	acceptance	NOUN
admet-2772	584	4	of	of	ADP
admet-2772	584	5	models	model	NOUN
admet-2772	584	6	,	,	PUNCT
admet-2772	584	7	it	it	PRON
admet-2772	584	8	is	be	AUX
admet-2772	584	9	crucial	crucial	ADJ
admet-2772	584	10	to	to	PART
admet-2772	584	11	consider	consider	VERB
admet-2772	584	12	model	model	NOUN
admet-2772	584	13	domain	domain	NOUN
admet-2772	584	14	,	,	PUNCT
admet-2772	584	15	uncertainty	uncertainty	NOUN
admet-2772	584	16	,	,	PUNCT
admet-2772	584	17	validity	validity	NOUN
admet-2772	584	18	,	,	PUNCT
admet-2772	584	19	and	and	CCONJ
admet-2772	584	20	predictability	predictability	NOUN
admet-2772	584	21	[	[	X
admet-2772	584	22	230	230	NUM
admet-2772	584	23	]	]	PUNCT
admet-2772	584	24	.	.	PUNCT
admet-2772	585	1	researchers	researcher	NOUN
admet-2772	585	2	emphasize	emphasize	VERB
admet-2772	585	3	the	the	DET
admet-2772	585	4	importance	importance	NOUN
admet-2772	585	5	of	of	ADP
admet-2772	585	6	using	use	VERB
admet-2772	585	7	appropriate	appropriate	ADJ
admet-2772	585	8	evaluation	evaluation	NOUN
admet-2772	585	9	metrics	metric	NOUN
admet-2772	585	10	,	,	PUNCT
admet-2772	585	11	tuning	tune	VERB
admet-2772	585	12	hyperparameters	hyperparameter	NOUN
admet-2772	585	13	,	,	PUNCT
admet-2772	585	14	and	and	CCONJ
admet-2772	585	15	ensuring	ensure	VERB
admet-2772	585	16	the	the	DET
admet-2772	585	17	trustworthiness	trustworthiness	NOUN
admet-2772	585	18	of	of	ADP
admet-2772	585	19	training	training	NOUN
admet-2772	585	20	datasets	dataset	NOUN
admet-2772	585	21	[	[	X
admet-2772	585	22	222	222	NUM
admet-2772	585	23	]	]	PUNCT
admet-2772	585	24	.	.	PUNCT
admet-2772	586	1	these	these	DET
admet-2772	586	2	considerations	consideration	NOUN
admet-2772	586	3	are	be	AUX
admet-2772	586	4	essential	essential	ADJ
admet-2772	586	5	for	for	ADP
admet-2772	586	6	developing	develop	VERB
admet-2772	586	7	reliable	reliable	ADJ
admet-2772	586	8	and	and	CCONJ
admet-2772	586	9	effective	effective	ADJ
admet-2772	586	10	models	model	NOUN
admet-2772	586	11	in	in	ADP
admet-2772	586	12	fields	field	NOUN
admet-2772	586	13	such	such	ADJ
admet-2772	586	14	as	as	ADP
admet-2772	586	15	toxicity	toxicity	NOUN
admet-2772	586	16	prediction	prediction	NOUN
admet-2772	586	17	,	,	PUNCT
admet-2772	586	18	aviation	aviation	NOUN
admet-2772	586	19	,	,	PUNCT
admet-2772	586	20	and	and	CCONJ
admet-2772	586	21	medical	medical	ADJ
admet-2772	586	22	imaging	imaging	NOUN
admet-2772	586	23	.	.	PUNCT
admet-2772	587	1	11	11	NUM
admet-2772	587	2	.	.	PUNCT
admet-2772	588	1	future	future	ADJ
admet-2772	588	2	directions	direction	NOUN
admet-2772	588	3	and	and	CCONJ
admet-2772	588	4	innovations	innovation	NOUN
admet-2772	588	5	11.1	11.1	NUM
admet-2772	588	6	.	.	PUNCT
admet-2772	589	1	integrating	integrate	VERB
admet-2772	589	2	ai	ai	VERB
admet-2772	589	3	with	with	ADP
admet-2772	589	4	experimental	experimental	ADJ
admet-2772	589	5	approaches	approach	NOUN
admet-2772	589	6	recent	recent	ADJ
admet-2772	589	7	research	research	NOUN
admet-2772	589	8	highlights	highlight	NOUN
admet-2772	589	9	the	the	DET
admet-2772	589	10	integration	integration	NOUN
admet-2772	589	11	of	of	ADP
admet-2772	589	12	ai	ai	VERB
admet-2772	589	13	with	with	ADP
admet-2772	589	14	experimental	experimental	ADJ
admet-2772	589	15	approaches	approach	NOUN
admet-2772	589	16	in	in	ADP
admet-2772	589	17	various	various	ADJ
admet-2772	589	18	fields	field	NOUN
admet-2772	589	19	.	.	PUNCT
admet-2772	590	1	ai	ai	AUX
admet-2772	590	2	and	and	CCONJ
admet-2772	590	3	ml	ml	ADP
admet-2772	590	4	models	model	NOUN
admet-2772	590	5	can	can	AUX
admet-2772	590	6	serve	serve	VERB
admet-2772	590	7	as	as	ADP
admet-2772	590	8	fast	fast	ADJ
admet-2772	590	9	surrogates	surrogate	NOUN
admet-2772	590	10	for	for	ADP
admet-2772	590	11	time	time	NOUN
admet-2772	590	12	-	-	PUNCT
admet-2772	590	13	consuming	consume	VERB
admet-2772	590	14	experiments	experiment	NOUN
admet-2772	590	15	or	or	CCONJ
admet-2772	590	16	computational	computational	ADJ
admet-2772	590	17	models	model	NOUN
admet-2772	590	18	,	,	PUNCT
admet-2772	590	19	enhancing	enhance	VERB
admet-2772	590	20	predictive	predictive	ADJ
admet-2772	590	21	capabilities	capability	NOUN
admet-2772	590	22	while	while	SCONJ
admet-2772	590	23	reducing	reduce	VERB
admet-2772	590	24	data	datum	NOUN
admet-2772	590	25	requirements	requirement	NOUN
admet-2772	590	26	[	[	X
admet-2772	590	27	231	231	NUM
admet-2772	590	28	]	]	PUNCT
admet-2772	590	29	.	.	PUNCT
admet-2772	591	1	in	in	ADP
admet-2772	591	2	molecular	molecular	ADJ
admet-2772	591	3	design	design	NOUN
admet-2772	591	4	,	,	PUNCT
admet-2772	591	5	ai	ai	AUX
admet-2772	591	6	techniques	technique	NOUN
admet-2772	591	7	are	be	AUX
admet-2772	591	8	being	be	AUX
admet-2772	591	9	combined	combine	VERB
admet-2772	591	10	with	with	ADP
admet-2772	591	11	experimental	experimental	ADJ
admet-2772	591	12	validation	validation	NOUN
admet-2772	591	13	and	and	CCONJ
admet-2772	591	14	chemistry	chemistry	NOUN
admet-2772	591	15	automation	automation	NOUN
admet-2772	591	16	,	,	PUNCT
admet-2772	591	17	although	although	SCONJ
admet-2772	591	18	these	these	DET
admet-2772	591	19	efforts	effort	NOUN
admet-2772	591	20	are	be	AUX
admet-2772	591	21	still	still	ADV
admet-2772	591	22	in	in	ADP
admet-2772	591	23	early	early	ADJ
admet-2772	591	24	stages	stage	NOUN
admet-2772	591	25	[	[	X
admet-2772	591	26	232	232	NUM
admet-2772	591	27	]	]	PUNCT
admet-2772	591	28	.	.	PUNCT
admet-2772	592	1	the	the	DET
admet-2772	592	2	development	development	NOUN
admet-2772	592	3	of	of	ADP
admet-2772	592	4	cell	cell	NOUN
admet-2772	592	5	therapies	therapy	NOUN
admet-2772	592	6	is	be	AUX
admet-2772	592	7	benefiting	benefit	VERB
admet-2772	592	8	from	from	ADP
admet-2772	592	9	ai	ai	PROPN
admet-2772	592	10	and	and	CCONJ
admet-2772	592	11	ml	ml	PROPN
admet-2772	592	12	methods	method	NOUN
admet-2772	592	13	,	,	PUNCT
admet-2772	592	14	which	which	PRON
admet-2772	592	15	can	can	AUX
admet-2772	592	16	generate	generate	VERB
admet-2772	592	17	predictive	predictive	ADJ
admet-2772	592	18	models	model	NOUN
admet-2772	592	19	and	and	CCONJ
admet-2772	592	20	design	design	NOUN
admet-2772	592	21	rules	rule	NOUN
admet-2772	592	22	based	base	VERB
admet-2772	592	23	on	on	ADP
admet-2772	592	24	high	high	ADJ
admet-2772	592	25	-	-	PUNCT
admet-2772	592	26	throughput	throughput	NOUN
admet-2772	592	27	screening	screen	VERB
admet-2772	592	28	data	datum	NOUN
admet-2772	592	29	[	[	X
admet-2772	592	30	233	233	NUM
admet-2772	592	31	]	]	PUNCT
admet-2772	592	32	.	.	PUNCT
admet-2772	593	1	the	the	DET
admet-2772	593	2	integration	integration	NOUN
admet-2772	593	3	of	of	ADP
admet-2772	593	4	ai	ai	VERB
admet-2772	593	5	with	with	ADP
admet-2772	593	6	geography	geography	NOUN
admet-2772	593	7	,	,	PUNCT
admet-2772	593	8	termed	term	VERB
admet-2772	593	9	geoai	geoai	NOUN
admet-2772	593	10	,	,	PUNCT
admet-2772	593	11	is	be	AUX
admet-2772	593	12	providing	provide	VERB
admet-2772	593	13	novel	novel	ADJ
admet-2772	593	14	approaches	approach	NOUN
admet-2772	593	15	for	for	ADP
admet-2772	593	16	addressing	address	VERB
admet-2772	593	17	environmental	environmental	ADJ
admet-2772	593	18	and	and	CCONJ
admet-2772	593	19	societal	societal	ADJ
admet-2772	593	20	problems	problem	NOUN
admet-2772	593	21	[	[	X
admet-2772	593	22	234	234	NUM
admet-2772	593	23	]	]	PUNCT
admet-2772	593	24	.	.	PUNCT
admet-2772	594	1	future	future	ADJ
admet-2772	594	2	directions	direction	NOUN
admet-2772	594	3	include	include	VERB
admet-2772	594	4	the	the	DET
admet-2772	594	5	automatic	automatic	ADJ
admet-2772	594	6	discovery	discovery	NOUN
admet-2772	594	7	of	of	ADP
admet-2772	594	8	physical	physical	ADJ
admet-2772	594	9	laws	law	NOUN
admet-2772	594	10	,	,	PUNCT
admet-2772	594	11	active	active	ADJ
admet-2772	594	12	learning	learning	NOUN
admet-2772	594	13	for	for	ADP
admet-2772	594	14	optimal	optimal	ADJ
admet-2772	594	15	experiment	experiment	NOUN
admet-2772	594	16	design	design	NOUN
admet-2772	594	17	,	,	PUNCT
admet-2772	594	18	and	and	CCONJ
admet-2772	594	19	the	the	DET
admet-2772	594	20	integration	integration	NOUN
admet-2772	594	21	of	of	ADP
admet-2772	594	22	multi	multi	ADJ
admet-2772	594	23	-	-	ADJ
admet-2772	594	24	fidelity	fidelity	ADJ
admet-2772	594	25	data	datum	NOUN
admet-2772	594	26	from	from	ADP
admet-2772	594	27	various	various	ADJ
admet-2772	594	28	computational	computational	ADJ
admet-2772	594	29	models	model	NOUN
admet-2772	594	30	and	and	CCONJ
admet-2772	594	31	experimental	experimental	ADJ
admet-2772	594	32	instruments	instrument	NOUN
admet-2772	594	33	[	[	X
admet-2772	594	34	231	231	NUM
admet-2772	594	35	]	]	PUNCT
admet-2772	594	36	.	.	PUNCT
admet-2772	595	1	11.2	11.2	NUM
admet-2772	595	2	.	.	PUNCT
admet-2772	596	1	advances	advance	NOUN
admet-2772	596	2	in	in	ADP
admet-2772	596	3	explainable	explainable	ADJ
admet-2772	596	4	ai	ai	VERB
admet-2772	596	5	explainable	explainable	ADJ
admet-2772	596	6	ai	ai	NOUN
admet-2772	596	7	(	(	PUNCT
admet-2772	596	8	xai	xai	PROPN
admet-2772	596	9	)	)	PUNCT
admet-2772	596	10	is	be	AUX
admet-2772	596	11	an	an	DET
admet-2772	596	12	emerging	emerge	VERB
admet-2772	596	13	field	field	NOUN
admet-2772	596	14	aimed	aim	VERB
admet-2772	596	15	at	at	ADP
admet-2772	596	16	increasing	increase	VERB
admet-2772	596	17	the	the	DET
admet-2772	596	18	interpretability	interpretability	NOUN
admet-2772	596	19	and	and	CCONJ
admet-2772	596	20	transparency	transparency	NOUN
admet-2772	596	21	of	of	ADP
admet-2772	596	22	machine	machine	NOUN
admet-2772	596	23	learning	learning	NOUN
admet-2772	596	24	models	model	NOUN
admet-2772	596	25	.	.	PUNCT
admet-2772	597	1	recent	recent	ADJ
admet-2772	597	2	research	research	NOUN
admet-2772	597	3	highlights	highlight	VERB
admet-2772	597	4	the	the	DET
admet-2772	597	5	integration	integration	NOUN
admet-2772	597	6	of	of	ADP
admet-2772	597	7	diverse	diverse	ADJ
admet-2772	597	8	approaches	approach	NOUN
admet-2772	597	9	to	to	PART
admet-2772	597	10	advance	advance	VERB
admet-2772	597	11	xai	xai	PROPN
admet-2772	597	12	.	.	PUNCT
admet-2772	598	1	experimental	experimental	ADJ
admet-2772	598	2	psychology	psychology	NOUN
admet-2772	598	3	methods	method	NOUN
admet-2772	598	4	can	can	AUX
admet-2772	598	5	contribute	contribute	VERB
admet-2772	598	6	to	to	ADP
admet-2772	598	7	xai	xai	PROPN
admet-2772	598	8	by	by	ADP
admet-2772	598	9	applying	apply	VERB
admet-2772	598	10	cognitive	cognitive	ADJ
admet-2772	598	11	modelling	modelling	NOUN
admet-2772	598	12	techniques	technique	NOUN
admet-2772	598	13	to	to	ADP
admet-2772	598	14	artificial	artificial	ADJ
admet-2772	598	15	black	black	ADJ
admet-2772	598	16	boxes	box	NOUN
admet-2772	598	17	[	[	X
admet-2772	598	18	235	235	NUM
admet-2772	598	19	]	]	PUNCT
admet-2772	598	20	.	.	PUNCT
admet-2772	599	1	formal	formal	ADJ
admet-2772	599	2	methods	method	NOUN
admet-2772	599	3	,	,	PUNCT
admet-2772	599	4	such	such	ADJ
admet-2772	599	5	as	as	ADP
admet-2772	599	6	algebraic	algebraic	ADJ
admet-2772	599	7	decision	decision	NOUN
admet-2772	599	8	diagrams	diagram	NOUN
admet-2772	599	9	,	,	PUNCT
admet-2772	599	10	can	can	AUX
admet-2772	599	11	enhance	enhance	VERB
admet-2772	599	12	explainability	explainability	NOUN
admet-2772	599	13	by	by	ADP
admet-2772	599	14	providing	provide	VERB
admet-2772	599	15	precise	precise	ADJ
admet-2772	599	16	characterizations	characterization	NOUN
admet-2772	599	17	of	of	ADP
admet-2772	599	18	ai	ai	VERB
admet-2772	599	19	outcomes	outcome	NOUN
admet-2772	599	20	[	[	X
admet-2772	599	21	236	236	NUM
admet-2772	599	22	]	]	PUNCT
admet-2772	599	23	.	.	PUNCT
admet-2772	600	1	the	the	DET
admet-2772	600	2	arts	art	NOUN
admet-2772	600	3	offer	offer	VERB
admet-2772	600	4	valuable	valuable	ADJ
admet-2772	600	5	contributions	contribution	NOUN
admet-2772	600	6	to	to	PART
admet-2772	600	7	address	address	VERB
admet-2772	600	8	limitations	limitation	NOUN
admet-2772	600	9	in	in	ADP
admet-2772	600	10	explainable	explainable	ADJ
admet-2772	600	11	ai	ai	NOUN
admet-2772	600	12	,	,	PUNCT
admet-2772	600	13	fostering	foster	VERB
admet-2772	600	14	collaborations	collaboration	NOUN
admet-2772	600	15	between	between	ADP
admet-2772	600	16	scientists	scientist	NOUN
admet-2772	600	17	and	and	CCONJ
admet-2772	600	18	artists	artist	NOUN
admet-2772	600	19	to	to	PART
admet-2772	600	20	investigate	investigate	VERB
admet-2772	600	21	humanmachine	humanmachine	ADJ
admet-2772	600	22	entanglements	entanglement	NOUN
admet-2772	600	23	[	[	X
admet-2772	600	24	237	237	NUM
admet-2772	600	25	]	]	PUNCT
admet-2772	600	26	.	.	PUNCT
admet-2772	601	1	current	current	ADJ
admet-2772	601	2	xai	xai	PROPN
admet-2772	601	3	approaches	approach	VERB
admet-2772	601	4	in	in	ADP
admet-2772	601	5	deep	deep	ADJ
admet-2772	601	6	learning	learning	NOUN
admet-2772	601	7	encompass	encompass	VERB
admet-2772	601	8	various	various	ADJ
admet-2772	601	9	applications	application	NOUN
admet-2772	601	10	,	,	PUNCT
admet-2772	601	11	evaluation	evaluation	NOUN
admet-2772	601	12	metrics	metric	NOUN
admet-2772	601	13	,	,	PUNCT
admet-2772	601	14	and	and	CCONJ
admet-2772	601	15	challenges	challenge	NOUN
admet-2772	601	16	,	,	PUNCT
admet-2772	601	17	with	with	ADP
admet-2772	601	18	ongoing	ongoing	ADJ
admet-2772	601	19	research	research	NOUN
admet-2772	601	20	focusing	focus	VERB
admet-2772	601	21	on	on	ADP
admet-2772	601	22	improving	improve	VERB
admet-2772	601	23	trust	trust	NOUN
admet-2772	601	24	,	,	PUNCT
admet-2772	601	25	accountability	accountability	NOUN
admet-2772	601	26	,	,	PUNCT
admet-2772	601	27	and	and	CCONJ
admet-2772	601	28	interoperability	interoperability	NOUN
admet-2772	601	29	of	of	ADP
admet-2772	601	30	complex	complex	ADJ
admet-2772	601	31	neural	neural	ADJ
admet-2772	601	32	networks	network	NOUN
admet-2772	601	33	[	[	X
admet-2772	601	34	238	238	NUM
admet-2772	601	35	]	]	PUNCT
admet-2772	601	36	.	.	PUNCT
admet-2772	602	1	these	these	DET
admet-2772	602	2	multidisciplinary	multidisciplinary	ADJ
admet-2772	602	3	efforts	effort	NOUN
admet-2772	602	4	aim	aim	VERB
admet-2772	602	5	to	to	PART
admet-2772	602	6	create	create	VERB
admet-2772	602	7	more	more	ADV
admet-2772	602	8	transparent	transparent	ADJ
admet-2772	602	9	and	and	CCONJ
admet-2772	602	10	understandable	understandable	ADJ
admet-2772	602	11	ai	ai	PROPN
admet-2772	602	12	systems	system	NOUN
admet-2772	602	13	across	across	ADP
admet-2772	602	14	diverse	diverse	ADJ
admet-2772	602	15	domains	domain	NOUN
admet-2772	602	16	.	.	PUNCT
admet-2772	603	1	admet	admet	PROPN
admet-2772	603	2	&	&	CCONJ
admet-2772	603	3	dmpk	dmpk	PROPN
admet-2772	603	4	13(3	13(3	NUM
admet-2772	603	5	)	)	PUNCT
admet-2772	603	6	(	(	PUNCT
admet-2772	603	7	2025	2025	NUM
admet-2772	603	8	)	)	PUNCT
admet-2772	603	9	2772	2772	NUM
admet-2772	603	10	machine	machine	NOUN
admet-2772	603	11	learning	learning	NOUN
admet-2772	603	12	models	model	NOUN
admet-2772	603	13	for	for	ADP
admet-2772	603	14	admet	admet	ADJ
admet-2772	603	15	prediction	prediction	NOUN
admet-2772	603	16	in	in	ADP
admet-2772	603	17	drug	drug	NOUN
admet-2772	603	18	development	development	NOUN
admet-2772	603	19	doi	doi	PROPN
admet-2772	603	20	:	:	PUNCT
admet-2772	603	21	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	603	22	23	23	NUM
admet-2772	603	23	11.3	11.3	NUM
admet-2772	603	24	.	.	PUNCT
admet-2772	604	1	potential	potential	NOUN
admet-2772	604	2	of	of	ADP
admet-2772	604	3	quantum	quantum	NOUN
admet-2772	604	4	computing	computing	NOUN
admet-2772	604	5	and	and	CCONJ
admet-2772	604	6	machine	machine	NOUN
admet-2772	604	7	learning	learn	VERB
admet-2772	604	8	recent	recent	ADJ
admet-2772	604	9	research	research	NOUN
admet-2772	604	10	explores	explore	VERB
admet-2772	604	11	the	the	DET
admet-2772	604	12	synergies	synergy	NOUN
admet-2772	604	13	between	between	ADP
admet-2772	604	14	quantum	quantum	NOUN
admet-2772	604	15	computing	computing	NOUN
admet-2772	604	16	,	,	PUNCT
admet-2772	604	17	ai	ai	VERB
admet-2772	604	18	and	and	CCONJ
admet-2772	604	19	ml	ml	NOUN
admet-2772	604	20	.	.	PUNCT
admet-2772	604	21	quantum	quantum	PROPN
admet-2772	604	22	computing	computing	NOUN
admet-2772	604	23	shows	show	VERB
admet-2772	604	24	significant	significant	ADJ
admet-2772	604	25	potential	potential	NOUN
admet-2772	604	26	in	in	ADP
admet-2772	604	27	revolutionizing	revolutionize	VERB
admet-2772	604	28	drug	drug	NOUN
admet-2772	604	29	discovery	discovery	NOUN
admet-2772	604	30	and	and	CCONJ
admet-2772	604	31	development	development	NOUN
admet-2772	604	32	.	.	PUNCT
admet-2772	605	1	it	it	PRON
admet-2772	605	2	offers	offer	VERB
admet-2772	605	3	faster	fast	ADJ
admet-2772	605	4	and	and	CCONJ
admet-2772	605	5	more	more	ADV
admet-2772	605	6	accurate	accurate	ADJ
admet-2772	605	7	molecular	molecular	ADJ
admet-2772	605	8	characterization	characterization	NOUN
admet-2772	605	9	through	through	ADP
admet-2772	605	10	quantum	quantum	ADJ
admet-2772	605	11	simulation	simulation	NOUN
admet-2772	605	12	,	,	PUNCT
admet-2772	605	13	outperforming	outperform	VERB
admet-2772	605	14	classical	classical	ADJ
admet-2772	605	15	quantum	quantum	ADJ
admet-2772	605	16	chemistry	chemistry	NOUN
admet-2772	605	17	methods	method	NOUN
admet-2772	605	18	[	[	X
admet-2772	605	19	239	239	NUM
admet-2772	605	20	]	]	PUNCT
admet-2772	605	21	.	.	PUNCT
admet-2772	606	1	quantum	quantum	ADJ
admet-2772	606	2	machine	machine	NOUN
admet-2772	606	3	learning	learning	NOUN
admet-2772	606	4	(	(	PUNCT
admet-2772	606	5	qml	qml	NOUN
admet-2772	606	6	)	)	PUNCT
admet-2772	606	7	algorithms	algorithm	NOUN
admet-2772	606	8	are	be	AUX
admet-2772	606	9	emerging	emerge	VERB
admet-2772	606	10	as	as	ADP
admet-2772	606	11	strong	strong	ADJ
admet-2772	606	12	competitors	competitor	NOUN
admet-2772	606	13	to	to	ADP
admet-2772	606	14	classical	classical	ADJ
admet-2772	606	15	approaches	approach	NOUN
admet-2772	606	16	,	,	PUNCT
admet-2772	606	17	particularly	particularly	ADV
admet-2772	606	18	in	in	ADP
admet-2772	606	19	the	the	DET
admet-2772	606	20	early	early	ADJ
admet-2772	606	21	stages	stage	NOUN
admet-2772	606	22	of	of	ADP
admet-2772	606	23	drug	drug	NOUN
admet-2772	606	24	discovery	discovery	NOUN
admet-2772	606	25	for	for	ADP
admet-2772	606	26	identifying	identify	VERB
admet-2772	606	27	novel	novel	ADJ
admet-2772	606	28	drug	drug	NOUN
admet-2772	606	29	-	-	PUNCT
admet-2772	606	30	like	like	ADJ
admet-2772	606	31	molecules	molecule	NOUN
admet-2772	606	32	[	[	X
admet-2772	606	33	240	240	NUM
admet-2772	606	34	]	]	PUNCT
admet-2772	606	35	.	.	PUNCT
admet-2772	607	1	qc	qc	PROPN
admet-2772	607	2	's	's	PART
admet-2772	607	3	ability	ability	NOUN
admet-2772	607	4	to	to	PART
admet-2772	607	5	perform	perform	VERB
admet-2772	607	6	complex	complex	ADJ
admet-2772	607	7	calculations	calculation	NOUN
admet-2772	607	8	efficiently	efficiently	ADV
admet-2772	607	9	could	could	AUX
admet-2772	607	10	accelerate	accelerate	VERB
admet-2772	607	11	the	the	DET
admet-2772	607	12	drug	drug	NOUN
admet-2772	607	13	discovery	discovery	NOUN
admet-2772	607	14	process	process	NOUN
admet-2772	607	15	,	,	PUNCT
admet-2772	607	16	making	make	VERB
admet-2772	607	17	it	it	PRON
admet-2772	607	18	more	more	ADV
admet-2772	607	19	cost	cost	NOUN
admet-2772	607	20	-	-	PUNCT
admet-2772	607	21	effective	effective	ADJ
admet-2772	607	22	and	and	CCONJ
admet-2772	607	23	accurate	accurate	ADJ
admet-2772	607	24	[	[	X
admet-2772	607	25	241	241	NUM
admet-2772	607	26	]	]	PUNCT
admet-2772	607	27	.	.	PUNCT
admet-2772	608	1	recent	recent	ADJ
admet-2772	608	2	applications	application	NOUN
admet-2772	608	3	of	of	ADP
admet-2772	608	4	qc	qc	PROPN
admet-2772	608	5	in	in	ADP
admet-2772	608	6	drug	drug	NOUN
admet-2772	608	7	development	development	NOUN
admet-2772	608	8	include	include	VERB
admet-2772	608	9	protein	protein	NOUN
admet-2772	608	10	structure	structure	NOUN
admet-2772	608	11	prediction	prediction	NOUN
admet-2772	608	12	,	,	PUNCT
admet-2772	608	13	molecular	molecular	ADJ
admet-2772	608	14	docking	docking	NOUN
admet-2772	608	15	,	,	PUNCT
admet-2772	608	16	quantum	quantum	NOUN
admet-2772	608	17	simulation	simulation	NOUN
admet-2772	608	18	,	,	PUNCT
admet-2772	608	19	and	and	CCONJ
admet-2772	608	20	quantitative	quantitative	ADJ
admet-2772	608	21	structureactivity	structureactivity	NOUN
admet-2772	608	22	relationship	relationship	NOUN
admet-2772	608	23	models	model	NOUN
admet-2772	608	24	[	[	X
admet-2772	608	25	242	242	NUM
admet-2772	608	26	]	]	PUNCT
admet-2772	608	27	.	.	PUNCT
admet-2772	609	1	while	while	SCONJ
admet-2772	609	2	current	current	ADJ
admet-2772	609	3	quantum	quantum	NOUN
admet-2772	609	4	devices	device	NOUN
admet-2772	609	5	are	be	AUX
admet-2772	609	6	still	still	ADV
admet-2772	609	7	susceptible	susceptible	ADJ
admet-2772	609	8	to	to	ADP
admet-2772	609	9	noise	noise	NOUN
admet-2772	609	10	and	and	CCONJ
admet-2772	609	11	errors	error	NOUN
admet-2772	609	12	,	,	PUNCT
admet-2772	609	13	hybrid	hybrid	ADJ
admet-2772	609	14	quantum	quantum	NOUN
admet-2772	609	15	-	-	PUNCT
admet-2772	609	16	classical	classical	ADJ
admet-2772	609	17	approaches	approach	NOUN
admet-2772	609	18	and	and	CCONJ
admet-2772	609	19	quantum	quantum	NOUN
admet-2772	609	20	-	-	PUNCT
admet-2772	609	21	inspired	inspire	VERB
admet-2772	609	22	devices	device	NOUN
admet-2772	609	23	like	like	ADP
admet-2772	609	24	quantum	quantum	NOUN
admet-2772	609	25	annealers	annealer	NOUN
admet-2772	609	26	have	have	AUX
admet-2772	609	27	demonstrated	demonstrate	VERB
admet-2772	609	28	quantum	quantum	ADJ
admet-2772	609	29	advantage	advantage	NOUN
admet-2772	609	30	[	[	X
admet-2772	609	31	242	242	NUM
admet-2772	609	32	]	]	PUNCT
admet-2772	609	33	.	.	PUNCT
admet-2772	610	1	further	further	ADJ
admet-2772	610	2	research	research	NOUN
admet-2772	610	3	and	and	CCONJ
admet-2772	610	4	development	development	NOUN
admet-2772	610	5	are	be	AUX
admet-2772	610	6	needed	need	VERB
admet-2772	610	7	to	to	PART
admet-2772	610	8	fully	fully	ADV
admet-2772	610	9	leverage	leverage	VERB
admet-2772	610	10	qc	qc	PROPN
admet-2772	610	11	's	's	PART
admet-2772	610	12	potential	potential	NOUN
admet-2772	610	13	in	in	ADP
admet-2772	610	14	drug	drug	NOUN
admet-2772	610	15	discovery	discovery	NOUN
admet-2772	611	1	[	[	X
admet-2772	611	2	241	241	NUM
admet-2772	611	3	]	]	PUNCT
admet-2772	611	4	.	.	PUNCT
admet-2772	612	1	11.4	11.4	NUM
admet-2772	612	2	.	.	PUNCT
admet-2772	613	1	regulatory	regulatory	ADJ
admet-2772	613	2	and	and	CCONJ
admet-2772	613	3	industry	industry	NOUN
admet-2772	613	4	trends	trend	NOUN
admet-2772	613	5	artificial	artificial	ADJ
admet-2772	613	6	intelligence	intelligence	NOUN
admet-2772	613	7	is	be	AUX
admet-2772	613	8	revolutionizing	revolutionize	VERB
admet-2772	613	9	drug	drug	NOUN
admet-2772	613	10	discovery	discovery	NOUN
admet-2772	613	11	and	and	CCONJ
admet-2772	613	12	preclinical	preclinical	ADJ
admet-2772	613	13	research	research	NOUN
admet-2772	613	14	by	by	ADP
admet-2772	613	15	integrating	integrate	VERB
admet-2772	613	16	with	with	ADP
admet-2772	613	17	experimental	experimental	ADJ
admet-2772	613	18	approaches	approach	NOUN
admet-2772	613	19	.	.	PUNCT
admet-2772	614	1	ai	ai	VERB
admet-2772	614	2	techniques	technique	NOUN
admet-2772	614	3	,	,	PUNCT
admet-2772	614	4	such	such	ADJ
admet-2772	614	5	as	as	ADP
admet-2772	614	6	machine	machine	NOUN
admet-2772	614	7	learning	learning	NOUN
admet-2772	614	8	and	and	CCONJ
admet-2772	614	9	neural	neural	ADJ
admet-2772	614	10	networks	network	NOUN
admet-2772	614	11	,	,	PUNCT
admet-2772	614	12	are	be	AUX
admet-2772	614	13	improving	improve	VERB
admet-2772	614	14	the	the	DET
admet-2772	614	15	efficiency	efficiency	NOUN
admet-2772	614	16	and	and	CCONJ
admet-2772	614	17	effectiveness	effectiveness	NOUN
admet-2772	614	18	of	of	ADP
admet-2772	614	19	drug	drug	NOUN
admet-2772	614	20	candidate	candidate	NOUN
admet-2772	614	21	identification	identification	NOUN
admet-2772	614	22	and	and	CCONJ
admet-2772	614	23	optimization	optimization	NOUN
admet-2772	614	24	[	[	X
admet-2772	614	25	243	243	NUM
admet-2772	614	26	]	]	PUNCT
admet-2772	614	27	.	.	PUNCT
admet-2772	615	1	the	the	DET
admet-2772	615	2	integration	integration	NOUN
admet-2772	615	3	of	of	ADP
admet-2772	615	4	virtual	virtual	ADJ
admet-2772	615	5	and	and	CCONJ
admet-2772	615	6	experimental	experimental	ADJ
admet-2772	615	7	screening	screening	NOUN
admet-2772	615	8	methods	method	NOUN
admet-2772	615	9	,	,	PUNCT
admet-2772	615	10	including	include	VERB
admet-2772	615	11	high	high	ADJ
admet-2772	615	12	-	-	PUNCT
admet-2772	615	13	throughput	throughput	NOUN
admet-2772	615	14	screening	screening	NOUN
admet-2772	615	15	and	and	CCONJ
admet-2772	615	16	dna	dna	NOUN
admet-2772	615	17	-	-	PUNCT
admet-2772	615	18	encoded	encode	VERB
admet-2772	615	19	libraries	library	NOUN
admet-2772	615	20	,	,	PUNCT
admet-2772	615	21	is	be	AUX
admet-2772	615	22	enhancing	enhance	VERB
admet-2772	615	23	early	early	ADJ
admet-2772	615	24	-	-	PUNCT
admet-2772	615	25	phase	phase	NOUN
admet-2772	615	26	drug	drug	NOUN
admet-2772	615	27	discovery	discovery	NOUN
admet-2772	616	1	[	[	X
admet-2772	616	2	243	243	NUM
admet-2772	616	3	]	]	PUNCT
admet-2772	616	4	.	.	PUNCT
admet-2772	617	1	ai	ai	AUX
admet-2772	617	2	combined	combine	VERB
admet-2772	617	3	with	with	ADP
admet-2772	617	4	new	new	ADJ
admet-2772	617	5	experimental	experimental	ADJ
admet-2772	617	6	technologies	technology	NOUN
admet-2772	617	7	is	be	AUX
admet-2772	617	8	expected	expect	VERB
admet-2772	617	9	to	to	PART
admet-2772	617	10	make	make	VERB
admet-2772	617	11	drug	drug	NOUN
admet-2772	617	12	discovery	discovery	NOUN
admet-2772	617	13	faster	fast	ADV
admet-2772	617	14	,	,	PUNCT
admet-2772	617	15	cheaper	cheap	ADJ
admet-2772	617	16	,	,	PUNCT
admet-2772	617	17	and	and	CCONJ
admet-2772	617	18	more	more	ADV
admet-2772	617	19	effective	effective	ADJ
admet-2772	617	20	[	[	X
admet-2772	617	21	244	244	NUM
admet-2772	617	22	]	]	PUNCT
admet-2772	617	23	.	.	PUNCT
admet-2772	618	1	additionally	additionally	ADV
admet-2772	618	2	,	,	PUNCT
admet-2772	618	3	integrated	integrate	VERB
admet-2772	618	4	approaches	approach	NOUN
admet-2772	618	5	to	to	ADP
admet-2772	618	6	testing	testing	NOUN
admet-2772	618	7	and	and	CCONJ
admet-2772	618	8	assessment	assessment	NOUN
admet-2772	618	9	(	(	PUNCT
admet-2772	618	10	iata	iata	PROPN
admet-2772	618	11	)	)	PUNCT
admet-2772	618	12	are	be	AUX
admet-2772	618	13	being	be	AUX
admet-2772	618	14	developed	develop	VERB
admet-2772	618	15	to	to	PART
admet-2772	618	16	replace	replace	VERB
admet-2772	618	17	animal	animal	NOUN
admet-2772	618	18	testing	testing	NOUN
admet-2772	618	19	in	in	ADP
admet-2772	618	20	toxicology	toxicology	NOUN
admet-2772	618	21	,	,	PUNCT
admet-2772	618	22	incorporating	incorporate	VERB
admet-2772	618	23	in	in	ADP
admet-2772	618	24	vitro	vitro	X
admet-2772	618	25	,	,	PUNCT
admet-2772	618	26	insilico	insilico	NOUN
admet-2772	618	27	,	,	PUNCT
admet-2772	618	28	and	and	CCONJ
admet-2772	618	29	in	in	ADP
admet-2772	618	30	vivo	vivo	ADJ
admet-2772	618	31	methods	method	NOUN
admet-2772	618	32	[	[	X
admet-2772	618	33	245	245	NUM
admet-2772	618	34	]	]	PUNCT
admet-2772	618	35	.	.	PUNCT
admet-2772	619	1	while	while	SCONJ
admet-2772	619	2	ai	ai	NOUN
admet-2772	619	3	-	-	PUNCT
admet-2772	619	4	driven	drive	VERB
admet-2772	619	5	approaches	approach	NOUN
admet-2772	619	6	offer	offer	VERB
admet-2772	619	7	significant	significant	ADJ
admet-2772	619	8	benefits	benefit	NOUN
admet-2772	619	9	,	,	PUNCT
admet-2772	619	10	challenges	challenge	NOUN
admet-2772	619	11	remain	remain	VERB
admet-2772	619	12	,	,	PUNCT
admet-2772	619	13	such	such	ADJ
admet-2772	619	14	as	as	ADP
admet-2772	619	15	the	the	DET
admet-2772	619	16	need	need	NOUN
admet-2772	619	17	for	for	ADP
admet-2772	619	18	high	high	ADJ
admet-2772	619	19	-	-	PUNCT
admet-2772	619	20	quality	quality	NOUN
admet-2772	619	21	databases	database	NOUN
admet-2772	619	22	and	and	CCONJ
admet-2772	619	23	addressing	address	VERB
admet-2772	619	24	regulatory	regulatory	ADJ
admet-2772	619	25	requirements	requirement	NOUN
admet-2772	619	26	[	[	X
admet-2772	619	27	245	245	NUM
admet-2772	619	28	]	]	PUNCT
admet-2772	619	29	.	.	PUNCT
admet-2772	620	1	12	12	NUM
admet-2772	620	2	.	.	PUNCT
admet-2772	621	1	conclusion	conclusion	VERB
admet-2772	621	2	the	the	DET
admet-2772	621	3	application	application	NOUN
admet-2772	621	4	of	of	ADP
admet-2772	621	5	artificial	artificial	ADJ
admet-2772	621	6	intelligence	intelligence	NOUN
admet-2772	621	7	and	and	CCONJ
admet-2772	621	8	machine	machine	NOUN
admet-2772	621	9	learning	learning	NOUN
admet-2772	621	10	in	in	ADP
admet-2772	621	11	absorption	absorption	NOUN
admet-2772	621	12	,	,	PUNCT
admet-2772	621	13	distribution	distribution	NOUN
admet-2772	621	14	,	,	PUNCT
admet-2772	621	15	metabolism	metabolism	NOUN
admet-2772	621	16	,	,	PUNCT
admet-2772	621	17	excretion	excretion	NOUN
admet-2772	621	18	and	and	CCONJ
admet-2772	621	19	toxicity	toxicity	NOUN
admet-2772	621	20	(	(	PUNCT
admet-2772	621	21	admet	admet	ADJ
admet-2772	621	22	)	)	PUNCT
admet-2772	621	23	predictions	prediction	NOUN
admet-2772	621	24	has	have	AUX
admet-2772	621	25	revolutionized	revolutionize	VERB
admet-2772	621	26	drug	drug	NOUN
admet-2772	621	27	discovery	discovery	NOUN
admet-2772	621	28	and	and	CCONJ
admet-2772	621	29	development	development	NOUN
admet-2772	621	30	.	.	PUNCT
admet-2772	622	1	traditional	traditional	ADJ
admet-2772	622	2	in	in	ADP
admet-2772	622	3	vitro	vitro	X
admet-2772	622	4	and	and	CCONJ
admet-2772	622	5	in	in	ADP
admet-2772	622	6	vivo	vivo	ADJ
admet-2772	622	7	approaches	approach	NOUN
admet-2772	622	8	,	,	PUNCT
admet-2772	622	9	though	though	SCONJ
admet-2772	622	10	essential	essential	ADJ
admet-2772	622	11	,	,	PUNCT
admet-2772	622	12	are	be	AUX
admet-2772	622	13	often	often	ADV
admet-2772	622	14	time	time	NOUN
admet-2772	622	15	-	-	PUNCT
admet-2772	622	16	consuming	consume	VERB
admet-2772	622	17	,	,	PUNCT
admet-2772	622	18	costly	costly	ADJ
admet-2772	622	19	,	,	PUNCT
admet-2772	622	20	and	and	CCONJ
admet-2772	622	21	sometimes	sometimes	ADV
admet-2772	622	22	unreliable	unreliable	ADJ
admet-2772	622	23	in	in	ADP
admet-2772	622	24	predicting	predict	VERB
admet-2772	622	25	human	human	ADJ
admet-2772	622	26	responses	response	NOUN
admet-2772	622	27	.	.	PUNCT
admet-2772	623	1	ai	ai	VERB
admet-2772	623	2	and	and	CCONJ
admet-2772	623	3	ml	ml	NOUN
admet-2772	623	4	-	-	PUNCT
admet-2772	623	5	driven	drive	VERB
admet-2772	623	6	computational	computational	ADJ
admet-2772	623	7	methods	method	NOUN
admet-2772	623	8	provide	provide	VERB
admet-2772	623	9	a	a	DET
admet-2772	623	10	faster	fast	ADJ
admet-2772	623	11	,	,	PUNCT
admet-2772	623	12	more	more	ADV
admet-2772	623	13	accurate	accurate	ADJ
admet-2772	623	14	,	,	PUNCT
admet-2772	623	15	and	and	CCONJ
admet-2772	623	16	cost	cost	NOUN
admet-2772	623	17	-	-	PUNCT
admet-2772	623	18	effective	effective	ADJ
admet-2772	623	19	alternative	alternative	NOUN
admet-2772	623	20	by	by	ADP
admet-2772	623	21	leveraging	leverage	VERB
admet-2772	623	22	large	large	ADJ
admet-2772	623	23	-	-	PUNCT
admet-2772	623	24	scale	scale	NOUN
admet-2772	623	25	datasets	dataset	NOUN
admet-2772	623	26	and	and	CCONJ
admet-2772	623	27	predictive	predictive	ADJ
admet-2772	623	28	modelling	modelling	NOUN
admet-2772	623	29	techniques	technique	NOUN
admet-2772	623	30	such	such	ADJ
admet-2772	623	31	as	as	ADP
admet-2772	623	32	deep	deep	ADJ
admet-2772	623	33	learning	learning	NOUN
admet-2772	623	34	,	,	PUNCT
admet-2772	623	35	support	support	VERB
admet-2772	623	36	vector	vector	NOUN
admet-2772	623	37	machines	machine	NOUN
admet-2772	623	38	,	,	PUNCT
admet-2772	623	39	and	and	CCONJ
admet-2772	623	40	ensemble	ensemble	ADJ
admet-2772	623	41	learning	learning	NOUN
admet-2772	623	42	.	.	PUNCT
admet-2772	624	1	molecular	molecular	ADJ
admet-2772	624	2	descriptors	descriptor	NOUN
admet-2772	624	3	,	,	PUNCT
admet-2772	624	4	ranging	range	VERB
admet-2772	624	5	from	from	ADP
admet-2772	624	6	0d	0d	NUM
admet-2772	624	7	to	to	ADP
admet-2772	624	8	4d	4d	NUM
admet-2772	624	9	,	,	PUNCT
admet-2772	624	10	alongside	alongside	ADP
admet-2772	624	11	feature	feature	NOUN
admet-2772	624	12	selection	selection	NOUN
admet-2772	624	13	methods	method	NOUN
admet-2772	624	14	like	like	ADP
admet-2772	624	15	filter	filter	NOUN
admet-2772	624	16	,	,	PUNCT
admet-2772	624	17	wrapper	wrapper	NOUN
admet-2772	624	18	,	,	PUNCT
admet-2772	624	19	and	and	CCONJ
admet-2772	624	20	embedded	embed	VERB
admet-2772	624	21	techniques	technique	NOUN
admet-2772	624	22	,	,	PUNCT
admet-2772	624	23	play	play	VERB
admet-2772	624	24	a	a	DET
admet-2772	624	25	crucial	crucial	ADJ
admet-2772	624	26	role	role	NOUN
admet-2772	624	27	in	in	ADP
admet-2772	624	28	refining	refining	NOUN
admet-2772	624	29	model	model	NOUN
admet-2772	624	30	accuracy	accuracy	NOUN
admet-2772	624	31	and	and	CCONJ
admet-2772	624	32	interpretability	interpretability	NOUN
admet-2772	624	33	.	.	PUNCT
admet-2772	625	1	these	these	DET
admet-2772	625	2	advancements	advancement	NOUN
admet-2772	625	3	facilitate	facilitate	VERB
admet-2772	625	4	high	high	ADJ
admet-2772	625	5	-	-	PUNCT
admet-2772	625	6	throughput	throughput	NOUN
admet-2772	625	7	virtual	virtual	ADJ
admet-2772	625	8	screening	screening	NOUN
admet-2772	625	9	,	,	PUNCT
admet-2772	625	10	enabling	enable	VERB
admet-2772	625	11	the	the	DET
admet-2772	625	12	early	early	ADJ
admet-2772	625	13	identification	identification	NOUN
admet-2772	625	14	of	of	ADP
admet-2772	625	15	drug	drug	NOUN
admet-2772	625	16	candidates	candidate	NOUN
admet-2772	625	17	with	with	ADP
admet-2772	625	18	favourable	favourable	ADJ
admet-2772	625	19	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	625	20	and	and	CCONJ
admet-2772	625	21	toxicity	toxicity	NOUN
admet-2772	625	22	profiles	profile	NOUN
admet-2772	625	23	,	,	PUNCT
admet-2772	625	24	thereby	thereby	ADV
admet-2772	625	25	reducing	reduce	VERB
admet-2772	625	26	the	the	DET
admet-2772	625	27	likelihood	likelihood	NOUN
admet-2772	625	28	of	of	ADP
admet-2772	625	29	latestage	latestage	NOUN
admet-2772	625	30	failures	failure	NOUN
admet-2772	625	31	.	.	PUNCT
admet-2772	626	1	additionally	additionally	ADV
admet-2772	626	2	,	,	PUNCT
admet-2772	626	3	deep	deep	ADJ
admet-2772	626	4	learning	learning	NOUN
admet-2772	626	5	architectures	architecture	NOUN
admet-2772	626	6	have	have	AUX
admet-2772	626	7	shown	show	VERB
admet-2772	626	8	significant	significant	ADJ
admet-2772	626	9	promise	promise	NOUN
admet-2772	626	10	in	in	ADP
admet-2772	626	11	predicting	predict	VERB
admet-2772	626	12	complex	complex	ADJ
admet-2772	626	13	metabolic	metabolic	NOUN
admet-2772	626	14	and	and	CCONJ
admet-2772	626	15	toxicity	toxicity	NOUN
admet-2772	626	16	pathways	pathway	NOUN
admet-2772	626	17	.	.	PUNCT
admet-2772	627	1	however	however	ADV
admet-2772	627	2	,	,	PUNCT
admet-2772	627	3	challenges	challenge	NOUN
admet-2772	627	4	persist	persist	VERB
admet-2772	627	5	,	,	PUNCT
admet-2772	627	6	including	include	VERB
admet-2772	627	7	data	datum	NOUN
admet-2772	627	8	quality	quality	NOUN
admet-2772	627	9	,	,	PUNCT
admet-2772	627	10	model	model	NOUN
admet-2772	627	11	generalizability	generalizability	NOUN
admet-2772	627	12	,	,	PUNCT
admet-2772	627	13	and	and	CCONJ
admet-2772	627	14	regulatory	regulatory	ADJ
admet-2772	627	15	acceptance	acceptance	NOUN
admet-2772	627	16	.	.	PUNCT
admet-2772	628	1	standardized	standardized	ADJ
admet-2772	628	2	datasets	dataset	NOUN
admet-2772	628	3	,	,	PUNCT
admet-2772	628	4	improved	improve	VERB
admet-2772	628	5	interpretability	interpretability	NOUN
admet-2772	628	6	of	of	ADP
admet-2772	628	7	ai	ai	NOUN
admet-2772	628	8	models	model	NOUN
admet-2772	628	9	,	,	PUNCT
admet-2772	628	10	and	and	CCONJ
admet-2772	628	11	rigorous	rigorous	ADJ
admet-2772	628	12	validation	validation	NOUN
admet-2772	628	13	protocols	protocol	NOUN
admet-2772	628	14	are	be	AUX
admet-2772	628	15	necessary	necessary	ADJ
admet-2772	628	16	for	for	ADP
admet-2772	628	17	broader	broad	ADJ
admet-2772	628	18	adoption	adoption	NOUN
admet-2772	628	19	.	.	PUNCT
admet-2772	629	1	regulatory	regulatory	ADJ
admet-2772	629	2	agencies	agency	NOUN
admet-2772	629	3	must	must	AUX
admet-2772	629	4	establish	establish	VERB
admet-2772	629	5	clear	clear	ADJ
admet-2772	629	6	guidelines	guideline	NOUN
admet-2772	629	7	for	for	ADP
admet-2772	629	8	integrating	integrate	VERB
admet-2772	629	9	ai	ai	VERB
admet-2772	629	10	-	-	PUNCT
admet-2772	629	11	driven	drive	VERB
admet-2772	629	12	admet	admet	NOUN
admet-2772	629	13	predictions	prediction	NOUN
admet-2772	629	14	into	into	ADP
admet-2772	629	15	drug	drug	NOUN
admet-2772	629	16	development	development	NOUN
admet-2772	629	17	workflows	workflow	NOUN
admet-2772	629	18	.	.	PUNCT
admet-2772	630	1	moving	move	VERB
admet-2772	630	2	forward	forward	ADV
admet-2772	630	3	,	,	PUNCT
admet-2772	630	4	integrating	integrate	VERB
admet-2772	630	5	ai	ai	ADJ
admet-2772	630	6	-	-	PUNCT
admet-2772	630	7	driven	drive	VERB
admet-2772	630	8	predictions	prediction	NOUN
admet-2772	630	9	with	with	ADP
admet-2772	630	10	experimental	experimental	ADJ
admet-2772	630	11	validation	validation	NOUN
admet-2772	630	12	will	will	AUX
admet-2772	630	13	be	be	AUX
admet-2772	630	14	key	key	ADJ
admet-2772	630	15	to	to	ADP
admet-2772	630	16	optimizing	optimize	VERB
admet-2772	630	17	drug	drug	NOUN
admet-2772	630	18	development	development	NOUN
admet-2772	630	19	pipelines	pipeline	NOUN
admet-2772	630	20	.	.	PUNCT
admet-2772	631	1	by	by	ADP
admet-2772	631	2	overcoming	overcome	VERB
admet-2772	631	3	current	current	ADJ
admet-2772	631	4	limitations	limitation	NOUN
admet-2772	631	5	and	and	CCONJ
admet-2772	631	6	fostering	foster	VERB
admet-2772	631	7	collaboration	collaboration	NOUN
admet-2772	631	8	between	between	ADP
admet-2772	631	9	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	631	10	m.	m.	NOUN
admet-2772	631	11	venkataraman	venkataraman	PROPN
admet-2772	631	12	et	et	PROPN
admet-2772	631	13	al	al	PROPN
admet-2772	631	14	.	.	PROPN
admet-2772	631	15	admet	admet	PROPN
admet-2772	631	16	&	&	CCONJ
admet-2772	631	17	dmpk	dmpk	PROPN
admet-2772	631	18	13(3	13(3	NUM
admet-2772	631	19	)	)	PUNCT
admet-2772	631	20	(	(	PUNCT
admet-2772	631	21	2025	2025	NUM
admet-2772	631	22	)	)	PUNCT
admet-2772	631	23	2772	2772	NUM
admet-2772	631	24	24	24	NUM
admet-2772	631	25	computational	computational	ADJ
admet-2772	631	26	and	and	CCONJ
admet-2772	631	27	experimental	experimental	ADJ
admet-2772	631	28	research	research	NOUN
admet-2772	631	29	,	,	PUNCT
admet-2772	631	30	ai	ai	VERB
admet-2772	631	31	and	and	CCONJ
admet-2772	631	32	ml	ml	ADV
admet-2772	631	33	can	can	AUX
admet-2772	631	34	drive	drive	VERB
admet-2772	631	35	more	more	ADV
admet-2772	631	36	efficient	efficient	ADJ
admet-2772	631	37	,	,	PUNCT
admet-2772	631	38	precise	precise	ADJ
admet-2772	631	39	,	,	PUNCT
admet-2772	631	40	and	and	CCONJ
admet-2772	631	41	cost	cost	NOUN
admet-2772	631	42	-	-	PUNCT
admet-2772	631	43	effective	effective	ADJ
admet-2772	631	44	drug	drug	NOUN
admet-2772	631	45	discovery	discovery	NOUN
admet-2772	631	46	,	,	PUNCT
admet-2772	631	47	ultimately	ultimately	ADV
admet-2772	631	48	leading	lead	VERB
admet-2772	631	49	to	to	ADP
admet-2772	631	50	safer	safe	ADJ
admet-2772	631	51	and	and	CCONJ
admet-2772	631	52	more	more	ADV
admet-2772	631	53	effective	effective	ADJ
admet-2772	631	54	therapeutics	therapeutic	NOUN
admet-2772	631	55	.	.	PUNCT
admet-2772	632	1	abbreviations	abbreviation	NOUN
admet-2772	632	2	admet	admet	NOUN
admet-2772	632	3	:	:	PUNCT
admet-2772	633	1	absorption	absorption	NOUN
admet-2772	633	2	,	,	PUNCT
admet-2772	633	3	distribution	distribution	NOUN
admet-2772	633	4	,	,	PUNCT
admet-2772	633	5	metabolism	metabolism	NOUN
admet-2772	633	6	,	,	PUNCT
admet-2772	633	7	excretion	excretion	NOUN
admet-2772	633	8	and	and	CCONJ
admet-2772	633	9	toxicity	toxicity	NOUN
admet-2772	633	10	adrs	adr	NOUN
admet-2772	633	11	:	:	PUNCT
admet-2772	633	12	adverse	adverse	ADJ
admet-2772	633	13	drug	drug	NOUN
admet-2772	633	14	reactions	reaction	NOUN
admet-2772	633	15	ann	ann	PROPN
admet-2772	633	16	:	:	PUNCT
admet-2772	633	17	artificial	artificial	ADJ
admet-2772	633	18	neural	neural	ADJ
admet-2772	633	19	network	network	NOUN
admet-2772	633	20	avb	avb	PROPN
admet-2772	633	21	:	:	PUNCT
admet-2772	633	22	adversarial	adversarial	ADJ
admet-2772	633	23	variational	variational	ADJ
admet-2772	633	24	bayes	bayes	PROPN
admet-2772	633	25	ba	ba	PROPN
admet-2772	633	26	:	:	PUNCT
admet-2772	633	27	bioavailability	bioavailability	NOUN
admet-2772	633	28	bbb	bbb	PROPN
admet-2772	633	29	:	:	PUNCT
admet-2772	633	30	blood	blood	NOUN
admet-2772	633	31	brain	brain	NOUN
admet-2772	633	32	barrier	barrier	NOUN
admet-2772	633	33	bert	bert	PROPN
admet-2772	633	34	:	:	PUNCT
admet-2772	633	35	bidirectional	bidirectional	ADJ
admet-2772	633	36	encoder	encoder	NOUN
admet-2772	633	37	representations	representation	VERB
admet-2772	633	38	from	from	ADP
admet-2772	633	39	transformers	transformer	NOUN
admet-2772	633	40	cfs	cfs	PROPN
admet-2772	633	41	:	:	PUNCT
admet-2772	633	42	correlation	correlation	NOUN
admet-2772	633	43	-	-	PUNCT
admet-2772	633	44	based	base	VERB
admet-2772	633	45	feature	feature	NOUN
admet-2772	633	46	selection	selection	NOUN
admet-2772	633	47	cl	cl	NOUN
admet-2772	633	48	:	:	PUNCT
admet-2772	633	49	clearance	clearance	NOUN
admet-2772	633	50	cnns	cnn	NOUN
admet-2772	633	51	:	:	PUNCT
admet-2772	633	52	convolutional	convolutional	ADJ
admet-2772	633	53	neural	neural	ADJ
admet-2772	633	54	networks	network	NOUN
admet-2772	633	55	cyp	cyp	ADJ
admet-2772	633	56	:	:	PUNCT
admet-2772	633	57	cytochrome	cytochrome	NOUN
admet-2772	633	58	ddis	ddis	NOUN
admet-2772	633	59	:	:	PUNCT
admet-2772	633	60	drug	drug	NOUN
admet-2772	633	61	-	-	PUNCT
admet-2772	633	62	drug	drug	NOUN
admet-2772	633	63	interactions	interaction	NOUN
admet-2772	633	64	dels	del	NOUN
admet-2772	633	65	:	:	PUNCT
admet-2772	633	66	dna	dna	NOUN
admet-2772	633	67	-	-	PUNCT
admet-2772	633	68	encoded	encode	VERB
admet-2772	633	69	libraries	library	NOUN
admet-2772	633	70	dili	dili	PROPN
admet-2772	633	71	:	:	PUNCT
admet-2772	633	72	drug	drug	NOUN
admet-2772	633	73	-	-	PUNCT
admet-2772	633	74	induced	induce	VERB
admet-2772	633	75	liver	liver	NOUN
admet-2772	633	76	injuries	injury	NOUN
admet-2772	633	77	dnn	dnn	PROPN
admet-2772	633	78	:	:	PUNCT
admet-2772	633	79	deep	deep	ADJ
admet-2772	633	80	neural	neural	ADJ
admet-2772	633	81	network	network	NOUN
admet-2772	633	82	erα	erα	NOUN
admet-2772	633	83	:	:	PUNCT
admet-2772	633	84	estrogen	estrogen	NOUN
admet-2772	633	85	receptor	receptor	NOUN
admet-2772	633	86	alpha	alpha	NOUN
admet-2772	633	87	fcnns	fcnn	NOUN
admet-2772	633	88	:	:	PUNCT
admet-2772	633	89	fully	fully	ADV
admet-2772	633	90	connected	connected	ADJ
admet-2772	633	91	neural	neural	ADJ
admet-2772	633	92	networks	network	NOUN
admet-2772	633	93	fu	fu	NOUN
admet-2772	633	94	:	:	PUNCT
admet-2772	633	95	unbound	unbound	NOUN
admet-2772	633	96	fraction	fraction	NOUN
admet-2772	633	97	gans	gan	NOUN
admet-2772	633	98	:	:	PUNCT
admet-2772	633	99	generative	generative	ADJ
admet-2772	633	100	adversarial	adversarial	ADJ
admet-2772	633	101	networks	network	NOUN
admet-2772	633	102	gnns	gnns	NOUN
admet-2772	633	103	:	:	PUNCT
admet-2772	633	104	graph	graph	NOUN
admet-2772	633	105	neural	neural	ADJ
admet-2772	633	106	networks	network	NOUN
admet-2772	633	107	iata	iata	PROPN
admet-2772	633	108	:	:	PUNCT
admet-2772	633	109	integrated	integrate	VERB
admet-2772	633	110	approaches	approach	NOUN
admet-2772	633	111	to	to	ADP
admet-2772	633	112	testing	testing	NOUN
admet-2772	633	113	and	and	CCONJ
admet-2772	633	114	assessment	assessment	NOUN
admet-2772	633	115	ivive	ivive	ADJ
admet-2772	633	116	:	:	PUNCT
admet-2772	633	117	in	in	ADP
admet-2772	633	118	vitro	vitro	NOUN
admet-2772	633	119	-	-	PUNCT
admet-2772	633	120	in	in	ADP
admet-2772	633	121	vivo	vivo	ADJ
admet-2772	633	122	extrapolation	extrapolation	NOUN
admet-2772	633	123	ke	ke	NOUN
admet-2772	633	124	:	:	PUNCT
admet-2772	633	125	elimination	elimination	NOUN
admet-2772	633	126	rate	rate	NOUN
admet-2772	633	127	constant	constant	ADJ
admet-2772	633	128	k	k	PROPN
admet-2772	633	129	-	-	PUNCT
admet-2772	633	130	nn	nn	ADJ
admet-2772	633	131	:	:	PUNCT
admet-2772	633	132	k	k	ADJ
admet-2772	633	133	-	-	PUNCT
admet-2772	633	134	nearest	near	ADJ
admet-2772	633	135	neighbours	neighbour	NOUN
admet-2772	633	136	lstm	lstm	NOUN
admet-2772	633	137	:	:	PUNCT
admet-2772	633	138	long	long	ADJ
admet-2772	633	139	short	short	ADJ
admet-2772	633	140	-	-	PUNCT
admet-2772	633	141	term	term	NOUN
admet-2772	633	142	memory	memory	NOUN
admet-2772	633	143	md	md	PROPN
admet-2772	633	144	:	:	PUNCT
admet-2772	633	145	molecular	molecular	ADJ
admet-2772	633	146	descriptors	descriptor	NOUN
admet-2772	633	147	ml	ml	VERB
admet-2772	633	148	:	:	PUNCT
admet-2772	633	149	machine	machine	NOUN
admet-2772	633	150	learning	learn	VERB
admet-2772	633	151	mtl	mtl	PROPN
admet-2772	633	152	:	:	PUNCT
admet-2772	633	153	multi	multi	ADJ
admet-2772	633	154	-	-	NOUN
admet-2772	633	155	task	task	ADJ
admet-2772	633	156	learning	learn	VERB
admet-2772	633	157	nn	nn	PROPN
admet-2772	633	158	:	:	PUNCT
admet-2772	633	159	neural	neural	ADJ
admet-2772	633	160	network	network	NOUN
admet-2772	633	161	pbpk	pbpk	NOUN
admet-2772	633	162	:	:	PUNCT
admet-2772	633	163	physiologically	physiologically	ADV
admet-2772	633	164	-	-	PUNCT
admet-2772	633	165	based	base	VERB
admet-2772	633	166	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	633	167	pfas	pfas	NOUN
admet-2772	633	168	:	:	PUNCT
admet-2772	633	169	polyfluorinated	polyfluorinate	VERB
admet-2772	633	170	alkyl	alkyl	NOUN
admet-2772	633	171	substances	substance	NOUN
admet-2772	633	172	pk	pk	NOUN
admet-2772	633	173	:	:	PUNCT
admet-2772	633	174	pharmacokinetics	pharmacokinetic	NOUN
admet-2772	633	175	ps	ps	NOUN
admet-2772	633	176	:	:	PUNCT
admet-2772	633	177	permeability	permeability	NOUN
admet-2772	633	178	-	-	PUNCT
admet-2772	633	179	surface	surface	NOUN
admet-2772	633	180	qml	qml	NOUN
admet-2772	633	181	:	:	PUNCT
admet-2772	633	182	quantum	quantum	ADJ
admet-2772	633	183	machine	machine	NOUN
admet-2772	633	184	learning	learn	VERB
admet-2772	633	185	qsar	qsar	NOUN
admet-2772	633	186	:	:	PUNCT
admet-2772	633	187	quantitative	quantitative	ADJ
admet-2772	633	188	structure	structure	NOUN
admet-2772	633	189	-	-	PUNCT
admet-2772	633	190	activity	activity	NOUN
admet-2772	633	191	relationship	relationship	NOUN
admet-2772	633	192	rbf	rbf	PROPN
admet-2772	633	193	:	:	PUNCT
admet-2772	633	194	radial	radial	ADJ
admet-2772	633	195	basis	basis	NOUN
admet-2772	633	196	function	function	NOUN
admet-2772	633	197	rf	rf	ADJ
admet-2772	633	198	:	:	PUNCT
admet-2772	633	199	random	random	ADJ
admet-2772	633	200	forest	forest	NOUN
admet-2772	633	201	rnns	rnn	NOUN
admet-2772	633	202	:	:	PUNCT
admet-2772	633	203	recurrent	recurrent	ADJ
admet-2772	633	204	neural	neural	ADJ
admet-2772	633	205	networks	network	NOUN
admet-2772	633	206	svm	svm	VERB
admet-2772	633	207	:	:	PUNCT
admet-2772	633	208	support	support	NOUN
admet-2772	633	209	vector	vector	NOUN
admet-2772	633	210	machines	machine	NOUN
admet-2772	633	211	vaes	vaes	ADJ
admet-2772	633	212	:	:	PUNCT
admet-2772	633	213	variational	variational	ADJ
admet-2772	633	214	autoencoders	autoencoder	NOUN
admet-2772	633	215	vd	vd	NOUN
admet-2772	633	216	:	:	PUNCT
admet-2772	633	217	volume	volume	NOUN
admet-2772	633	218	of	of	ADP
admet-2772	633	219	distribution	distribution	NOUN
admet-2772	633	220	xai	xai	NOUN
admet-2772	633	221	:	:	PUNCT
admet-2772	633	222	explainable	explainable	ADJ
admet-2772	633	223	artificial	artificial	ADJ
admet-2772	633	224	intelligence	intelligence	NOUN
admet-2772	633	225	conflict	conflict	NOUN
admet-2772	633	226	of	of	ADP
admet-2772	633	227	interest	interest	NOUN
admet-2772	633	228	:	:	PUNCT
admet-2772	633	229	the	the	DET
admet-2772	633	230	authors	author	NOUN
admet-2772	633	231	declare	declare	VERB
admet-2772	633	232	no	no	DET
admet-2772	633	233	conflicts	conflict	NOUN
admet-2772	633	234	of	of	ADP
admet-2772	633	235	interest	interest	NOUN
admet-2772	633	236	related	relate	VERB
admet-2772	633	237	to	to	ADP
admet-2772	633	238	this	this	DET
admet-2772	633	239	review	review	NOUN
admet-2772	633	240	article	article	NOUN
admet-2772	633	241	.	.	PUNCT
admet-2772	634	1	author	author	NOUN
admet-2772	634	2	contributions	contribution	NOUN
admet-2772	634	3	:	:	PUNCT
admet-2772	634	4	all	all	DET
admet-2772	634	5	authors	author	NOUN
admet-2772	634	6	contributed	contribute	VERB
admet-2772	634	7	to	to	ADP
admet-2772	634	8	the	the	DET
admet-2772	634	9	study	study	NOUN
admet-2772	634	10	conception	conception	NOUN
admet-2772	634	11	and	and	CCONJ
admet-2772	634	12	design	design	NOUN
admet-2772	634	13	.	.	PUNCT
admet-2772	635	1	material	material	NOUN
admet-2772	635	2	preparation	preparation	NOUN
admet-2772	635	3	,	,	PUNCT
admet-2772	635	4	data	data	NOUN
admet-2772	635	5	collection	collection	NOUN
admet-2772	635	6	,	,	PUNCT
admet-2772	635	7	and	and	CCONJ
admet-2772	635	8	analysis	analysis	NOUN
admet-2772	635	9	were	be	AUX
admet-2772	635	10	performed	perform	VERB
admet-2772	635	11	by	by	ADP
admet-2772	635	12	gopi	gopi	PROPN
admet-2772	635	13	chand	chand	PROPN
admet-2772	635	14	rao	rao	PROPN
admet-2772	635	15	,	,	PUNCT
admet-2772	635	16	jeevan	jeevan	PROPN
admet-2772	635	17	karthik	karthik	PROPN
admet-2772	635	18	madavareddi	madavareddi	PROPN
admet-2772	635	19	,	,	PUNCT
admet-2772	635	20	and	and	CCONJ
admet-2772	635	21	magesh	magesh	PROPN
admet-2772	635	22	venkataraman	venkataraman	PROPN
admet-2772	635	23	.	.	PUNCT
admet-2772	636	1	magesh	magesh	PROPN
admet-2772	636	2	venkataraman	venkataraman	NOUN
admet-2772	636	3	also	also	ADV
admet-2772	636	4	contributed	contribute	VERB
admet-2772	636	5	to	to	ADP
admet-2772	636	6	methodology	methodology	NOUN
admet-2772	636	7	development	development	NOUN
admet-2772	636	8	and	and	CCONJ
admet-2772	636	9	project	project	NOUN
admet-2772	636	10	administration	administration	NOUN
admet-2772	636	11	.	.	PUNCT
admet-2772	637	1	srinivas	srinivas	PROPN
admet-2772	637	2	rao	rao	PROPN
admet-2772	637	3	maddi	maddi	PROPN
admet-2772	637	4	and	and	CCONJ
admet-2772	637	5	magesh	magesh	PROPN
admet-2772	637	6	venkataraman	venkataraman	NOUN
admet-2772	637	7	supervised	supervise	VERB
admet-2772	637	8	the	the	DET
admet-2772	637	9	study	study	NOUN
admet-2772	637	10	and	and	CCONJ
admet-2772	637	11	contributed	contribute	VERB
admet-2772	637	12	to	to	ADP
admet-2772	637	13	the	the	DET
admet-2772	637	14	review	review	NOUN
admet-2772	637	15	and	and	CCONJ
admet-2772	637	16	editing	editing	NOUN
admet-2772	637	17	of	of	ADP
admet-2772	637	18	the	the	DET
admet-2772	637	19	manuscript	manuscript	NOUN
admet-2772	637	20	.	.	PUNCT
admet-2772	638	1	the	the	DET
admet-2772	638	2	original	original	ADJ
admet-2772	638	3	draft	draft	NOUN
admet-2772	638	4	was	be	AUX
admet-2772	638	5	written	write	VERB
admet-2772	638	6	by	by	ADP
admet-2772	638	7	magesh	magesh	PROPN
admet-2772	638	8	venkataraman	venkataraman	PROPN
admet-2772	638	9	,	,	PUNCT
admet-2772	638	10	gopi	gopi	PROPN
admet-2772	638	11	chand	chand	PROPN
admet-2772	638	12	rao	rao	PROPN
admet-2772	638	13	,	,	PUNCT
admet-2772	638	14	and	and	CCONJ
admet-2772	638	15	jeevan	jeevan	PROPN
admet-2772	638	16	karthik	karthik	PROPN
admet-2772	638	17	madavareddi	madavareddi	PROPN
admet-2772	638	18	.	.	PUNCT
admet-2772	639	1	all	all	DET
admet-2772	639	2	authors	author	NOUN
admet-2772	639	3	read	read	VERB
admet-2772	639	4	and	and	CCONJ
admet-2772	639	5	approved	approve	VERB
admet-2772	639	6	the	the	DET
admet-2772	639	7	final	final	ADJ
admet-2772	639	8	manuscript	manuscript	NOUN
admet-2772	639	9	.	.	PUNCT
admet-2772	640	1	funding	funding	NOUN
admet-2772	640	2	sources	source	NOUN
admet-2772	640	3	:	:	PUNCT
admet-2772	640	4	this	this	DET
admet-2772	640	5	research	research	NOUN
admet-2772	640	6	did	do	AUX
admet-2772	640	7	not	not	PART
admet-2772	640	8	receive	receive	VERB
admet-2772	640	9	any	any	DET
admet-2772	640	10	specific	specific	ADJ
admet-2772	640	11	grant	grant	NOUN
admet-2772	640	12	from	from	ADP
admet-2772	640	13	funding	fund	VERB
admet-2772	640	14	agencies	agency	NOUN
admet-2772	640	15	in	in	ADP
admet-2772	640	16	the	the	DET
admet-2772	640	17	public	public	ADJ
admet-2772	640	18	,	,	PUNCT
admet-2772	640	19	commercial	commercial	ADJ
admet-2772	640	20	,	,	PUNCT
admet-2772	640	21	or	or	CCONJ
admet-2772	640	22	not	not	PART
admet-2772	640	23	-	-	PUNCT
admet-2772	640	24	for	for	ADP
admet-2772	640	25	-	-	PUNCT
admet-2772	640	26	profit	profit	NOUN
admet-2772	640	27	sectors	sector	NOUN
admet-2772	640	28	.	.	PUNCT
admet-2772	641	1	references	reference	NOUN
admet-2772	641	2	[	[	X
admet-2772	641	3	1	1	NUM
admet-2772	641	4	]	]	X
admet-2772	641	5	n.	n.	PROPN
admet-2772	641	6	berdigaliyev	berdigaliyev	PROPN
admet-2772	641	7	,	,	PUNCT
admet-2772	641	8	m.	m.	NOUN
admet-2772	641	9	aljofan	aljofan	PROPN
admet-2772	641	10	.	.	PUNCT
admet-2772	642	1	an	an	DET
admet-2772	642	2	overview	overview	NOUN
admet-2772	642	3	of	of	ADP
admet-2772	642	4	drug	drug	NOUN
admet-2772	642	5	discovery	discovery	NOUN
admet-2772	642	6	and	and	CCONJ
admet-2772	642	7	development	development	NOUN
admet-2772	642	8	.	.	PUNCT
admet-2772	643	1	future	future	ADJ
admet-2772	643	2	medicinal	medicinal	ADJ
admet-2772	643	3	chemistry	chemistry	NOUN
admet-2772	643	4	12	12	NUM
admet-2772	643	5	(	(	PUNCT
admet-2772	643	6	2020	2020	NUM
admet-2772	643	7	)	)	PUNCT
admet-2772	643	8	939	939	NUM
admet-2772	643	9	-	-	SYM
admet-2772	643	10	947	947	NUM
admet-2772	643	11	.	.	PUNCT
admet-2772	644	1	https://doi.org/10.4155/fmc-2019-0307	https://doi.org/10.4155/fmc-2019-0307	NOUN
admet-2772	645	1	[	[	X
admet-2772	645	2	2	2	NUM
admet-2772	645	3	]	]	PUNCT
admet-2772	646	1	z.	z.	PROPN
admet-2772	646	2	pei	pei	PROPN
admet-2772	646	3	.	.	PUNCT
admet-2772	647	1	computer	computer	NOUN
admet-2772	647	2	-	-	PUNCT
admet-2772	647	3	aided	aid	VERB
admet-2772	647	4	drug	drug	NOUN
admet-2772	647	5	discovery	discovery	NOUN
admet-2772	647	6	:	:	PUNCT
admet-2772	647	7	from	from	ADP
admet-2772	647	8	traditional	traditional	ADJ
admet-2772	647	9	simulation	simulation	NOUN
admet-2772	647	10	methods	method	NOUN
admet-2772	647	11	to	to	PART
admet-2772	647	12	language	language	NOUN
admet-2772	647	13	models	model	NOUN
admet-2772	647	14	and	and	CCONJ
admet-2772	647	15	quantum	quantum	NOUN
admet-2772	647	16	computing	computing	NOUN
admet-2772	647	17	.	.	PUNCT
admet-2772	648	1	cell	cell	NOUN
admet-2772	648	2	reports	report	VERB
admet-2772	648	3	physical	physical	ADJ
admet-2772	648	4	science	science	NOUN
admet-2772	648	5	5	5	NUM
admet-2772	648	6	(	(	PUNCT
admet-2772	648	7	2024	2024	NUM
admet-2772	648	8	)	)	PUNCT
admet-2772	648	9	11	11	NUM
admet-2772	648	10	-	-	SYM
admet-2772	648	11	21	21	NUM
admet-2772	648	12	.	.	PUNCT
admet-2772	649	1	https://doi.org/10.1016/j.xcrp.2024.102334	https://doi.org/10.1016/j.xcrp.2024.102334	VERB
admet-2772	649	2	[	[	X
admet-2772	649	3	3	3	X
admet-2772	649	4	]	]	PUNCT
admet-2772	649	5	j.	j.	PROPN
admet-2772	649	6	vamathevan	vamathevan	PROPN
admet-2772	649	7	,	,	PUNCT
admet-2772	649	8	d.	d.	PROPN
admet-2772	649	9	clark	clark	PROPN
admet-2772	649	10	,	,	PUNCT
admet-2772	649	11	p.	p.	NOUN
admet-2772	649	12	czodrowski	czodrowski	PROPN
admet-2772	649	13	,	,	PUNCT
admet-2772	649	14	i.	i.	PROPN
admet-2772	649	15	dunham	dunham	PROPN
admet-2772	649	16	,	,	PUNCT
admet-2772	649	17	e.	e.	PROPN
admet-2772	649	18	ferran	ferran	PROPN
admet-2772	649	19	,	,	PUNCT
admet-2772	649	20	g.	g.	PROPN
admet-2772	649	21	lee	lee	PROPN
admet-2772	649	22	,	,	PUNCT
admet-2772	649	23	b.	b.	PROPN
admet-2772	649	24	li	li	PROPN
admet-2772	649	25	,	,	PUNCT
admet-2772	649	26	a.	a.	PROPN
admet-2772	649	27	madabhushi	madabhushi	PROPN
admet-2772	649	28	,	,	PUNCT
admet-2772	649	29	p.	p.	NOUN
admet-2772	649	30	shah	shah	PROPN
admet-2772	649	31	,	,	PUNCT
admet-2772	649	32	m.	m.	NOUN
admet-2772	649	33	spitzer	spitzer	PROPN
admet-2772	649	34	,	,	PUNCT
admet-2772	649	35	s.	s.	PROPN
admet-2772	649	36	zhao	zhao	PROPN
admet-2772	649	37	.	.	PUNCT
admet-2772	650	1	applications	application	NOUN
admet-2772	650	2	of	of	ADP
admet-2772	650	3	machine	machine	NOUN
admet-2772	650	4	learning	learn	VERB
admet-2772	650	5	in	in	ADP
admet-2772	650	6	drug	drug	NOUN
admet-2772	650	7	discovery	discovery	NOUN
admet-2772	650	8	and	and	CCONJ
admet-2772	650	9	development	development	NOUN
admet-2772	650	10	.	.	PUNCT
admet-2772	651	1	nature	nature	NOUN
admet-2772	651	2	reviews	review	VERB
admet-2772	651	3	drug	drug	NOUN
admet-2772	651	4	discovery	discovery	NOUN
admet-2772	651	5	18	18	NUM
admet-2772	651	6	(	(	PUNCT
admet-2772	651	7	2019	2019	NUM
admet-2772	651	8	)	)	PUNCT
admet-2772	651	9	463	463	NUM
admet-2772	651	10	-	-	SYM
admet-2772	651	11	477	477	NUM
admet-2772	651	12	.	.	PUNCT
admet-2772	651	13	https://doi.org/10.1038/s41573-019-0024-5	https://doi.org/10.1038/s41573-019-0024-5	NOUN
admet-2772	652	1	[	[	X
admet-2772	652	2	4	4	X
admet-2772	652	3	]	]	PUNCT
admet-2772	652	4	s.	s.	PROPN
admet-2772	652	5	dara	dara	PROPN
admet-2772	652	6	,	,	PUNCT
admet-2772	652	7	s.	s.	PROPN
admet-2772	652	8	dhamercherla	dhamercherla	PROPN
admet-2772	652	9	,	,	PUNCT
admet-2772	652	10	s.s	s.s	PROPN
admet-2772	652	11	.	.	PROPN
admet-2772	652	12	jadav	jadav	PROPN
admet-2772	652	13	,	,	PUNCT
admet-2772	652	14	c.m	c.m	PROPN
admet-2772	652	15	.	.	PUNCT
admet-2772	652	16	babu	babu	PROPN
admet-2772	652	17	,	,	PUNCT
admet-2772	652	18	m.j	m.j	PROPN
admet-2772	652	19	.	.	PROPN
admet-2772	652	20	ahsan	ahsan	PROPN
admet-2772	652	21	.	.	PUNCT
admet-2772	653	1	machine	machine	NOUN
admet-2772	653	2	learning	learn	VERB
admet-2772	653	3	in	in	ADP
admet-2772	653	4	drug	drug	NOUN
admet-2772	653	5	discovery	discovery	NOUN
admet-2772	653	6	:	:	PUNCT
admet-2772	653	7	a	a	DET
admet-2772	653	8	review	review	NOUN
admet-2772	653	9	.	.	PUNCT
admet-2772	654	1	artificial	artificial	ADJ
admet-2772	654	2	intelligence	intelligence	NOUN
admet-2772	654	3	review	review	NOUN
admet-2772	654	4	55	55	NUM
admet-2772	654	5	(	(	PUNCT
admet-2772	654	6	2022	2022	NUM
admet-2772	654	7	)	)	PUNCT
admet-2772	654	8	1947	1947	NUM
admet-2772	654	9	-	-	SYM
admet-2772	654	10	1999	1999	NUM
admet-2772	654	11	.	.	PUNCT
admet-2772	655	1	https://doi.org/10.1007/s10462-02110058-4	https://doi.org/10.1007/s10462-02110058-4	PROPN
admet-2772	655	2	[	[	X
admet-2772	655	3	5	5	NUM
admet-2772	655	4	]	]	PUNCT
admet-2772	655	5	g.	g.	PROPN
admet-2772	655	6	xiong	xiong	PROPN
admet-2772	655	7	,	,	PUNCT
admet-2772	655	8	z.	z.	PROPN
admet-2772	655	9	wu	wu	PROPN
admet-2772	655	10	,	,	PUNCT
admet-2772	655	11	j.	j.	PROPN
admet-2772	655	12	yi	yi	PROPN
admet-2772	655	13	,	,	PUNCT
admet-2772	655	14	l.	l.	PROPN
admet-2772	655	15	fu	fu	PROPN
admet-2772	655	16	,	,	PUNCT
admet-2772	655	17	z.	z.	PROPN
admet-2772	655	18	yang	yang	PROPN
admet-2772	655	19	,	,	PUNCT
admet-2772	655	20	c.	c.	PROPN
admet-2772	655	21	hsieh	hsieh	PROPN
admet-2772	655	22	,	,	PUNCT
admet-2772	655	23	m.	m.	NOUN
admet-2772	655	24	yin	yin	PROPN
admet-2772	655	25	,	,	PUNCT
admet-2772	655	26	x.	x.	PROPN
admet-2772	655	27	zeng	zeng	PROPN
admet-2772	655	28	,	,	PUNCT
admet-2772	655	29	c.	c.	PROPN
admet-2772	655	30	wu	wu	PROPN
admet-2772	655	31	,	,	PUNCT
admet-2772	655	32	a.	a.	PROPN
admet-2772	655	33	lu	lu	PROPN
admet-2772	655	34	,	,	PUNCT
admet-2772	655	35	x.	x.	PROPN
admet-2772	655	36	chen	chen	PROPN
admet-2772	655	37	,	,	PUNCT
admet-2772	655	38	t.	t.	PROPN
admet-2772	655	39	hou	hou	PROPN
admet-2772	655	40	,	,	PUNCT
admet-2772	655	41	d.	d.	PROPN
admet-2772	655	42	cao	cao	PROPN
admet-2772	655	43	.	.	PUNCT
admet-2772	656	1	admetlab	admetlab	PROPN
admet-2772	656	2	2.0	2.0	NUM
admet-2772	656	3	:	:	PUNCT
admet-2772	656	4	an	an	DET
admet-2772	656	5	integrated	integrate	VERB
admet-2772	656	6	online	online	ADJ
admet-2772	656	7	platform	platform	NOUN
admet-2772	656	8	for	for	ADP
admet-2772	656	9	accurate	accurate	ADJ
admet-2772	656	10	and	and	CCONJ
admet-2772	656	11	comprehensive	comprehensive	ADJ
admet-2772	656	12	predictions	prediction	NOUN
admet-2772	656	13	of	of	ADP
admet-2772	656	14	admet	admet	NOUN
admet-2772	656	15	properties	property	NOUN
admet-2772	656	16	.	.	PUNCT
admet-2772	657	1	nucleic	nucleic	ADJ
admet-2772	657	2	acids	acid	NOUN
admet-2772	657	3	research	research	NOUN
admet-2772	657	4	49	49	NUM
admet-2772	657	5	(	(	PUNCT
admet-2772	657	6	2021	2021	NUM
admet-2772	657	7	)	)	PUNCT
admet-2772	657	8	w5	w5	PROPN
admet-2772	657	9	-	-	PUNCT
admet-2772	657	10	w14	w14	PROPN
admet-2772	657	11	.	.	PUNCT
admet-2772	658	1	https://doi.org/10.1093/nar/gkab255	https://doi.org/10.1093/nar/gkab255	PROPN
admet-2772	658	2	https://doi.org/10.4155/fmc-2019-0307	https://doi.org/10.4155/fmc-2019-0307	PROPN
admet-2772	658	3	https://doi.org/10.1016/j.xcrp.2024.102334	https://doi.org/10.1016/j.xcrp.2024.102334	PROPN
admet-2772	658	4	https://doi.org/10.1038/s41573-019-0024-5	https://doi.org/10.1038/s41573-019-0024-5	PROPN
admet-2772	658	5	https://doi.org/10.1007/s10462-021-10058-4	https://doi.org/10.1007/s10462-021-10058-4	NUM
admet-2772	658	6	https://doi.org/10.1007/s10462-021-10058-4	https://doi.org/10.1007/s10462-021-10058-4	NUM
admet-2772	658	7	https://doi.org/10.1093/nar/gkab255	https://doi.org/10.1093/nar/gkab255	NOUN
admet-2772	658	8	admet	admet	PROPN
admet-2772	658	9	&	&	CCONJ
admet-2772	658	10	dmpk	dmpk	PROPN
admet-2772	658	11	13(3	13(3	NUM
admet-2772	658	12	)	)	PUNCT
admet-2772	658	13	(	(	PUNCT
admet-2772	658	14	2025	2025	NUM
admet-2772	658	15	)	)	PUNCT
admet-2772	658	16	2772	2772	NUM
admet-2772	658	17	machine	machine	NOUN
admet-2772	658	18	learning	learning	NOUN
admet-2772	658	19	models	model	NOUN
admet-2772	658	20	for	for	ADP
admet-2772	658	21	admet	admet	ADJ
admet-2772	658	22	prediction	prediction	NOUN
admet-2772	658	23	in	in	ADP
admet-2772	658	24	drug	drug	NOUN
admet-2772	658	25	development	development	NOUN
admet-2772	658	26	doi	doi	PROPN
admet-2772	658	27	:	:	PUNCT
admet-2772	658	28	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	658	29	25	25	NUM
admet-2772	658	30	[	[	SYM
admet-2772	658	31	6	6	NUM
admet-2772	658	32	]	]	X
admet-2772	658	33	j.a	j.a	PROPN
admet-2772	658	34	.	.	PROPN
admet-2772	658	35	pradeepkiran	pradeepkiran	PROPN
admet-2772	658	36	,	,	PUNCT
admet-2772	658	37	s.b	s.b	PROPN
admet-2772	658	38	.	.	PROPN
admet-2772	658	39	sainath	sainath	PROPN
admet-2772	658	40	.	.	PUNCT
admet-2772	659	1	brucella	brucella	PROPN
admet-2772	659	2	melitensis	melitensis	PROPN
admet-2772	659	3	:	:	PUNCT
admet-2772	659	4	identification	identification	NOUN
admet-2772	659	5	and	and	CCONJ
admet-2772	659	6	characterization	characterization	NOUN
admet-2772	659	7	of	of	ADP
admet-2772	659	8	potential	potential	ADJ
admet-2772	659	9	drug	drug	NOUN
admet-2772	659	10	targets	target	NOUN
admet-2772	659	11	,	,	PUNCT
admet-2772	659	12	elsevier	elsevier	PROPN
admet-2772	659	13	,	,	PUNCT
admet-2772	659	14	texas	texas	PROPN
admet-2772	659	15	,	,	PUNCT
admet-2772	659	16	us	we	PRON
admet-2772	659	17	,	,	PUNCT
admet-2772	659	18	(	(	PUNCT
admet-2772	659	19	2021	2021	NUM
admet-2772	659	20	)	)	PUNCT
admet-2772	659	21	133	133	NUM
admet-2772	659	22	-	-	SYM
admet-2772	659	23	176	176	NUM
admet-2772	659	24	.	.	PUNCT
admet-2772	659	25	https://doi.org/10.1016/c2020-0-03079-3	https://doi.org/10.1016/c2020-0-03079-3	PROPN
admet-2772	660	1	[	[	X
admet-2772	660	2	7	7	NUM
admet-2772	660	3	]	]	X
admet-2772	660	4	d.	d.	PROPN
admet-2772	660	5	sun	sun	PROPN
admet-2772	660	6	,	,	PUNCT
admet-2772	660	7	w.	w.	PROPN
admet-2772	660	8	gao	gao	PROPN
admet-2772	660	9	,	,	PUNCT
admet-2772	660	10	h.	h.	PROPN
admet-2772	660	11	hu	hu	PROPN
admet-2772	660	12	,	,	PUNCT
admet-2772	660	13	s.	s.	PROPN
admet-2772	660	14	zhou	zhou	PROPN
admet-2772	660	15	.	.	PUNCT
admet-2772	661	1	why	why	SCONJ
admet-2772	661	2	90	90	NUM
admet-2772	661	3	%	%	NOUN
admet-2772	661	4	of	of	ADP
admet-2772	661	5	clinical	clinical	ADJ
admet-2772	661	6	drug	drug	NOUN
admet-2772	661	7	development	development	NOUN
admet-2772	661	8	fails	fail	VERB
admet-2772	661	9	and	and	CCONJ
admet-2772	661	10	how	how	SCONJ
admet-2772	661	11	to	to	PART
admet-2772	661	12	improve	improve	VERB
admet-2772	661	13	it	it	PRON
admet-2772	661	14	?	?	PUNCT
admet-2772	662	1	acta	acta	PROPN
admet-2772	662	2	pharmaceutica	pharmaceutica	PROPN
admet-2772	662	3	sinica	sinica	PROPN
admet-2772	662	4	b	b	PROPN
admet-2772	662	5	12	12	NUM
admet-2772	662	6	(	(	PUNCT
admet-2772	662	7	2022	2022	NUM
admet-2772	662	8	)	)	PUNCT
admet-2772	662	9	3049	3049	NUM
admet-2772	662	10	-	-	SYM
admet-2772	662	11	3062	3062	NUM
admet-2772	662	12	.	.	PUNCT
admet-2772	663	1	https://doi.org/10.1016/j.apsb.2022.02.002	https://doi.org/10.1016/j.apsb.2022.02.002	NOUN
admet-2772	663	2	[	[	X
admet-2772	663	3	8	8	X
admet-2772	663	4	]	]	PUNCT
admet-2772	663	5	j.	j.	PROPN
admet-2772	663	6	jiménez	jiménez	PROPN
admet-2772	663	7	-	-	PUNCT
admet-2772	663	8	luna	luna	PROPN
admet-2772	663	9	,	,	PUNCT
admet-2772	663	10	f.	f.	PROPN
admet-2772	663	11	grisoni	grisoni	PROPN
admet-2772	663	12	,	,	PUNCT
admet-2772	663	13	n.	n.	PROPN
admet-2772	663	14	weskamp	weskamp	PROPN
admet-2772	663	15	,	,	PUNCT
admet-2772	663	16	g.	g.	PROPN
admet-2772	663	17	schneider	schneider	PROPN
admet-2772	663	18	.	.	PUNCT
admet-2772	664	1	artificial	artificial	ADJ
admet-2772	664	2	intelligence	intelligence	NOUN
admet-2772	664	3	in	in	ADP
admet-2772	664	4	drug	drug	NOUN
admet-2772	664	5	discovery	discovery	NOUN
admet-2772	664	6	:	:	PUNCT
admet-2772	664	7	recent	recent	ADJ
admet-2772	664	8	advances	advance	NOUN
admet-2772	664	9	and	and	CCONJ
admet-2772	664	10	future	future	ADJ
admet-2772	664	11	perspectives	perspective	NOUN
admet-2772	664	12	.	.	PUNCT
admet-2772	665	1	expert	expert	ADJ
admet-2772	665	2	opinion	opinion	NOUN
admet-2772	665	3	on	on	ADP
admet-2772	665	4	drug	drug	NOUN
admet-2772	665	5	discovery	discovery	NOUN
admet-2772	665	6	16	16	NUM
admet-2772	665	7	(	(	PUNCT
admet-2772	665	8	2021	2021	NUM
admet-2772	665	9	)	)	PUNCT
admet-2772	665	10	949	949	NUM
admet-2772	665	11	-	-	SYM
admet-2772	665	12	959	959	NUM
admet-2772	665	13	.	.	PUNCT
admet-2772	665	14	https://doi.org/10.1080/17460441.2021.1909567	https://doi.org/10.1080/17460441.2021.1909567	X
admet-2772	666	1	[	[	X
admet-2772	666	2	9	9	NUM
admet-2772	666	3	]	]	PUNCT
admet-2772	666	4	s.	s.	PROPN
admet-2772	666	5	harrer	harrer	PROPN
admet-2772	666	6	,	,	PUNCT
admet-2772	666	7	p.	p.	NOUN
admet-2772	666	8	shah	shah	PROPN
admet-2772	666	9	,	,	PUNCT
admet-2772	666	10	b.	b.	PROPN
admet-2772	666	11	antony	antony	PROPN
admet-2772	666	12	,	,	PUNCT
admet-2772	666	13	j.	j.	PROPN
admet-2772	666	14	hu	hu	PROPN
admet-2772	666	15	.	.	PUNCT
admet-2772	667	1	artificial	artificial	ADJ
admet-2772	667	2	intelligence	intelligence	NOUN
admet-2772	667	3	for	for	ADP
admet-2772	667	4	clinical	clinical	ADJ
admet-2772	667	5	trial	trial	NOUN
admet-2772	667	6	design	design	NOUN
admet-2772	667	7	.	.	PUNCT
admet-2772	668	1	trends	trend	NOUN
admet-2772	668	2	in	in	ADP
admet-2772	668	3	pharmacological	pharmacological	ADJ
admet-2772	668	4	sciences	science	NOUN
admet-2772	668	5	40	40	NUM
admet-2772	668	6	(	(	PUNCT
admet-2772	668	7	2019	2019	NUM
admet-2772	668	8	)	)	PUNCT
admet-2772	668	9	577	577	NUM
admet-2772	668	10	-	-	SYM
admet-2772	668	11	591	591	NUM
admet-2772	668	12	.	.	PUNCT
admet-2772	669	1	https://doi.org/10.1016/j.tips.2019.05.005	https://doi.org/10.1016/j.tips.2019.05.005	NOUN
admet-2772	669	2	[	[	X
admet-2772	669	3	10	10	NUM
admet-2772	669	4	]	]	X
admet-2772	669	5	m.j	m.j	PROPN
admet-2772	669	6	.	.	PROPN
admet-2772	669	7	wildey	wildey	PROPN
admet-2772	669	8	,	,	PUNCT
admet-2772	669	9	a.	a.	NOUN
admet-2772	669	10	haunso	haunso	PROPN
admet-2772	669	11	,	,	PUNCT
admet-2772	669	12	m.	m.	NOUN
admet-2772	669	13	tudor	tudor	PROPN
admet-2772	669	14	,	,	PUNCT
admet-2772	669	15	m.	m.	NOUN
admet-2772	669	16	webb	webb	PROPN
admet-2772	669	17	,	,	PUNCT
admet-2772	669	18	j.h	j.h	PROPN
admet-2772	669	19	.	.	PROPN
admet-2772	669	20	connick	connick	PROPN
admet-2772	669	21	.	.	PUNCT
admet-2772	670	1	high	high	ADJ
admet-2772	670	2	-	-	PUNCT
admet-2772	670	3	throughput	throughput	NOUN
admet-2772	670	4	screening	screening	NOUN
admet-2772	670	5	.	.	PUNCT
admet-2772	671	1	annual	annual	ADJ
admet-2772	671	2	reports	report	NOUN
admet-2772	671	3	in	in	ADP
admet-2772	671	4	medicinal	medicinal	ADJ
admet-2772	671	5	chemistry	chemistry	NOUN
admet-2772	671	6	50	50	NUM
admet-2772	671	7	(	(	PUNCT
admet-2772	671	8	2017	2017	NUM
admet-2772	671	9	)	)	PUNCT
admet-2772	671	10	149	149	NUM
admet-2772	671	11	-	-	SYM
admet-2772	671	12	195	195	NUM
admet-2772	671	13	.	.	PUNCT
admet-2772	672	1	https://doi.org/10.1016/bs.armc.2017.08.004	https://doi.org/10.1016/bs.armc.2017.08.004	PUNCT
admet-2772	673	1	[	[	X
admet-2772	673	2	11	11	NUM
admet-2772	673	3	]	]	X
admet-2772	673	4	s.	s.	PROPN
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admet-2772	673	6	,	,	PUNCT
admet-2772	673	7	a.t.k	a.t.k	PROPN
admet-2772	673	8	.	.	PUNCT
admet-2772	673	9	baidya	baidya	PROPN
admet-2772	673	10	,	,	PUNCT
admet-2772	673	11	a.	a.	PROPN
admet-2772	673	12	mandal	mandal	PROPN
admet-2772	673	13	,	,	PUNCT
admet-2772	673	14	a.t	a.t	PROPN
admet-2772	673	15	.	.	PROPN
admet-2772	673	16	mathew	mathew	PROPN
admet-2772	673	17	,	,	PUNCT
admet-2772	673	18	b.	b.	PROPN
admet-2772	673	19	das	das	PROPN
admet-2772	673	20	,	,	PUNCT
admet-2772	673	21	b.	b.	PROPN
admet-2772	673	22	devi	devi	PROPN
admet-2772	673	23	,	,	PUNCT
admet-2772	673	24	r.	r.	PROPN
admet-2772	673	25	kumar	kumar	PROPN
admet-2772	673	26	.	.	PUNCT
admet-2772	674	1	deep	deep	ADJ
admet-2772	674	2	learning	learning	NOUN
admet-2772	674	3	tools	tool	NOUN
admet-2772	674	4	for	for	ADP
admet-2772	674	5	advancing	advance	VERB
admet-2772	674	6	drug	drug	NOUN
admet-2772	674	7	discovery	discovery	NOUN
admet-2772	674	8	and	and	CCONJ
admet-2772	674	9	development	development	NOUN
admet-2772	674	10	.	.	PUNCT
admet-2772	675	1	3	3	NUM
admet-2772	675	2	biotech	biotech	NOUN
admet-2772	675	3	12	12	NUM
admet-2772	675	4	(	(	PUNCT
admet-2772	675	5	2022	2022	NUM
admet-2772	675	6	)	)	PUNCT
admet-2772	675	7	110	110	NUM
admet-2772	675	8	.	.	PUNCT
admet-2772	676	1	https://doi.org/10.1007/s13205-022-03165-8	https://doi.org/10.1007/s13205-022-03165-8	PRON
admet-2772	677	1	[	[	X
admet-2772	677	2	12	12	NUM
admet-2772	677	3	]	]	X
admet-2772	677	4	c.r	c.r	PROPN
admet-2772	677	5	.	.	PROPN
admet-2772	677	6	hooijmans	hooijmans	PROPN
admet-2772	677	7	,	,	PUNCT
admet-2772	677	8	r.b.m	r.b.m	ADJ
admet-2772	677	9	.	.	PROPN
admet-2772	677	10	de	de	PROPN
admet-2772	677	11	vries	vries	PROPN
admet-2772	677	12	,	,	PUNCT
admet-2772	677	13	m.	m.	NOUN
admet-2772	677	14	ritskes	ritske	NOUN
admet-2772	677	15	-	-	PUNCT
admet-2772	677	16	hoitinga	hoitinga	PROPN
admet-2772	677	17	,	,	PUNCT
admet-2772	677	18	m.m	m.m	PROPN
admet-2772	677	19	.	.	PROPN
admet-2772	677	20	rovers	rovers	PROPN
admet-2772	677	21	,	,	PUNCT
admet-2772	677	22	m.m	m.m	PROPN
admet-2772	677	23	.	.	PROPN
admet-2772	677	24	leeflang	leeflang	PROPN
admet-2772	677	25	,	,	PUNCT
admet-2772	677	26	j.	j.	PROPN
admet-2772	677	27	inthout	inthout	PROPN
admet-2772	677	28	,	,	PUNCT
admet-2772	677	29	k.e	k.e	PROPN
admet-2772	677	30	.	.	PROPN
admet-2772	677	31	wever	wever	PROPN
admet-2772	677	32	,	,	PUNCT
admet-2772	677	33	l.	l.	PROPN
admet-2772	677	34	hooft	hooft	PROPN
admet-2772	677	35	,	,	PUNCT
admet-2772	677	36	h.	h.	PROPN
admet-2772	677	37	de	de	PROPN
admet-2772	677	38	beer	beer	PROPN
admet-2772	677	39	,	,	PUNCT
admet-2772	677	40	t.	t.	PROPN
admet-2772	677	41	kuijpers	kuijpers	PROPN
admet-2772	677	42	,	,	PUNCT
admet-2772	677	43	m.r	m.r	PROPN
admet-2772	677	44	.	.	PROPN
admet-2772	677	45	macleod	macleod	PROPN
admet-2772	677	46	,	,	PUNCT
admet-2772	677	47	e.s	e.s	PROPN
admet-2772	677	48	.	.	PROPN
admet-2772	677	49	sena	sena	PROPN
admet-2772	677	50	,	,	PUNCT
admet-2772	677	51	g.	g.	PROPN
admet-2772	677	52	ter	ter	PROPN
admet-2772	677	53	riet	riet	PROPN
admet-2772	677	54	,	,	PUNCT
admet-2772	677	55	r.l	r.l	PROPN
admet-2772	677	56	.	.	PROPN
admet-2772	677	57	morgan	morgan	PROPN
admet-2772	677	58	,	,	PUNCT
admet-2772	677	59	k.a	k.a	PROPN
admet-2772	677	60	.	.	PROPN
admet-2772	677	61	thayer	thayer	PROPN
admet-2772	677	62	,	,	PUNCT
admet-2772	677	63	a.a	a.a	PROPN
admet-2772	677	64	.	.	PROPN
admet-2772	677	65	rooney	rooney	PROPN
admet-2772	677	66	,	,	PUNCT
admet-2772	677	67	g.h	g.h	PROPN
admet-2772	677	68	.	.	PROPN
admet-2772	677	69	guyatt	guyatt	PROPN
admet-2772	677	70	,	,	PUNCT
admet-2772	677	71	h.j	h.j	PROPN
admet-2772	677	72	.	.	PROPN
admet-2772	677	73	schünemann	schünemann	PROPN
admet-2772	677	74	,	,	PUNCT
admet-2772	677	75	m.w	m.w	PROPN
admet-2772	677	76	.	.	PROPN
admet-2772	677	77	langendam	langendam	PROPN
admet-2772	677	78	.	.	PUNCT
admet-2772	678	1	facilitating	facilitate	VERB
admet-2772	678	2	healthcare	healthcare	NOUN
admet-2772	678	3	decisions	decision	NOUN
admet-2772	678	4	by	by	ADP
admet-2772	678	5	assessing	assess	VERB
admet-2772	678	6	the	the	DET
admet-2772	678	7	certainty	certainty	NOUN
admet-2772	678	8	in	in	ADP
admet-2772	678	9	the	the	DET
admet-2772	678	10	evidence	evidence	NOUN
admet-2772	678	11	from	from	ADP
admet-2772	678	12	preclinical	preclinical	ADJ
admet-2772	678	13	animal	animal	NOUN
admet-2772	678	14	studies	study	NOUN
admet-2772	678	15	.	.	PUNCT
admet-2772	679	1	plos	plos	PROPN
admet-2772	679	2	one	one	NUM
admet-2772	679	3	13(1	13(1	NUM
admet-2772	679	4	)	)	PUNCT
admet-2772	679	5	(	(	PUNCT
admet-2772	679	6	2018	2018	NUM
admet-2772	679	7	)	)	PUNCT
admet-2772	679	8	e0187271	e0187271	NOUN
admet-2772	679	9	.	.	PUNCT
admet-2772	680	1	https://doi.org/10.1371/journal.pone.0187271	https://doi.org/10.1371/journal.pone.0187271	NOUN
admet-2772	680	2	[	[	X
admet-2772	680	3	13	13	NUM
admet-2772	680	4	]	]	X
admet-2772	680	5	n.	n.	PROPN
admet-2772	680	6	singh	singh	PROPN
admet-2772	680	7	,	,	PUNCT
admet-2772	680	8	p.	p.	NOUN
admet-2772	680	9	vayer	vayer	PROPN
admet-2772	680	10	,	,	PUNCT
admet-2772	680	11	s.	s.	PROPN
admet-2772	680	12	tanwar	tanwar	PROPN
admet-2772	680	13	,	,	PUNCT
admet-2772	680	14	j.-l	j.-l	PROPN
admet-2772	680	15	.	.	PUNCT
admet-2772	681	1	poyet	poyet	PROPN
admet-2772	681	2	,	,	PUNCT
admet-2772	681	3	k.	k.	PROPN
admet-2772	682	1	tsaioun	tsaioun	PROPN
admet-2772	682	2	,	,	PUNCT
admet-2772	682	3	b.o	b.o	PROPN
admet-2772	682	4	.	.	PROPN
admet-2772	682	5	villoutreix	villoutreix	PROPN
admet-2772	682	6	.	.	PUNCT
admet-2772	683	1	drug	drug	NOUN
admet-2772	683	2	discovery	discovery	PROPN
admet-2772	683	3	and	and	CCONJ
admet-2772	683	4	development	development	NOUN
admet-2772	683	5	:	:	PUNCT
admet-2772	683	6	introduction	introduction	NOUN
admet-2772	683	7	to	to	ADP
admet-2772	683	8	the	the	DET
admet-2772	683	9	general	general	ADJ
admet-2772	683	10	public	public	ADJ
admet-2772	683	11	and	and	CCONJ
admet-2772	683	12	patient	patient	ADJ
admet-2772	683	13	groups	group	NOUN
admet-2772	683	14	.	.	PUNCT
admet-2772	684	1	frontiers	frontier	NOUN
admet-2772	684	2	in	in	ADP
admet-2772	684	3	drug	drug	NOUN
admet-2772	684	4	discovery	discovery	NOUN
admet-2772	684	5	3	3	NUM
admet-2772	684	6	(	(	PUNCT
admet-2772	684	7	2023	2023	NUM
admet-2772	684	8	)	)	PUNCT
admet-2772	684	9	1201419	1201419	NUM
admet-2772	684	10	.	.	PUNCT
admet-2772	685	1	https://doi.org/10.3389/fddsv.2023.1201419	https://doi.org/10.3389/fddsv.2023.1201419	PROPN
admet-2772	686	1	[	[	X
admet-2772	686	2	14	14	NUM
admet-2772	686	3	]	]	X
admet-2772	686	4	f.	f.	PROPN
admet-2772	686	5	wu	wu	PROPN
admet-2772	686	6	,	,	PUNCT
admet-2772	686	7	y.	y.	PROPN
admet-2772	686	8	zhou	zhou	PROPN
admet-2772	686	9	,	,	PUNCT
admet-2772	686	10	l.	l.	PROPN
admet-2772	686	11	li	li	PROPN
admet-2772	686	12	,	,	PUNCT
admet-2772	686	13	x.	x.	PROPN
admet-2772	686	14	shen	shen	PROPN
admet-2772	686	15	,	,	PUNCT
admet-2772	686	16	g.	g.	PROPN
admet-2772	686	17	chen	chen	PROPN
admet-2772	686	18	,	,	PUNCT
admet-2772	686	19	x.	x.	PROPN
admet-2772	686	20	wang	wang	PROPN
admet-2772	686	21	,	,	PUNCT
admet-2772	686	22	x.	x.	PROPN
admet-2772	686	23	liang	liang	PROPN
admet-2772	686	24	,	,	PUNCT
admet-2772	686	25	m.	m.	PROPN
admet-2772	686	26	tan	tan	PROPN
admet-2772	686	27	,	,	PUNCT
admet-2772	686	28	z.	z.	PROPN
admet-2772	686	29	huang	huang	PROPN
admet-2772	686	30	.	.	PUNCT
admet-2772	687	1	computational	computational	ADJ
admet-2772	687	2	approaches	approach	NOUN
admet-2772	687	3	in	in	ADP
admet-2772	687	4	preclinical	preclinical	ADJ
admet-2772	687	5	studies	study	NOUN
admet-2772	687	6	on	on	ADP
admet-2772	687	7	drug	drug	NOUN
admet-2772	687	8	discovery	discovery	NOUN
admet-2772	687	9	and	and	CCONJ
admet-2772	687	10	development	development	NOUN
admet-2772	687	11	.	.	PUNCT
admet-2772	688	1	frontiers	frontier	NOUN
admet-2772	688	2	in	in	ADP
admet-2772	688	3	chemistry	chemistry	NOUN
admet-2772	688	4	8	8	NUM
admet-2772	688	5	(	(	PUNCT
admet-2772	688	6	2020	2020	NUM
admet-2772	688	7	)	)	PUNCT
admet-2772	688	8	726	726	NUM
admet-2772	688	9	.	.	PUNCT
admet-2772	689	1	https://doi.org/10.3389/fchem.2020.00726	https://doi.org/10.3389/fchem.2020.00726	PROPN
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admet-2772	690	2	15	15	NUM
admet-2772	690	3	]	]	X
admet-2772	690	4	d.	d.	PROPN
admet-2772	690	5	wang	wang	PROPN
admet-2772	690	6	,	,	PUNCT
admet-2772	690	7	w.	w.	PROPN
admet-2772	690	8	liu	liu	PROPN
admet-2772	690	9	,	,	PUNCT
admet-2772	690	10	z.	z.	PROPN
admet-2772	690	11	shen	shen	PROPN
admet-2772	690	12	,	,	PUNCT
admet-2772	690	13	l.	l.	PROPN
admet-2772	690	14	jiang	jiang	PROPN
admet-2772	690	15	,	,	PUNCT
admet-2772	690	16	j.	j.	PROPN
admet-2772	690	17	wang	wang	PROPN
admet-2772	690	18	,	,	PUNCT
admet-2772	690	19	s.	s.	PROPN
admet-2772	690	20	li	li	PROPN
admet-2772	690	21	,	,	PUNCT
admet-2772	690	22	h.	h.	PROPN
admet-2772	690	23	li	li	PROPN
admet-2772	690	24	.	.	PROPN
admet-2772	691	1	deep	deep	ADJ
admet-2772	691	2	learning	learning	NOUN
admet-2772	691	3	based	base	VERB
admet-2772	691	4	drug	drug	NOUN
admet-2772	691	5	metabolites	metabolite	NOUN
admet-2772	691	6	prediction	prediction	NOUN
admet-2772	691	7	.	.	PUNCT
admet-2772	692	1	frontiers	frontier	NOUN
admet-2772	692	2	in	in	ADP
admet-2772	692	3	pharmacology	pharmacology	NOUN
admet-2772	692	4	10	10	NUM
admet-2772	692	5	(	(	PUNCT
admet-2772	692	6	2020	2020	NUM
admet-2772	692	7	)	)	PUNCT
admet-2772	692	8	1586	1586	NUM
admet-2772	692	9	.	.	PUNCT
admet-2772	693	1	https://doi.org/10.3389/fphar.2019.01586	https://doi.org/10.3389/fphar.2019.01586	PROPN
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admet-2772	693	3	16	16	NUM
admet-2772	693	4	]	]	X
admet-2772	693	5	y.	y.	PROPN
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admet-2772	693	7	,	,	PUNCT
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admet-2772	693	9	wang	wang	PROPN
admet-2772	693	10	.	.	PUNCT
admet-2772	694	1	machine	machine	NOUN
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admet-2772	694	4	toxicity	toxicity	NOUN
admet-2772	694	5	prediction	prediction	NOUN
admet-2772	694	6	:	:	PUNCT
admet-2772	694	7	from	from	ADP
admet-2772	694	8	chemical	chemical	ADJ
admet-2772	694	9	structural	structural	ADJ
admet-2772	694	10	description	description	NOUN
admet-2772	694	11	to	to	ADP
admet-2772	694	12	transcriptome	transcriptome	ADJ
admet-2772	694	13	analysis	analysis	NOUN
admet-2772	694	14	.	.	PUNCT
admet-2772	695	1	international	international	ADJ
admet-2772	695	2	journal	journal	NOUN
admet-2772	695	3	of	of	ADP
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admet-2772	695	5	sciences	science	NOUN
admet-2772	695	6	19(8	19(8	NUM
admet-2772	695	7	)	)	PUNCT
admet-2772	695	8	(	(	PUNCT
admet-2772	695	9	2018	2018	NUM
admet-2772	695	10	)	)	PUNCT
admet-2772	695	11	2358	2358	NUM
admet-2772	695	12	.	.	PUNCT
admet-2772	696	1	https://doi.org/10.3390/ijms19082358	https://doi.org/10.3390/ijms19082358	NOUN
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admet-2772	696	3	17	17	NUM
admet-2772	696	4	]	]	PUNCT
admet-2772	696	5	k.	k.	PROPN
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admet-2772	696	7	,	,	PUNCT
admet-2772	696	8	s.	s.	PROPN
admet-2772	696	9	mondal	mondal	PROPN
admet-2772	696	10	,	,	PUNCT
admet-2772	696	11	b.	b.	PROPN
admet-2772	696	12	nemade	nemade	PROPN
admet-2772	696	13	.	.	PUNCT
admet-2772	697	1	data	data	PROPN
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admet-2772	697	6	data	datum	NOUN
admet-2772	697	7	augmentation	augmentation	NOUN
admet-2772	697	8	techniques	technique	NOUN
admet-2772	697	9	.	.	PUNCT
admet-2772	698	1	global	global	ADJ
admet-2772	698	2	transitions	transition	NOUN
admet-2772	698	3	proceedings	proceeding	NOUN
admet-2772	698	4	3	3	NUM
admet-2772	698	5	(	(	PUNCT
admet-2772	698	6	2022	2022	NUM
admet-2772	698	7	)	)	PUNCT
admet-2772	698	8	91	91	NUM
admet-2772	698	9	-	-	SYM
admet-2772	698	10	99	99	NUM
admet-2772	698	11	.	.	PUNCT
admet-2772	699	1	https://doi.org/10.1016/j.gltp.2022.04.020	https://doi.org/10.1016/j.gltp.2022.04.020	NOUN
admet-2772	699	2	[	[	X
admet-2772	699	3	18	18	NUM
admet-2772	699	4	]	]	PUNCT
admet-2772	699	5	k.	k.	PROPN
admet-2772	699	6	bhayani	bhayani	PROPN
admet-2772	699	7	,	,	PUNCT
admet-2772	699	8	d.	d.	PROPN
admet-2772	699	9	tanna	tanna	PROPN
admet-2772	699	10	,	,	PUNCT
admet-2772	699	11	v.	v.	PROPN
admet-2772	699	12	maan	maan	PROPN
admet-2772	699	13	,	,	PUNCT
admet-2772	699	14	dhiraj	dhiraj	PROPN
admet-2772	699	15	,	,	PUNCT
admet-2772	699	16	s.	s.	PROPN
admet-2772	699	17	kumar	kumar	PROPN
admet-2772	699	18	.	.	PUNCT
admet-2772	700	1	an	an	DET
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admet-2772	700	4	the	the	DET
admet-2772	700	5	impact	impact	NOUN
admet-2772	700	6	of	of	ADP
admet-2772	700	7	feature	feature	NOUN
admet-2772	700	8	quality	quality	NOUN
admet-2772	700	9	versus	versus	ADP
admet-2772	700	10	feature	feature	NOUN
admet-2772	700	11	quantity	quantity	NOUN
admet-2772	700	12	on	on	ADP
admet-2772	700	13	the	the	DET
admet-2772	700	14	performance	performance	NOUN
admet-2772	700	15	of	of	ADP
admet-2772	700	16	a	a	DET
admet-2772	700	17	machine	machine	NOUN
admet-2772	700	18	learning	learn	VERB
admet-2772	700	19	model	model	NOUN
admet-2772	700	20	.	.	PUNCT
admet-2772	701	1	in	in	ADP
admet-2772	701	2	:	:	PUNCT
admet-2772	701	3	ieee	ieee	NOUN
admet-2772	701	4	int	int	NOUN
admet-2772	701	5	.	.	PUNCT
admet-2772	701	6	conf	conf	PROPN
admet-2772	701	7	.	.	PUNCT
admet-2772	702	1	contemp	contemp	NOUN
admet-2772	702	2	.	.	PUNCT
admet-2772	703	1	comput	comput	NOUN
admet-2772	703	2	.	.	PUNCT
admet-2772	704	1	commun	commun	PROPN
admet-2772	704	2	.	.	PROPN
admet-2772	704	3	,	,	PUNCT
admet-2772	704	4	ieee	ieee	PROPN
admet-2772	704	5	,	,	PUNCT
admet-2772	704	6	bangalore	bangalore	PROPN
admet-2772	704	7	,	,	PUNCT
admet-2772	704	8	india	india	PROPN
admet-2772	704	9	,	,	PUNCT
admet-2772	704	10	(	(	PUNCT
admet-2772	704	11	2023	2023	NUM
admet-2772	704	12	):	):	PUNCT
admet-2772	704	13	pp.1	pp.1	NOUN
admet-2772	704	14	-	-	SYM
admet-2772	704	15	5	5	NUM
admet-2772	704	16	https://doi.org/10.1109/inc457730.2023.10262824	https://doi.org/10.1109/inc457730.2023.10262824	NOUN
admet-2772	704	17	[	[	X
admet-2772	704	18	19	19	NUM
admet-2772	704	19	]	]	X
admet-2772	704	20	s.c	s.c	PROPN
admet-2772	704	21	.	.	PROPN
admet-2772	704	22	rathi	rathi	PROPN
admet-2772	704	23	,	,	PUNCT
admet-2772	704	24	s.	s.	PROPN
admet-2772	704	25	misra	misra	PROPN
admet-2772	704	26	,	,	PUNCT
admet-2772	704	27	r.	r.	PROPN
admet-2772	704	28	colomo	colomo	PROPN
admet-2772	704	29	-	-	PUNCT
admet-2772	704	30	palacios	palacios	PROPN
admet-2772	704	31	,	,	PUNCT
admet-2772	704	32	r.	r.	PROPN
admet-2772	704	33	adarsh	adarsh	PROPN
admet-2772	704	34	,	,	PUNCT
admet-2772	704	35	l.b.m	l.b.m	PROPN
admet-2772	704	36	.	.	PUNCT
admet-2772	705	1	neti	neti	PROPN
admet-2772	705	2	,	,	PUNCT
admet-2772	705	3	l.	l.	PROPN
admet-2772	705	4	kumar	kumar	PROPN
admet-2772	705	5	.	.	PROPN
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admet-2772	706	2	evaluation	evaluation	NOUN
admet-2772	706	3	of	of	ADP
admet-2772	706	4	the	the	DET
admet-2772	706	5	performance	performance	NOUN
admet-2772	706	6	of	of	ADP
admet-2772	706	7	data	datum	NOUN
admet-2772	706	8	sampling	sampling	NOUN
admet-2772	706	9	and	and	CCONJ
admet-2772	706	10	feature	feature	NOUN
admet-2772	706	11	selection	selection	NOUN
admet-2772	706	12	techniques	technique	NOUN
admet-2772	706	13	for	for	ADP
admet-2772	706	14	software	software	NOUN
admet-2772	706	15	fault	fault	NOUN
admet-2772	706	16	prediction	prediction	NOUN
admet-2772	706	17	.	.	PUNCT
admet-2772	707	1	expert	expert	NOUN
admet-2772	707	2	systems	system	NOUN
admet-2772	707	3	with	with	ADP
admet-2772	707	4	applications	application	NOUN
admet-2772	707	5	223	223	NUM
admet-2772	707	6	(	(	PUNCT
admet-2772	707	7	2023	2023	NUM
admet-2772	707	8	)	)	PUNCT
admet-2772	707	9	119806	119806	NUM
admet-2772	707	10	.	.	PUNCT
admet-2772	708	1	https://doi.org/10.1016/j.eswa.2023.119806	https://doi.org/10.1016/j.eswa.2023.119806	PROPN
admet-2772	708	2	[	[	X
admet-2772	708	3	20	20	NUM
admet-2772	708	4	]	]	PUNCT
admet-2772	708	5	f.	f.	PROPN
admet-2772	708	6	caloni	caloni	PROPN
admet-2772	708	7	,	,	PUNCT
admet-2772	708	8	i.	i.	PROPN
admet-2772	708	9	de	de	PROPN
admet-2772	708	10	angelis	angelis	PROPN
admet-2772	708	11	,	,	PUNCT
admet-2772	708	12	t.	t.	PROPN
admet-2772	708	13	hartung	hartung	PROPN
admet-2772	708	14	.	.	PUNCT
admet-2772	709	1	replacement	replacement	NOUN
admet-2772	709	2	of	of	ADP
admet-2772	709	3	animal	animal	NOUN
admet-2772	709	4	testing	testing	NOUN
admet-2772	709	5	by	by	ADP
admet-2772	709	6	integrated	integrated	ADJ
admet-2772	709	7	approaches	approach	NOUN
admet-2772	709	8	to	to	ADP
admet-2772	709	9	testing	testing	NOUN
admet-2772	709	10	and	and	CCONJ
admet-2772	709	11	assessment	assessment	NOUN
admet-2772	709	12	(	(	PUNCT
admet-2772	709	13	iata	iata	NOUN
admet-2772	709	14	):	):	PUNCT
admet-2772	709	15	a	a	DET
admet-2772	709	16	call	call	NOUN
admet-2772	709	17	for	for	ADP
admet-2772	709	18	in	in	ADP
admet-2772	709	19	vivitrosi	vivitrosi	NOUN
admet-2772	709	20	.	.	PUNCT
admet-2772	710	1	archives	archive	NOUN
admet-2772	710	2	of	of	ADP
admet-2772	710	3	toxicology	toxicology	NOUN
admet-2772	710	4	96	96	NUM
admet-2772	710	5	(	(	PUNCT
admet-2772	710	6	2022	2022	NUM
admet-2772	710	7	)	)	PUNCT
admet-2772	710	8	1935	1935	NUM
admet-2772	710	9	-	-	SYM
admet-2772	710	10	1950	1950	NUM
admet-2772	710	11	.	.	PUNCT
admet-2772	711	1	https://doi.org/10.1007/s00204-022-03299-x	https://doi.org/10.1007/s00204-022-03299-x	NOUN
admet-2772	712	1	[	[	PUNCT
admet-2772	712	2	21	21	NUM
admet-2772	712	3	]	]	X
admet-2772	712	4	j.	j.	PROPN
admet-2772	712	5	grzegorzewski	grzegorzewski	PROPN
admet-2772	712	6	,	,	PUNCT
admet-2772	712	7	j.	j.	PROPN
admet-2772	712	8	brandhorst	brandhorst	PROPN
admet-2772	712	9	,	,	PUNCT
admet-2772	712	10	k.	k.	PROPN
admet-2772	712	11	green	green	PROPN
admet-2772	712	12	,	,	PUNCT
admet-2772	712	13	d.	d.	PROPN
admet-2772	712	14	eleftheriadou	eleftheriadou	NOUN
admet-2772	712	15	,	,	PUNCT
admet-2772	712	16	y.	y.	PROPN
admet-2772	712	17	duport	duport	PROPN
admet-2772	712	18	,	,	PUNCT
admet-2772	712	19	f.	f.	PROPN
admet-2772	712	20	barthorscht	barthorscht	PROPN
admet-2772	712	21	,	,	PUNCT
admet-2772	712	22	a.	a.	NOUN
admet-2772	712	23	köller	köller	PROPN
admet-2772	712	24	,	,	PUNCT
admet-2772	712	25	d.y.j	d.y.j	PROPN
admet-2772	712	26	.	.	PUNCT
admet-2772	713	1	ke	ke	PROPN
admet-2772	713	2	,	,	PUNCT
admet-2772	713	3	s.	s.	PROPN
admet-2772	713	4	de	de	PROPN
admet-2772	713	5	angelis	angelis	PROPN
admet-2772	713	6	,	,	PUNCT
admet-2772	713	7	m.	m.	NOUN
admet-2772	713	8	könig	könig	PROPN
admet-2772	713	9	.	.	PUNCT
admet-2772	714	1	pk	pk	PROPN
admet-2772	714	2	-	-	PUNCT
admet-2772	714	3	db	db	NOUN
admet-2772	714	4	:	:	PUNCT
admet-2772	714	5	pharmacokinetics	pharmacokinetic	NOUN
admet-2772	714	6	database	database	NOUN
admet-2772	714	7	for	for	ADP
admet-2772	714	8	individualized	individualized	ADJ
admet-2772	714	9	and	and	CCONJ
admet-2772	714	10	stratified	stratified	ADJ
admet-2772	714	11	computational	computational	ADJ
admet-2772	714	12	modeling	modeling	NOUN
admet-2772	714	13	.	.	PUNCT
admet-2772	715	1	nucleic	nucleic	ADJ
admet-2772	715	2	acids	acid	NOUN
admet-2772	715	3	research	research	NOUN
admet-2772	715	4	49	49	NUM
admet-2772	715	5	(	(	PUNCT
admet-2772	715	6	2021	2021	NUM
admet-2772	715	7	)	)	PUNCT
admet-2772	716	1	d1358	d1358	NOUN
admet-2772	716	2	-	-	PUNCT
admet-2772	716	3	d1364	d1364	PROPN
admet-2772	716	4	.	.	PUNCT
admet-2772	717	1	https://doi.org/10.1093/nar/gkaa990	https://doi.org/10.1093/nar/gkaa990	PROPN
admet-2772	717	2	[	[	X
admet-2772	717	3	22	22	NUM
admet-2772	717	4	]	]	X
admet-2772	717	5	e.	e.	PROPN
admet-2772	717	6	pihan	pihan	PROPN
admet-2772	717	7	,	,	PUNCT
admet-2772	717	8	l.	l.	PROPN
admet-2772	717	9	colliandre	colliandre	PROPN
admet-2772	717	10	,	,	PUNCT
admet-2772	717	11	j.f	j.f	PROPN
admet-2772	717	12	.	.	PROPN
admet-2772	717	13	guichou	guichou	PROPN
admet-2772	717	14	,	,	PUNCT
admet-2772	717	15	d.	d.	PROPN
admet-2772	717	16	douguet	douguet	PROPN
admet-2772	717	17	.	.	PUNCT
admet-2772	718	1	e	e	X
admet-2772	718	2	-	-	NOUN
admet-2772	718	3	drug3d	drug3d	ADJ
admet-2772	718	4	:	:	PUNCT
admet-2772	718	5	3d	3d	NUM
admet-2772	718	6	structure	structure	NOUN
admet-2772	718	7	collections	collection	NOUN
admet-2772	718	8	dedicated	dedicate	VERB
admet-2772	718	9	to	to	ADP
admet-2772	718	10	drug	drug	NOUN
admet-2772	718	11	repurposing	repurpose	VERB
admet-2772	718	12	and	and	CCONJ
admet-2772	718	13	fragment	fragment	NOUN
admet-2772	718	14	-	-	PUNCT
admet-2772	718	15	based	base	VERB
admet-2772	718	16	drug	drug	NOUN
admet-2772	718	17	design	design	NOUN
admet-2772	718	18	.	.	PUNCT
admet-2772	719	1	bioinformatics	bioinformatic	NOUN
admet-2772	719	2	28	28	NUM
admet-2772	719	3	(	(	PUNCT
admet-2772	719	4	2012	2012	NUM
admet-2772	719	5	)	)	PUNCT
admet-2772	719	6	1540	1540	NUM
admet-2772	719	7	-	-	SYM
admet-2772	719	8	1541	1541	NUM
admet-2772	719	9	.	.	PUNCT
admet-2772	720	1	https://doi.org/10.1093/bioinformatics/bts186	https://doi.org/10.1093/bioinformatics/bts186	ADJ
admet-2772	720	2	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	720	3	https://doi.org/10.1016/c2020-0-03079-3	https://doi.org/10.1016/c2020-0-03079-3	PROPN
admet-2772	720	4	https://doi.org/10.1016/j.apsb.2022.02.002	https://doi.org/10.1016/j.apsb.2022.02.002	NOUN
admet-2772	720	5	https://doi.org/10.1080/17460441.2021.1909567	https://doi.org/10.1080/17460441.2021.1909567	PROPN
admet-2772	720	6	https://doi.org/10.1016/j.tips.2019.05.005	https://doi.org/10.1016/j.tips.2019.05.005	VERB
admet-2772	720	7	https://doi.org/10.1016/bs.armc.2017.08.004	https://doi.org/10.1016/bs.armc.2017.08.004	NOUN
admet-2772	720	8	https://doi.org/10.1007/s13205-022-03165-8	https://doi.org/10.1007/s13205-022-03165-8	PROPN
admet-2772	720	9	https://doi.org/10.1371/journal.pone.0187271	https://doi.org/10.1371/journal.pone.0187271	VERB
admet-2772	720	10	https://doi.org/10.3389/fddsv.2023.1201419	https://doi.org/10.3389/fddsv.2023.1201419	PROPN
admet-2772	720	11	https://doi.org/10.3389/fchem.2020.00726	https://doi.org/10.3389/fchem.2020.00726	PROPN
admet-2772	720	12	https://doi.org/10.3389/fphar.2019.01586	https://doi.org/10.3389/fphar.2019.01586	PROPN
admet-2772	720	13	https://doi.org/10.3390/ijms19082358	https://doi.org/10.3390/ijms19082358	NOUN
admet-2772	721	1	https://doi.org/10.1016/j.gltp.2022.04.020	https://doi.org/10.1016/j.gltp.2022.04.020	X
admet-2772	721	2	https://doi.org/10.1109/inc457730.2023.10262824	https://doi.org/10.1109/inc457730.2023.10262824	PROPN
admet-2772	721	3	https://doi.org/10.1016/j.eswa.2023.119806	https://doi.org/10.1016/j.eswa.2023.119806	PROPN
admet-2772	721	4	https://doi.org/10.1007/s00204-022-03299-x	https://doi.org/10.1007/s00204-022-03299-x	NOUN
admet-2772	721	5	https://doi.org/10.1093/nar/gkaa990	https://doi.org/10.1093/nar/gkaa990	NOUN
admet-2772	721	6	https://doi.org/10.1093/bioinformatics/bts186	https://doi.org/10.1093/bioinformatics/bts186	ADJ
admet-2772	721	7	m.	m.	PROPN
admet-2772	721	8	venkataraman	venkataraman	PROPN
admet-2772	721	9	et	et	PROPN
admet-2772	721	10	al	al	PROPN
admet-2772	721	11	.	.	PROPN
admet-2772	721	12	admet	admet	PROPN
admet-2772	721	13	&	&	CCONJ
admet-2772	721	14	dmpk	dmpk	PROPN
admet-2772	721	15	13(3	13(3	NUM
admet-2772	721	16	)	)	PUNCT
admet-2772	721	17	(	(	PUNCT
admet-2772	721	18	2025	2025	NUM
admet-2772	721	19	)	)	PUNCT
admet-2772	721	20	2772	2772	NUM
admet-2772	721	21	26	26	NUM
admet-2772	722	1	[	[	X
admet-2772	722	2	23	23	NUM
admet-2772	722	3	]	]	X
admet-2772	722	4	d.s	d.s	PROPN
admet-2772	722	5	.	.	PROPN
admet-2772	722	6	wishart	wishart	PROPN
admet-2772	722	7	,	,	PUNCT
admet-2772	722	8	y.d	y.d	PROPN
admet-2772	722	9	.	.	PROPN
admet-2772	722	10	feunang	feunang	PROPN
admet-2772	722	11	,	,	PUNCT
admet-2772	722	12	a.c	a.c	PROPN
admet-2772	722	13	.	.	PROPN
admet-2772	722	14	guo	guo	PROPN
admet-2772	722	15	,	,	PUNCT
admet-2772	722	16	e.j	e.j	PROPN
admet-2772	722	17	.	.	PROPN
admet-2772	722	18	lo	lo	PROPN
admet-2772	722	19	,	,	PUNCT
admet-2772	722	20	a.	a.	NOUN
admet-2772	722	21	marcu	marcu	PROPN
admet-2772	722	22	,	,	PUNCT
admet-2772	722	23	j.r	j.r	PROPN
admet-2772	722	24	.	.	PROPN
admet-2772	722	25	grant	grant	PROPN
admet-2772	722	26	,	,	PUNCT
admet-2772	722	27	t.	t.	PROPN
admet-2772	722	28	sajed	sajed	PROPN
admet-2772	722	29	,	,	PUNCT
admet-2772	722	30	d.	d.	PROPN
admet-2772	722	31	johnson	johnson	PROPN
admet-2772	722	32	,	,	PUNCT
admet-2772	722	33	c.	c.	PROPN
admet-2772	722	34	li	li	PROPN
admet-2772	722	35	,	,	PUNCT
admet-2772	722	36	z.	z.	PROPN
admet-2772	722	37	sayeeda	sayeeda	PROPN
admet-2772	722	38	,	,	PUNCT
admet-2772	722	39	n.	n.	PROPN
admet-2772	722	40	assempour	assempour	PROPN
admet-2772	722	41	,	,	PUNCT
admet-2772	722	42	i.	i.	PROPN
admet-2772	722	43	iynkkaran	iynkkaran	PROPN
admet-2772	722	44	,	,	PUNCT
admet-2772	722	45	y.	y.	PROPN
admet-2772	722	46	liu	liu	PROPN
admet-2772	722	47	,	,	PUNCT
admet-2772	722	48	a.	a.	PROPN
admet-2772	722	49	maciejewski	maciejewski	PROPN
admet-2772	722	50	,	,	PUNCT
admet-2772	722	51	n.	n.	PROPN
admet-2772	722	52	gale	gale	PROPN
admet-2772	722	53	,	,	PUNCT
admet-2772	722	54	a.	a.	PROPN
admet-2772	722	55	wilson	wilson	PROPN
admet-2772	722	56	,	,	PUNCT
admet-2772	722	57	l.	l.	PROPN
admet-2772	722	58	chin	chin	PROPN
admet-2772	722	59	,	,	PUNCT
admet-2772	722	60	r.	r.	PROPN
admet-2772	722	61	cummings	cummings	PROPN
admet-2772	722	62	,	,	PUNCT
admet-2772	722	63	di	di	NOUN
admet-2772	722	64	.	.	PROPN
admet-2772	722	65	le	le	PROPN
admet-2772	722	66	,	,	PUNCT
admet-2772	722	67	a.	a.	PROPN
admet-2772	722	68	pon	pon	PROPN
admet-2772	722	69	,	,	PUNCT
admet-2772	722	70	c.	c.	PROPN
admet-2772	722	71	knox	knox	PROPN
admet-2772	722	72	,	,	PUNCT
admet-2772	722	73	m.	m.	PROPN
admet-2772	722	74	wilson	wilson	PROPN
admet-2772	722	75	.	.	PUNCT
admet-2772	723	1	drugbank	drugbank	VERB
admet-2772	723	2	5.0	5.0	NUM
admet-2772	723	3	:	:	PUNCT
admet-2772	723	4	a	a	DET
admet-2772	723	5	major	major	ADJ
admet-2772	723	6	update	update	NOUN
admet-2772	723	7	to	to	ADP
admet-2772	723	8	the	the	DET
admet-2772	723	9	drugbank	drugbank	NOUN
admet-2772	723	10	database	database	NOUN
admet-2772	723	11	for	for	ADP
admet-2772	723	12	2018	2018	NUM
admet-2772	723	13	.	.	PUNCT
admet-2772	724	1	nucleic	nucleic	ADJ
admet-2772	724	2	acids	acid	NOUN
admet-2772	724	3	research	research	NOUN
admet-2772	724	4	46	46	NUM
admet-2772	724	5	(	(	PUNCT
admet-2772	724	6	2018	2018	NUM
admet-2772	724	7	)	)	PUNCT
admet-2772	725	1	d1074	d1074	PROPN
admet-2772	725	2	-	-	PROPN
admet-2772	725	3	d1082	d1082	PROPN
admet-2772	725	4	.	.	PUNCT
admet-2772	726	1	https://doi.org/10.1093/nar/gkx1037	https://doi.org/10.1093/nar/gkx1037	NUM
admet-2772	727	1	[	[	X
admet-2772	727	2	24	24	NUM
admet-2772	727	3	]	]	PUNCT
admet-2772	727	4	a.	a.	NOUN
admet-2772	727	5	gaulton	gaulton	PROPN
admet-2772	727	6	,	,	PUNCT
admet-2772	727	7	l.j	l.j	PROPN
admet-2772	727	8	.	.	PROPN
admet-2772	727	9	bellis	bellis	PROPN
admet-2772	727	10	,	,	PUNCT
admet-2772	727	11	a.p	a.p	PROPN
admet-2772	727	12	.	.	PROPN
admet-2772	727	13	bento	bento	PROPN
admet-2772	727	14	,	,	PUNCT
admet-2772	727	15	j.	j.	PROPN
admet-2772	727	16	chambers	chambers	PROPN
admet-2772	727	17	,	,	PUNCT
admet-2772	727	18	m.	m.	NOUN
admet-2772	727	19	davies	davy	NOUN
admet-2772	727	20	,	,	PUNCT
admet-2772	727	21	a.	a.	NOUN
admet-2772	727	22	hersey	hersey	PROPN
admet-2772	727	23	,	,	PUNCT
admet-2772	727	24	y.	y.	PROPN
admet-2772	727	25	light	light	PROPN
admet-2772	727	26	,	,	PUNCT
admet-2772	727	27	s.	s.	PROPN
admet-2772	727	28	mcglinchey	mcglinchey	PROPN
admet-2772	727	29	,	,	PUNCT
admet-2772	727	30	d.	d.	PROPN
admet-2772	727	31	michalovich	michalovich	PROPN
admet-2772	727	32	,	,	PUNCT
admet-2772	727	33	b.	b.	PROPN
admet-2772	727	34	al	al	PROPN
admet-2772	727	35	-	-	PUNCT
admet-2772	727	36	lazikani	lazikani	PROPN
admet-2772	727	37	,	,	PUNCT
admet-2772	727	38	j.p	j.p	PROPN
admet-2772	727	39	.	.	PROPN
admet-2772	727	40	overington	overington	PROPN
admet-2772	727	41	.	.	PUNCT
admet-2772	728	1	chembl	chembl	NOUN
admet-2772	728	2	:	:	PUNCT
admet-2772	728	3	a	a	DET
admet-2772	728	4	large	large	ADJ
admet-2772	728	5	-	-	PUNCT
admet-2772	728	6	scale	scale	NOUN
admet-2772	728	7	bioactivity	bioactivity	NOUN
admet-2772	728	8	database	database	NOUN
admet-2772	728	9	for	for	ADP
admet-2772	728	10	drug	drug	NOUN
admet-2772	728	11	discovery	discovery	NOUN
admet-2772	728	12	.	.	PUNCT
admet-2772	729	1	nucleic	nucleic	ADJ
admet-2772	729	2	acids	acid	NOUN
admet-2772	729	3	research	research	NOUN
admet-2772	729	4	40	40	NUM
admet-2772	729	5	(	(	PUNCT
admet-2772	729	6	2012	2012	NUM
admet-2772	729	7	)	)	PUNCT
admet-2772	729	8	d1100	d1100	PROPN
admet-2772	729	9	-	-	PUNCT
admet-2772	729	10	d1107	d1107	PROPN
admet-2772	729	11	.	.	PUNCT
admet-2772	730	1	https://doi.org/10.1093/nar/gkr777	https://doi.org/10.1093/nar/gkr777	PROPN
admet-2772	730	2	[	[	X
admet-2772	730	3	25	25	NUM
admet-2772	730	4	]	]	X
admet-2772	730	5	y.	y.	PROPN
admet-2772	730	6	zhou	zhou	PROPN
admet-2772	730	7	,	,	PUNCT
admet-2772	730	8	y.	y.	PROPN
admet-2772	730	9	zhang	zhang	PROPN
admet-2772	730	10	,	,	PUNCT
admet-2772	730	11	d.	d.	PROPN
admet-2772	730	12	zhao	zhao	PROPN
admet-2772	730	13	,	,	PUNCT
admet-2772	730	14	x.	x.	PROPN
admet-2772	730	15	yu	yu	PROPN
admet-2772	730	16	,	,	PUNCT
admet-2772	730	17	x.	x.	PROPN
admet-2772	730	18	shen	shen	PROPN
admet-2772	730	19	,	,	PUNCT
admet-2772	730	20	y.	y.	PROPN
admet-2772	730	21	zhou	zhou	PROPN
admet-2772	730	22	,	,	PUNCT
admet-2772	730	23	s.	s.	PROPN
admet-2772	730	24	wang	wang	PROPN
admet-2772	730	25	,	,	PUNCT
admet-2772	730	26	y.	y.	PROPN
admet-2772	730	27	qiu	qiu	PROPN
admet-2772	730	28	,	,	PUNCT
admet-2772	730	29	y.	y.	PROPN
admet-2772	730	30	chen	chen	PROPN
admet-2772	730	31	,	,	PUNCT
admet-2772	730	32	f.	f.	PROPN
admet-2772	730	33	zhu	zhu	PROPN
admet-2772	730	34	.	.	PUNCT
admet-2772	731	1	t	t	PROPN
admet-2772	731	2	td	td	NOUN
admet-2772	731	3	:	:	PUNCT
admet-2772	731	4	ther	ther	PROPN
admet-2772	731	5	apeutic	apeutic	ADJ
admet-2772	731	6	targ	targ	PROPN
admet-2772	731	7	et	et	PROPN
admet-2772	731	8	d	d	PROPN
admet-2772	731	9	atabase	atabase	PROPN
admet-2772	731	10	describing	describe	VERB
admet-2772	731	11	tar	tar	NOUN
admet-2772	731	12	get	get	VERB
admet-2772	731	13	drugg	drugg	NOUN
admet-2772	731	14	ability	ability	NOUN
admet-2772	731	15	inf	inf	NOUN
admet-2772	731	16	ormation	ormation	NOUN
admet-2772	731	17	.	.	PUNCT
admet-2772	732	1	nucleic	nucleic	ADJ
admet-2772	732	2	acids	acid	NOUN
admet-2772	732	3	research	research	NOUN
admet-2772	732	4	52	52	NUM
admet-2772	732	5	(	(	PUNCT
admet-2772	732	6	2024	2024	NUM
admet-2772	732	7	)	)	PUNCT
admet-2772	732	8	d1465	d1465	NOUN
admet-2772	732	9	-	-	NOUN
admet-2772	732	10	d1477	d1477	NOUN
admet-2772	732	11	.	.	PUNCT
admet-2772	733	1	https://doi.org/10.1093/nar/gkad751	https://doi.org/10.1093/nar/gkad751	PROPN
admet-2772	734	1	[	[	X
admet-2772	734	2	26	26	NUM
admet-2772	734	3	]	]	X
admet-2772	734	4	r.r	r.r	PROPN
admet-2772	734	5	.	.	PROPN
admet-2772	734	6	sayre	sayre	PROPN
admet-2772	734	7	,	,	PUNCT
admet-2772	734	8	j.f	j.f	PROPN
admet-2772	734	9	.	.	PROPN
admet-2772	734	10	wambaugh	wambaugh	PROPN
admet-2772	734	11	,	,	PUNCT
admet-2772	734	12	c.m	c.m	PROPN
admet-2772	734	13	.	.	PROPN
admet-2772	734	14	grulke	grulke	ADJ
admet-2772	734	15	.	.	PUNCT
admet-2772	735	1	database	database	NOUN
admet-2772	735	2	of	of	ADP
admet-2772	735	3	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	735	4	time	time	NOUN
admet-2772	735	5	-	-	PUNCT
admet-2772	735	6	series	series	NOUN
admet-2772	735	7	data	datum	NOUN
admet-2772	735	8	and	and	CCONJ
admet-2772	735	9	parameters	parameter	NOUN
admet-2772	735	10	for	for	ADP
admet-2772	735	11	144	144	NUM
admet-2772	735	12	environmental	environmental	ADJ
admet-2772	735	13	chemicals	chemical	NOUN
admet-2772	735	14	.	.	PUNCT
admet-2772	736	1	scientific	scientific	ADJ
admet-2772	736	2	data	datum	NOUN
admet-2772	736	3	7	7	NUM
admet-2772	736	4	(	(	PUNCT
admet-2772	736	5	2020	2020	NUM
admet-2772	736	6	)	)	PUNCT
admet-2772	736	7	122	122	NUM
admet-2772	736	8	.	.	PUNCT
admet-2772	736	9	https://doi.org/10.1038/s41597-020-0455-1	https://doi.org/10.1038/s41597-020-0455-1	PUNCT
admet-2772	737	1	[	[	X
admet-2772	737	2	27	27	NUM
admet-2772	737	3	]	]	PUNCT
admet-2772	737	4	s.	s.	PROPN
admet-2772	737	5	kim	kim	PROPN
admet-2772	737	6	,	,	PUNCT
admet-2772	737	7	j.	j.	PROPN
admet-2772	737	8	chen	chen	PROPN
admet-2772	737	9	,	,	PUNCT
admet-2772	737	10	t.	t.	PROPN
admet-2772	737	11	cheng	cheng	PROPN
admet-2772	737	12	,	,	PUNCT
admet-2772	737	13	a.	a.	PROPN
admet-2772	737	14	gindulyte	gindulyte	PROPN
admet-2772	737	15	,	,	PUNCT
admet-2772	737	16	j.	j.	PROPN
admet-2772	737	17	he	he	PROPN
admet-2772	737	18	,	,	PUNCT
admet-2772	737	19	s.	s.	PROPN
admet-2772	737	20	he	he	PRON
admet-2772	737	21	,	,	PUNCT
admet-2772	737	22	q.	q.	PROPN
admet-2772	737	23	li	li	PROPN
admet-2772	737	24	,	,	PUNCT
admet-2772	737	25	b.a	b.a	PROPN
admet-2772	737	26	.	.	PROPN
admet-2772	737	27	shoemaker	shoemaker	PROPN
admet-2772	737	28	,	,	PUNCT
admet-2772	737	29	p.a	p.a	PROPN
admet-2772	737	30	.	.	PROPN
admet-2772	737	31	thiessen	thiessen	PROPN
admet-2772	737	32	,	,	PUNCT
admet-2772	737	33	b.	b.	PROPN
admet-2772	737	34	yu	yu	PROPN
admet-2772	737	35	,	,	PUNCT
admet-2772	737	36	l.	l.	PROPN
admet-2772	737	37	zaslavsky	zaslavsky	PROPN
admet-2772	737	38	,	,	PUNCT
admet-2772	737	39	j.	j.	PROPN
admet-2772	737	40	zhang	zhang	PROPN
admet-2772	737	41	,	,	PUNCT
admet-2772	737	42	e.e	e.e	PROPN
admet-2772	737	43	.	.	PROPN
admet-2772	737	44	bolton	bolton	PROPN
admet-2772	737	45	.	.	PUNCT
admet-2772	738	1	pubchem	pubchem	NOUN
admet-2772	738	2	2019	2019	NUM
admet-2772	738	3	update	update	NOUN
admet-2772	738	4	:	:	PUNCT
admet-2772	738	5	improved	improved	ADJ
admet-2772	738	6	access	access	NOUN
admet-2772	738	7	to	to	ADP
admet-2772	738	8	chemical	chemical	NOUN
admet-2772	738	9	data	datum	NOUN
admet-2772	738	10	.	.	PUNCT
admet-2772	739	1	nucleic	nucleic	ADJ
admet-2772	739	2	acids	acid	NOUN
admet-2772	739	3	research	research	NOUN
admet-2772	739	4	47	47	NUM
admet-2772	739	5	(	(	PUNCT
admet-2772	739	6	2019	2019	NUM
admet-2772	739	7	)	)	PUNCT
admet-2772	739	8	d1102	d1102	PROPN
admet-2772	739	9	-	-	PUNCT
admet-2772	739	10	d1109	d1109	PROPN
admet-2772	739	11	.	.	PUNCT
admet-2772	740	1	https://doi.org/10.1093/nar/gky1033	https://doi.org/10.1093/nar/gky1033	PROPN
admet-2772	741	1	[	[	X
admet-2772	741	2	28	28	NUM
admet-2772	741	3	]	]	X
admet-2772	741	4	t.	t.	PROPN
admet-2772	741	5	sterling	sterling	PROPN
admet-2772	741	6	,	,	PUNCT
admet-2772	741	7	j.j	j.j	PROPN
admet-2772	741	8	.	.	PROPN
admet-2772	741	9	irwin	irwin	PROPN
admet-2772	741	10	.	.	PUNCT
admet-2772	741	11	zinc	zinc	NOUN
admet-2772	741	12	15	15	NUM
admet-2772	741	13	ligand	ligand	NOUN
admet-2772	741	14	discovery	discovery	NOUN
admet-2772	741	15	for	for	ADP
admet-2772	741	16	everyone	everyone	PRON
admet-2772	741	17	.	.	PUNCT
admet-2772	742	1	journal	journal	PROPN
admet-2772	742	2	of	of	ADP
admet-2772	742	3	chemical	chemical	ADJ
admet-2772	742	4	information	information	NOUN
admet-2772	742	5	and	and	CCONJ
admet-2772	742	6	modeling	model	VERB
admet-2772	742	7	55	55	NUM
admet-2772	742	8	(	(	PUNCT
admet-2772	742	9	2015	2015	NUM
admet-2772	742	10	)	)	PUNCT
admet-2772	742	11	2324	2324	NUM
admet-2772	742	12	-	-	SYM
admet-2772	742	13	2337	2337	NUM
admet-2772	742	14	.	.	PUNCT
admet-2772	743	1	https://doi.org/10.1021/acs.jcim.5b00559	https://doi.org/10.1021/acs.jcim.5b00559	VERB
admet-2772	743	2	[	[	X
admet-2772	743	3	29	29	NUM
admet-2772	743	4	]	]	PUNCT
admet-2772	743	5	s.	s.	PROPN
admet-2772	743	6	preissner	preissner	PROPN
admet-2772	743	7	,	,	PUNCT
admet-2772	743	8	k.	k.	PROPN
admet-2772	743	9	kroll	kroll	PROPN
admet-2772	743	10	,	,	PUNCT
admet-2772	743	11	m.	m.	NOUN
admet-2772	743	12	dunkel	dunkel	NOUN
admet-2772	743	13	,	,	PUNCT
admet-2772	743	14	c.	c.	NOUN
admet-2772	743	15	senger	senger	NOUN
admet-2772	743	16	,	,	PUNCT
admet-2772	743	17	g.	g.	PROPN
admet-2772	743	18	goldsobel	goldsobel	PROPN
admet-2772	743	19	,	,	PUNCT
admet-2772	743	20	d.	d.	PROPN
admet-2772	743	21	kuzman	kuzman	PROPN
admet-2772	743	22	,	,	PUNCT
admet-2772	743	23	s.	s.	PROPN
admet-2772	743	24	guenther	guenther	PROPN
admet-2772	743	25	,	,	PUNCT
admet-2772	743	26	r.	r.	PROPN
admet-2772	743	27	winnenburg	winnenburg	PROPN
admet-2772	743	28	,	,	PUNCT
admet-2772	743	29	m.	m.	NOUN
admet-2772	743	30	schroeder	schroeder	PROPN
admet-2772	743	31	,	,	PUNCT
admet-2772	743	32	r.	r.	PROPN
admet-2772	743	33	preissner	preissner	PROPN
admet-2772	743	34	.	.	PUNCT
admet-2772	744	1	supercyp	supercyp	PROPN
admet-2772	744	2	:	:	PUNCT
admet-2772	744	3	a	a	DET
admet-2772	744	4	comprehensive	comprehensive	ADJ
admet-2772	744	5	database	database	NOUN
admet-2772	744	6	on	on	ADP
admet-2772	744	7	cytochrome	cytochrome	ADJ
admet-2772	744	8	p450	p450	PROPN
admet-2772	744	9	enzymes	enzyme	NOUN
admet-2772	744	10	including	include	VERB
admet-2772	744	11	a	a	DET
admet-2772	744	12	tool	tool	NOUN
admet-2772	744	13	for	for	ADP
admet-2772	744	14	analysis	analysis	NOUN
admet-2772	744	15	of	of	ADP
admet-2772	744	16	cyp	cyp	ADJ
admet-2772	744	17	-	-	PUNCT
admet-2772	744	18	drug	drug	NOUN
admet-2772	744	19	interactions	interaction	NOUN
admet-2772	744	20	.	.	PUNCT
admet-2772	745	1	nucleic	nucleic	ADJ
admet-2772	745	2	acids	acid	NOUN
admet-2772	745	3	research	research	NOUN
admet-2772	745	4	38	38	NUM
admet-2772	745	5	(	(	PUNCT
admet-2772	745	6	2009	2009	NUM
admet-2772	745	7	)	)	PUNCT
admet-2772	745	8	d237	d237	PROPN
admet-2772	745	9	-	-	PUNCT
admet-2772	745	10	d243	d243	PROPN
admet-2772	745	11	.	.	PUNCT
admet-2772	746	1	https://doi.org/10.1093/nar/gkp970	https://doi.org/10.1093/nar/gkp970	PROPN
admet-2772	747	1	[	[	X
admet-2772	747	2	30	30	NUM
admet-2772	747	3	]	]	X
admet-2772	747	4	y.	y.	PROPN
admet-2772	747	5	xu	xu	PROPN
admet-2772	747	6	,	,	PUNCT
admet-2772	747	7	x.	x.	PROPN
admet-2772	747	8	liu	liu	PROPN
admet-2772	747	9	,	,	PUNCT
admet-2772	747	10	w.	w.	PROPN
admet-2772	747	11	xia	xia	PROPN
admet-2772	747	12	,	,	PUNCT
admet-2772	747	13	j.	j.	PROPN
admet-2772	747	14	ge	ge	PROPN
admet-2772	747	15	,	,	PUNCT
admet-2772	747	16	c.w	c.w	PROPN
admet-2772	747	17	.	.	PROPN
admet-2772	747	18	ju	ju	PROPN
admet-2772	747	19	,	,	PUNCT
admet-2772	747	20	h.	h.	PROPN
admet-2772	747	21	zhang	zhang	PROPN
admet-2772	747	22	,	,	PUNCT
admet-2772	747	23	j.z.h	j.z.h	PROPN
admet-2772	747	24	.	.	PUNCT
admet-2772	747	25	zhang	zhang	PROPN
admet-2772	747	26	.	.	PUNCT
admet-2772	747	27	chemxtree	chemxtree	PROPN
admet-2772	747	28	:	:	PUNCT
admet-2772	747	29	a	a	DET
admet-2772	747	30	feature	feature	NOUN
admet-2772	747	31	-	-	PUNCT
admet-2772	747	32	enhanced	enhance	VERB
admet-2772	747	33	graph	graph	NOUN
admet-2772	747	34	neural	neural	ADJ
admet-2772	747	35	network	network	NOUN
admet-2772	747	36	-	-	PUNCT
admet-2772	747	37	neural	neural	ADJ
admet-2772	747	38	decision	decision	NOUN
admet-2772	747	39	tree	tree	NOUN
admet-2772	747	40	framework	framework	NOUN
admet-2772	747	41	for	for	ADP
admet-2772	747	42	admet	admet	PROPN
admet-2772	747	43	prediction	prediction	NOUN
admet-2772	747	44	.	.	PUNCT
admet-2772	748	1	journal	journal	PROPN
admet-2772	748	2	of	of	ADP
admet-2772	748	3	chemical	chemical	ADJ
admet-2772	748	4	information	information	NOUN
admet-2772	748	5	and	and	CCONJ
admet-2772	748	6	modeling	model	VERB
admet-2772	748	7	64(22	64(22	NUM
admet-2772	748	8	)	)	PUNCT
admet-2772	748	9	(	(	PUNCT
admet-2772	748	10	2024	2024	NUM
admet-2772	748	11	)	)	PUNCT
admet-2772	748	12	8440	8440	NUM
admet-2772	748	13	-	-	SYM
admet-2772	748	14	8452	8452	NUM
admet-2772	748	15	.	.	PUNCT
admet-2772	749	1	https://doi.org/10.1021/acs.jcim.4c01186	https://doi.org/10.1021/acs.jcim.4c01186	X
admet-2772	749	2	[	[	X
admet-2772	749	3	31	31	NUM
admet-2772	749	4	]	]	X
admet-2772	749	5	e.n	e.n	PROPN
admet-2772	749	6	.	.	PROPN
admet-2772	749	7	feinberg	feinberg	PROPN
admet-2772	749	8	,	,	PUNCT
admet-2772	749	9	e.	e.	PROPN
admet-2772	749	10	joshi	joshi	PROPN
admet-2772	749	11	,	,	PUNCT
admet-2772	749	12	v.s.	v.s.	ADJ
admet-2772	749	13	pande	pande	PROPN
admet-2772	749	14	,	,	PUNCT
admet-2772	749	15	a.c	a.c	PROPN
admet-2772	749	16	.	.	PROPN
admet-2772	749	17	cheng	cheng	PROPN
admet-2772	749	18	.	.	PUNCT
admet-2772	750	1	improvement	improvement	NOUN
admet-2772	750	2	in	in	ADP
admet-2772	750	3	admet	admet	PROPN
admet-2772	750	4	prediction	prediction	NOUN
admet-2772	750	5	with	with	ADP
admet-2772	750	6	multitask	multitask	ADJ
admet-2772	750	7	deep	deep	ADJ
admet-2772	750	8	featurization	featurization	NOUN
admet-2772	750	9	.	.	PUNCT
admet-2772	751	1	journal	journal	NOUN
admet-2772	751	2	of	of	ADP
admet-2772	751	3	medicinal	medicinal	ADJ
admet-2772	751	4	chemistry	chemistry	NOUN
admet-2772	751	5	63	63	NUM
admet-2772	751	6	(	(	PUNCT
admet-2772	751	7	2020	2020	NUM
admet-2772	751	8	)	)	PUNCT
admet-2772	751	9	8835	8835	NUM
admet-2772	751	10	-	-	SYM
admet-2772	751	11	8848	8848	NUM
admet-2772	751	12	.	.	PUNCT
admet-2772	752	1	https://doi.org/10.1021/acs.jmedchem.9b02187	https://doi.org/10.1021/acs.jmedchem.9b02187	X
admet-2772	753	1	[	[	X
admet-2772	753	2	32	32	NUM
admet-2772	753	3	]	]	PUNCT
admet-2772	753	4	m.	m.	NOUN
admet-2772	753	5	malekipirbazari	malekipirbazari	PROPN
admet-2772	753	6	,	,	PUNCT
admet-2772	753	7	v.	v.	PROPN
admet-2772	753	8	aksakalli	aksakalli	PROPN
admet-2772	753	9	,	,	PUNCT
admet-2772	753	10	w.	w.	PROPN
admet-2772	753	11	shafqat	shafqat	PROPN
admet-2772	753	12	,	,	PUNCT
admet-2772	753	13	a.	a.	NOUN
admet-2772	753	14	eberhard	eberhard	NOUN
admet-2772	753	15	.	.	PUNCT
admet-2772	754	1	performance	performance	NOUN
admet-2772	754	2	comparison	comparison	NOUN
admet-2772	754	3	of	of	ADP
admet-2772	754	4	feature	feature	NOUN
admet-2772	754	5	selection	selection	NOUN
admet-2772	754	6	and	and	CCONJ
admet-2772	754	7	extraction	extraction	NOUN
admet-2772	754	8	methods	method	NOUN
admet-2772	754	9	with	with	ADP
admet-2772	754	10	random	random	ADJ
admet-2772	754	11	instance	instance	NOUN
admet-2772	754	12	selection	selection	NOUN
admet-2772	754	13	.	.	PUNCT
admet-2772	755	1	expert	expert	NOUN
admet-2772	755	2	systems	system	NOUN
admet-2772	755	3	with	with	ADP
admet-2772	755	4	applications	application	NOUN
admet-2772	755	5	179	179	NUM
admet-2772	755	6	(	(	PUNCT
admet-2772	755	7	2021	2021	NUM
admet-2772	755	8	)	)	PUNCT
admet-2772	755	9	115072	115072	NUM
admet-2772	755	10	.	.	PUNCT
admet-2772	756	1	https://doi.org/10.1016/j.eswa.2021.115072	https://doi.org/10.1016/j.eswa.2021.115072	ADJ
admet-2772	756	2	[	[	X
admet-2772	756	3	33	33	NUM
admet-2772	756	4	]	]	PUNCT
admet-2772	756	5	b.	b.	PROPN
admet-2772	756	6	venkatesh	venkatesh	PROPN
admet-2772	756	7	,	,	PUNCT
admet-2772	756	8	j.	j.	PROPN
admet-2772	756	9	anuradha	anuradha	PROPN
admet-2772	756	10	.	.	PUNCT
admet-2772	757	1	a	a	DET
admet-2772	757	2	review	review	NOUN
admet-2772	757	3	of	of	ADP
admet-2772	757	4	feature	feature	NOUN
admet-2772	757	5	selection	selection	NOUN
admet-2772	757	6	and	and	CCONJ
admet-2772	757	7	its	its	PRON
admet-2772	757	8	methods	method	NOUN
admet-2772	757	9	.	.	PUNCT
admet-2772	758	1	cybernetics	cybernetic	NOUN
admet-2772	758	2	and	and	CCONJ
admet-2772	758	3	information	information	NOUN
admet-2772	758	4	technologies	technology	NOUN
admet-2772	758	5	19	19	NUM
admet-2772	758	6	(	(	PUNCT
admet-2772	758	7	2019	2019	NUM
admet-2772	758	8	)	)	PUNCT
admet-2772	758	9	3	3	NUM
admet-2772	758	10	-	-	SYM
admet-2772	758	11	26	26	NUM
admet-2772	758	12	.	.	PUNCT
admet-2772	759	1	https://doi.org/10.2478/cait-2019-0001	https://doi.org/10.2478/cait-2019-0001	X
admet-2772	759	2	[	[	X
admet-2772	759	3	34	34	NUM
admet-2772	759	4	]	]	X
admet-2772	759	5	n.	n.	PROPN
admet-2772	759	6	sánchez	sánchez	PROPN
admet-2772	759	7	-	-	PUNCT
admet-2772	759	8	maroño	maroño	PROPN
admet-2772	759	9	,	,	PUNCT
admet-2772	759	10	a.	a.	NOUN
admet-2772	759	11	alonso	alonso	PROPN
admet-2772	759	12	-	-	PUNCT
admet-2772	759	13	betanzos	betanzo	NOUN
admet-2772	759	14	,	,	PUNCT
admet-2772	759	15	m.	m.	NOUN
admet-2772	759	16	tombilla	tombilla	NOUN
admet-2772	759	17	-	-	PUNCT
admet-2772	759	18	sanromán	sanromán	NOUN
admet-2772	759	19	.	.	PUNCT
admet-2772	760	1	filter	filter	NOUN
admet-2772	760	2	methods	method	NOUN
admet-2772	760	3	for	for	ADP
admet-2772	760	4	feature	feature	NOUN
admet-2772	760	5	selection	selection	NOUN
admet-2772	760	6	a	a	DET
admet-2772	760	7	comparative	comparative	ADJ
admet-2772	760	8	study	study	NOUN
admet-2772	760	9	.	.	PUNCT
admet-2772	761	1	lecture	lecture	NOUN
admet-2772	761	2	notes	note	NOUN
admet-2772	761	3	in	in	ADP
admet-2772	761	4	computer	computer	NOUN
admet-2772	761	5	science	science	NOUN
admet-2772	761	6	(	(	PUNCT
admet-2772	761	7	including	include	VERB
admet-2772	761	8	subseries	subserie	NOUN
admet-2772	761	9	lecture	lecture	VERB
admet-2772	761	10	notes	note	NOUN
admet-2772	761	11	in	in	ADP
admet-2772	761	12	artificial	artificial	ADJ
admet-2772	761	13	intelligence	intelligence	NOUN
admet-2772	761	14	and	and	CCONJ
admet-2772	761	15	lecture	lecture	NOUN
admet-2772	761	16	notes	note	NOUN
admet-2772	761	17	in	in	ADP
admet-2772	761	18	bioinformatics	bioinformatics	NOUN
admet-2772	761	19	)	)	PUNCT
admet-2772	761	20	4881	4881	NUM
admet-2772	761	21	lncs	lnc	NOUN
admet-2772	761	22	(	(	PUNCT
admet-2772	761	23	2007	2007	NUM
admet-2772	761	24	)	)	PUNCT
admet-2772	761	25	178	178	NUM
admet-2772	761	26	-	-	SYM
admet-2772	761	27	187	187	NUM
admet-2772	761	28	.	.	PUNCT
admet-2772	761	29	https://doi.org/10.1007/978-3-540-77226-2_19	https://doi.org/10.1007/978-3-540-77226-2_19	PART
admet-2772	762	1	[	[	X
admet-2772	762	2	35	35	NUM
admet-2772	762	3	]	]	X
admet-2772	762	4	s.s.s.j	s.s.s.j	PROPN
admet-2772	762	5	.	.	PROPN
admet-2772	762	6	ahmed	ahmed	PROPN
admet-2772	762	7	,	,	PUNCT
admet-2772	762	8	v.	v.	PROPN
admet-2772	762	9	ramakrishnan	ramakrishnan	PROPN
admet-2772	762	10	.	.	PUNCT
admet-2772	763	1	systems	system	NOUN
admet-2772	763	2	biological	biological	ADJ
admet-2772	763	3	approach	approach	NOUN
admet-2772	763	4	of	of	ADP
admet-2772	763	5	molecular	molecular	ADJ
admet-2772	763	6	descriptors	descriptor	NOUN
admet-2772	763	7	connectivity	connectivity	NOUN
admet-2772	763	8	:	:	PUNCT
admet-2772	763	9	optimal	optimal	ADJ
admet-2772	763	10	descriptors	descriptor	NOUN
admet-2772	763	11	for	for	ADP
admet-2772	763	12	oral	oral	ADJ
admet-2772	763	13	bioavailability	bioavailability	NOUN
admet-2772	763	14	prediction	prediction	NOUN
admet-2772	763	15	.	.	PUNCT
admet-2772	764	1	plos	plos	PROPN
admet-2772	764	2	one	one	NUM
admet-2772	764	3	7	7	NUM
admet-2772	764	4	(	(	PUNCT
admet-2772	764	5	2012	2012	NUM
admet-2772	764	6	)	)	PUNCT
admet-2772	764	7	e40654	e40654	PROPN
admet-2772	764	8	.	.	PUNCT
admet-2772	765	1	https://doi.org/10.1371/journal.pone.0040654	https://doi.org/10.1371/journal.pone.0040654	PROPN
admet-2772	766	1	[	[	X
admet-2772	766	2	36	36	NUM
admet-2772	766	3	]	]	X
admet-2772	766	4	i.	i.	NOUN
admet-2772	766	5	tsamardinos	tsamardinos	PROPN
admet-2772	766	6	,	,	PUNCT
admet-2772	766	7	g.	g.	PROPN
admet-2772	766	8	borboudakis	borboudakis	PROPN
admet-2772	766	9	,	,	PUNCT
admet-2772	766	10	p.	p.	PROPN
admet-2772	766	11	katsogridakis	katsogridakis	PROPN
admet-2772	766	12	,	,	PUNCT
admet-2772	766	13	p.	p.	PROPN
admet-2772	766	14	pratikakis	pratikakis	PROPN
admet-2772	766	15	,	,	PUNCT
admet-2772	766	16	v.	v.	ADP
admet-2772	766	17	christophides	christophide	NOUN
admet-2772	766	18	.	.	PUNCT
admet-2772	767	1	a	a	DET
admet-2772	767	2	greedy	greedy	ADJ
admet-2772	767	3	feature	feature	NOUN
admet-2772	767	4	selection	selection	NOUN
admet-2772	767	5	algorithm	algorithm	NOUN
admet-2772	767	6	for	for	ADP
admet-2772	767	7	big	big	ADJ
admet-2772	767	8	data	datum	NOUN
admet-2772	767	9	of	of	ADP
admet-2772	767	10	high	high	ADJ
admet-2772	767	11	dimensionality	dimensionality	NOUN
admet-2772	767	12	.	.	PUNCT
admet-2772	768	1	machine	machine	NOUN
admet-2772	768	2	learning	learn	VERB
admet-2772	768	3	108	108	NUM
admet-2772	768	4	(	(	PUNCT
admet-2772	768	5	2019	2019	NUM
admet-2772	768	6	)	)	PUNCT
admet-2772	768	7	149	149	NUM
admet-2772	768	8	-	-	SYM
admet-2772	768	9	202	202	NUM
admet-2772	768	10	.	.	PUNCT
admet-2772	768	11	https://doi.org/10.1007/s10994-018-5748-7	https://doi.org/10.1007/s10994-018-5748-7	PUNCT
admet-2772	769	1	[	[	X
admet-2772	769	2	37	37	NUM
admet-2772	769	3	]	]	X
admet-2772	769	4	h.	h.	PROPN
admet-2772	769	5	liu	liu	PROPN
admet-2772	769	6	,	,	PUNCT
admet-2772	769	7	m.	m.	NOUN
admet-2772	769	8	zhou	zhou	PROPN
admet-2772	769	9	,	,	PUNCT
admet-2772	769	10	q.	q.	PROPN
admet-2772	769	11	liu	liu	PROPN
admet-2772	769	12	.	.	PUNCT
admet-2772	770	1	an	an	DET
admet-2772	770	2	embedded	embed	VERB
admet-2772	770	3	feature	feature	NOUN
admet-2772	770	4	selection	selection	NOUN
admet-2772	770	5	method	method	NOUN
admet-2772	770	6	for	for	ADP
admet-2772	770	7	imbalanced	imbalanced	ADJ
admet-2772	770	8	data	datum	NOUN
admet-2772	770	9	classification	classification	NOUN
admet-2772	770	10	.	.	PUNCT
admet-2772	771	1	ieee	ieee	PROPN
admet-2772	771	2	/	/	SYM
admet-2772	771	3	caa	caa	PROPN
admet-2772	771	4	journal	journal	PROPN
admet-2772	771	5	of	of	ADP
admet-2772	771	6	automatica	automatica	PROPN
admet-2772	771	7	sinica	sinica	PROPN
admet-2772	771	8	6	6	NUM
admet-2772	771	9	(	(	PUNCT
admet-2772	771	10	2019	2019	NUM
admet-2772	771	11	)	)	PUNCT
admet-2772	771	12	703	703	NUM
admet-2772	771	13	-	-	SYM
admet-2772	771	14	715	715	NUM
admet-2772	771	15	.	.	PUNCT
admet-2772	772	1	https://doi.org/10.1109/jas.2019.1911447	https://doi.org/10.1109/jas.2019.1911447	NOUN
admet-2772	773	1	[	[	X
admet-2772	773	2	38	38	NUM
admet-2772	773	3	]	]	X
admet-2772	773	4	h.h	h.h	PROPN
admet-2772	773	5	.	.	PROPN
admet-2772	773	6	hsu	hsu	PROPN
admet-2772	773	7	,	,	PUNCT
admet-2772	773	8	c.w	c.w	PROPN
admet-2772	773	9	.	.	PROPN
admet-2772	773	10	hsieh	hsieh	PROPN
admet-2772	773	11	,	,	PUNCT
admet-2772	773	12	m.	m.	NOUN
admet-2772	773	13	da	da	PROPN
admet-2772	773	14	lu	lu	PROPN
admet-2772	773	15	.	.	PUNCT
admet-2772	773	16	hybrid	hybrid	ADJ
admet-2772	773	17	feature	feature	NOUN
admet-2772	773	18	selection	selection	NOUN
admet-2772	773	19	by	by	ADP
admet-2772	773	20	combining	combine	VERB
admet-2772	773	21	filters	filter	NOUN
admet-2772	773	22	and	and	CCONJ
admet-2772	773	23	wrappers	wrapper	NOUN
admet-2772	773	24	.	.	PUNCT
admet-2772	774	1	expert	expert	NOUN
admet-2772	774	2	systems	system	NOUN
admet-2772	774	3	with	with	ADP
admet-2772	774	4	applications	application	NOUN
admet-2772	774	5	38	38	NUM
admet-2772	774	6	(	(	PUNCT
admet-2772	774	7	2011	2011	NUM
admet-2772	774	8	)	)	PUNCT
admet-2772	774	9	8144	8144	NUM
admet-2772	774	10	-	-	SYM
admet-2772	774	11	8150	8150	NUM
admet-2772	774	12	.	.	PUNCT
admet-2772	775	1	https://doi.org/10.1016/j.eswa.2010.12.156	https://doi.org/10.1016/j.eswa.2010.12.156	NOUN
admet-2772	775	2	https://doi.org/10.1093/nar/gkx1037	https://doi.org/10.1093/nar/gkx1037	NUM
admet-2772	775	3	https://doi.org/10.1093/nar/gkr777	https://doi.org/10.1093/nar/gkr777	PROPN
admet-2772	775	4	https://doi.org/10.1093/nar/gkad751	https://doi.org/10.1093/nar/gkad751	PRON
admet-2772	775	5	https://doi.org/10.1038/s41597-020-0455-1	https://doi.org/10.1038/s41597-020-0455-1	AUX
admet-2772	775	6	https://doi.org/10.1093/nar/gky1033	https://doi.org/10.1093/nar/gky1033	VERB
admet-2772	775	7	https://doi.org/10.1021/acs.jcim.5b00559	https://doi.org/10.1021/acs.jcim.5b00559	PROPN
admet-2772	775	8	https://doi.org/10.1093/nar/gkp970	https://doi.org/10.1093/nar/gkp970	PROPN
admet-2772	775	9	https://doi.org/10.1021/acs.jcim.4c01186	https://doi.org/10.1021/acs.jcim.4c01186	VERB
admet-2772	775	10	https://doi.org/10.1021/acs.jmedchem.9b02187	https://doi.org/10.1021/acs.jmedchem.9b02187	ADP
admet-2772	776	1	https://doi.org/10.1016/j.eswa.2021.115072	https://doi.org/10.1016/j.eswa.2021.115072	PROPN
admet-2772	776	2	https://doi.org/10.2478/cait-2019-0001	https://doi.org/10.2478/cait-2019-0001	PROPN
admet-2772	776	3	https://doi.org/10.1007/978-3-540-77226-2_19	https://doi.org/10.1007/978-3-540-77226-2_19	PROPN
admet-2772	776	4	https://doi.org/10.1371/journal.pone.0040654	https://doi.org/10.1371/journal.pone.0040654	PROPN
admet-2772	776	5	https://doi.org/10.1007/s10994-018-5748-7	https://doi.org/10.1007/s10994-018-5748-7	NUM
admet-2772	776	6	https://doi.org/10.1109/jas.2019.1911447	https://doi.org/10.1109/jas.2019.1911447	PROPN
admet-2772	776	7	https://doi.org/10.1016/j.eswa.2010.12.156	https://doi.org/10.1016/j.eswa.2010.12.156	PROPN
admet-2772	776	8	admet	admet	PROPN
admet-2772	776	9	&	&	CCONJ
admet-2772	776	10	dmpk	dmpk	PROPN
admet-2772	776	11	13(3	13(3	NUM
admet-2772	776	12	)	)	PUNCT
admet-2772	776	13	(	(	PUNCT
admet-2772	776	14	2025	2025	NUM
admet-2772	776	15	)	)	PUNCT
admet-2772	776	16	2772	2772	NUM
admet-2772	776	17	machine	machine	NOUN
admet-2772	776	18	learning	learning	NOUN
admet-2772	776	19	models	model	NOUN
admet-2772	776	20	for	for	ADP
admet-2772	776	21	admet	admet	ADJ
admet-2772	776	22	prediction	prediction	NOUN
admet-2772	776	23	in	in	ADP
admet-2772	776	24	drug	drug	NOUN
admet-2772	776	25	development	development	NOUN
admet-2772	776	26	doi	doi	PROPN
admet-2772	776	27	:	:	PUNCT
admet-2772	776	28	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	776	29	27	27	NUM
admet-2772	776	30	[	[	SYM
admet-2772	776	31	39	39	NUM
admet-2772	776	32	]	]	PUNCT
admet-2772	776	33	p.	p.	NOUN
admet-2772	776	34	carracedo	carracedo	PROPN
admet-2772	776	35	-	-	PUNCT
admet-2772	776	36	reboredo	reboredo	PROPN
admet-2772	776	37	,	,	PUNCT
admet-2772	776	38	j.	j.	PROPN
admet-2772	776	39	liñares	liñares	PROPN
admet-2772	776	40	-	-	PUNCT
admet-2772	776	41	blanco	blanco	PROPN
admet-2772	776	42	,	,	PUNCT
admet-2772	776	43	n.	n.	PROPN
admet-2772	776	44	rodríguez	rodríguez	PROPN
admet-2772	776	45	-	-	PUNCT
admet-2772	776	46	fernández	fernández	PROPN
admet-2772	776	47	,	,	PUNCT
admet-2772	776	48	f.	f.	PROPN
admet-2772	776	49	cedrón	cedrón	PROPN
admet-2772	776	50	,	,	PUNCT
admet-2772	776	51	f.j	f.j	PROPN
admet-2772	776	52	.	.	PROPN
admet-2772	776	53	novoa	novoa	NOUN
admet-2772	776	54	,	,	PUNCT
admet-2772	776	55	a.	a.	PROPN
admet-2772	776	56	carballal	carballal	PROPN
admet-2772	776	57	,	,	PUNCT
admet-2772	776	58	v.	v.	ADP
admet-2772	776	59	maojo	maojo	PROPN
admet-2772	776	60	,	,	PUNCT
admet-2772	776	61	a.	a.	NOUN
admet-2772	776	62	pazos	pazos	PROPN
admet-2772	776	63	,	,	PUNCT
admet-2772	776	64	c.	c.	PROPN
admet-2772	776	65	fernandez	fernandez	PROPN
admet-2772	776	66	-	-	PUNCT
admet-2772	776	67	lozano	lozano	PROPN
admet-2772	776	68	.	.	PUNCT
admet-2772	777	1	a	a	DET
admet-2772	777	2	review	review	NOUN
admet-2772	777	3	on	on	ADP
admet-2772	777	4	machine	machine	NOUN
admet-2772	777	5	learning	learn	VERB
admet-2772	777	6	approaches	approach	NOUN
admet-2772	777	7	and	and	CCONJ
admet-2772	777	8	trends	trend	NOUN
admet-2772	777	9	in	in	ADP
admet-2772	777	10	drug	drug	NOUN
admet-2772	777	11	discovery	discovery	NOUN
admet-2772	777	12	.	.	PUNCT
admet-2772	778	1	computational	computational	ADJ
admet-2772	778	2	and	and	CCONJ
admet-2772	778	3	structural	structural	ADJ
admet-2772	778	4	biotechnology	biotechnology	NOUN
admet-2772	778	5	journal	journal	NOUN
admet-2772	778	6	19	19	NUM
admet-2772	778	7	(	(	PUNCT
admet-2772	778	8	2021	2021	NUM
admet-2772	778	9	)	)	PUNCT
admet-2772	778	10	4538	4538	NUM
admet-2772	778	11	-	-	SYM
admet-2772	778	12	4558	4558	NUM
admet-2772	778	13	.	.	PUNCT
admet-2772	779	1	https://doi.org/10.1016/j.csbj.2021.08.011	https://doi.org/10.1016/j.csbj.2021.08.011	NOUN
admet-2772	779	2	[	[	X
admet-2772	779	3	40	40	NUM
admet-2772	779	4	]	]	PUNCT
admet-2772	779	5	f.	f.	PROPN
admet-2772	779	6	grisoni	grisoni	PROPN
admet-2772	779	7	,	,	PUNCT
admet-2772	779	8	d.	d.	PROPN
admet-2772	779	9	ballabio	ballabio	PROPN
admet-2772	779	10	,	,	PUNCT
admet-2772	779	11	r.	r.	PROPN
admet-2772	779	12	todeschini	todeschini	PROPN
admet-2772	779	13	,	,	PUNCT
admet-2772	779	14	v.	v.	PROPN
admet-2772	779	15	consonni	consonni	PROPN
admet-2772	779	16	.	.	PUNCT
admet-2772	780	1	molecular	molecular	ADJ
admet-2772	780	2	descriptors	descriptor	NOUN
admet-2772	780	3	for	for	ADP
admet-2772	780	4	structure	structure	NOUN
admet-2772	780	5	-	-	PUNCT
admet-2772	780	6	activity	activity	NOUN
admet-2772	780	7	applications	application	NOUN
admet-2772	780	8	:	:	PUNCT
admet-2772	780	9	a	a	DET
admet-2772	780	10	hands	hand	NOUN
admet-2772	780	11	-	-	PUNCT
admet-2772	780	12	on	on	ADP
admet-2772	780	13	approach	approach	NOUN
admet-2772	780	14	.	.	PUNCT
admet-2772	781	1	methods	method	NOUN
admet-2772	781	2	in	in	ADP
admet-2772	781	3	molecular	molecular	ADJ
admet-2772	781	4	biology	biology	NOUN
admet-2772	781	5	1800	1800	NUM
admet-2772	781	6	(	(	PUNCT
admet-2772	781	7	2018	2018	NUM
admet-2772	781	8	)	)	PUNCT
admet-2772	781	9	3	3	NUM
admet-2772	781	10	-	-	SYM
admet-2772	781	11	53	53	NUM
admet-2772	781	12	.	.	PUNCT
admet-2772	782	1	https://doi.org/10.1007/978-1-4939-7899-1_1	https://doi.org/10.1007/978-1-4939-7899-1_1	PRON
admet-2772	782	2	[	[	X
admet-2772	782	3	41	41	NUM
admet-2772	782	4	]	]	PUNCT
admet-2772	782	5	a.	a.	NOUN
admet-2772	782	6	mauri	mauri	PROPN
admet-2772	782	7	,	,	PUNCT
admet-2772	782	8	v.	v.	PROPN
admet-2772	782	9	consonni	consonni	PROPN
admet-2772	782	10	,	,	PUNCT
admet-2772	782	11	r.	r.	PROPN
admet-2772	782	12	todeschini	todeschini	PROPN
admet-2772	782	13	.	.	PUNCT
admet-2772	783	1	molecular	molecular	ADJ
admet-2772	783	2	descriptors	descriptor	NOUN
admet-2772	783	3	.	.	PUNCT
admet-2772	784	1	handbook	handbook	NOUN
admet-2772	784	2	of	of	ADP
admet-2772	784	3	computational	computational	ADJ
admet-2772	784	4	chemistry	chemistry	NOUN
admet-2772	784	5	(	(	PUNCT
admet-2772	784	6	2017	2017	NUM
admet-2772	784	7	)	)	PUNCT
admet-2772	784	8	2065	2065	NUM
admet-2772	784	9	-	-	SYM
admet-2772	784	10	2093	2093	NUM
admet-2772	784	11	.	.	PUNCT
admet-2772	785	1	https://doi.org/10.1007/978-3-319-27282-5_51	https://doi.org/10.1007/978-3-319-27282-5_51	PUNCT
admet-2772	786	1	[	[	X
admet-2772	786	2	42	42	NUM
admet-2772	786	3	]	]	PUNCT
admet-2772	786	4	t.	t.	PROPN
admet-2772	786	5	mueller	mueller	PROPN
admet-2772	786	6	,	,	PUNCT
admet-2772	786	7	a.g	a.g	PROPN
admet-2772	786	8	.	.	PROPN
admet-2772	786	9	kusne	kusne	PROPN
admet-2772	786	10	,	,	PUNCT
admet-2772	786	11	r.	r.	PROPN
admet-2772	786	12	ramprasad	ramprasad	PROPN
admet-2772	786	13	.	.	PUNCT
admet-2772	786	14	machine	machine	NOUN
admet-2772	786	15	learning	learning	NOUN
admet-2772	786	16	in	in	ADP
admet-2772	786	17	materials	material	NOUN
admet-2772	786	18	science	science	NOUN
admet-2772	786	19	:	:	PUNCT
admet-2772	786	20	recent	recent	ADJ
admet-2772	786	21	progress	progress	NOUN
admet-2772	786	22	and	and	CCONJ
admet-2772	786	23	emerging	emerge	VERB
admet-2772	786	24	applications	application	NOUN
admet-2772	786	25	.	.	PUNCT
admet-2772	787	1	reviews	review	NOUN
admet-2772	787	2	in	in	ADP
admet-2772	787	3	computational	computational	ADJ
admet-2772	787	4	chemistry	chemistry	NOUN
admet-2772	787	5	29	29	NUM
admet-2772	787	6	(	(	PUNCT
admet-2772	787	7	2016	2016	NUM
admet-2772	787	8	)	)	PUNCT
admet-2772	787	9	186	186	NUM
admet-2772	787	10	-	-	SYM
admet-2772	787	11	273	273	NUM
admet-2772	787	12	.	.	PUNCT
admet-2772	788	1	https://doi.org/10.1002/9781119148739.ch4	https://doi.org/10.1002/9781119148739.ch4	VERB
admet-2772	788	2	[	[	X
admet-2772	788	3	43	43	NUM
admet-2772	788	4	]	]	X
admet-2772	788	5	r.	r.	PROPN
admet-2772	788	6	todeschini	todeschini	PROPN
admet-2772	788	7	,	,	PUNCT
admet-2772	788	8	v.	v.	PROPN
admet-2772	788	9	consonni	consonni	PROPN
admet-2772	788	10	.	.	PUNCT
admet-2772	789	1	molecular	molecular	ADJ
admet-2772	789	2	descriptors	descriptor	NOUN
admet-2772	789	3	for	for	ADP
admet-2772	789	4	chemoinformatics	chemoinformatic	NOUN
admet-2772	789	5	.	.	PUNCT
admet-2772	790	1	molecular	molecular	ADJ
admet-2772	790	2	descriptors	descriptor	NOUN
admet-2772	790	3	for	for	ADP
admet-2772	790	4	chemoinformatics	chemoinformatic	NOUN
admet-2772	790	5	2	2	NUM
admet-2772	790	6	(	(	PUNCT
admet-2772	790	7	2010	2010	NUM
admet-2772	790	8	)	)	PUNCT
admet-2772	790	9	1	1	NUM
admet-2772	790	10	-	-	SYM
admet-2772	790	11	252	252	NUM
admet-2772	790	12	.	.	PUNCT
admet-2772	790	13	https://doi.org/10.1002/9783527628766	https://doi.org/10.1002/9783527628766	NOUN
admet-2772	791	1	[	[	X
admet-2772	791	2	44	44	NUM
admet-2772	791	3	]	]	X
admet-2772	791	4	a.i	a.i	PROPN
admet-2772	791	5	.	.	PROPN
admet-2772	791	6	odugbemi	odugbemi	PROPN
admet-2772	791	7	,	,	PUNCT
admet-2772	791	8	c.	c.	PROPN
admet-2772	791	9	nyirenda	nyirenda	NOUN
admet-2772	791	10	,	,	PUNCT
admet-2772	791	11	a.	a.	NOUN
admet-2772	791	12	christoffels	christoffels	PROPN
admet-2772	791	13	,	,	PUNCT
admet-2772	791	14	s.a	s.a	PROPN
admet-2772	791	15	.	.	PROPN
admet-2772	791	16	egieyeh	egieyeh	PROPN
admet-2772	791	17	.	.	PUNCT
admet-2772	792	1	artificial	artificial	ADJ
admet-2772	792	2	intelligence	intelligence	NOUN
admet-2772	792	3	in	in	ADP
admet-2772	792	4	antidiabetic	antidiabetic	ADJ
admet-2772	792	5	drug	drug	NOUN
admet-2772	792	6	discovery	discovery	NOUN
admet-2772	792	7	:	:	PUNCT
admet-2772	792	8	the	the	DET
admet-2772	792	9	advances	advance	NOUN
admet-2772	792	10	in	in	ADP
admet-2772	792	11	qsar	qsar	NOUN
admet-2772	792	12	and	and	CCONJ
admet-2772	792	13	the	the	DET
admet-2772	792	14	prediction	prediction	NOUN
admet-2772	792	15	of	of	ADP
admet-2772	792	16	α	α	NOUN
admet-2772	792	17	-	-	PUNCT
admet-2772	792	18	glucosidase	glucosidase	ADJ
admet-2772	792	19	inhibitors	inhibitor	NOUN
admet-2772	792	20	.	.	PUNCT
admet-2772	793	1	computational	computational	ADJ
admet-2772	793	2	and	and	CCONJ
admet-2772	793	3	structural	structural	ADJ
admet-2772	793	4	biotechnology	biotechnology	NOUN
admet-2772	793	5	journal	journal	NOUN
admet-2772	793	6	23	23	NUM
admet-2772	793	7	(	(	PUNCT
admet-2772	793	8	2024	2024	NUM
admet-2772	793	9	)	)	PUNCT
admet-2772	793	10	2964	2964	NUM
admet-2772	793	11	-	-	SYM
admet-2772	793	12	2977	2977	NUM
admet-2772	793	13	.	.	PUNCT
admet-2772	794	1	https://doi.org/10.1016/j.csbj.2024.07.003	https://doi.org/10.1016/j.csbj.2024.07.003	NOUN
admet-2772	794	2	[	[	X
admet-2772	794	3	45	45	NUM
admet-2772	794	4	]	]	PUNCT
admet-2772	794	5	j.	j.	PROPN
admet-2772	794	6	deng	deng	PROPN
admet-2772	794	7	,	,	PUNCT
admet-2772	794	8	z.	z.	PROPN
admet-2772	794	9	yang	yang	PROPN
admet-2772	794	10	,	,	PUNCT
admet-2772	794	11	h.	h.	PROPN
admet-2772	794	12	wang	wang	PROPN
admet-2772	794	13	,	,	PUNCT
admet-2772	794	14	i.	i.	PROPN
admet-2772	794	15	ojima	ojima	PROPN
admet-2772	794	16	,	,	PUNCT
admet-2772	794	17	d.	d.	PROPN
admet-2772	794	18	samaras	samaras	PROPN
admet-2772	794	19	,	,	PUNCT
admet-2772	794	20	f.	f.	PROPN
admet-2772	794	21	wang	wang	PROPN
admet-2772	794	22	.	.	PUNCT
admet-2772	795	1	a	a	DET
admet-2772	795	2	systematic	systematic	ADJ
admet-2772	795	3	study	study	NOUN
admet-2772	795	4	of	of	ADP
admet-2772	795	5	key	key	ADJ
admet-2772	795	6	elements	element	NOUN
admet-2772	795	7	underlying	underlie	VERB
admet-2772	795	8	molecular	molecular	ADJ
admet-2772	795	9	property	property	NOUN
admet-2772	795	10	prediction	prediction	NOUN
admet-2772	795	11	.	.	PUNCT
admet-2772	796	1	nature	nature	NOUN
admet-2772	796	2	communications	communication	NOUN
admet-2772	796	3	14	14	NUM
admet-2772	796	4	(	(	PUNCT
admet-2772	796	5	2023	2023	NUM
admet-2772	796	6	)	)	PUNCT
admet-2772	796	7	6395	6395	NUM
admet-2772	796	8	.	.	PUNCT
admet-2772	797	1	https://doi.org/10.1038/s41467-023-41948-6	https://doi.org/10.1038/s41467-023-41948-6	X
admet-2772	798	1	[	[	X
admet-2772	798	2	46	46	NUM
admet-2772	798	3	]	]	PUNCT
admet-2772	798	4	b.	b.	PROPN
admet-2772	798	5	chandrasekaran	chandrasekaran	PROPN
admet-2772	798	6	,	,	PUNCT
admet-2772	798	7	s.n	s.n	PROPN
admet-2772	798	8	.	.	PROPN
admet-2772	798	9	abed	abed	PROPN
admet-2772	798	10	,	,	PUNCT
admet-2772	798	11	o.	o.	PROPN
admet-2772	798	12	al	al	PROPN
admet-2772	798	13	-	-	PUNCT
admet-2772	798	14	attraqchi	attraqchi	PROPN
admet-2772	798	15	,	,	PUNCT
admet-2772	798	16	k.	k.	PROPN
admet-2772	798	17	kuche	kuche	PROPN
admet-2772	798	18	,	,	PUNCT
admet-2772	798	19	r.k	r.k	PROPN
admet-2772	798	20	.	.	PROPN
admet-2772	798	21	tekade	tekade	PROPN
admet-2772	798	22	.	.	PUNCT
admet-2772	799	1	computer	computer	NOUN
admet-2772	799	2	-	-	PUNCT
admet-2772	799	3	aided	aid	VERB
admet-2772	799	4	prediction	prediction	NOUN
admet-2772	799	5	of	of	ADP
admet-2772	799	6	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	799	7	(	(	PUNCT
admet-2772	799	8	admet	admet	ADJ
admet-2772	799	9	)	)	PUNCT
admet-2772	799	10	properties	property	NOUN
admet-2772	799	11	.	.	PUNCT
admet-2772	800	1	dosage	dosage	NOUN
admet-2772	800	2	form	form	NOUN
admet-2772	800	3	design	design	NOUN
admet-2772	800	4	parameters	parameter	NOUN
admet-2772	800	5	2	2	NUM
admet-2772	800	6	(	(	PUNCT
admet-2772	800	7	2018	2018	NUM
admet-2772	800	8	)	)	PUNCT
admet-2772	800	9	731	731	NUM
admet-2772	800	10	-	-	SYM
admet-2772	800	11	755	755	NUM
admet-2772	800	12	.	.	PUNCT
admet-2772	801	1	https://doi.org/10.1016/b978-0-12-814421-3.00021-x	https://doi.org/10.1016/b978-0-12-814421-3.00021-x	NOUN
admet-2772	802	1	[	[	X
admet-2772	802	2	47	47	NUM
admet-2772	802	3	]	]	X
admet-2772	802	4	d.	d.	PROPN
admet-2772	802	5	wan	wan	PROPN
admet-2772	802	6	,	,	PUNCT
admet-2772	802	7	j.	j.	PROPN
admet-2772	802	8	yang	yang	PROPN
admet-2772	802	9	,	,	PUNCT
admet-2772	802	10	t.	t.	PROPN
admet-2772	802	11	zhang	zhang	PROPN
admet-2772	802	12	,	,	PUNCT
admet-2772	802	13	y.	y.	PROPN
admet-2772	802	14	xiong	xiong	PROPN
admet-2772	802	15	.	.	PUNCT
admet-2772	803	1	a	a	DET
admet-2772	803	2	novel	novel	ADJ
admet-2772	803	3	method	method	NOUN
admet-2772	803	4	to	to	PART
admet-2772	803	5	identify	identify	VERB
admet-2772	803	6	influential	influential	ADJ
admet-2772	803	7	nodes	node	NOUN
admet-2772	803	8	based	base	VERB
admet-2772	803	9	on	on	ADP
admet-2772	803	10	hybrid	hybrid	ADJ
admet-2772	803	11	topology	topology	NOUN
admet-2772	803	12	structure	structure	NOUN
admet-2772	803	13	.	.	PUNCT
admet-2772	804	1	physical	physical	ADJ
admet-2772	804	2	communication	communication	NOUN
admet-2772	804	3	58	58	NUM
admet-2772	804	4	(	(	PUNCT
admet-2772	804	5	2023	2023	NUM
admet-2772	804	6	)	)	PUNCT
admet-2772	804	7	102046	102046	NUM
admet-2772	804	8	.	.	PUNCT
admet-2772	805	1	https://doi.org/10.1016/j.phycom.2023.102046	https://doi.org/10.1016/j.phycom.2023.102046	NOUN
admet-2772	805	2	[	[	X
admet-2772	805	3	48	48	NUM
admet-2772	805	4	]	]	X
admet-2772	805	5	d.c	d.c	PROPN
admet-2772	805	6	.	.	PROPN
admet-2772	805	7	kombo	kombo	PROPN
admet-2772	805	8	,	,	PUNCT
admet-2772	805	9	k.	k.	PROPN
admet-2772	805	10	tallapragada	tallapragada	PROPN
admet-2772	805	11	,	,	PUNCT
admet-2772	805	12	r.	r.	PROPN
admet-2772	805	13	jain	jain	PROPN
admet-2772	805	14	,	,	PUNCT
admet-2772	805	15	j.	j.	PROPN
admet-2772	805	16	chewning	chewning	PROPN
admet-2772	805	17	,	,	PUNCT
admet-2772	805	18	a.a	a.a	PROPN
admet-2772	805	19	.	.	PROPN
admet-2772	805	20	mazurov	mazurov	PROPN
admet-2772	805	21	,	,	PUNCT
admet-2772	805	22	j.d	j.d	PROPN
admet-2772	805	23	.	.	PROPN
admet-2772	805	24	speake	speake	PROPN
admet-2772	805	25	,	,	PUNCT
admet-2772	805	26	t.a	t.a	PROPN
admet-2772	805	27	.	.	PROPN
admet-2772	805	28	hauser	hauser	PROPN
admet-2772	805	29	,	,	PUNCT
admet-2772	805	30	s.	s.	PROPN
admet-2772	805	31	toler	toler	PROPN
admet-2772	805	32	.	.	PUNCT
admet-2772	806	1	3d	3d	PROPN
admet-2772	806	2	molecular	molecular	ADJ
admet-2772	806	3	descriptors	descriptor	NOUN
admet-2772	806	4	important	important	ADJ
admet-2772	806	5	for	for	ADP
admet-2772	806	6	clinical	clinical	ADJ
admet-2772	806	7	success	success	NOUN
admet-2772	806	8	.	.	PUNCT
admet-2772	807	1	journal	journal	PROPN
admet-2772	807	2	of	of	ADP
admet-2772	807	3	chemical	chemical	ADJ
admet-2772	807	4	information	information	NOUN
admet-2772	807	5	and	and	CCONJ
admet-2772	807	6	modeling	model	VERB
admet-2772	807	7	53	53	NUM
admet-2772	807	8	(	(	PUNCT
admet-2772	807	9	2013	2013	NUM
admet-2772	807	10	)	)	PUNCT
admet-2772	807	11	327	327	NUM
admet-2772	807	12	-	-	SYM
admet-2772	807	13	342	342	NUM
admet-2772	807	14	.	.	PUNCT
admet-2772	808	1	https://doi.org/10.1021/ci300445e	https://doi.org/10.1021/ci300445e	PROPN
admet-2772	808	2	[	[	X
admet-2772	808	3	49	49	NUM
admet-2772	808	4	]	]	PUNCT
admet-2772	808	5	d.	d.	PROPN
admet-2772	808	6	fourches	fourches	PROPN
admet-2772	808	7	,	,	PUNCT
admet-2772	808	8	j.	j.	PROPN
admet-2772	808	9	ash	ash	PROPN
admet-2772	808	10	.	.	PUNCT
admet-2772	809	1	4dquantitative	4dquantitative	NUM
admet-2772	809	2	structure	structure	NOUN
admet-2772	809	3	-	-	PUNCT
admet-2772	809	4	activity	activity	NOUN
admet-2772	809	5	relationship	relationship	NOUN
admet-2772	809	6	modeling	modeling	NOUN
admet-2772	809	7	:	:	PUNCT
admet-2772	809	8	making	make	VERB
admet-2772	809	9	a	a	DET
admet-2772	809	10	comeback	comeback	NOUN
admet-2772	809	11	.	.	PUNCT
admet-2772	810	1	expert	expert	ADJ
admet-2772	810	2	opinion	opinion	NOUN
admet-2772	810	3	on	on	ADP
admet-2772	810	4	drug	drug	NOUN
admet-2772	810	5	discovery	discovery	NOUN
admet-2772	810	6	14	14	NUM
admet-2772	810	7	(	(	PUNCT
admet-2772	810	8	2019	2019	NUM
admet-2772	810	9	)	)	PUNCT
admet-2772	810	10	1227	1227	NUM
admet-2772	810	11	-	-	SYM
admet-2772	810	12	1235	1235	NUM
admet-2772	810	13	.	.	PUNCT
admet-2772	810	14	https://doi.org/10.1080/17460441.2019.1664467	https://doi.org/10.1080/17460441.2019.1664467	PUNCT
admet-2772	811	1	[	[	X
admet-2772	811	2	50	50	NUM
admet-2772	811	3	]	]	PUNCT
admet-2772	811	4	e.	e.	PROPN
admet-2772	811	5	jung	jung	PROPN
admet-2772	811	6	,	,	PUNCT
admet-2772	811	7	j.	j.	PROPN
admet-2772	811	8	kim	kim	PROPN
admet-2772	811	9	,	,	PUNCT
admet-2772	811	10	m.	m.	PROPN
admet-2772	811	11	kim	kim	PROPN
admet-2772	811	12	,	,	PUNCT
admet-2772	811	13	d.h	d.h	PROPN
admet-2772	811	14	.	.	PROPN
admet-2772	811	15	jung	jung	PROPN
admet-2772	811	16	,	,	PUNCT
admet-2772	811	17	h.	h.	PROPN
admet-2772	811	18	rhee	rhee	PROPN
admet-2772	811	19	,	,	PUNCT
admet-2772	811	20	j.m	j.m	PROPN
admet-2772	811	21	.	.	PROPN
admet-2772	811	22	shin	shin	PROPN
admet-2772	811	23	,	,	PUNCT
admet-2772	811	24	k.	k.	PROPN
admet-2772	811	25	choi	choi	PROPN
admet-2772	811	26	,	,	PUNCT
admet-2772	811	27	s.k	s.k	PROPN
admet-2772	811	28	.	.	PROPN
admet-2772	811	29	kang	kang	PROPN
admet-2772	811	30	,	,	PUNCT
admet-2772	811	31	m.k	m.k	PROPN
admet-2772	811	32	.	.	PUNCT
admet-2772	811	33	kim	kim	PROPN
admet-2772	811	34	,	,	PUNCT
admet-2772	811	35	c.h	c.h	PROPN
admet-2772	811	36	.	.	PROPN
admet-2772	811	37	yun	yun	PROPN
admet-2772	811	38	,	,	PUNCT
admet-2772	811	39	y.j	y.j	PROPN
admet-2772	811	40	.	.	PUNCT
admet-2772	811	41	choi	choi	PROPN
admet-2772	811	42	,	,	PUNCT
admet-2772	811	43	s.h	s.h	PROPN
admet-2772	811	44	.	.	PROPN
admet-2772	811	45	choi	choi	NOUN
admet-2772	811	46	.	.	PUNCT
admet-2772	812	1	artificial	artificial	ADJ
admet-2772	812	2	neural	neural	ADJ
admet-2772	812	3	network	network	NOUN
admet-2772	812	4	models	model	NOUN
admet-2772	812	5	for	for	ADP
admet-2772	812	6	prediction	prediction	NOUN
admet-2772	812	7	of	of	ADP
admet-2772	812	8	intestinal	intestinal	ADJ
admet-2772	812	9	permeability	permeability	NOUN
admet-2772	812	10	of	of	ADP
admet-2772	812	11	oligopeptides	oligopeptide	NOUN
admet-2772	812	12	.	.	PUNCT
admet-2772	813	1	bmc	bmc	ADJ
admet-2772	813	2	bioinformatics	bioinformatics	NOUN
admet-2772	813	3	8	8	NUM
admet-2772	813	4	(	(	PUNCT
admet-2772	813	5	2007	2007	NUM
admet-2772	813	6	)	)	PUNCT
admet-2772	813	7	245	245	NUM
admet-2772	813	8	.	.	PUNCT
admet-2772	814	1	https://doi.org/10.1186/1471-2105-8-245	https://doi.org/10.1186/1471-2105-8-245	PROPN
admet-2772	814	2	[	[	X
admet-2772	814	3	51	51	NUM
admet-2772	814	4	]	]	PUNCT
admet-2772	814	5	r.	r.	PROPN
admet-2772	814	6	kumar	kumar	PROPN
admet-2772	814	7	,	,	PUNCT
admet-2772	814	8	a.	a.	PROPN
admet-2772	814	9	sharma	sharma	PROPN
admet-2772	814	10	,	,	PUNCT
admet-2772	814	11	m.h	m.h	PROPN
admet-2772	814	12	.	.	PROPN
admet-2772	814	13	siddiqui	siddiqui	PROPN
admet-2772	814	14	,	,	PUNCT
admet-2772	814	15	r.k	r.k	PROPN
admet-2772	814	16	.	.	PROPN
admet-2772	814	17	tiwari	tiwari	PROPN
admet-2772	814	18	.	.	PUNCT
admet-2772	815	1	prediction	prediction	NOUN
admet-2772	815	2	of	of	ADP
admet-2772	815	3	human	human	ADJ
admet-2772	815	4	intestinal	intestinal	ADJ
admet-2772	815	5	absorption	absorption	NOUN
admet-2772	815	6	of	of	ADP
admet-2772	815	7	compounds	compound	NOUN
admet-2772	815	8	using	use	VERB
admet-2772	815	9	artificial	artificial	ADJ
admet-2772	815	10	intelligence	intelligence	NOUN
admet-2772	815	11	techniques	technique	NOUN
admet-2772	815	12	.	.	PUNCT
admet-2772	816	1	current	current	ADJ
admet-2772	816	2	drug	drug	NOUN
admet-2772	816	3	discovery	discovery	NOUN
admet-2772	816	4	technologies	technology	NOUN
admet-2772	816	5	14	14	NUM
admet-2772	816	6	(	(	PUNCT
admet-2772	816	7	2017	2017	NUM
admet-2772	816	8	)	)	PUNCT
admet-2772	816	9	244	244	NUM
admet-2772	816	10	254	254	NUM
admet-2772	816	11	.	.	PUNCT
admet-2772	816	12	https://doi.org/10.2174/1570163814666170404160911	https://doi.org/10.2174/1570163814666170404160911	X
admet-2772	817	1	[	[	X
admet-2772	817	2	52	52	NUM
admet-2772	817	3	]	]	X
admet-2772	817	4	v.	v.	CCONJ
admet-2772	817	5	acuña	acuña	PROPN
admet-2772	817	6	-	-	PUNCT
admet-2772	817	7	guzman	guzman	PROPN
admet-2772	817	8	,	,	PUNCT
admet-2772	817	9	m.e	m.e	PROPN
admet-2772	817	10	.	.	PROPN
admet-2772	817	11	montoya	montoya	PROPN
admet-2772	817	12	-	-	PUNCT
admet-2772	817	13	alfaro	alfaro	PROPN
admet-2772	817	14	,	,	PUNCT
admet-2772	817	15	l.p	l.p	PROPN
admet-2772	817	16	.	.	PROPN
admet-2772	817	17	negrón	negrón	NOUN
admet-2772	817	18	-	-	PUNCT
admet-2772	817	19	ballarte	ballarte	NOUN
admet-2772	817	20	,	,	PUNCT
admet-2772	817	21	c.	c.	PROPN
admet-2772	817	22	solis	solis	PROPN
admet-2772	817	23	-	-	PUNCT
admet-2772	817	24	calero	calero	PROPN
admet-2772	817	25	.	.	PUNCT
admet-2772	818	1	a	a	DET
admet-2772	818	2	machine	machine	NOUN
admet-2772	818	3	learning	learn	VERB
admet-2772	818	4	approach	approach	NOUN
admet-2772	818	5	for	for	ADP
admet-2772	818	6	predicting	predict	VERB
admet-2772	818	7	caco-2	caco-2	NUM
admet-2772	818	8	cell	cell	NOUN
admet-2772	818	9	permeability	permeability	NOUN
admet-2772	818	10	in	in	ADP
admet-2772	818	11	natural	natural	ADJ
admet-2772	818	12	products	product	NOUN
admet-2772	818	13	from	from	ADP
admet-2772	818	14	the	the	DET
admet-2772	818	15	biodiversity	biodiversity	NOUN
admet-2772	818	16	in	in	ADP
admet-2772	818	17	peru	peru	PROPN
admet-2772	818	18	.	.	PUNCT
admet-2772	819	1	pharmaceuticals	pharmaceutical	NOUN
admet-2772	819	2	17(6	17(6	NUM
admet-2772	819	3	)	)	PUNCT
admet-2772	819	4	(	(	PUNCT
admet-2772	819	5	2024	2024	NUM
admet-2772	819	6	)	)	PUNCT
admet-2772	819	7	750	750	NUM
admet-2772	819	8	.	.	PUNCT
admet-2772	820	1	https://doi.org/10.3390/ph17060750	https://doi.org/10.3390/ph17060750	PRON
admet-2772	821	1	[	[	X
admet-2772	821	2	53	53	NUM
admet-2772	821	3	]	]	PUNCT
admet-2772	821	4	p.	p.	PROPN
admet-2772	821	5	stenberg	stenberg	PROPN
admet-2772	821	6	,	,	PUNCT
admet-2772	821	7	u.	u.	PROPN
admet-2772	821	8	norinder	norinder	PROPN
admet-2772	821	9	,	,	PUNCT
admet-2772	821	10	k.	k.	PROPN
admet-2772	821	11	luthman	luthman	PROPN
admet-2772	821	12	,	,	PUNCT
admet-2772	821	13	p.	p.	PROPN
admet-2772	821	14	artursson	artursson	PROPN
admet-2772	821	15	.	.	PUNCT
admet-2772	822	1	experimental	experimental	ADJ
admet-2772	822	2	and	and	CCONJ
admet-2772	822	3	computational	computational	ADJ
admet-2772	822	4	screening	screening	NOUN
admet-2772	822	5	models	model	NOUN
admet-2772	822	6	for	for	ADP
admet-2772	822	7	the	the	DET
admet-2772	822	8	prediction	prediction	NOUN
admet-2772	822	9	of	of	ADP
admet-2772	822	10	intestinal	intestinal	ADJ
admet-2772	822	11	drug	drug	NOUN
admet-2772	822	12	absorption	absorption	NOUN
admet-2772	822	13	.	.	PUNCT
admet-2772	823	1	journal	journal	PROPN
admet-2772	823	2	of	of	ADP
admet-2772	823	3	medicinal	medicinal	ADJ
admet-2772	823	4	chemistry	chemistry	NOUN
admet-2772	823	5	44	44	NUM
admet-2772	823	6	(	(	PUNCT
admet-2772	823	7	2001	2001	NUM
admet-2772	823	8	)	)	PUNCT
admet-2772	823	9	1927	1927	NUM
admet-2772	823	10	-	-	SYM
admet-2772	823	11	1937	1937	NUM
admet-2772	823	12	.	.	PUNCT
admet-2772	824	1	https://doi.org/10.1021/jm001101a	https://doi.org/10.1021/jm001101a	VERB
admet-2772	825	1	[	[	X
admet-2772	825	2	54	54	NUM
admet-2772	825	3	]	]	PUNCT
admet-2772	825	4	t.	t.	PROPN
admet-2772	825	5	hou	hou	PROPN
admet-2772	825	6	,	,	PUNCT
admet-2772	825	7	j.	j.	PROPN
admet-2772	825	8	wang	wang	PROPN
admet-2772	825	9	,	,	PUNCT
admet-2772	825	10	w.	w.	PROPN
admet-2772	825	11	zhang	zhang	PROPN
admet-2772	825	12	,	,	PUNCT
admet-2772	825	13	x.	x.	PROPN
admet-2772	825	14	xu	xu	PROPN
admet-2772	825	15	.	.	PUNCT
admet-2772	826	1	adme	adme	NOUN
admet-2772	826	2	evaluation	evaluation	NOUN
admet-2772	826	3	in	in	ADP
admet-2772	826	4	drug	drug	NOUN
admet-2772	826	5	discovery	discovery	NOUN
admet-2772	826	6	.	.	PUNCT
admet-2772	827	1	7	7	X
admet-2772	827	2	.	.	X
admet-2772	827	3	prediction	prediction	NOUN
admet-2772	827	4	of	of	ADP
admet-2772	827	5	oral	oral	ADJ
admet-2772	827	6	absorption	absorption	NOUN
admet-2772	827	7	by	by	ADP
admet-2772	827	8	correlation	correlation	NOUN
admet-2772	827	9	and	and	CCONJ
admet-2772	827	10	classification	classification	NOUN
admet-2772	827	11	.	.	PUNCT
admet-2772	828	1	journal	journal	PROPN
admet-2772	828	2	of	of	ADP
admet-2772	828	3	chemical	chemical	ADJ
admet-2772	828	4	information	information	NOUN
admet-2772	828	5	and	and	CCONJ
admet-2772	828	6	modeling	model	VERB
admet-2772	828	7	47	47	NUM
admet-2772	828	8	(	(	PUNCT
admet-2772	828	9	2007	2007	NUM
admet-2772	828	10	)	)	PUNCT
admet-2772	828	11	208	208	NUM
admet-2772	828	12	-	-	SYM
admet-2772	828	13	218	218	NUM
admet-2772	828	14	.	.	PUNCT
admet-2772	829	1	https://doi.org/10.1021/ci600343x	https://doi.org/10.1021/ci600343x	PROPN
admet-2772	830	1	[	[	X
admet-2772	830	2	55	55	NUM
admet-2772	830	3	]	]	PUNCT
admet-2772	830	4	e.	e.	PROPN
admet-2772	830	5	deconinck	deconinck	PROPN
admet-2772	830	6	,	,	PUNCT
admet-2772	830	7	h.	h.	PROPN
admet-2772	830	8	ates	ates	PROPN
admet-2772	830	9	,	,	PUNCT
admet-2772	830	10	n.	n.	PROPN
admet-2772	830	11	callebaut	callebaut	PROPN
admet-2772	830	12	,	,	PUNCT
admet-2772	830	13	e.	e.	PROPN
admet-2772	830	14	van	van	PROPN
admet-2772	830	15	gyseghem	gyseghem	PROPN
admet-2772	830	16	,	,	PUNCT
admet-2772	830	17	y.	y.	PROPN
admet-2772	830	18	vander	vander	PROPN
admet-2772	830	19	heyden	heyden	PROPN
admet-2772	830	20	.	.	PUNCT
admet-2772	831	1	evaluation	evaluation	NOUN
admet-2772	831	2	of	of	ADP
admet-2772	831	3	chromatographic	chromatographic	ADJ
admet-2772	831	4	descriptors	descriptor	NOUN
admet-2772	831	5	for	for	ADP
admet-2772	831	6	the	the	DET
admet-2772	831	7	prediction	prediction	NOUN
admet-2772	831	8	of	of	ADP
admet-2772	831	9	gastro	gastro	ADJ
admet-2772	831	10	-	-	PUNCT
admet-2772	831	11	intestinal	intestinal	ADJ
admet-2772	831	12	absorption	absorption	NOUN
admet-2772	831	13	of	of	ADP
admet-2772	831	14	drugs	drug	NOUN
admet-2772	831	15	.	.	PUNCT
admet-2772	832	1	journal	journal	PROPN
admet-2772	832	2	of	of	ADP
admet-2772	832	3	chromatography	chromatography	NOUN
admet-2772	832	4	a	a	DET
admet-2772	832	5	1138	1138	NUM
admet-2772	832	6	(	(	PUNCT
admet-2772	832	7	2007	2007	NUM
admet-2772	832	8	)	)	PUNCT
admet-2772	832	9	190	190	NUM
admet-2772	832	10	-	-	SYM
admet-2772	832	11	202	202	NUM
admet-2772	832	12	.	.	PUNCT
admet-2772	833	1	https://doi.org/10.1016/j.chroma.2006.10.068	https://doi.org/10.1016/j.chroma.2006.10.068	VERB
admet-2772	833	2	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	833	3	https://doi.org/10.1016/j.csbj.2021.08.011	https://doi.org/10.1016/j.csbj.2021.08.011	PROPN
admet-2772	833	4	https://doi.org/10.1007/978-1-4939-7899-1_1	https://doi.org/10.1007/978-1-4939-7899-1_1	PROPN
admet-2772	833	5	https://doi.org/10.1007/978-3-319-27282-5_51	https://doi.org/10.1007/978-3-319-27282-5_51	PROPN
admet-2772	833	6	https://doi.org/10.1002/9781119148739.ch4	https://doi.org/10.1002/9781119148739.ch4	ADJ
admet-2772	833	7	https://doi.org/10.1002/9783527628766	https://doi.org/10.1002/9783527628766	ADJ
admet-2772	833	8	https://doi.org/10.1016/j.csbj.2024.07.003	https://doi.org/10.1016/j.csbj.2024.07.003	NOUN
admet-2772	833	9	https://doi.org/10.1038/s41467-023-41948-6	https://doi.org/10.1038/s41467-023-41948-6	NUM
admet-2772	834	1	https://doi.org/10.1016/b978-0-12-814421-3.00021-x	https://doi.org/10.1016/b978-0-12-814421-3.00021-x	PROPN
admet-2772	834	2	https://doi.org/10.1016/j.phycom.2023.102046	https://doi.org/10.1016/j.phycom.2023.102046	NOUN
admet-2772	834	3	https://doi.org/10.1021/ci300445e	https://doi.org/10.1021/ci300445e	PROPN
admet-2772	834	4	https://doi.org/10.1080/17460441.2019.1664467	https://doi.org/10.1080/17460441.2019.1664467	PROPN
admet-2772	834	5	https://doi.org/10.1186/1471-2105-8-245	https://doi.org/10.1186/1471-2105-8-245	PROPN
admet-2772	834	6	https://doi.org/10.2174/1570163814666170404160911	https://doi.org/10.2174/1570163814666170404160911	VERB
admet-2772	834	7	https://doi.org/10.3390/ph17060750	https://doi.org/10.3390/ph17060750	PRON
admet-2772	834	8	https://doi.org/10.1021/jm001101a	https://doi.org/10.1021/jm001101a	NOUN
admet-2772	834	9	https://doi.org/10.1021/ci600343x	https://doi.org/10.1021/ci600343x	NOUN
admet-2772	835	1	https://doi.org/10.1016/j.chroma.2006.10.068	https://doi.org/10.1016/j.chroma.2006.10.068	VERB
admet-2772	835	2	m.	m.	NOUN
admet-2772	835	3	venkataraman	venkataraman	PROPN
admet-2772	835	4	et	et	PROPN
admet-2772	835	5	al	al	PROPN
admet-2772	835	6	.	.	PROPN
admet-2772	835	7	admet	admet	PROPN
admet-2772	835	8	&	&	CCONJ
admet-2772	835	9	dmpk	dmpk	PROPN
admet-2772	835	10	13(3	13(3	NUM
admet-2772	835	11	)	)	PUNCT
admet-2772	835	12	(	(	PUNCT
admet-2772	835	13	2025	2025	NUM
admet-2772	835	14	)	)	PUNCT
admet-2772	835	15	2772	2772	NUM
admet-2772	835	16	28	28	NUM
admet-2772	836	1	[	[	X
admet-2772	836	2	56	56	NUM
admet-2772	836	3	]	]	PUNCT
admet-2772	836	4	a.	a.	NOUN
admet-2772	836	5	talevi	talevi	NOUN
admet-2772	836	6	,	,	PUNCT
admet-2772	836	7	m.	m.	NOUN
admet-2772	836	8	goodarzi	goodarzi	PROPN
admet-2772	836	9	,	,	PUNCT
admet-2772	836	10	e.	e.	PROPN
admet-2772	836	11	v.	v.	PROPN
admet-2772	836	12	ortiz	ortiz	PROPN
admet-2772	836	13	,	,	PUNCT
admet-2772	836	14	p.r	p.r	PROPN
admet-2772	836	15	.	.	PROPN
admet-2772	836	16	duchowicz	duchowicz	PROPN
admet-2772	836	17	,	,	PUNCT
admet-2772	836	18	c.l	c.l	PROPN
admet-2772	836	19	.	.	PROPN
admet-2772	836	20	bellera	bellera	PROPN
admet-2772	836	21	,	,	PUNCT
admet-2772	836	22	g.	g.	PROPN
admet-2772	836	23	pesce	pesce	PROPN
admet-2772	836	24	,	,	PUNCT
admet-2772	836	25	e.a	e.a	PROPN
admet-2772	836	26	.	.	PROPN
admet-2772	836	27	castro	castro	PROPN
admet-2772	836	28	,	,	PUNCT
admet-2772	836	29	l.e	l.e	PROPN
admet-2772	836	30	.	.	PROPN
admet-2772	836	31	brunoblanch	brunoblanch	PROPN
admet-2772	836	32	.	.	PUNCT
admet-2772	837	1	prediction	prediction	NOUN
admet-2772	837	2	of	of	ADP
admet-2772	837	3	drug	drug	NOUN
admet-2772	837	4	intestinal	intestinal	ADJ
admet-2772	837	5	absorption	absorption	NOUN
admet-2772	837	6	by	by	ADP
admet-2772	837	7	new	new	ADJ
admet-2772	837	8	linear	linear	PROPN
admet-2772	837	9	and	and	CCONJ
admet-2772	837	10	non	non	ADJ
admet-2772	837	11	-	-	ADJ
admet-2772	837	12	linear	linear	ADJ
admet-2772	837	13	qspr	qspr	NOUN
admet-2772	837	14	.	.	PUNCT
admet-2772	838	1	european	european	PROPN
admet-2772	838	2	journal	journal	PROPN
admet-2772	838	3	of	of	ADP
admet-2772	838	4	medicinal	medicinal	ADJ
admet-2772	838	5	chemistry	chemistry	NOUN
admet-2772	838	6	46	46	NUM
admet-2772	838	7	(	(	PUNCT
admet-2772	838	8	2011	2011	NUM
admet-2772	838	9	)	)	PUNCT
admet-2772	838	10	218	218	NUM
admet-2772	838	11	-	-	SYM
admet-2772	838	12	228	228	NUM
admet-2772	838	13	.	.	PUNCT
admet-2772	839	1	https://doi.org/10.1016/j.ejmech.2010.11.005	https://doi.org/10.1016/j.ejmech.2010.11.005	PROPN
admet-2772	840	1	[	[	X
admet-2772	840	2	57	57	NUM
admet-2772	840	3	]	]	PUNCT
admet-2772	840	4	a.	a.	NOUN
admet-2772	840	5	yan	yan	PROPN
admet-2772	840	6	,	,	PUNCT
admet-2772	840	7	z.	z.	PROPN
admet-2772	840	8	wang	wang	PROPN
admet-2772	840	9	,	,	PUNCT
admet-2772	840	10	z.	z.	PROPN
admet-2772	840	11	cai	cai	PROPN
admet-2772	840	12	.	.	PUNCT
admet-2772	841	1	prediction	prediction	NOUN
admet-2772	841	2	of	of	ADP
admet-2772	841	3	human	human	ADJ
admet-2772	841	4	intestinal	intestinal	ADJ
admet-2772	841	5	absorption	absorption	NOUN
admet-2772	841	6	by	by	ADP
admet-2772	841	7	ga	ga	PROPN
admet-2772	841	8	feature	feature	NOUN
admet-2772	841	9	selection	selection	NOUN
admet-2772	841	10	and	and	CCONJ
admet-2772	841	11	support	support	NOUN
admet-2772	841	12	vector	vector	NOUN
admet-2772	841	13	machine	machine	NOUN
admet-2772	841	14	regression	regression	NOUN
admet-2772	841	15	.	.	PUNCT
admet-2772	842	1	international	international	ADJ
admet-2772	842	2	journal	journal	NOUN
admet-2772	842	3	of	of	ADP
admet-2772	842	4	molecular	molecular	ADJ
admet-2772	842	5	sciences	science	NOUN
admet-2772	842	6	9	9	NUM
admet-2772	842	7	(	(	PUNCT
admet-2772	842	8	2008	2008	NUM
admet-2772	842	9	)	)	PUNCT
admet-2772	842	10	1961	1961	NUM
admet-2772	842	11	-	-	SYM
admet-2772	842	12	1976	1976	NUM
admet-2772	842	13	.	.	PUNCT
admet-2772	843	1	https://doi.org/10.3390/ijms9101961	https://doi.org/10.3390/ijms9101961	PROPN
admet-2772	843	2	[	[	X
admet-2772	843	3	58	58	NUM
admet-2772	843	4	]	]	PUNCT
admet-2772	843	5	j.	j.	PROPN
admet-2772	843	6	shen	shen	PROPN
admet-2772	843	7	,	,	PUNCT
admet-2772	843	8	f.	f.	PROPN
admet-2772	843	9	cheng	cheng	PROPN
admet-2772	843	10	,	,	PUNCT
admet-2772	843	11	y.	y.	PROPN
admet-2772	843	12	xu	xu	PROPN
admet-2772	843	13	,	,	PUNCT
admet-2772	843	14	w.	w.	PROPN
admet-2772	843	15	li	li	PROPN
admet-2772	843	16	,	,	PUNCT
admet-2772	843	17	y.	y.	PROPN
admet-2772	843	18	tang	tang	PROPN
admet-2772	843	19	.	.	PUNCT
admet-2772	844	1	estimation	estimation	NOUN
admet-2772	844	2	of	of	ADP
admet-2772	844	3	adme	adme	NOUN
admet-2772	844	4	properties	property	NOUN
admet-2772	844	5	with	with	ADP
admet-2772	844	6	substructure	substructure	NOUN
admet-2772	844	7	pattern	pattern	NOUN
admet-2772	844	8	recognition	recognition	NOUN
admet-2772	844	9	.	.	PUNCT
admet-2772	845	1	journal	journal	PROPN
admet-2772	845	2	of	of	ADP
admet-2772	845	3	chemical	chemical	ADJ
admet-2772	845	4	information	information	NOUN
admet-2772	845	5	and	and	CCONJ
admet-2772	845	6	modeling	model	VERB
admet-2772	845	7	50	50	NUM
admet-2772	845	8	(	(	PUNCT
admet-2772	845	9	2010	2010	NUM
admet-2772	845	10	)	)	PUNCT
admet-2772	845	11	1034	1034	NUM
admet-2772	845	12	-	-	SYM
admet-2772	845	13	1041	1041	NUM
admet-2772	845	14	.	.	PUNCT
admet-2772	846	1	https://doi.org/10.1021/ci100104j	https://doi.org/10.1021/ci100104j	PROPN
admet-2772	847	1	[	[	X
admet-2772	847	2	59	59	NUM
admet-2772	847	3	]	]	PUNCT
admet-2772	847	4	r.	r.	PROPN
admet-2772	847	5	bei	bei	PROPN
admet-2772	847	6	,	,	PUNCT
admet-2772	847	7	j.	j.	PROPN
admet-2772	847	8	thomas	thomas	PROPN
admet-2772	847	9	,	,	PUNCT
admet-2772	847	10	s.	s.	PROPN
admet-2772	847	11	kapur	kapur	PROPN
admet-2772	847	12	,	,	PUNCT
admet-2772	847	13	m.	m.	NOUN
admet-2772	847	14	woldeyes	woldeyes	PROPN
admet-2772	847	15	,	,	PUNCT
admet-2772	847	16	a.	a.	NOUN
admet-2772	847	17	rauk	rauk	PROPN
admet-2772	847	18	,	,	PUNCT
admet-2772	847	19	j.	j.	PROPN
admet-2772	847	20	robarge	robarge	PROPN
admet-2772	847	21	,	,	PUNCT
admet-2772	847	22	j.	j.	PROPN
admet-2772	847	23	feng	feng	PROPN
admet-2772	847	24	,	,	PUNCT
admet-2772	847	25	k.	k.	PROPN
admet-2772	847	26	abbou	abbou	PROPN
admet-2772	847	27	oucherif	oucherif	PROPN
admet-2772	847	28	.	.	PUNCT
admet-2772	848	1	predicting	predict	VERB
admet-2772	848	2	the	the	DET
admet-2772	848	3	clinical	clinical	ADJ
admet-2772	848	4	subcutaneous	subcutaneous	ADJ
admet-2772	848	5	absorption	absorption	NOUN
admet-2772	848	6	rate	rate	NOUN
admet-2772	848	7	constant	constant	ADJ
admet-2772	848	8	of	of	ADP
admet-2772	848	9	monoclonal	monoclonal	NOUN
admet-2772	848	10	antibodies	antibody	NOUN
admet-2772	848	11	using	use	VERB
admet-2772	848	12	only	only	ADV
admet-2772	848	13	the	the	DET
admet-2772	848	14	primary	primary	ADJ
admet-2772	848	15	sequence	sequence	NOUN
admet-2772	848	16	:	:	PUNCT
admet-2772	848	17	a	a	DET
admet-2772	848	18	machine	machine	NOUN
admet-2772	848	19	learning	learn	VERB
admet-2772	848	20	approach	approach	NOUN
admet-2772	848	21	.	.	PUNCT
admet-2772	849	1	mabs	mab	NOUN
admet-2772	849	2	16	16	NUM
admet-2772	849	3	(	(	PUNCT
admet-2772	849	4	2024	2024	NUM
admet-2772	849	5	)	)	PUNCT
admet-2772	849	6	2352887	2352887	NUM
admet-2772	849	7	.	.	PUNCT
admet-2772	850	1	https://doi.org/10.1080/19420862.2024.2352887	https://doi.org/10.1080/19420862.2024.2352887	VERB
admet-2772	851	1	[	[	X
admet-2772	851	2	60	60	NUM
admet-2772	851	3	]	]	X
admet-2772	851	4	y.	y.	PROPN
admet-2772	851	5	kamiya	kamiya	PROPN
admet-2772	851	6	,	,	PUNCT
admet-2772	851	7	k.	k.	PROPN
admet-2772	851	8	handa	handa	PROPN
admet-2772	851	9	,	,	PUNCT
admet-2772	851	10	t.	t.	PROPN
admet-2772	851	11	miura	miura	PROPN
admet-2772	851	12	,	,	PUNCT
admet-2772	851	13	j.	j.	PROPN
admet-2772	851	14	ohori	ohori	PROPN
admet-2772	851	15	,	,	PUNCT
admet-2772	851	16	a.	a.	PROPN
admet-2772	851	17	kato	kato	PROPN
admet-2772	851	18	,	,	PUNCT
admet-2772	851	19	m.	m.	PROPN
admet-2772	851	20	shimizu	shimizu	PROPN
admet-2772	851	21	,	,	PUNCT
admet-2772	851	22	m.	m.	PROPN
admet-2772	851	23	kitajima	kitajima	PROPN
admet-2772	851	24	,	,	PUNCT
admet-2772	851	25	h.	h.	PROPN
admet-2772	851	26	yamazaki	yamazaki	PROPN
admet-2772	851	27	.	.	PUNCT
admet-2772	852	1	machine	machine	NOUN
admet-2772	852	2	learning	learn	VERB
admet-2772	852	3	prediction	prediction	NOUN
admet-2772	852	4	of	of	ADP
admet-2772	852	5	the	the	DET
admet-2772	852	6	three	three	NUM
admet-2772	852	7	main	main	ADJ
admet-2772	852	8	input	input	NOUN
admet-2772	852	9	parameters	parameter	NOUN
admet-2772	852	10	of	of	ADP
admet-2772	852	11	a	a	DET
admet-2772	852	12	simplified	simplified	ADJ
admet-2772	852	13	physiologically	physiologically	ADV
admet-2772	852	14	based	base	VERB
admet-2772	852	15	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	852	16	model	model	NOUN
admet-2772	852	17	subsequently	subsequently	ADV
admet-2772	852	18	used	use	VERB
admet-2772	852	19	to	to	PART
admet-2772	852	20	generate	generate	VERB
admet-2772	852	21	time	time	NOUN
admet-2772	852	22	-	-	PUNCT
admet-2772	852	23	dependent	dependent	ADJ
admet-2772	852	24	plasma	plasma	NOUN
admet-2772	852	25	concentration	concentration	NOUN
admet-2772	852	26	data	datum	NOUN
admet-2772	852	27	in	in	ADP
admet-2772	852	28	humans	human	NOUN
admet-2772	852	29	after	after	ADP
admet-2772	852	30	oral	oral	ADJ
admet-2772	852	31	doses	dose	NOUN
admet-2772	852	32	of	of	ADP
admet-2772	852	33	212	212	NUM
admet-2772	852	34	disparate	disparate	ADJ
admet-2772	852	35	chemicals	chemical	NOUN
admet-2772	852	36	.	.	PUNCT
admet-2772	853	1	biological	biological	ADJ
admet-2772	853	2	and	and	CCONJ
admet-2772	853	3	pharmaceutical	pharmaceutical	ADJ
admet-2772	853	4	bulletin	bulletin	NOUN
admet-2772	853	5	45	45	NUM
admet-2772	853	6	(	(	PUNCT
admet-2772	853	7	2022	2022	NUM
admet-2772	853	8	)	)	PUNCT
admet-2772	853	9	124	124	NUM
admet-2772	853	10	-	-	SYM
admet-2772	853	11	128	128	NUM
admet-2772	853	12	.	.	PUNCT
admet-2772	854	1	https://doi.org/10.1248/bpb.b21-00769	https://doi.org/10.1248/bpb.b21-00769	NOUN
admet-2772	855	1	[	[	X
admet-2772	855	2	61	61	NUM
admet-2772	855	3	]	]	X
admet-2772	855	4	v.d	v.d	PROPN
admet-2772	855	5	.	.	PROPN
admet-2772	855	6	karalis	karalis	PROPN
admet-2772	855	7	.	.	PUNCT
admet-2772	855	8	machine	machine	NOUN
admet-2772	855	9	learning	learning	NOUN
admet-2772	855	10	in	in	ADP
admet-2772	855	11	bioequivalence	bioequivalence	NOUN
admet-2772	855	12	:	:	PUNCT
admet-2772	855	13	towards	towards	ADP
admet-2772	855	14	identifying	identify	VERB
admet-2772	855	15	an	an	DET
admet-2772	855	16	appropriate	appropriate	ADJ
admet-2772	855	17	measure	measure	NOUN
admet-2772	855	18	of	of	ADP
admet-2772	855	19	absorption	absorption	NOUN
admet-2772	855	20	rate	rate	NOUN
admet-2772	855	21	.	.	PUNCT
admet-2772	856	1	applied	apply	VERB
admet-2772	856	2	sciences	sciences	PROPN
admet-2772	856	3	(	(	PUNCT
admet-2772	856	4	switzerland	switzerland	PROPN
admet-2772	856	5	)	)	PUNCT
admet-2772	856	6	13(1	13(1	NUM
admet-2772	856	7	)	)	PUNCT
admet-2772	856	8	(	(	PUNCT
admet-2772	856	9	2023	2023	NUM
admet-2772	856	10	)	)	PUNCT
admet-2772	856	11	418	418	NUM
admet-2772	856	12	.	.	PUNCT
admet-2772	857	1	https://doi.org/10.3390/app13010418	https://doi.org/10.3390/app13010418	NOUN
admet-2772	858	1	[	[	X
admet-2772	858	2	62	62	NUM
admet-2772	858	3	]	]	PUNCT
admet-2772	858	4	k.	k.	PROPN
admet-2772	858	5	kumar	kumar	PROPN
admet-2772	858	6	,	,	PUNCT
admet-2772	858	7	v.	v.	PROPN
admet-2772	858	8	chupakhin	chupakhin	PROPN
admet-2772	858	9	,	,	PUNCT
admet-2772	858	10	a.	a.	NOUN
admet-2772	858	11	vos	vos	PROPN
admet-2772	858	12	,	,	PUNCT
admet-2772	858	13	d.	d.	PROPN
admet-2772	858	14	morrison	morrison	PROPN
admet-2772	858	15	,	,	PUNCT
admet-2772	858	16	d.	d.	PROPN
admet-2772	858	17	rassokhin	rassokhin	PROPN
admet-2772	858	18	,	,	PUNCT
admet-2772	858	19	m.j	m.j	PROPN
admet-2772	858	20	.	.	PROPN
admet-2772	858	21	dellwo	dellwo	PROPN
admet-2772	858	22	,	,	PUNCT
admet-2772	858	23	k.	k.	PROPN
admet-2772	858	24	mccormick	mccormick	PROPN
admet-2772	858	25	,	,	PUNCT
admet-2772	858	26	e.	e.	PROPN
admet-2772	858	27	paternoster	paternoster	PROPN
admet-2772	858	28	,	,	PUNCT
admet-2772	858	29	h.	h.	PROPN
admet-2772	858	30	ceulemans	ceulemans	PROPN
admet-2772	858	31	,	,	PUNCT
admet-2772	858	32	r.l	r.l	PROPN
admet-2772	858	33	.	.	PROPN
admet-2772	858	34	desjarlais	desjarlais	PROPN
admet-2772	858	35	.	.	PUNCT
admet-2772	859	1	development	development	NOUN
admet-2772	859	2	and	and	CCONJ
admet-2772	859	3	implementation	implementation	NOUN
admet-2772	859	4	of	of	ADP
admet-2772	859	5	an	an	DET
admet-2772	859	6	enterprise	enterprise	NOUN
admet-2772	859	7	-	-	PUNCT
admet-2772	859	8	wide	wide	ADJ
admet-2772	859	9	predictive	predictive	ADJ
admet-2772	859	10	model	model	NOUN
admet-2772	859	11	for	for	ADP
admet-2772	859	12	early	early	ADJ
admet-2772	859	13	absorption	absorption	NOUN
admet-2772	859	14	,	,	PUNCT
admet-2772	859	15	distribution	distribution	NOUN
admet-2772	859	16	,	,	PUNCT
admet-2772	859	17	metabolism	metabolism	NOUN
admet-2772	859	18	and	and	CCONJ
admet-2772	859	19	excretion	excretion	NOUN
admet-2772	859	20	properties	property	NOUN
admet-2772	859	21	.	.	PUNCT
admet-2772	860	1	future	future	ADJ
admet-2772	860	2	medicinal	medicinal	ADJ
admet-2772	860	3	chemistry	chemistry	NOUN
admet-2772	860	4	13	13	NUM
admet-2772	860	5	(	(	PUNCT
admet-2772	860	6	2021	2021	NUM
admet-2772	860	7	)	)	PUNCT
admet-2772	860	8	1639	1639	NUM
admet-2772	860	9	-	-	SYM
admet-2772	860	10	1654	1654	NUM
admet-2772	860	11	.	.	PUNCT
admet-2772	861	1	https://doi.org/10.4155/fmc-2021-0138	https://doi.org/10.4155/fmc-2021-0138	PROPN
admet-2772	862	1	[	[	X
admet-2772	862	2	63	63	NUM
admet-2772	862	3	]	]	PUNCT
admet-2772	862	4	u.	u.	PROPN
admet-2772	862	5	fagerholm	fagerholm	PROPN
admet-2772	862	6	,	,	PUNCT
admet-2772	862	7	s.	s.	PROPN
admet-2772	862	8	hellberg	hellberg	PROPN
admet-2772	862	9	,	,	PUNCT
admet-2772	862	10	o.	o.	PROPN
admet-2772	862	11	spjuth	spjuth	PROPN
admet-2772	862	12	.	.	PUNCT
admet-2772	863	1	article	article	NOUN
admet-2772	863	2	advances	advance	VERB
admet-2772	863	3	in	in	ADP
admet-2772	863	4	predictions	prediction	NOUN
admet-2772	863	5	of	of	ADP
admet-2772	863	6	oral	oral	ADJ
admet-2772	863	7	bioavailability	bioavailability	NOUN
admet-2772	863	8	of	of	ADP
admet-2772	863	9	candidate	candidate	NOUN
admet-2772	863	10	drugs	drug	NOUN
admet-2772	863	11	in	in	ADP
admet-2772	863	12	man	man	NOUN
admet-2772	863	13	with	with	ADP
admet-2772	863	14	new	new	ADJ
admet-2772	863	15	machine	machine	NOUN
admet-2772	863	16	learning	learn	VERB
admet-2772	863	17	methodology	methodology	NOUN
admet-2772	863	18	.	.	PUNCT
admet-2772	864	1	molecules	molecule	NOUN
admet-2772	864	2	26(9	26(9	NUM
admet-2772	864	3	)	)	PUNCT
admet-2772	864	4	(	(	PUNCT
admet-2772	864	5	2021	2021	NUM
admet-2772	864	6	)	)	PUNCT
admet-2772	864	7	2572	2572	NUM
admet-2772	864	8	.	.	PUNCT
admet-2772	865	1	https://doi.org/10.3390/molecules26092572	https://doi.org/10.3390/molecules26092572	PROPN
admet-2772	865	2	[	[	X
admet-2772	865	3	64	64	NUM
admet-2772	865	4	]	]	PUNCT
admet-2772	865	5	h.	h.	PROPN
admet-2772	865	6	bennett	bennett	PROPN
admet-2772	865	7	-	-	PUNCT
admet-2772	865	8	lenane	lenane	PROPN
admet-2772	865	9	,	,	PUNCT
admet-2772	865	10	b.t	b.t	PROPN
admet-2772	865	11	.	.	PROPN
admet-2772	865	12	griffin	griffin	PROPN
admet-2772	865	13	,	,	PUNCT
admet-2772	865	14	j.p	j.p	PROPN
admet-2772	865	15	.	.	PROPN
admet-2772	865	16	o’shea	o’shea	PROPN
admet-2772	865	17	.	.	PUNCT
admet-2772	866	1	machine	machine	NOUN
admet-2772	866	2	learning	learn	VERB
admet-2772	866	3	methods	method	NOUN
admet-2772	866	4	for	for	ADP
admet-2772	866	5	prediction	prediction	NOUN
admet-2772	866	6	of	of	ADP
admet-2772	866	7	food	food	NOUN
admet-2772	866	8	effects	effect	NOUN
admet-2772	866	9	on	on	ADP
admet-2772	866	10	bioavailability	bioavailability	NOUN
admet-2772	866	11	:	:	PUNCT
admet-2772	866	12	a	a	DET
admet-2772	866	13	comparison	comparison	NOUN
admet-2772	866	14	of	of	ADP
admet-2772	866	15	support	support	NOUN
admet-2772	866	16	vector	vector	NOUN
admet-2772	866	17	machines	machine	NOUN
admet-2772	866	18	and	and	CCONJ
admet-2772	866	19	artificial	artificial	ADJ
admet-2772	866	20	neural	neural	ADJ
admet-2772	866	21	networks	network	NOUN
admet-2772	866	22	.	.	PUNCT
admet-2772	867	1	european	european	ADJ
admet-2772	867	2	journal	journal	PROPN
admet-2772	867	3	of	of	ADP
admet-2772	867	4	pharmaceutical	pharmaceutical	PROPN
admet-2772	867	5	sciences	science	NOUN
admet-2772	867	6	168	168	NUM
admet-2772	867	7	(	(	PUNCT
admet-2772	867	8	2022	2022	NUM
admet-2772	867	9	)	)	PUNCT
admet-2772	867	10	106018	106018	NUM
admet-2772	867	11	.	.	PUNCT
admet-2772	868	1	https://doi.org/10.1016/j.ejps.2021.106018	https://doi.org/10.1016/j.ejps.2021.106018	NOUN
admet-2772	869	1	[	[	X
admet-2772	869	2	65	65	NUM
admet-2772	869	3	]	]	X
admet-2772	869	4	s.s.s	s.s.s	PROPN
admet-2772	869	5	.	.	PUNCT
admet-2772	870	1	ng	ng	PROPN
admet-2772	870	2	,	,	PUNCT
admet-2772	870	3	y.	y.	PROPN
admet-2772	870	4	lu	lu	PROPN
admet-2772	870	5	.	.	PUNCT
admet-2772	871	1	evaluating	evaluate	VERB
admet-2772	871	2	the	the	DET
admet-2772	871	3	use	use	NOUN
admet-2772	871	4	of	of	ADP
admet-2772	871	5	graph	graph	NOUN
admet-2772	871	6	neural	neural	ADJ
admet-2772	871	7	networks	network	NOUN
admet-2772	871	8	and	and	CCONJ
admet-2772	871	9	transfer	transfer	NOUN
admet-2772	871	10	learning	learning	NOUN
admet-2772	871	11	for	for	ADP
admet-2772	871	12	oral	oral	ADJ
admet-2772	871	13	bioavailability	bioavailability	NOUN
admet-2772	871	14	prediction	prediction	NOUN
admet-2772	871	15	.	.	PUNCT
admet-2772	872	1	journal	journal	PROPN
admet-2772	872	2	of	of	ADP
admet-2772	872	3	chemical	chemical	ADJ
admet-2772	872	4	information	information	NOUN
admet-2772	872	5	and	and	CCONJ
admet-2772	872	6	modeling	model	VERB
admet-2772	872	7	63	63	NUM
admet-2772	872	8	(	(	PUNCT
admet-2772	872	9	2023	2023	NUM
admet-2772	872	10	)	)	PUNCT
admet-2772	872	11	5035	5035	NUM
admet-2772	872	12	-	-	SYM
admet-2772	872	13	5044	5044	NUM
admet-2772	872	14	.	.	PUNCT
admet-2772	873	1	https://doi.org/10.1021/acs.jcim.3c00554	https://doi.org/10.1021/acs.jcim.3c00554	NOUN
admet-2772	874	1	[	[	X
admet-2772	874	2	66	66	NUM
admet-2772	874	3	]	]	PUNCT
admet-2772	874	4	k.	k.	PROPN
admet-2772	874	5	holt	holt	PROPN
admet-2772	874	6	,	,	PUNCT
admet-2772	874	7	s.	s.	PROPN
admet-2772	874	8	nagar	nagar	PROPN
admet-2772	874	9	,	,	PUNCT
admet-2772	874	10	k.	k.	PROPN
admet-2772	874	11	korzekwa	korzekwa	PROPN
admet-2772	874	12	.	.	PUNCT
admet-2772	875	1	methods	method	NOUN
admet-2772	875	2	to	to	PART
admet-2772	875	3	predict	predict	VERB
admet-2772	875	4	volume	volume	NOUN
admet-2772	875	5	of	of	ADP
admet-2772	875	6	distribution	distribution	NOUN
admet-2772	875	7	.	.	PUNCT
admet-2772	876	1	current	current	ADJ
admet-2772	876	2	pharmacology	pharmacology	NOUN
admet-2772	876	3	reports	report	VERB
admet-2772	876	4	5	5	NUM
admet-2772	876	5	(	(	PUNCT
admet-2772	876	6	2019	2019	NUM
admet-2772	876	7	)	)	PUNCT
admet-2772	876	8	391	391	NUM
admet-2772	876	9	-	-	SYM
admet-2772	876	10	399	399	NUM
admet-2772	876	11	.	.	PUNCT
admet-2772	876	12	https://doi.org/10.1007/s40495-019-00186-5	https://doi.org/10.1007/s40495-019-00186-5	NUM
admet-2772	877	1	[	[	X
admet-2772	877	2	67	67	NUM
admet-2772	877	3	]	]	PUNCT
admet-2772	877	4	x.	x.	PROPN
admet-2772	877	5	liu	liu	PROPN
admet-2772	877	6	,	,	PUNCT
admet-2772	877	7	b.j	b.j	PROPN
admet-2772	877	8	.	.	PROPN
admet-2772	877	9	smith	smith	PROPN
admet-2772	877	10	,	,	PUNCT
admet-2772	877	11	c.	c.	PROPN
admet-2772	877	12	chen	chen	PROPN
admet-2772	877	13	,	,	PUNCT
admet-2772	877	14	e.	e.	PROPN
admet-2772	877	15	callegari	callegari	PROPN
admet-2772	877	16	,	,	PUNCT
admet-2772	877	17	s.l	s.l	PROPN
admet-2772	877	18	.	.	PROPN
admet-2772	877	19	becker	becker	PROPN
admet-2772	877	20	,	,	PUNCT
admet-2772	877	21	x.	x.	PROPN
admet-2772	877	22	chen	chen	PROPN
admet-2772	877	23	,	,	PUNCT
admet-2772	877	24	j.	j.	PROPN
admet-2772	877	25	cianfrogna	cianfrogna	PROPN
admet-2772	877	26	,	,	PUNCT
admet-2772	877	27	a.c	a.c	PROPN
admet-2772	877	28	.	.	PROPN
admet-2772	877	29	doran	doran	PROPN
admet-2772	877	30	,	,	PUNCT
admet-2772	877	31	s.d	s.d	PROPN
admet-2772	877	32	.	.	PROPN
admet-2772	877	33	doran	doran	PROPN
admet-2772	877	34	,	,	PUNCT
admet-2772	877	35	j.p	j.p	PROPN
admet-2772	877	36	.	.	PROPN
admet-2772	877	37	gibbs	gibbs	PROPN
admet-2772	877	38	,	,	PUNCT
admet-2772	877	39	n.	n.	PROPN
admet-2772	877	40	hosea	hosea	PROPN
admet-2772	877	41	,	,	PUNCT
admet-2772	877	42	j.	j.	PROPN
admet-2772	877	43	liu	liu	PROPN
admet-2772	877	44	,	,	PUNCT
admet-2772	877	45	f.r	f.r	PROPN
admet-2772	877	46	.	.	PROPN
admet-2772	877	47	nelson	nelson	PROPN
admet-2772	877	48	,	,	PUNCT
admet-2772	877	49	m.a	m.a	PROPN
admet-2772	877	50	.	.	PROPN
admet-2772	877	51	szewc	szewc	PROPN
admet-2772	877	52	,	,	PUNCT
admet-2772	877	53	j.	j.	PROPN
admet-2772	877	54	van	van	PROPN
admet-2772	877	55	deusen	deusen	PROPN
admet-2772	877	56	.	.	PUNCT
admet-2772	878	1	use	use	NOUN
admet-2772	878	2	of	of	ADP
admet-2772	878	3	a	a	DET
admet-2772	878	4	physiologically	physiologically	ADV
admet-2772	878	5	based	base	VERB
admet-2772	878	6	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	878	7	model	model	NOUN
admet-2772	878	8	to	to	PART
admet-2772	878	9	study	study	VERB
admet-2772	878	10	the	the	DET
admet-2772	878	11	time	time	NOUN
admet-2772	878	12	to	to	PART
admet-2772	878	13	reach	reach	VERB
admet-2772	878	14	brain	brain	NOUN
admet-2772	878	15	equilibrium	equilibrium	NOUN
admet-2772	878	16	:	:	PUNCT
admet-2772	878	17	an	an	DET
admet-2772	878	18	experimental	experimental	ADJ
admet-2772	878	19	analysis	analysis	NOUN
admet-2772	878	20	of	of	ADP
admet-2772	878	21	the	the	DET
admet-2772	878	22	role	role	NOUN
admet-2772	878	23	of	of	ADP
admet-2772	878	24	blood	blood	NOUN
admet-2772	878	25	-	-	PUNCT
admet-2772	878	26	brain	brain	NOUN
admet-2772	878	27	barrier	barrier	NOUN
admet-2772	878	28	permeability	permeability	NOUN
admet-2772	878	29	,	,	PUNCT
admet-2772	878	30	plasma	plasma	NOUN
admet-2772	878	31	protein	protein	NOUN
admet-2772	878	32	binding	bind	VERB
admet-2772	878	33	,	,	PUNCT
admet-2772	878	34	and	and	CCONJ
admet-2772	878	35	brain	brain	NOUN
admet-2772	878	36	tissue	tissue	NOUN
admet-2772	878	37	binding	bind	VERB
admet-2772	878	38	.	.	PUNCT
admet-2772	879	1	journal	journal	PROPN
admet-2772	879	2	of	of	ADP
admet-2772	879	3	pharmacology	pharmacology	NOUN
admet-2772	879	4	and	and	CCONJ
admet-2772	879	5	experimental	experimental	ADJ
admet-2772	879	6	therapeutics	therapeutic	NOUN
admet-2772	879	7	313	313	NUM
admet-2772	879	8	(	(	PUNCT
admet-2772	879	9	2005	2005	NUM
admet-2772	879	10	)	)	PUNCT
admet-2772	879	11	1254	1254	NUM
admet-2772	879	12	-	-	SYM
admet-2772	879	13	1262	1262	NUM
admet-2772	879	14	.	.	PUNCT
admet-2772	880	1	https://doi.org/10.1124/jpet.104.079319	https://doi.org/10.1124/jpet.104.079319	PROPN
admet-2772	880	2	[	[	X
admet-2772	880	3	68	68	NUM
admet-2772	880	4	]	]	X
admet-2772	880	5	q.r	q.r	PROPN
admet-2772	880	6	.	.	PROPN
admet-2772	880	7	smith	smith	PROPN
admet-2772	880	8	,	,	PUNCT
admet-2772	880	9	r.	r.	PROPN
admet-2772	880	10	samala	samala	PROPN
admet-2772	880	11	.	.	PUNCT
admet-2772	881	1	in	in	ADP
admet-2772	881	2	situ	situ	NOUN
admet-2772	881	3	and	and	CCONJ
admet-2772	881	4	in	in	ADP
admet-2772	881	5	vivo	vivo	NOUN
admet-2772	881	6	animal	animal	NOUN
admet-2772	881	7	models	model	NOUN
admet-2772	881	8	.	.	PUNCT
admet-2772	882	1	aaps	aap	NOUN
admet-2772	882	2	advances	advance	VERB
admet-2772	882	3	in	in	ADP
admet-2772	882	4	the	the	DET
admet-2772	882	5	pharmaceutical	pharmaceutical	ADJ
admet-2772	882	6	sciences	sciences	PROPN
admet-2772	882	7	series	series	NOUN
admet-2772	882	8	10	10	NUM
admet-2772	882	9	(	(	PUNCT
admet-2772	882	10	2014	2014	NUM
admet-2772	882	11	)	)	PUNCT
admet-2772	882	12	199	199	NUM
admet-2772	882	13	-	-	SYM
admet-2772	882	14	211	211	NUM
admet-2772	882	15	.	.	PUNCT
admet-2772	883	1	https://doi.org/10.1007/978-1-4614-9105-7_7	https://doi.org/10.1007/978-1-4614-9105-7_7	NOUN
admet-2772	883	2	[	[	X
admet-2772	883	3	69	69	NUM
admet-2772	883	4	]	]	X
admet-2772	883	5	n.n	n.n	PROPN
admet-2772	883	6	.	.	PROPN
admet-2772	883	7	wang	wang	PROPN
admet-2772	883	8	,	,	PUNCT
admet-2772	883	9	c.	c.	PROPN
admet-2772	883	10	huang	huang	PROPN
admet-2772	883	11	,	,	PUNCT
admet-2772	883	12	j.	j.	PROPN
admet-2772	883	13	dong	dong	PROPN
admet-2772	883	14	,	,	PUNCT
admet-2772	883	15	z.j	z.j	PROPN
admet-2772	883	16	.	.	PROPN
admet-2772	883	17	yao	yao	PROPN
admet-2772	883	18	,	,	PUNCT
admet-2772	883	19	m.f	m.f	PROPN
admet-2772	883	20	.	.	PUNCT
admet-2772	884	1	zhu	zhu	PROPN
admet-2772	884	2	,	,	PUNCT
admet-2772	884	3	z.k	z.k	PROPN
admet-2772	884	4	.	.	PROPN
admet-2772	884	5	deng	deng	PROPN
admet-2772	884	6	,	,	PUNCT
admet-2772	884	7	b.	b.	PROPN
admet-2772	884	8	lv	lv	PROPN
admet-2772	884	9	,	,	PUNCT
admet-2772	884	10	a.p	a.p	PROPN
admet-2772	884	11	.	.	PROPN
admet-2772	884	12	lu	lu	PROPN
admet-2772	884	13	,	,	PUNCT
admet-2772	884	14	a.f	a.f	PROPN
admet-2772	885	1	.	.	PROPN
admet-2772	885	2	chen	chen	PROPN
admet-2772	885	3	,	,	PUNCT
admet-2772	885	4	d.s	d.s	PROPN
admet-2772	885	5	.	.	PROPN
admet-2772	885	6	cao	cao	PROPN
admet-2772	885	7	.	.	PUNCT
admet-2772	886	1	predicting	predict	VERB
admet-2772	886	2	human	human	ADJ
admet-2772	886	3	intestinal	intestinal	ADJ
admet-2772	886	4	absorption	absorption	NOUN
admet-2772	886	5	with	with	ADP
admet-2772	886	6	modified	modify	VERB
admet-2772	886	7	random	random	ADJ
admet-2772	886	8	forest	forest	NOUN
admet-2772	886	9	approach	approach	NOUN
admet-2772	886	10	:	:	PUNCT
admet-2772	886	11	a	a	DET
admet-2772	886	12	comprehensive	comprehensive	ADJ
admet-2772	886	13	evaluation	evaluation	NOUN
admet-2772	886	14	of	of	ADP
admet-2772	886	15	molecular	molecular	ADJ
admet-2772	886	16	representation	representation	NOUN
admet-2772	886	17	,	,	PUNCT
admet-2772	886	18	unbalanced	unbalanced	ADJ
admet-2772	886	19	data	datum	NOUN
admet-2772	886	20	,	,	PUNCT
admet-2772	886	21	and	and	CCONJ
admet-2772	886	22	applicability	applicability	NOUN
admet-2772	886	23	domain	domain	NOUN
admet-2772	886	24	issues	issue	NOUN
admet-2772	886	25	.	.	PUNCT
admet-2772	887	1	rsc	rsc	PROPN
admet-2772	887	2	advances	advance	VERB
admet-2772	887	3	7	7	NUM
admet-2772	887	4	(	(	PUNCT
admet-2772	887	5	2017	2017	NUM
admet-2772	887	6	)	)	PUNCT
admet-2772	887	7	19007	19007	NUM
admet-2772	887	8	-	-	SYM
admet-2772	887	9	19018	19018	NUM
admet-2772	887	10	.	.	PUNCT
admet-2772	888	1	https://doi.org/10.1039/c6ra28442f	https://doi.org/10.1039/c6ra28442f	PROPN
admet-2772	888	2	https://doi.org/10.1016/j.ejmech.2010.11.005	https://doi.org/10.1016/j.ejmech.2010.11.005	VERB
admet-2772	888	3	https://doi.org/10.3390/ijms9101961	https://doi.org/10.3390/ijms9101961	PROPN
admet-2772	888	4	https://doi.org/10.1021/ci100104j	https://doi.org/10.1021/ci100104j	NOUN
admet-2772	888	5	https://doi.org/10.1080/19420862.2024.2352887	https://doi.org/10.1080/19420862.2024.2352887	PROPN
admet-2772	888	6	https://doi.org/10.1248/bpb.b21-00769	https://doi.org/10.1248/bpb.b21-00769	PROPN
admet-2772	888	7	https://doi.org/10.3390/app13010418	https://doi.org/10.3390/app13010418	PROPN
admet-2772	888	8	https://doi.org/10.4155/fmc-2021-0138	https://doi.org/10.4155/fmc-2021-0138	PROPN
admet-2772	888	9	https://doi.org/10.3390/molecules26092572	https://doi.org/10.3390/molecules26092572	PROPN
admet-2772	888	10	https://doi.org/10.1016/j.ejps.2021.106018	https://doi.org/10.1016/j.ejps.2021.106018	PROPN
admet-2772	888	11	https://doi.org/10.1021/acs.jcim.3c00554	https://doi.org/10.1021/acs.jcim.3c00554	PROPN
admet-2772	888	12	https://doi.org/10.1007/s40495-019-00186-5	https://doi.org/10.1007/s40495-019-00186-5	NUM
admet-2772	888	13	https://doi.org/10.1124/jpet.104.079319	https://doi.org/10.1124/jpet.104.079319	PROPN
admet-2772	888	14	https://doi.org/10.1007/978-1-4614-9105-7_7	https://doi.org/10.1007/978-1-4614-9105-7_7	PROPN
admet-2772	888	15	https://doi.org/10.1039/c6ra28442f	https://doi.org/10.1039/c6ra28442f	PROPN
admet-2772	888	16	admet	admet	PROPN
admet-2772	888	17	&	&	CCONJ
admet-2772	888	18	dmpk	dmpk	PROPN
admet-2772	888	19	13(3	13(3	NUM
admet-2772	888	20	)	)	PUNCT
admet-2772	888	21	(	(	PUNCT
admet-2772	888	22	2025	2025	NUM
admet-2772	888	23	)	)	PUNCT
admet-2772	888	24	2772	2772	NUM
admet-2772	888	25	machine	machine	NOUN
admet-2772	888	26	learning	learning	NOUN
admet-2772	888	27	models	model	NOUN
admet-2772	888	28	for	for	ADP
admet-2772	888	29	admet	admet	ADJ
admet-2772	888	30	prediction	prediction	NOUN
admet-2772	888	31	in	in	ADP
admet-2772	888	32	drug	drug	NOUN
admet-2772	888	33	development	development	NOUN
admet-2772	888	34	doi	doi	PROPN
admet-2772	888	35	:	:	PUNCT
admet-2772	888	36	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	888	37	29	29	NUM
admet-2772	889	1	[	[	SYM
admet-2772	889	2	70	70	NUM
admet-2772	889	3	]	]	X
admet-2772	889	4	e.	e.	PROPN
admet-2772	889	5	v.	v.	PROPN
admet-2772	889	6	radchenko	radchenko	PROPN
admet-2772	889	7	,	,	PUNCT
admet-2772	889	8	a.s	a.s	PROPN
admet-2772	889	9	.	.	PROPN
admet-2772	889	10	dyabina	dyabina	PROPN
admet-2772	889	11	,	,	PUNCT
admet-2772	889	12	v.a	v.a	PROPN
admet-2772	889	13	.	.	PROPN
admet-2772	889	14	palyulin	palyulin	PROPN
admet-2772	889	15	.	.	PROPN
admet-2772	890	1	towards	towards	ADP
admet-2772	890	2	deep	deep	ADJ
admet-2772	890	3	neural	neural	ADJ
admet-2772	890	4	network	network	NOUN
admet-2772	890	5	models	model	NOUN
admet-2772	890	6	for	for	ADP
admet-2772	890	7	the	the	DET
admet-2772	890	8	prediction	prediction	NOUN
admet-2772	890	9	of	of	ADP
admet-2772	890	10	the	the	DET
admet-2772	890	11	blood	blood	NOUN
admet-2772	890	12	-	-	PUNCT
admet-2772	890	13	brain	brain	NOUN
admet-2772	890	14	barrier	barrier	NOUN
admet-2772	890	15	permeability	permeability	NOUN
admet-2772	890	16	for	for	ADP
admet-2772	890	17	diverse	diverse	ADJ
admet-2772	890	18	organic	organic	ADJ
admet-2772	890	19	compounds	compound	NOUN
admet-2772	890	20	.	.	PUNCT
admet-2772	891	1	molecules	molecule	NOUN
admet-2772	891	2	25(24	25(24	NUM
admet-2772	891	3	)	)	PUNCT
admet-2772	891	4	(	(	PUNCT
admet-2772	891	5	2020	2020	NUM
admet-2772	891	6	)	)	PUNCT
admet-2772	891	7	5901	5901	NUM
admet-2772	891	8	.	.	PUNCT
admet-2772	892	1	https://doi.org/10.3390/molecules25245901	https://doi.org/10.3390/molecules25245901	PROPN
admet-2772	893	1	[	[	X
admet-2772	893	2	71	71	NUM
admet-2772	893	3	]	]	X
admet-2772	893	4	v.	v.	PROPN
admet-2772	893	5	antontsev	antontsev	PROPN
admet-2772	893	6	,	,	PUNCT
admet-2772	893	7	a.	a.	PROPN
admet-2772	893	8	jagarapu	jagarapu	PROPN
admet-2772	893	9	,	,	PUNCT
admet-2772	893	10	y.	y.	PROPN
admet-2772	893	11	bundey	bundey	PROPN
admet-2772	893	12	,	,	PUNCT
admet-2772	893	13	h.	h.	PROPN
admet-2772	893	14	hou	hou	PROPN
admet-2772	893	15	,	,	PUNCT
admet-2772	893	16	m.	m.	NOUN
admet-2772	893	17	khotimchenko	khotimchenko	PROPN
admet-2772	893	18	,	,	PUNCT
admet-2772	893	19	j.	j.	PROPN
admet-2772	893	20	walsh	walsh	PROPN
admet-2772	893	21	,	,	PUNCT
admet-2772	893	22	j.	j.	PROPN
admet-2772	893	23	varshney	varshney	PROPN
admet-2772	893	24	.	.	PUNCT
admet-2772	894	1	a	a	DET
admet-2772	894	2	hybrid	hybrid	ADJ
admet-2772	894	3	modeling	modeling	NOUN
admet-2772	894	4	approach	approach	NOUN
admet-2772	894	5	for	for	ADP
admet-2772	894	6	assessing	assess	VERB
admet-2772	894	7	mechanistic	mechanistic	ADJ
admet-2772	894	8	models	model	NOUN
admet-2772	894	9	of	of	ADP
admet-2772	894	10	small	small	ADJ
admet-2772	894	11	molecule	molecule	NOUN
admet-2772	894	12	partitioning	partitioning	NOUN
admet-2772	894	13	in	in	ADP
admet-2772	894	14	vivo	vivo	NOUN
admet-2772	894	15	using	use	VERB
admet-2772	894	16	a	a	DET
admet-2772	894	17	machine	machine	NOUN
admet-2772	894	18	learning	learning	NOUN
admet-2772	894	19	-	-	PUNCT
admet-2772	894	20	integrated	integrate	VERB
admet-2772	894	21	modeling	modeling	NOUN
admet-2772	894	22	platform	platform	NOUN
admet-2772	894	23	.	.	PUNCT
admet-2772	895	1	scientific	scientific	ADJ
admet-2772	895	2	reports	report	NOUN
admet-2772	895	3	11	11	NUM
admet-2772	895	4	(	(	PUNCT
admet-2772	895	5	2021	2021	NUM
admet-2772	895	6	)	)	PUNCT
admet-2772	895	7	11143	11143	NUM
admet-2772	895	8	.	.	PUNCT
admet-2772	896	1	https://doi.org/10.1038/s41598-021-90637-1	https://doi.org/10.1038/s41598-021-90637-1	NOUN
admet-2772	897	1	[	[	X
admet-2772	897	2	72	72	NUM
admet-2772	897	3	]	]	X
admet-2772	897	4	y.	y.	PROPN
admet-2772	897	5	yuan	yuan	PROPN
admet-2772	897	6	,	,	PUNCT
admet-2772	897	7	s.	s.	PROPN
admet-2772	897	8	chang	chang	PROPN
admet-2772	897	9	,	,	PUNCT
admet-2772	897	10	z.	z.	PROPN
admet-2772	897	11	zhang	zhang	PROPN
admet-2772	897	12	,	,	PUNCT
admet-2772	897	13	z.	z.	PROPN
admet-2772	897	14	li	li	PROPN
admet-2772	897	15	,	,	PUNCT
admet-2772	897	16	s.	s.	PROPN
admet-2772	897	17	li	li	PROPN
admet-2772	897	18	,	,	PUNCT
admet-2772	897	19	p.	p.	PROPN
admet-2772	897	20	xie	xie	PROPN
admet-2772	897	21	,	,	PUNCT
admet-2772	897	22	w.p	w.p	PROPN
admet-2772	897	23	.	.	PROPN
admet-2772	897	24	yau	yau	PROPN
admet-2772	897	25	,	,	PUNCT
admet-2772	897	26	h.	h.	PROPN
admet-2772	897	27	lin	lin	PROPN
admet-2772	897	28	,	,	PUNCT
admet-2772	897	29	w.	w.	PROPN
admet-2772	897	30	cai	cai	PROPN
admet-2772	897	31	,	,	PUNCT
admet-2772	897	32	y.	y.	PROPN
admet-2772	897	33	zhang	zhang	PROPN
admet-2772	897	34	,	,	PUNCT
admet-2772	897	35	x.	x.	PROPN
admet-2772	897	36	xiang	xiang	PROPN
admet-2772	897	37	.	.	PUNCT
admet-2772	898	1	a	a	DET
admet-2772	898	2	novel	novel	ADJ
admet-2772	898	3	strategy	strategy	NOUN
admet-2772	898	4	for	for	ADP
admet-2772	898	5	prediction	prediction	NOUN
admet-2772	898	6	of	of	ADP
admet-2772	898	7	human	human	ADJ
admet-2772	898	8	plasma	plasma	NOUN
admet-2772	898	9	protein	protein	NOUN
admet-2772	898	10	binding	bind	VERB
admet-2772	898	11	using	use	VERB
admet-2772	898	12	machine	machine	NOUN
admet-2772	898	13	learning	learn	VERB
admet-2772	898	14	techniques	technique	NOUN
admet-2772	898	15	.	.	PUNCT
admet-2772	899	1	chemometrics	chemometric	NOUN
admet-2772	899	2	and	and	CCONJ
admet-2772	899	3	intelligent	intelligent	ADJ
admet-2772	899	4	laboratory	laboratory	NOUN
admet-2772	899	5	systems	system	NOUN
admet-2772	899	6	199	199	NUM
admet-2772	899	7	(	(	PUNCT
admet-2772	899	8	2020	2020	NUM
admet-2772	899	9	)	)	PUNCT
admet-2772	899	10	103962	103962	NUM
admet-2772	899	11	.	.	PUNCT
admet-2772	900	1	https://doi.org/10.1016/j.chemolab.2020.103962	https://doi.org/10.1016/j.chemolab.2020.103962	PROPN
admet-2772	900	2	[	[	X
admet-2772	900	3	73	73	NUM
admet-2772	900	4	]	]	PUNCT
admet-2772	900	5	a.	a.	NOUN
admet-2772	900	6	khaouane	khaouane	PROPN
admet-2772	900	7	,	,	PUNCT
admet-2772	900	8	s.	s.	PROPN
admet-2772	900	9	ferhat	ferhat	PROPN
admet-2772	900	10	,	,	PUNCT
admet-2772	900	11	s.	s.	PROPN
admet-2772	900	12	hanini	hanini	PROPN
admet-2772	900	13	.	.	PUNCT
admet-2772	901	1	a	a	DET
admet-2772	901	2	novel	novel	ADJ
admet-2772	901	3	methodology	methodology	NOUN
admet-2772	901	4	for	for	ADP
admet-2772	901	5	human	human	ADJ
admet-2772	901	6	plasma	plasma	NOUN
admet-2772	901	7	protein	protein	NOUN
admet-2772	901	8	binding	bind	VERB
admet-2772	901	9	:	:	PUNCT
admet-2772	901	10	prediction	prediction	NOUN
admet-2772	901	11	,	,	PUNCT
admet-2772	901	12	validation	validation	NOUN
admet-2772	901	13	,	,	PUNCT
admet-2772	901	14	and	and	CCONJ
admet-2772	901	15	applicability	applicability	NOUN
admet-2772	901	16	domain	domain	NOUN
admet-2772	901	17	.	.	PUNCT
admet-2772	902	1	pharmaceutical	pharmaceutical	NOUN
admet-2772	902	2	and	and	CCONJ
admet-2772	902	3	biomedical	biomedical	ADJ
admet-2772	902	4	research	research	NOUN
admet-2772	902	5	8	8	NUM
admet-2772	902	6	(	(	PUNCT
admet-2772	902	7	2022	2022	NUM
admet-2772	902	8	)	)	PUNCT
admet-2772	902	9	311	311	NUM
admet-2772	902	10	-	-	SYM
admet-2772	902	11	322	322	NUM
admet-2772	902	12	.	.	PUNCT
admet-2772	903	1	https://doi.org/10.32598/pbr.8.4.1086.1	https://doi.org/10.32598/pbr.8.4.1086.1	PROPN
admet-2772	904	1	[	[	X
admet-2772	904	2	74	74	NUM
admet-2772	904	3	]	]	SYM
admet-2772	904	4	i.f	i.f	PROPN
admet-2772	904	5	.	.	PUNCT
admet-2772	904	6	martins	martin	NOUN
admet-2772	904	7	,	,	PUNCT
admet-2772	904	8	a.l	a.l	PROPN
admet-2772	904	9	.	.	PROPN
admet-2772	904	10	teixeira	teixeira	PROPN
admet-2772	904	11	,	,	PUNCT
admet-2772	904	12	l.	l.	PROPN
admet-2772	904	13	pinheiro	pinheiro	PROPN
admet-2772	904	14	,	,	PUNCT
admet-2772	904	15	a.o	a.o	PROPN
admet-2772	904	16	.	.	PROPN
admet-2772	904	17	falcao	falcao	PROPN
admet-2772	904	18	.	.	PUNCT
admet-2772	905	1	a	a	DET
admet-2772	905	2	bayesian	bayesian	NOUN
admet-2772	905	3	approach	approach	NOUN
admet-2772	905	4	to	to	ADP
admet-2772	905	5	in	in	ADP
admet-2772	905	6	silico	silico	NOUN
admet-2772	905	7	blood	blood	NOUN
admet-2772	905	8	-	-	PUNCT
admet-2772	905	9	brain	brain	NOUN
admet-2772	905	10	barrier	barrier	NOUN
admet-2772	905	11	penetration	penetration	NOUN
admet-2772	905	12	modeling	modeling	NOUN
admet-2772	905	13	.	.	PUNCT
admet-2772	906	1	journal	journal	PROPN
admet-2772	906	2	of	of	ADP
admet-2772	906	3	chemical	chemical	ADJ
admet-2772	906	4	information	information	NOUN
admet-2772	906	5	and	and	CCONJ
admet-2772	906	6	modeling	model	VERB
admet-2772	906	7	52	52	NUM
admet-2772	906	8	(	(	PUNCT
admet-2772	906	9	2012	2012	NUM
admet-2772	906	10	)	)	PUNCT
admet-2772	906	11	1686	1686	NUM
admet-2772	906	12	-	-	SYM
admet-2772	906	13	1697	1697	NUM
admet-2772	906	14	.	.	PUNCT
admet-2772	907	1	https://doi.org/10.1021/ci300124c	https://doi.org/10.1021/ci300124c	PROPN
admet-2772	908	1	[	[	X
admet-2772	908	2	75	75	NUM
admet-2772	908	3	]	]	PUNCT
admet-2772	908	4	h.	h.	PROPN
admet-2772	908	5	golmohammadi	golmohammadi	PROPN
admet-2772	908	6	,	,	PUNCT
admet-2772	908	7	z.	z.	PROPN
admet-2772	908	8	dashtbozorgi	dashtbozorgi	PROPN
admet-2772	908	9	,	,	PUNCT
admet-2772	908	10	w.e	w.e	PROPN
admet-2772	908	11	.	.	PROPN
admet-2772	908	12	acree	acree	PROPN
admet-2772	908	13	.	.	PUNCT
admet-2772	909	1	quantitative	quantitative	ADJ
admet-2772	909	2	structure	structure	NOUN
admet-2772	909	3	-	-	PUNCT
admet-2772	909	4	activity	activity	NOUN
admet-2772	909	5	relationship	relationship	NOUN
admet-2772	909	6	prediction	prediction	NOUN
admet-2772	909	7	of	of	ADP
admet-2772	909	8	blood	blood	NOUN
admet-2772	909	9	-	-	PUNCT
admet-2772	909	10	to	to	ADP
admet-2772	909	11	-	-	PUNCT
admet-2772	909	12	brain	brain	NOUN
admet-2772	909	13	partitioning	partition	VERB
admet-2772	909	14	behavior	behavior	NOUN
admet-2772	909	15	using	use	VERB
admet-2772	909	16	support	support	NOUN
admet-2772	909	17	vector	vector	NOUN
admet-2772	909	18	machine	machine	NOUN
admet-2772	909	19	.	.	PUNCT
admet-2772	910	1	european	european	PROPN
admet-2772	910	2	journal	journal	PROPN
admet-2772	910	3	of	of	ADP
admet-2772	910	4	pharmaceutical	pharmaceutical	PROPN
admet-2772	910	5	sciences	science	NOUN
admet-2772	910	6	47	47	NUM
admet-2772	910	7	(	(	PUNCT
admet-2772	910	8	2012	2012	NUM
admet-2772	910	9	)	)	PUNCT
admet-2772	910	10	421	421	NUM
admet-2772	910	11	-	-	SYM
admet-2772	910	12	429	429	NUM
admet-2772	910	13	.	.	PUNCT
admet-2772	911	1	https://doi.org/10.1016/j.ejps.2012.06.021	https://doi.org/10.1016/j.ejps.2012.06.021	PROPN
admet-2772	912	1	[	[	X
admet-2772	912	2	76	76	NUM
admet-2772	912	3	]	]	X
admet-2772	912	4	h.	h.	PROPN
admet-2772	912	5	iwata	iwata	PROPN
admet-2772	912	6	,	,	PUNCT
admet-2772	912	7	t.	t.	PROPN
admet-2772	912	8	matsuo	matsuo	PROPN
admet-2772	912	9	,	,	PUNCT
admet-2772	912	10	h.	h.	PROPN
admet-2772	912	11	mamada	mamada	PROPN
admet-2772	912	12	,	,	PUNCT
admet-2772	912	13	t.	t.	PROPN
admet-2772	912	14	motomura	motomura	PROPN
admet-2772	912	15	,	,	PUNCT
admet-2772	912	16	m.	m.	PROPN
admet-2772	912	17	matsushita	matsushita	PROPN
admet-2772	912	18	,	,	PUNCT
admet-2772	912	19	t.	t.	PROPN
admet-2772	912	20	fujiwara	fujiwara	PROPN
admet-2772	912	21	,	,	PUNCT
admet-2772	912	22	k.	k.	PROPN
admet-2772	912	23	maeda	maeda	PROPN
admet-2772	912	24	,	,	PUNCT
admet-2772	912	25	k.	k.	PROPN
admet-2772	912	26	handa	handa	PROPN
admet-2772	912	27	.	.	PUNCT
admet-2772	913	1	predicting	predict	VERB
admet-2772	913	2	total	total	ADJ
admet-2772	913	3	drug	drug	NOUN
admet-2772	913	4	clearance	clearance	NOUN
admet-2772	913	5	and	and	CCONJ
admet-2772	913	6	volumes	volume	NOUN
admet-2772	913	7	of	of	ADP
admet-2772	913	8	distribution	distribution	NOUN
admet-2772	913	9	using	use	VERB
admet-2772	913	10	the	the	DET
admet-2772	913	11	machine	machine	NOUN
admet-2772	913	12	learning	learning	NOUN
admet-2772	913	13	-	-	PUNCT
admet-2772	913	14	mediated	mediate	VERB
admet-2772	913	15	multimodal	multimodal	NOUN
admet-2772	913	16	method	method	NOUN
admet-2772	913	17	through	through	ADP
admet-2772	913	18	the	the	DET
admet-2772	913	19	imputation	imputation	NOUN
admet-2772	913	20	of	of	ADP
admet-2772	913	21	various	various	ADJ
admet-2772	913	22	nonclinical	nonclinical	ADJ
admet-2772	913	23	data	datum	NOUN
admet-2772	913	24	.	.	PUNCT
admet-2772	914	1	journal	journal	PROPN
admet-2772	914	2	of	of	ADP
admet-2772	914	3	chemical	chemical	ADJ
admet-2772	914	4	information	information	NOUN
admet-2772	914	5	and	and	CCONJ
admet-2772	914	6	modeling	model	VERB
admet-2772	914	7	62	62	NUM
admet-2772	914	8	(	(	PUNCT
admet-2772	914	9	2022	2022	NUM
admet-2772	914	10	)	)	PUNCT
admet-2772	914	11	4057	4057	NUM
admet-2772	914	12	-	-	SYM
admet-2772	914	13	4065	4065	NUM
admet-2772	914	14	.	.	PUNCT
admet-2772	915	1	https://doi.org/10.1021/acs.jcim.2c00318	https://doi.org/10.1021/acs.jcim.2c00318	ADP
admet-2772	915	2	[	[	X
admet-2772	915	3	77	77	NUM
admet-2772	915	4	]	]	X
admet-2772	915	5	n.	n.	PROPN
admet-2772	915	6	parrott	parrott	PROPN
admet-2772	915	7	,	,	PUNCT
admet-2772	915	8	n.	n.	PROPN
admet-2772	915	9	manevski	manevski	PROPN
admet-2772	915	10	,	,	PUNCT
admet-2772	915	11	a.	a.	PROPN
admet-2772	915	12	olivares	olivare	NOUN
admet-2772	915	13	-	-	PUNCT
admet-2772	915	14	morales	morale	NOUN
admet-2772	915	15	.	.	PUNCT
admet-2772	916	1	can	can	AUX
admet-2772	916	2	we	we	PRON
admet-2772	916	3	predict	predict	VERB
admet-2772	916	4	clinical	clinical	ADJ
admet-2772	916	5	pharmacokinetics	pharmacokinetic	NOUN
admet-2772	916	6	of	of	ADP
admet-2772	916	7	highly	highly	ADV
admet-2772	916	8	lipophilic	lipophilic	ADJ
admet-2772	916	9	compounds	compound	NOUN
admet-2772	916	10	by	by	ADP
admet-2772	916	11	integration	integration	NOUN
admet-2772	916	12	of	of	ADP
admet-2772	916	13	machine	machine	NOUN
admet-2772	916	14	learning	learning	NOUN
admet-2772	916	15	or	or	CCONJ
admet-2772	916	16	in	in	ADP
admet-2772	916	17	vitro	vitro	X
admet-2772	916	18	data	datum	NOUN
admet-2772	916	19	into	into	ADP
admet-2772	916	20	physiologically	physiologically	ADV
admet-2772	916	21	based	base	VERB
admet-2772	916	22	models	model	NOUN
admet-2772	916	23	?	?	PUNCT
admet-2772	917	1	a	a	DET
admet-2772	917	2	feasibility	feasibility	NOUN
admet-2772	917	3	study	study	NOUN
admet-2772	917	4	based	base	VERB
admet-2772	917	5	on	on	ADP
admet-2772	917	6	12	12	NUM
admet-2772	917	7	development	development	NOUN
admet-2772	917	8	compounds	compound	NOUN
admet-2772	917	9	.	.	PUNCT
admet-2772	918	1	molecular	molecular	ADJ
admet-2772	918	2	pharmaceutics	pharmaceutic	NOUN
admet-2772	918	3	19	19	NUM
admet-2772	918	4	(	(	PUNCT
admet-2772	918	5	2022	2022	NUM
admet-2772	918	6	)	)	PUNCT
admet-2772	918	7	3858	3858	NUM
admet-2772	918	8	-	-	SYM
admet-2772	918	9	3868	3868	NUM
admet-2772	918	10	.	.	PUNCT
admet-2772	919	1	https://doi.org/10.1021/acs.molpharmaceut.2c00350	https://doi.org/10.1021/acs.molpharmaceut.2c00350	PRON
admet-2772	920	1	[	[	X
admet-2772	920	2	78	78	NUM
admet-2772	920	3	]	]	PUNCT
admet-2772	920	4	v.	v.	ADP
admet-2772	920	5	mulpuru	mulpuru	X
admet-2772	920	6	,	,	PUNCT
admet-2772	920	7	n.	n.	PROPN
admet-2772	920	8	mishra	mishra	PROPN
admet-2772	920	9	.	.	PROPN
admet-2772	921	1	in	in	ADP
admet-2772	921	2	silico	silico	NOUN
admet-2772	921	3	prediction	prediction	NOUN
admet-2772	921	4	of	of	ADP
admet-2772	921	5	fraction	fraction	NOUN
admet-2772	921	6	unbound	unbound	NOUN
admet-2772	921	7	in	in	ADP
admet-2772	921	8	human	human	ADJ
admet-2772	921	9	plasma	plasma	NOUN
admet-2772	921	10	from	from	ADP
admet-2772	921	11	chemical	chemical	NOUN
admet-2772	921	12	fingerprint	fingerprint	NOUN
admet-2772	921	13	using	use	VERB
admet-2772	921	14	automated	automate	VERB
admet-2772	921	15	machine	machine	NOUN
admet-2772	921	16	learning	learning	NOUN
admet-2772	921	17	.	.	PUNCT
admet-2772	922	1	acs	acs	PROPN
admet-2772	922	2	omega	omega	NOUN
admet-2772	922	3	6	6	NUM
admet-2772	922	4	(	(	PUNCT
admet-2772	922	5	2021	2021	NUM
admet-2772	922	6	)	)	PUNCT
admet-2772	922	7	6791	6791	NUM
admet-2772	922	8	-	-	SYM
admet-2772	922	9	6797	6797	NUM
admet-2772	922	10	.	.	PUNCT
admet-2772	923	1	https://doi.org/10.1021/acsomega.0c05846	https://doi.org/10.1021/acsomega.0c05846	NOUN
admet-2772	923	2	[	[	X
admet-2772	923	3	79	79	NUM
admet-2772	923	4	]	]	PUNCT
admet-2772	923	5	h.	h.	PROPN
admet-2772	923	6	cao	cao	PROPN
admet-2772	923	7	,	,	PUNCT
admet-2772	923	8	j.	j.	PROPN
admet-2772	923	9	peng	peng	PROPN
admet-2772	923	10	,	,	PUNCT
admet-2772	923	11	z.	z.	PROPN
admet-2772	923	12	zhou	zhou	PROPN
admet-2772	923	13	,	,	PUNCT
admet-2772	923	14	z.	z.	PROPN
admet-2772	923	15	yang	yang	PROPN
admet-2772	923	16	,	,	PUNCT
admet-2772	923	17	l.	l.	PROPN
admet-2772	923	18	wang	wang	PROPN
admet-2772	923	19	,	,	PUNCT
admet-2772	923	20	y.	y.	PROPN
admet-2772	923	21	sun	sun	PROPN
admet-2772	923	22	,	,	PUNCT
admet-2772	923	23	y.	y.	PROPN
admet-2772	923	24	wang	wang	PROPN
admet-2772	923	25	,	,	PUNCT
admet-2772	923	26	y.	y.	PROPN
admet-2772	923	27	liang	liang	PROPN
admet-2772	923	28	.	.	PUNCT
admet-2772	924	1	investigation	investigation	NOUN
admet-2772	924	2	of	of	ADP
admet-2772	924	3	the	the	DET
admet-2772	924	4	binding	bind	VERB
admet-2772	924	5	fraction	fraction	NOUN
admet-2772	924	6	of	of	ADP
admet-2772	924	7	pfas	pfas	NOUN
admet-2772	924	8	in	in	ADP
admet-2772	924	9	human	human	ADJ
admet-2772	924	10	plasma	plasma	NOUN
admet-2772	924	11	and	and	CCONJ
admet-2772	924	12	underlying	underlying	ADJ
admet-2772	924	13	mechanisms	mechanism	NOUN
admet-2772	924	14	based	base	VERB
admet-2772	924	15	on	on	ADP
admet-2772	924	16	machine	machine	NOUN
admet-2772	924	17	learning	learning	NOUN
admet-2772	924	18	and	and	CCONJ
admet-2772	924	19	molecular	molecular	ADJ
admet-2772	924	20	dynamics	dynamic	NOUN
admet-2772	924	21	simulation	simulation	NOUN
admet-2772	924	22	.	.	PUNCT
admet-2772	925	1	environmental	environmental	ADJ
admet-2772	925	2	science	science	NOUN
admet-2772	925	3	and	and	CCONJ
admet-2772	925	4	technology	technology	NOUN
admet-2772	925	5	57	57	NUM
admet-2772	925	6	(	(	PUNCT
admet-2772	925	7	2023	2023	NUM
admet-2772	925	8	)	)	PUNCT
admet-2772	925	9	17762	17762	NUM
admet-2772	925	10	-	-	SYM
admet-2772	925	11	17773	17773	NUM
admet-2772	925	12	.	.	PUNCT
admet-2772	926	1	https://doi.org/10.1021/acs.est.2c04400	https://doi.org/10.1021/acs.est.2c04400	NOUN
admet-2772	927	1	[	[	X
admet-2772	927	2	80	80	NUM
admet-2772	927	3	]	]	PUNCT
admet-2772	927	4	m.	m.	NOUN
admet-2772	927	5	riedl	riedl	PROPN
admet-2772	927	6	,	,	PUNCT
admet-2772	927	7	s.	s.	PROPN
admet-2772	927	8	mukherjee	mukherjee	PROPN
admet-2772	927	9	,	,	PUNCT
admet-2772	927	10	m.	m.	NOUN
admet-2772	927	11	gauthier	gauthier	PROPN
admet-2772	927	12	.	.	PUNCT
admet-2772	928	1	descriptor	descriptor	NOUN
admet-2772	928	2	-	-	PUNCT
admet-2772	928	3	free	free	ADJ
admet-2772	928	4	deep	deep	ADJ
admet-2772	928	5	learning	learning	NOUN
admet-2772	928	6	qsar	qsar	NOUN
admet-2772	928	7	model	model	NOUN
admet-2772	928	8	for	for	ADP
admet-2772	928	9	the	the	DET
admet-2772	928	10	fraction	fraction	NOUN
admet-2772	928	11	unbound	unbound	NOUN
admet-2772	928	12	in	in	ADP
admet-2772	928	13	human	human	ADJ
admet-2772	928	14	plasma	plasma	NOUN
admet-2772	928	15	.	.	PUNCT
admet-2772	929	1	molecular	molecular	ADJ
admet-2772	929	2	pharmaceutics	pharmaceutic	NOUN
admet-2772	929	3	20	20	NUM
admet-2772	929	4	(	(	PUNCT
admet-2772	929	5	2023	2023	NUM
admet-2772	929	6	)	)	PUNCT
admet-2772	929	7	4984	4984	NUM
admet-2772	929	8	-	-	SYM
admet-2772	929	9	4993	4993	NUM
admet-2772	929	10	.	.	PUNCT
admet-2772	930	1	https://doi.org/10.1021/acs.molpharmaceut.3c00129	https://doi.org/10.1021/acs.molpharmaceut.3c00129	PROPN
admet-2772	931	1	[	[	X
admet-2772	931	2	81	81	NUM
admet-2772	931	3	]	]	PUNCT
admet-2772	931	4	f.	f.	PROPN
admet-2772	931	5	hammann	hammann	PROPN
admet-2772	931	6	,	,	PUNCT
admet-2772	931	7	h.	h.	PROPN
admet-2772	931	8	gutmann	gutmann	PROPN
admet-2772	931	9	,	,	PUNCT
admet-2772	931	10	u.	u.	PROPN
admet-2772	931	11	baumann	baumann	PROPN
admet-2772	931	12	,	,	PUNCT
admet-2772	931	13	c.	c.	PROPN
admet-2772	931	14	helma	helma	PROPN
admet-2772	931	15	,	,	PUNCT
admet-2772	931	16	j.	j.	PROPN
admet-2772	931	17	drewe	drewe	PROPN
admet-2772	931	18	.	.	PUNCT
admet-2772	932	1	classification	classification	NOUN
admet-2772	932	2	of	of	ADP
admet-2772	932	3	cytochrome	cytochrome	ADJ
admet-2772	932	4	p450	p450	PROPN
admet-2772	932	5	activities	activity	NOUN
admet-2772	932	6	using	use	VERB
admet-2772	932	7	machine	machine	NOUN
admet-2772	932	8	learning	learning	NOUN
admet-2772	932	9	methods	method	NOUN
admet-2772	932	10	.	.	PUNCT
admet-2772	933	1	molecular	molecular	ADJ
admet-2772	933	2	pharmaceutics	pharmaceutic	NOUN
admet-2772	933	3	6	6	NUM
admet-2772	933	4	(	(	PUNCT
admet-2772	933	5	2009	2009	NUM
admet-2772	933	6	)	)	PUNCT
admet-2772	933	7	1920	1920	NUM
admet-2772	933	8	-	-	SYM
admet-2772	933	9	1926	1926	NUM
admet-2772	933	10	.	.	PUNCT
admet-2772	934	1	https://doi.org/10.1021/mp900217x	https://doi.org/10.1021/mp900217x	X
admet-2772	935	1	[	[	X
admet-2772	935	2	82	82	X
admet-2772	935	3	]	]	PUNCT
admet-2772	935	4	t.	t.	PROPN
admet-2772	935	5	fox	fox	PROPN
admet-2772	935	6	,	,	PUNCT
admet-2772	935	7	j.	j.	PROPN
admet-2772	935	8	kriegl	kriegl	PROPN
admet-2772	935	9	.	.	PUNCT
admet-2772	936	1	machine	machine	NOUN
admet-2772	936	2	learning	learn	VERB
admet-2772	936	3	techniques	technique	NOUN
admet-2772	936	4	for	for	ADP
admet-2772	936	5	in	in	ADP
admet-2772	936	6	silico	silico	NOUN
admet-2772	936	7	modeling	modeling	NOUN
admet-2772	936	8	of	of	ADP
admet-2772	936	9	drug	drug	NOUN
admet-2772	936	10	metabolism	metabolism	NOUN
admet-2772	936	11	.	.	PUNCT
admet-2772	937	1	current	current	ADJ
admet-2772	937	2	topics	topic	NOUN
admet-2772	937	3	in	in	ADP
admet-2772	937	4	medicinal	medicinal	ADJ
admet-2772	937	5	chemistry	chemistry	NOUN
admet-2772	937	6	6	6	NUM
admet-2772	937	7	(	(	PUNCT
admet-2772	937	8	2006	2006	NUM
admet-2772	937	9	)	)	PUNCT
admet-2772	937	10	1579	1579	NUM
admet-2772	937	11	-	-	SYM
admet-2772	937	12	1591	1591	NUM
admet-2772	937	13	.	.	PUNCT
admet-2772	938	1	https://doi.org/10.2174/156802606778108915	https://doi.org/10.2174/156802606778108915	PUNCT
admet-2772	939	1	[	[	X
admet-2772	939	2	83	83	NUM
admet-2772	939	3	]	]	X
admet-2772	939	4	h.x	h.x	PROPN
admet-2772	939	5	.	.	PROPN
admet-2772	939	6	liu	liu	PROPN
admet-2772	939	7	,	,	PUNCT
admet-2772	939	8	x.j	x.j	PROPN
admet-2772	939	9	.	.	PROPN
admet-2772	939	10	yao	yao	PROPN
admet-2772	939	11	,	,	PUNCT
admet-2772	939	12	r.s	r.s	PROPN
admet-2772	939	13	.	.	PROPN
admet-2772	939	14	zhang	zhang	PROPN
admet-2772	939	15	,	,	PUNCT
admet-2772	939	16	m.c	m.c	PROPN
admet-2772	939	17	.	.	PROPN
admet-2772	939	18	liu	liu	PROPN
admet-2772	939	19	,	,	PUNCT
admet-2772	939	20	z.d	z.d	PROPN
admet-2772	939	21	.	.	PROPN
admet-2772	939	22	hu	hu	PROPN
admet-2772	939	23	,	,	PUNCT
admet-2772	939	24	b.t	b.t	PROPN
admet-2772	939	25	.	.	PROPN
admet-2772	939	26	fan	fan	PROPN
admet-2772	939	27	.	.	PUNCT
admet-2772	939	28	prediction	prediction	NOUN
admet-2772	939	29	of	of	ADP
admet-2772	939	30	the	the	DET
admet-2772	939	31	tissue	tissue	NOUN
admet-2772	939	32	/	/	SYM
admet-2772	939	33	blood	blood	NOUN
admet-2772	939	34	partition	partition	NOUN
admet-2772	939	35	coefficients	coefficient	NOUN
admet-2772	939	36	of	of	ADP
admet-2772	939	37	organic	organic	ADJ
admet-2772	939	38	compounds	compound	NOUN
admet-2772	939	39	based	base	VERB
admet-2772	939	40	on	on	ADP
admet-2772	939	41	the	the	DET
admet-2772	939	42	molecular	molecular	ADJ
admet-2772	939	43	structure	structure	NOUN
admet-2772	939	44	using	use	VERB
admet-2772	939	45	least	least	ADJ
admet-2772	939	46	-	-	PUNCT
admet-2772	939	47	squares	square	NOUN
admet-2772	939	48	support	support	NOUN
admet-2772	939	49	vector	vector	NOUN
admet-2772	939	50	machines	machine	NOUN
admet-2772	939	51	.	.	PUNCT
admet-2772	940	1	journal	journal	PROPN
admet-2772	940	2	of	of	ADP
admet-2772	940	3	computer	computer	NOUN
admet-2772	940	4	-	-	PUNCT
admet-2772	940	5	aided	aid	VERB
admet-2772	940	6	molecular	molecular	ADJ
admet-2772	940	7	design	design	NOUN
admet-2772	940	8	19	19	NUM
admet-2772	940	9	(	(	PUNCT
admet-2772	940	10	2005	2005	NUM
admet-2772	940	11	)	)	PUNCT
admet-2772	940	12	499	499	NUM
admet-2772	940	13	-	-	NUM
admet-2772	940	14	508	508	NUM
admet-2772	940	15	.	.	PUNCT
admet-2772	941	1	https://doi.org/10.1007/s10822-005-9003-5	https://doi.org/10.1007/s10822-005-9003-5	NOUN
admet-2772	942	1	[	[	X
admet-2772	942	2	84	84	NUM
admet-2772	942	3	]	]	X
admet-2772	942	4	j.y	j.y	PROPN
admet-2772	942	5	.	.	PROPN
admet-2772	942	6	ryu	ryu	PROPN
admet-2772	942	7	,	,	PUNCT
admet-2772	942	8	j.h	j.h	PROPN
admet-2772	942	9	.	.	PROPN
admet-2772	942	10	lee	lee	PROPN
admet-2772	942	11	,	,	PUNCT
admet-2772	942	12	b.h	b.h	PROPN
admet-2772	942	13	.	.	PROPN
admet-2772	942	14	lee	lee	PROPN
admet-2772	942	15	,	,	PUNCT
admet-2772	942	16	j.s	j.s	PROPN
admet-2772	942	17	.	.	PROPN
admet-2772	942	18	song	song	PROPN
admet-2772	942	19	,	,	PUNCT
admet-2772	942	20	s.	s.	PROPN
admet-2772	942	21	ahn	ahn	PROPN
admet-2772	942	22	,	,	PUNCT
admet-2772	942	23	k.s	k.s	PROPN
admet-2772	942	24	.	.	PUNCT
admet-2772	943	1	oh	oh	INTJ
admet-2772	943	2	.	.	PUNCT
admet-2772	944	1	predms	predms	NOUN
admet-2772	944	2	:	:	PUNCT
admet-2772	944	3	a	a	DET
admet-2772	944	4	random	random	ADJ
admet-2772	944	5	forest	forest	NOUN
admet-2772	944	6	model	model	NOUN
admet-2772	944	7	for	for	ADP
admet-2772	944	8	predicting	predict	VERB
admet-2772	944	9	metabolic	metabolic	NOUN
admet-2772	944	10	stability	stability	NOUN
admet-2772	944	11	of	of	ADP
admet-2772	944	12	drug	drug	NOUN
admet-2772	944	13	candidates	candidate	NOUN
admet-2772	944	14	in	in	ADP
admet-2772	944	15	human	human	ADJ
admet-2772	944	16	liver	liver	NOUN
admet-2772	944	17	microsomes	microsome	NOUN
admet-2772	944	18	.	.	PUNCT
admet-2772	945	1	bioinformatics	bioinformatic	NOUN
admet-2772	945	2	38	38	NUM
admet-2772	945	3	(	(	PUNCT
admet-2772	945	4	2022	2022	NUM
admet-2772	945	5	)	)	PUNCT
admet-2772	945	6	364368	364368	NUM
admet-2772	945	7	.	.	PUNCT
admet-2772	946	1	https://doi.org/10.1093/bioinformatics/btab547	https://doi.org/10.1093/bioinformatics/btab547	X
admet-2772	946	2	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	X
admet-2772	946	3	https://doi.org/10.3390/molecules25245901	https://doi.org/10.3390/molecules25245901	PROPN
admet-2772	946	4	https://doi.org/10.1038/s41598-021-90637-1	https://doi.org/10.1038/s41598-021-90637-1	PROPN
admet-2772	947	1	https://doi.org/10.1016/j.chemolab.2020.103962	https://doi.org/10.1016/j.chemolab.2020.103962	PROPN
admet-2772	947	2	https://doi.org/10.32598/pbr.8.4.1086.1	https://doi.org/10.32598/pbr.8.4.1086.1	PROPN
admet-2772	947	3	https://doi.org/10.1021/ci300124c	https://doi.org/10.1021/ci300124c	PROPN
admet-2772	947	4	https://doi.org/10.1016/j.ejps.2012.06.021	https://doi.org/10.1016/j.ejps.2012.06.021	VERB
admet-2772	947	5	https://doi.org/10.1021/acs.jcim.2c00318	https://doi.org/10.1021/acs.jcim.2c00318	ADP
admet-2772	947	6	https://doi.org/10.1021/acs.molpharmaceut.2c00350	https://doi.org/10.1021/acs.molpharmaceut.2c00350	ADJ
admet-2772	947	7	https://doi.org/10.1021/acsomega.0c05846	https://doi.org/10.1021/acsomega.0c05846	VERB
admet-2772	947	8	https://doi.org/10.1021/acs.est.2c04400	https://doi.org/10.1021/acs.est.2c04400	NOUN
admet-2772	947	9	https://doi.org/10.1021/acs.molpharmaceut.3c00129	https://doi.org/10.1021/acs.molpharmaceut.3c00129	PROPN
admet-2772	947	10	https://doi.org/10.1021/mp900217x	https://doi.org/10.1021/mp900217x	PROPN
admet-2772	947	11	https://doi.org/10.2174/156802606778108915	https://doi.org/10.2174/156802606778108915	X
admet-2772	947	12	https://doi.org/10.1007/s10822-005-9003-5	https://doi.org/10.1007/s10822-005-9003-5	NUM
admet-2772	947	13	https://doi.org/10.1093/bioinformatics/btab547	https://doi.org/10.1093/bioinformatics/btab547	PROPN
admet-2772	948	1	m.	m.	PROPN
admet-2772	948	2	venkataraman	venkataraman	PROPN
admet-2772	948	3	et	et	PROPN
admet-2772	948	4	al	al	PROPN
admet-2772	948	5	.	.	PROPN
admet-2772	948	6	admet	admet	PROPN
admet-2772	948	7	&	&	CCONJ
admet-2772	948	8	dmpk	dmpk	PROPN
admet-2772	948	9	13(3	13(3	NUM
admet-2772	948	10	)	)	PUNCT
admet-2772	948	11	(	(	PUNCT
admet-2772	948	12	2025	2025	NUM
admet-2772	948	13	)	)	PUNCT
admet-2772	948	14	2772	2772	NUM
admet-2772	948	15	30	30	NUM
admet-2772	949	1	[	[	SYM
admet-2772	949	2	85	85	NUM
admet-2772	949	3	]	]	PUNCT
admet-2772	949	4	m.	m.	NOUN
admet-2772	949	5	baranwal	baranwal	PROPN
admet-2772	949	6	,	,	PUNCT
admet-2772	949	7	a.	a.	NOUN
admet-2772	949	8	magner	magner	NOUN
admet-2772	949	9	,	,	PUNCT
admet-2772	949	10	p.	p.	NOUN
admet-2772	949	11	elvati	elvati	PROPN
admet-2772	949	12	,	,	PUNCT
admet-2772	949	13	j.	j.	PROPN
admet-2772	949	14	saldinger	saldinger	PROPN
admet-2772	949	15	,	,	PUNCT
admet-2772	949	16	a.	a.	NOUN
admet-2772	949	17	violi	violi	PROPN
admet-2772	949	18	,	,	PUNCT
admet-2772	949	19	a.	a.	NOUN
admet-2772	949	20	violi	violi	PROPN
admet-2772	949	21	,	,	PUNCT
admet-2772	949	22	a.o	a.o	PROPN
admet-2772	949	23	.	.	PROPN
admet-2772	949	24	hero	hero	PROPN
admet-2772	949	25	.	.	PUNCT
admet-2772	950	1	a	a	DET
admet-2772	950	2	deep	deep	ADJ
admet-2772	950	3	learning	learning	NOUN
admet-2772	950	4	architecture	architecture	NOUN
admet-2772	950	5	for	for	ADP
admet-2772	950	6	metabolic	metabolic	NOUN
admet-2772	950	7	pathway	pathway	NOUN
admet-2772	950	8	prediction	prediction	NOUN
admet-2772	950	9	.	.	PUNCT
admet-2772	951	1	bioinformatics	bioinformatic	NOUN
admet-2772	951	2	36	36	NUM
admet-2772	951	3	(	(	PUNCT
admet-2772	951	4	2020	2020	NUM
admet-2772	951	5	)	)	PUNCT
admet-2772	951	6	2547	2547	NUM
admet-2772	951	7	-	-	SYM
admet-2772	951	8	2553	2553	NUM
admet-2772	951	9	.	.	PUNCT
admet-2772	952	1	https://doi.org/10.1093/bioinformatics/btz954	https://doi.org/10.1093/bioinformatics/btz954	NOUN
admet-2772	952	2	[	[	X
admet-2772	952	3	86	86	NUM
admet-2772	952	4	]	]	X
admet-2772	952	5	n.n	n.n	PROPN
admet-2772	952	6	.	.	PROPN
admet-2772	952	7	wang	wang	PROPN
admet-2772	952	8	,	,	PUNCT
admet-2772	952	9	x.g	x.g	PROPN
admet-2772	952	10	.	.	PROPN
admet-2772	952	11	wang	wang	PROPN
admet-2772	952	12	,	,	PUNCT
admet-2772	952	13	g.l	g.l	PROPN
admet-2772	952	14	.	.	PROPN
admet-2772	952	15	xiong	xiong	PROPN
admet-2772	952	16	,	,	PUNCT
admet-2772	952	17	z.y	z.y	PROPN
admet-2772	952	18	.	.	PROPN
admet-2772	952	19	yang	yang	PROPN
admet-2772	952	20	,	,	PUNCT
admet-2772	952	21	a.p	a.p	PROPN
admet-2772	952	22	.	.	PROPN
admet-2772	952	23	lu	lu	PROPN
admet-2772	952	24	,	,	PUNCT
admet-2772	952	25	x.	x.	PROPN
admet-2772	952	26	chen	chen	PROPN
admet-2772	952	27	,	,	PUNCT
admet-2772	952	28	s.	s.	PROPN
admet-2772	952	29	liu	liu	PROPN
admet-2772	952	30	,	,	PUNCT
admet-2772	952	31	t.j	t.j	PROPN
admet-2772	952	32	.	.	PROPN
admet-2772	952	33	hou	hou	PROPN
admet-2772	952	34	,	,	PUNCT
admet-2772	952	35	d.s	d.s	PROPN
admet-2772	952	36	.	.	PROPN
admet-2772	952	37	cao	cao	PROPN
admet-2772	952	38	.	.	PUNCT
admet-2772	953	1	machine	machine	NOUN
admet-2772	953	2	learning	learn	VERB
admet-2772	953	3	to	to	PART
admet-2772	953	4	predict	predict	VERB
admet-2772	953	5	metabolic	metabolic	NOUN
admet-2772	953	6	drug	drug	NOUN
admet-2772	953	7	interactions	interaction	NOUN
admet-2772	953	8	related	relate	VERB
admet-2772	953	9	to	to	ADP
admet-2772	953	10	cytochrome	cytochrome	VERB
admet-2772	953	11	p450	p450	NUM
admet-2772	953	12	isozymes	isozyme	NOUN
admet-2772	953	13	.	.	PUNCT
admet-2772	954	1	journal	journal	PROPN
admet-2772	954	2	of	of	ADP
admet-2772	954	3	cheminformatics	cheminformatics	PROPN
admet-2772	954	4	14	14	NUM
admet-2772	954	5	(	(	PUNCT
admet-2772	954	6	2022	2022	NUM
admet-2772	954	7	)	)	PUNCT
admet-2772	954	8	23	23	NUM
admet-2772	954	9	.	.	PUNCT
admet-2772	955	1	https://doi.org/10.1186/s13321-022-00602-x	https://doi.org/10.1186/s13321-022-00602-x	PROPN
admet-2772	956	1	[	[	X
admet-2772	956	2	87	87	NUM
admet-2772	956	3	]	]	PUNCT
admet-2772	956	4	h.	h.	PROPN
admet-2772	956	5	mamada	mamada	PROPN
admet-2772	956	6	,	,	PUNCT
admet-2772	956	7	y.	y.	PROPN
admet-2772	956	8	nomura	nomura	PROPN
admet-2772	956	9	,	,	PUNCT
admet-2772	956	10	y.	y.	PROPN
admet-2772	956	11	uesawa	uesawa	PROPN
admet-2772	956	12	.	.	PUNCT
admet-2772	957	1	prediction	prediction	NOUN
admet-2772	957	2	model	model	NOUN
admet-2772	957	3	of	of	ADP
admet-2772	957	4	clearance	clearance	NOUN
admet-2772	957	5	by	by	ADP
admet-2772	957	6	a	a	DET
admet-2772	957	7	novel	novel	ADJ
admet-2772	957	8	quantitative	quantitative	ADJ
admet-2772	957	9	structure	structure	NOUN
admet-2772	957	10	-	-	PUNCT
admet-2772	957	11	activity	activity	NOUN
admet-2772	957	12	relationship	relationship	NOUN
admet-2772	957	13	approach	approach	NOUN
admet-2772	957	14	,	,	PUNCT
admet-2772	957	15	combination	combination	VERB
admet-2772	957	16	deepsnap	deepsnap	NOUN
admet-2772	957	17	-	-	PUNCT
admet-2772	957	18	deep	deep	ADJ
admet-2772	957	19	learning	learning	NOUN
admet-2772	957	20	and	and	CCONJ
admet-2772	957	21	conventional	conventional	ADJ
admet-2772	957	22	machine	machine	NOUN
admet-2772	957	23	learning	learning	NOUN
admet-2772	957	24	.	.	PUNCT
admet-2772	958	1	acs	acs	PROPN
admet-2772	958	2	omega	omega	NOUN
admet-2772	958	3	6	6	NUM
admet-2772	958	4	(	(	PUNCT
admet-2772	958	5	2021	2021	NUM
admet-2772	958	6	)	)	PUNCT
admet-2772	958	7	23570	23570	NUM
admet-2772	958	8	-	-	SYM
admet-2772	958	9	23577	23577	NUM
admet-2772	958	10	.	.	PUNCT
admet-2772	959	1	https://doi.org/10.1021/acsomega.1c03689	https://doi.org/10.1021/acsomega.1c03689	NOUN
admet-2772	959	2	[	[	X
admet-2772	959	3	88	88	NUM
admet-2772	959	4	]	]	X
admet-2772	959	5	c.e	c.e	PROPN
admet-2772	959	6	.	.	PROPN
admet-2772	959	7	keefer	keefer	PROPN
admet-2772	959	8	,	,	PUNCT
admet-2772	959	9	g.	g.	PROPN
admet-2772	959	10	chang	chang	PROPN
admet-2772	959	11	,	,	PUNCT
admet-2772	959	12	l.	l.	PROPN
admet-2772	959	13	di	di	PROPN
admet-2772	959	14	,	,	PUNCT
admet-2772	959	15	n.a	n.a	PROPN
admet-2772	959	16	.	.	PROPN
admet-2772	959	17	woody	woody	PROPN
admet-2772	959	18	,	,	PUNCT
admet-2772	959	19	d.a	d.a	PROPN
admet-2772	959	20	.	.	PROPN
admet-2772	959	21	tess	tess	PROPN
admet-2772	959	22	,	,	PUNCT
admet-2772	959	23	s.m	s.m	PROPN
admet-2772	959	24	.	.	PROPN
admet-2772	959	25	osgood	osgood	PROPN
admet-2772	959	26	,	,	PUNCT
admet-2772	959	27	b.	b.	PROPN
admet-2772	959	28	kapinos	kapinos	PROPN
admet-2772	959	29	,	,	PUNCT
admet-2772	959	30	j.	j.	PROPN
admet-2772	959	31	racich	racich	PROPN
admet-2772	959	32	,	,	PUNCT
admet-2772	959	33	a.a	a.a	PROPN
admet-2772	959	34	.	.	PROPN
admet-2772	959	35	carlo	carlo	PROPN
admet-2772	959	36	,	,	PUNCT
admet-2772	959	37	a.	a.	PROPN
admet-2772	959	38	balesano	balesano	PROPN
admet-2772	959	39	,	,	PUNCT
admet-2772	959	40	n.	n.	PROPN
admet-2772	959	41	ferguson	ferguson	PROPN
admet-2772	959	42	,	,	PUNCT
admet-2772	959	43	c.	c.	PROPN
admet-2772	959	44	orozco	orozco	PROPN
admet-2772	959	45	,	,	PUNCT
admet-2772	959	46	l.	l.	PROPN
admet-2772	959	47	zueva	zueva	PROPN
admet-2772	959	48	,	,	PUNCT
admet-2772	959	49	l.	l.	PROPN
admet-2772	959	50	luo	luo	PROPN
admet-2772	959	51	.	.	PUNCT
admet-2772	960	1	the	the	DET
admet-2772	960	2	comparison	comparison	NOUN
admet-2772	960	3	of	of	ADP
admet-2772	960	4	machine	machine	NOUN
admet-2772	960	5	learning	learning	NOUN
admet-2772	960	6	and	and	CCONJ
admet-2772	960	7	mechanistic	mechanistic	ADJ
admet-2772	960	8	in	in	ADP
admet-2772	960	9	vitro	vitro	NOUN
admet-2772	960	10	-	-	PUNCT
admet-2772	960	11	in	in	ADP
admet-2772	960	12	vivo	vivo	ADJ
admet-2772	960	13	extrapolation	extrapolation	NOUN
admet-2772	960	14	models	model	NOUN
admet-2772	960	15	for	for	ADP
admet-2772	960	16	the	the	DET
admet-2772	960	17	prediction	prediction	NOUN
admet-2772	960	18	of	of	ADP
admet-2772	960	19	human	human	ADJ
admet-2772	960	20	intrinsic	intrinsic	ADJ
admet-2772	960	21	clearance	clearance	NOUN
admet-2772	960	22	.	.	PUNCT
admet-2772	961	1	molecular	molecular	ADJ
admet-2772	961	2	pharmaceutics	pharmaceutic	NOUN
admet-2772	961	3	20	20	NUM
admet-2772	961	4	(	(	PUNCT
admet-2772	961	5	2023	2023	NUM
admet-2772	961	6	)	)	PUNCT
admet-2772	961	7	5616	5616	NUM
admet-2772	961	8	-	-	SYM
admet-2772	961	9	5630	5630	NUM
admet-2772	961	10	.	.	PUNCT
admet-2772	962	1	https://doi.org/10.1021/acs.molpharmaceut.3c00502	https://doi.org/10.1021/acs.molpharmaceut.3c00502	X
admet-2772	963	1	[	[	X
admet-2772	963	2	89	89	NUM
admet-2772	963	3	]	]	X
admet-2772	963	4	r.	r.	PROPN
admet-2772	963	5	rodríguez	rodríguez	PROPN
admet-2772	963	6	-	-	PUNCT
admet-2772	963	7	pérez	pérez	NOUN
admet-2772	963	8	,	,	PUNCT
admet-2772	963	9	m.	m.	NOUN
admet-2772	963	10	trunzer	trunzer	NOUN
admet-2772	963	11	,	,	PUNCT
admet-2772	963	12	n.	n.	PROPN
admet-2772	963	13	schneider	schneider	PROPN
admet-2772	963	14	,	,	PUNCT
admet-2772	963	15	b.	b.	PROPN
admet-2772	963	16	faller	faller	PROPN
admet-2772	963	17	,	,	PUNCT
admet-2772	963	18	g.	g.	PROPN
admet-2772	963	19	gerebtzoff	gerebtzoff	PROPN
admet-2772	963	20	.	.	PUNCT
admet-2772	964	1	multispecies	multispecies	PROPN
admet-2772	964	2	machine	machine	NOUN
admet-2772	964	3	learning	learn	VERB
admet-2772	964	4	predictions	prediction	NOUN
admet-2772	964	5	of	of	ADP
admet-2772	964	6	in	in	ADP
admet-2772	964	7	vitro	vitro	X
admet-2772	964	8	intrinsic	intrinsic	ADJ
admet-2772	964	9	clearance	clearance	NOUN
admet-2772	964	10	with	with	ADP
admet-2772	964	11	uncertainty	uncertainty	NOUN
admet-2772	964	12	quantification	quantification	NOUN
admet-2772	964	13	analyses	analysis	NOUN
admet-2772	964	14	.	.	PUNCT
admet-2772	965	1	molecular	molecular	ADJ
admet-2772	965	2	pharmaceutics	pharmaceutic	NOUN
admet-2772	965	3	20	20	NUM
admet-2772	965	4	(	(	PUNCT
admet-2772	965	5	2023	2023	NUM
admet-2772	965	6	)	)	PUNCT
admet-2772	965	7	383	383	NUM
admet-2772	965	8	-	-	SYM
admet-2772	965	9	394	394	NUM
admet-2772	965	10	.	.	PUNCT
admet-2772	966	1	https://doi.org/10.1021/acs.molpharmaceut.2c00680	https://doi.org/10.1021/acs.molpharmaceut.2c00680	PUNCT
admet-2772	967	1	[	[	X
admet-2772	967	2	90	90	NUM
admet-2772	967	3	]	]	PUNCT
admet-2772	967	4	a.	a.	PROPN
admet-2772	967	5	andrews	andrews	PROPN
admet-2772	967	6	-	-	PUNCT
admet-2772	967	7	morger	morger	PROPN
admet-2772	967	8	,	,	PUNCT
admet-2772	967	9	m.	m.	NOUN
admet-2772	967	10	reutlinger	reutlinger	NOUN
admet-2772	967	11	,	,	PUNCT
admet-2772	967	12	n.	n.	PROPN
admet-2772	967	13	parrott	parrott	PROPN
admet-2772	967	14	,	,	PUNCT
admet-2772	967	15	a.	a.	PROPN
admet-2772	967	16	olivares	olivare	NOUN
admet-2772	967	17	-	-	PUNCT
admet-2772	967	18	morales	morale	NOUN
admet-2772	967	19	.	.	PUNCT
admet-2772	968	1	a	a	DET
admet-2772	968	2	machine	machine	NOUN
admet-2772	968	3	learning	learn	VERB
admet-2772	968	4	framework	framework	NOUN
admet-2772	968	5	to	to	PART
admet-2772	968	6	improve	improve	VERB
admet-2772	968	7	rat	rat	NOUN
admet-2772	968	8	clearance	clearance	NOUN
admet-2772	968	9	predictions	prediction	NOUN
admet-2772	968	10	and	and	CCONJ
admet-2772	968	11	inform	inform	VERB
admet-2772	968	12	physiologically	physiologically	ADV
admet-2772	968	13	based	base	VERB
admet-2772	968	14	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	968	15	modeling	modeling	NOUN
admet-2772	968	16	.	.	PUNCT
admet-2772	969	1	molecular	molecular	ADJ
admet-2772	969	2	pharmaceutics	pharmaceutic	NOUN
admet-2772	969	3	20	20	NUM
admet-2772	969	4	(	(	PUNCT
admet-2772	969	5	2023	2023	NUM
admet-2772	969	6	)	)	PUNCT
admet-2772	969	7	5052	5052	NUM
admet-2772	969	8	-	-	SYM
admet-2772	969	9	5065	5065	NUM
admet-2772	969	10	.	.	PUNCT
admet-2772	970	1	https://doi.org/10.1021/acs.molpharmaceut.3c00374	https://doi.org/10.1021/acs.molpharmaceut.3c00374	NOUN
admet-2772	971	1	[	[	X
admet-2772	971	2	91	91	NUM
admet-2772	971	3	]	]	X
admet-2772	971	4	t.t	t.t	PROPN
admet-2772	971	5	.	.	PROPN
admet-2772	971	6	van	van	PROPN
admet-2772	971	7	tran	tran	PROPN
admet-2772	971	8	,	,	PUNCT
admet-2772	971	9	h.	h.	PROPN
admet-2772	971	10	tayara	tayara	PROPN
admet-2772	971	11	,	,	PUNCT
admet-2772	971	12	k.t	k.t	PROPN
admet-2772	971	13	.	.	PROPN
admet-2772	971	14	chong	chong	PROPN
admet-2772	971	15	.	.	PUNCT
admet-2772	972	1	artificial	artificial	ADJ
admet-2772	972	2	intelligence	intelligence	NOUN
admet-2772	972	3	in	in	ADP
admet-2772	972	4	drug	drug	NOUN
admet-2772	972	5	metabolism	metabolism	NOUN
admet-2772	972	6	and	and	CCONJ
admet-2772	972	7	excretion	excretion	NOUN
admet-2772	972	8	prediction	prediction	NOUN
admet-2772	972	9	:	:	PUNCT
admet-2772	972	10	recent	recent	ADJ
admet-2772	972	11	advances	advance	NOUN
admet-2772	972	12	,	,	PUNCT
admet-2772	972	13	challenges	challenge	NOUN
admet-2772	972	14	,	,	PUNCT
admet-2772	972	15	and	and	CCONJ
admet-2772	972	16	future	future	ADJ
admet-2772	972	17	perspectives	perspective	NOUN
admet-2772	972	18	.	.	PUNCT
admet-2772	973	1	pharmaceutics	pharmaceutic	NOUN
admet-2772	973	2	15(4	15(4	NUM
admet-2772	973	3	)	)	PUNCT
admet-2772	973	4	(	(	PUNCT
admet-2772	973	5	2023	2023	NUM
admet-2772	973	6	)	)	PUNCT
admet-2772	973	7	1260	1260	NUM
admet-2772	973	8	.	.	PUNCT
admet-2772	974	1	https://doi.org/10.3390/pharmaceutics15041260	https://doi.org/10.3390/pharmaceutics15041260	PROPN
admet-2772	975	1	[	[	X
admet-2772	975	2	92	92	NUM
admet-2772	975	3	]	]	PUNCT
admet-2772	975	4	r.	r.	PROPN
admet-2772	975	5	watanabe	watanabe	PROPN
admet-2772	975	6	,	,	PUNCT
admet-2772	975	7	r.	r.	PROPN
admet-2772	975	8	ohashi	ohashi	PROPN
admet-2772	975	9	,	,	PUNCT
admet-2772	975	10	t.	t.	PROPN
admet-2772	975	11	esaki	esaki	PROPN
admet-2772	975	12	,	,	PUNCT
admet-2772	975	13	h.	h.	PROPN
admet-2772	975	14	kawashima	kawashima	PROPN
admet-2772	975	15	,	,	PUNCT
admet-2772	975	16	y.	y.	PROPN
admet-2772	975	17	natsume	natsume	PROPN
admet-2772	975	18	-	-	PUNCT
admet-2772	975	19	kitatani	kitatani	PROPN
admet-2772	975	20	,	,	PUNCT
admet-2772	975	21	c.	c.	PROPN
admet-2772	975	22	nagao	nagao	PROPN
admet-2772	975	23	,	,	PUNCT
admet-2772	975	24	k.	k.	PROPN
admet-2772	975	25	mizuguchi	mizuguchi	PROPN
admet-2772	975	26	.	.	PUNCT
admet-2772	976	1	development	development	NOUN
admet-2772	976	2	of	of	ADP
admet-2772	976	3	an	an	DET
admet-2772	976	4	in	in	ADP
admet-2772	976	5	silico	silico	NOUN
admet-2772	976	6	prediction	prediction	NOUN
admet-2772	976	7	system	system	NOUN
admet-2772	976	8	of	of	ADP
admet-2772	976	9	human	human	ADJ
admet-2772	976	10	renal	renal	ADJ
admet-2772	976	11	excretion	excretion	NOUN
admet-2772	976	12	and	and	CCONJ
admet-2772	976	13	clearance	clearance	NOUN
admet-2772	976	14	from	from	ADP
admet-2772	976	15	chemical	chemical	ADJ
admet-2772	976	16	structure	structure	NOUN
admet-2772	976	17	information	information	NOUN
admet-2772	976	18	incorporating	incorporate	VERB
admet-2772	976	19	fraction	fraction	NOUN
admet-2772	976	20	unbound	unbound	NOUN
admet-2772	976	21	in	in	ADP
admet-2772	976	22	plasma	plasma	NOUN
admet-2772	976	23	as	as	ADP
admet-2772	976	24	a	a	DET
admet-2772	976	25	descriptor	descriptor	NOUN
admet-2772	976	26	.	.	PUNCT
admet-2772	977	1	scientific	scientific	ADJ
admet-2772	977	2	reports	report	NOUN
admet-2772	977	3	9	9	NUM
admet-2772	977	4	(	(	PUNCT
admet-2772	977	5	2019	2019	NUM
admet-2772	977	6	)	)	PUNCT
admet-2772	977	7	18782	18782	NUM
admet-2772	977	8	.	.	PUNCT
admet-2772	978	1	https://doi.org/10.1038/s41598-019-55325-1	https://doi.org/10.1038/s41598-019-55325-1	VERB
admet-2772	979	1	[	[	X
admet-2772	979	2	93	93	NUM
admet-2772	979	3	]	]	X
admet-2772	979	4	d.	d.	PROPN
admet-2772	979	5	bassani	bassani	PROPN
admet-2772	979	6	,	,	PUNCT
admet-2772	979	7	n.j	n.j	PROPN
admet-2772	979	8	.	.	PROPN
admet-2772	979	9	parrott	parrott	PROPN
admet-2772	979	10	,	,	PUNCT
admet-2772	979	11	n.	n.	PROPN
admet-2772	979	12	manevski	manevski	PROPN
admet-2772	979	13	,	,	PUNCT
admet-2772	979	14	j.d	j.d	PROPN
admet-2772	979	15	.	.	PROPN
admet-2772	979	16	zhang	zhang	PROPN
admet-2772	979	17	.	.	PUNCT
admet-2772	980	1	another	another	DET
admet-2772	980	2	string	string	NOUN
admet-2772	980	3	to	to	ADP
admet-2772	980	4	your	your	PRON
admet-2772	980	5	bow	bow	NOUN
admet-2772	980	6	:	:	PUNCT
admet-2772	980	7	machine	machine	NOUN
admet-2772	980	8	learning	learn	VERB
admet-2772	980	9	prediction	prediction	NOUN
admet-2772	980	10	of	of	ADP
admet-2772	980	11	the	the	DET
admet-2772	980	12	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	980	13	properties	property	NOUN
admet-2772	980	14	of	of	ADP
admet-2772	980	15	small	small	ADJ
admet-2772	980	16	molecules	molecule	NOUN
admet-2772	980	17	.	.	PUNCT
admet-2772	981	1	expert	expert	ADJ
admet-2772	981	2	opinion	opinion	NOUN
admet-2772	981	3	on	on	ADP
admet-2772	981	4	drug	drug	NOUN
admet-2772	981	5	discovery	discovery	NOUN
admet-2772	981	6	19	19	NUM
admet-2772	981	7	(	(	PUNCT
admet-2772	981	8	2024	2024	NUM
admet-2772	981	9	)	)	PUNCT
admet-2772	981	10	683	683	NUM
admet-2772	981	11	-	-	SYM
admet-2772	981	12	698	698	NUM
admet-2772	981	13	.	.	PUNCT
admet-2772	982	1	https://doi.org/10.1080/17460441.2024.2348157	https://doi.org/10.1080/17460441.2024.2348157	X
admet-2772	983	1	[	[	X
admet-2772	983	2	94	94	X
admet-2772	983	3	]	]	X
admet-2772	983	4	s.	s.	PROPN
admet-2772	983	5	seal	seal	PROPN
admet-2772	983	6	,	,	PUNCT
admet-2772	983	7	m.-a	m.-a	NOUN
admet-2772	983	8	.	.	PUNCT
admet-2772	984	1	trapotsi	trapotsi	PROPN
admet-2772	984	2	,	,	PUNCT
admet-2772	984	3	v.	v.	CCONJ
admet-2772	984	4	subramanian	subramanian	ADJ
admet-2772	984	5	,	,	PUNCT
admet-2772	984	6	o.	o.	PROPN
admet-2772	984	7	spjuth	spjuth	PROPN
admet-2772	984	8	,	,	PUNCT
admet-2772	984	9	n.	n.	PROPN
admet-2772	984	10	greene	greene	PROPN
admet-2772	984	11	,	,	PUNCT
admet-2772	984	12	a.	a.	NOUN
admet-2772	984	13	bender	bender	PROPN
admet-2772	984	14	.	.	PUNCT
admet-2772	985	1	pksmart	pksmart	VERB
admet-2772	985	2	:	:	PUNCT
admet-2772	985	3	an	an	DET
admet-2772	985	4	open	open	ADJ
admet-2772	985	5	-	-	PUNCT
admet-2772	985	6	source	source	NOUN
admet-2772	985	7	computational	computational	ADJ
admet-2772	985	8	model	model	NOUN
admet-2772	985	9	to	to	PART
admet-2772	985	10	predict	predict	VERB
admet-2772	985	11	in	in	ADP
admet-2772	985	12	vivo	vivo	ADJ
admet-2772	985	13	pharmacokinetics	pharmacokinetic	NOUN
admet-2772	985	14	of	of	ADP
admet-2772	985	15	small	small	ADJ
admet-2772	985	16	molecules	molecule	NOUN
admet-2772	985	17	.	.	PUNCT
admet-2772	986	1	biorxiv	biorxiv	NOUN
admet-2772	986	2	(	(	PUNCT
admet-2772	986	3	2024	2024	NUM
admet-2772	986	4	)	)	PUNCT
admet-2772	986	5	.	.	PUNCT
admet-2772	987	1	https://doi.org/10.1101/2024.02.02.578658	https://doi.org/10.1101/2024.02.02.578658	NOUN
admet-2772	987	2	[	[	X
admet-2772	987	3	95	95	NUM
admet-2772	987	4	]	]	PUNCT
admet-2772	987	5	j.	j.	PROPN
admet-2772	987	6	fan	fan	PROPN
admet-2772	987	7	,	,	PUNCT
admet-2772	987	8	s.	s.	PROPN
admet-2772	987	9	shi	shi	PROPN
admet-2772	987	10	,	,	PUNCT
admet-2772	987	11	h.	h.	PROPN
admet-2772	987	12	xiang	xiang	PROPN
admet-2772	987	13	,	,	PUNCT
admet-2772	987	14	l.	l.	PROPN
admet-2772	987	15	fu	fu	PROPN
admet-2772	987	16	,	,	PUNCT
admet-2772	987	17	y.	y.	PROPN
admet-2772	987	18	duan	duan	PROPN
admet-2772	987	19	,	,	PUNCT
admet-2772	987	20	d.	d.	PROPN
admet-2772	987	21	cao	cao	PROPN
admet-2772	987	22	,	,	PUNCT
admet-2772	987	23	h.	h.	PROPN
admet-2772	987	24	lu	lu	PROPN
admet-2772	987	25	.	.	PUNCT
admet-2772	988	1	predicting	predict	VERB
admet-2772	988	2	elimination	elimination	NOUN
admet-2772	988	3	of	of	ADP
admet-2772	988	4	small	small	ADJ
admet-2772	988	5	-	-	PUNCT
admet-2772	988	6	molecule	molecule	NOUN
admet-2772	988	7	drug	drug	NOUN
admet-2772	988	8	half	half	ADJ
admet-2772	988	9	-	-	PUNCT
admet-2772	988	10	life	life	NOUN
admet-2772	988	11	in	in	ADP
admet-2772	988	12	pharmacokinetics	pharmacokinetic	NOUN
admet-2772	988	13	using	use	VERB
admet-2772	988	14	ensemble	ensemble	ADJ
admet-2772	988	15	and	and	CCONJ
admet-2772	988	16	consensus	consensus	NOUN
admet-2772	988	17	machine	machine	NOUN
admet-2772	988	18	learning	learning	NOUN
admet-2772	988	19	methods	method	NOUN
admet-2772	988	20	.	.	PUNCT
admet-2772	989	1	journal	journal	PROPN
admet-2772	989	2	of	of	ADP
admet-2772	989	3	chemical	chemical	ADJ
admet-2772	989	4	information	information	NOUN
admet-2772	989	5	and	and	CCONJ
admet-2772	989	6	modeling	model	VERB
admet-2772	989	7	64	64	NUM
admet-2772	989	8	(	(	PUNCT
admet-2772	989	9	2024	2024	NUM
admet-2772	989	10	)	)	PUNCT
admet-2772	989	11	3080	3080	NUM
admet-2772	989	12	-	-	SYM
admet-2772	989	13	3092	3092	NUM
admet-2772	989	14	.	.	PUNCT
admet-2772	990	1	https://doi.org/10.1021/acs.jcim.3c02030	https://doi.org/10.1021/acs.jcim.3c02030	X
admet-2772	991	1	[	[	X
admet-2772	991	2	96	96	NUM
admet-2772	991	3	]	]	X
admet-2772	991	4	y.w	y.w	PROPN
admet-2772	991	5	.	.	PROPN
admet-2772	991	6	hsiao	hsiao	PROPN
admet-2772	991	7	,	,	PUNCT
admet-2772	991	8	u.	u.	PROPN
admet-2772	991	9	fagerholm	fagerholm	PROPN
admet-2772	991	10	,	,	PUNCT
admet-2772	991	11	u.	u.	PROPN
admet-2772	991	12	norinder	norinder	PROPN
admet-2772	991	13	.	.	PUNCT
admet-2772	992	1	in	in	ADP
admet-2772	992	2	silico	silico	NOUN
admet-2772	992	3	categorization	categorization	NOUN
admet-2772	992	4	of	of	ADP
admet-2772	992	5	in	in	ADP
admet-2772	992	6	vivo	vivo	ADJ
admet-2772	992	7	intrinsic	intrinsic	ADJ
admet-2772	992	8	clearance	clearance	NOUN
admet-2772	992	9	using	use	VERB
admet-2772	992	10	machine	machine	NOUN
admet-2772	992	11	learning	learning	NOUN
admet-2772	992	12	.	.	PUNCT
admet-2772	993	1	molecular	molecular	ADJ
admet-2772	993	2	pharmaceutics	pharmaceutic	NOUN
admet-2772	993	3	10	10	NUM
admet-2772	993	4	(	(	PUNCT
admet-2772	993	5	2013	2013	NUM
admet-2772	993	6	)	)	PUNCT
admet-2772	993	7	1318	1318	NUM
admet-2772	993	8	-	-	SYM
admet-2772	993	9	1321	1321	NUM
admet-2772	993	10	.	.	PUNCT
admet-2772	994	1	https://doi.org/10.1021/mp300484r	https://doi.org/10.1021/mp300484r	PROPN
admet-2772	995	1	[	[	X
admet-2772	995	2	97	97	NUM
admet-2772	995	3	]	]	X
admet-2772	995	4	h.	h.	PROPN
admet-2772	995	5	iwata	iwata	PROPN
admet-2772	995	6	,	,	PUNCT
admet-2772	995	7	t.	t.	PROPN
admet-2772	995	8	matsuo	matsuo	PROPN
admet-2772	995	9	,	,	PUNCT
admet-2772	995	10	h.	h.	PROPN
admet-2772	995	11	mamada	mamada	PROPN
admet-2772	995	12	,	,	PUNCT
admet-2772	995	13	t.	t.	PROPN
admet-2772	995	14	motomura	motomura	PROPN
admet-2772	995	15	,	,	PUNCT
admet-2772	995	16	m.	m.	PROPN
admet-2772	995	17	matsushita	matsushita	PROPN
admet-2772	995	18	,	,	PUNCT
admet-2772	995	19	t.	t.	PROPN
admet-2772	995	20	fujiwara	fujiwara	PROPN
admet-2772	995	21	,	,	PUNCT
admet-2772	995	22	m.	m.	NOUN
admet-2772	995	23	kazuya	kazuya	PROPN
admet-2772	995	24	,	,	PUNCT
admet-2772	995	25	k.	k.	PROPN
admet-2772	995	26	handa	handa	PROPN
admet-2772	995	27	.	.	PUNCT
admet-2772	996	1	prediction	prediction	NOUN
admet-2772	996	2	of	of	ADP
admet-2772	996	3	total	total	ADJ
admet-2772	996	4	drug	drug	NOUN
admet-2772	996	5	clearance	clearance	NOUN
admet-2772	996	6	in	in	ADP
admet-2772	996	7	humans	human	NOUN
admet-2772	996	8	using	use	VERB
admet-2772	996	9	animal	animal	NOUN
admet-2772	996	10	data	datum	NOUN
admet-2772	996	11	:	:	PUNCT
admet-2772	996	12	proposal	proposal	NOUN
admet-2772	996	13	of	of	ADP
admet-2772	996	14	a	a	DET
admet-2772	996	15	multimodal	multimodal	NOUN
admet-2772	996	16	learning	learning	NOUN
admet-2772	996	17	method	method	NOUN
admet-2772	996	18	based	base	VERB
admet-2772	996	19	on	on	ADP
admet-2772	996	20	deep	deep	ADJ
admet-2772	996	21	learning	learning	NOUN
admet-2772	996	22	.	.	PUNCT
admet-2772	997	1	journal	journal	PROPN
admet-2772	997	2	of	of	ADP
admet-2772	997	3	pharmaceutical	pharmaceutical	PROPN
admet-2772	997	4	sciences	science	NOUN
admet-2772	997	5	110	110	NUM
admet-2772	997	6	(	(	PUNCT
admet-2772	997	7	2021	2021	NUM
admet-2772	997	8	)	)	PUNCT
admet-2772	997	9	18341841	18341841	NUM
admet-2772	997	10	.	.	PUNCT
admet-2772	998	1	https://doi.org/10.1016/j.xphs.2021.01.020	https://doi.org/10.1016/j.xphs.2021.01.020	PUNCT
admet-2772	998	2	[	[	X
admet-2772	998	3	98	98	NUM
admet-2772	998	4	]	]	X
admet-2772	998	5	y.	y.	PROPN
admet-2772	998	6	kosugi	kosugi	PROPN
admet-2772	998	7	,	,	PUNCT
admet-2772	998	8	n.	n.	PROPN
admet-2772	998	9	hosea	hosea	PROPN
admet-2772	998	10	.	.	PUNCT
admet-2772	999	1	direct	direct	ADJ
admet-2772	999	2	comparison	comparison	NOUN
admet-2772	999	3	of	of	ADP
admet-2772	999	4	total	total	ADJ
admet-2772	999	5	clearance	clearance	NOUN
admet-2772	999	6	prediction	prediction	NOUN
admet-2772	999	7	:	:	PUNCT
admet-2772	999	8	computational	computational	ADJ
admet-2772	999	9	machine	machine	NOUN
admet-2772	999	10	learning	learn	VERB
admet-2772	999	11	model	model	NOUN
admet-2772	999	12	versus	versus	ADP
admet-2772	999	13	bottom	bottom	ADJ
admet-2772	999	14	-	-	PUNCT
admet-2772	999	15	up	up	ADP
admet-2772	999	16	approach	approach	NOUN
admet-2772	999	17	using	use	VERB
admet-2772	999	18	in	in	ADP
admet-2772	999	19	vitro	vitro	X
admet-2772	999	20	assay	assay	NOUN
admet-2772	999	21	.	.	PUNCT
admet-2772	1000	1	molecular	molecular	ADJ
admet-2772	1000	2	pharmaceutics	pharmaceutic	NOUN
admet-2772	1000	3	17	17	NUM
admet-2772	1000	4	(	(	PUNCT
admet-2772	1000	5	2020	2020	NUM
admet-2772	1000	6	)	)	PUNCT
admet-2772	1000	7	2299	2299	NUM
admet-2772	1000	8	-	-	SYM
admet-2772	1000	9	2309	2309	NUM
admet-2772	1000	10	.	.	PUNCT
admet-2772	1001	1	https://doi.org/10.1021/acs.molpharmaceut.9b01294	https://doi.org/10.1021/acs.molpharmaceut.9b01294	NOUN
admet-2772	1002	1	[	[	X
admet-2772	1002	2	99	99	NUM
admet-2772	1002	3	]	]	PUNCT
admet-2772	1002	4	p.	p.	NOUN
admet-2772	1002	5	paixão	paixão	PROPN
admet-2772	1002	6	,	,	PUNCT
admet-2772	1002	7	l.f	l.f	PROPN
admet-2772	1002	8	.	.	PROPN
admet-2772	1002	9	gouveia	gouveia	PROPN
admet-2772	1002	10	,	,	PUNCT
admet-2772	1002	11	j.a.g	j.a.g	PROPN
admet-2772	1002	12	.	.	PUNCT
admet-2772	1002	13	morais	morais	PROPN
admet-2772	1002	14	.	.	PUNCT
admet-2772	1002	15	prediction	prediction	NOUN
admet-2772	1002	16	of	of	ADP
admet-2772	1002	17	the	the	DET
admet-2772	1002	18	in	in	X
admet-2772	1002	19	vitro	vitro	X
admet-2772	1002	20	intrinsic	intrinsic	ADJ
admet-2772	1002	21	clearance	clearance	NOUN
admet-2772	1002	22	determined	determine	VERB
admet-2772	1002	23	in	in	ADP
admet-2772	1002	24	suspensions	suspension	NOUN
admet-2772	1002	25	of	of	ADP
admet-2772	1002	26	human	human	ADJ
admet-2772	1002	27	hepatocytes	hepatocyte	NOUN
admet-2772	1002	28	by	by	ADP
admet-2772	1002	29	using	use	VERB
admet-2772	1002	30	artificial	artificial	ADJ
admet-2772	1002	31	neural	neural	ADJ
admet-2772	1002	32	networks	network	NOUN
admet-2772	1002	33	.	.	PUNCT
admet-2772	1003	1	european	european	ADJ
admet-2772	1003	2	journal	journal	PROPN
admet-2772	1003	3	of	of	ADP
admet-2772	1003	4	pharmaceutical	pharmaceutical	PROPN
admet-2772	1003	5	sciences	science	NOUN
admet-2772	1003	6	39	39	NUM
admet-2772	1003	7	(	(	PUNCT
admet-2772	1003	8	2010	2010	NUM
admet-2772	1003	9	)	)	PUNCT
admet-2772	1003	10	310	310	NUM
admet-2772	1003	11	-	-	SYM
admet-2772	1003	12	321	321	NUM
admet-2772	1003	13	.	.	PUNCT
admet-2772	1004	1	https://doi.org/10.1016/j.ejps.2009.12.007	https://doi.org/10.1016/j.ejps.2009.12.007	ADJ
admet-2772	1004	2	https://doi.org/10.1093/bioinformatics/btz954	https://doi.org/10.1093/bioinformatics/btz954	NOUN
admet-2772	1004	3	https://doi.org/10.1186/s13321-022-00602-x	https://doi.org/10.1186/s13321-022-00602-x	PROPN
admet-2772	1004	4	https://doi.org/10.1021/acsomega.1c03689	https://doi.org/10.1021/acsomega.1c03689	NOUN
admet-2772	1004	5	https://doi.org/10.1021/acs.molpharmaceut.3c00502	https://doi.org/10.1021/acs.molpharmaceut.3c00502	INTJ
admet-2772	1005	1	https://doi.org/10.1021/acs.molpharmaceut.2c00680	https://doi.org/10.1021/acs.molpharmaceut.2c00680	PRON
admet-2772	1005	2	https://doi.org/10.1021/acs.molpharmaceut.3c00374	https://doi.org/10.1021/acs.molpharmaceut.3c00374	NOUN
admet-2772	1005	3	https://doi.org/10.3390/pharmaceutics15041260	https://doi.org/10.3390/pharmaceutics15041260	X
admet-2772	1005	4	https://doi.org/10.1038/s41598-019-55325-1	https://doi.org/10.1038/s41598-019-55325-1	X
admet-2772	1005	5	https://doi.org/10.1080/17460441.2024.2348157	https://doi.org/10.1080/17460441.2024.2348157	PROPN
admet-2772	1006	1	https://doi.org/10.1101/2024.02.02.578658	https://doi.org/10.1101/2024.02.02.578658	PROPN
admet-2772	1006	2	https://doi.org/10.1021/acs.jcim.3c02030	https://doi.org/10.1021/acs.jcim.3c02030	PROPN
admet-2772	1006	3	https://doi.org/10.1021/mp300484r	https://doi.org/10.1021/mp300484r	PROPN
admet-2772	1006	4	https://doi.org/10.1016/j.xphs.2021.01.020	https://doi.org/10.1016/j.xphs.2021.01.020	VERB
admet-2772	1006	5	https://doi.org/10.1021/acs.molpharmaceut.9b01294	https://doi.org/10.1021/acs.molpharmaceut.9b01294	PRON
admet-2772	1006	6	https://doi.org/10.1016/j.ejps.2009.12.007	https://doi.org/10.1016/j.ejps.2009.12.007	PROPN
admet-2772	1006	7	admet	admet	PROPN
admet-2772	1006	8	&	&	CCONJ
admet-2772	1006	9	dmpk	dmpk	PROPN
admet-2772	1006	10	13(3	13(3	NUM
admet-2772	1006	11	)	)	PUNCT
admet-2772	1006	12	(	(	PUNCT
admet-2772	1006	13	2025	2025	NUM
admet-2772	1006	14	)	)	PUNCT
admet-2772	1006	15	2772	2772	NUM
admet-2772	1006	16	machine	machine	NOUN
admet-2772	1006	17	learning	learning	NOUN
admet-2772	1006	18	models	model	NOUN
admet-2772	1006	19	for	for	ADP
admet-2772	1006	20	admet	admet	ADJ
admet-2772	1006	21	prediction	prediction	NOUN
admet-2772	1006	22	in	in	ADP
admet-2772	1006	23	drug	drug	NOUN
admet-2772	1006	24	development	development	NOUN
admet-2772	1006	25	doi	doi	PROPN
admet-2772	1006	26	:	:	PUNCT
admet-2772	1006	27	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	1006	28	31	31	NUM
admet-2772	1006	29	[	[	SYM
admet-2772	1006	30	100	100	NUM
admet-2772	1006	31	]	]	X
admet-2772	1006	32	s.w	s.w	PROPN
admet-2772	1006	33	.	.	PROPN
admet-2772	1006	34	paine	paine	PROPN
admet-2772	1006	35	,	,	PUNCT
admet-2772	1006	36	p.	p.	PROPN
admet-2772	1006	37	barton	barton	PROPN
admet-2772	1006	38	,	,	PUNCT
admet-2772	1006	39	j.	j.	PROPN
admet-2772	1006	40	bird	bird	PROPN
admet-2772	1006	41	,	,	PUNCT
admet-2772	1006	42	r.	r.	PROPN
admet-2772	1006	43	denton	denton	PROPN
admet-2772	1006	44	,	,	PUNCT
admet-2772	1006	45	k.	k.	PROPN
admet-2772	1006	46	menochet	menochet	PROPN
admet-2772	1006	47	,	,	PUNCT
admet-2772	1006	48	a.	a.	PROPN
admet-2772	1006	49	smith	smith	PROPN
admet-2772	1006	50	,	,	PUNCT
admet-2772	1006	51	n.p	n.p	PROPN
admet-2772	1006	52	.	.	PROPN
admet-2772	1006	53	tomkinson	tomkinson	PROPN
admet-2772	1006	54	,	,	PUNCT
admet-2772	1006	55	k.k	k.k	PROPN
admet-2772	1006	56	.	.	PROPN
admet-2772	1006	57	chohan	chohan	PROPN
admet-2772	1006	58	.	.	PUNCT
admet-2772	1007	1	a	a	DET
admet-2772	1007	2	rapid	rapid	ADJ
admet-2772	1007	3	computational	computational	ADJ
admet-2772	1007	4	filter	filter	NOUN
admet-2772	1007	5	for	for	ADP
admet-2772	1007	6	predicting	predict	VERB
admet-2772	1007	7	the	the	DET
admet-2772	1007	8	rate	rate	NOUN
admet-2772	1007	9	of	of	ADP
admet-2772	1007	10	human	human	ADJ
admet-2772	1007	11	renal	renal	ADJ
admet-2772	1007	12	clearance	clearance	NOUN
admet-2772	1007	13	.	.	PUNCT
admet-2772	1008	1	journal	journal	NOUN
admet-2772	1008	2	of	of	ADP
admet-2772	1008	3	molecular	molecular	ADJ
admet-2772	1008	4	graphics	graphic	NOUN
admet-2772	1008	5	and	and	CCONJ
admet-2772	1008	6	modelling	model	VERB
admet-2772	1008	7	29	29	NUM
admet-2772	1008	8	(	(	PUNCT
admet-2772	1008	9	2010	2010	NUM
admet-2772	1008	10	)	)	PUNCT
admet-2772	1008	11	529	529	NUM
admet-2772	1008	12	-	-	SYM
admet-2772	1008	13	537	537	NUM
admet-2772	1008	14	.	.	PUNCT
admet-2772	1009	1	https://doi.org/10.1016/j.jmgm.2010.10.003	https://doi.org/10.1016/j.jmgm.2010.10.003	PRON
admet-2772	1009	2	[	[	X
admet-2772	1009	3	101	101	NUM
admet-2772	1009	4	]	]	X
admet-2772	1009	5	y.	y.	PROPN
admet-2772	1009	6	wang	wang	PROPN
admet-2772	1009	7	,	,	PUNCT
admet-2772	1009	8	h.	h.	PROPN
admet-2772	1009	9	liu	liu	PROPN
admet-2772	1009	10	,	,	PUNCT
admet-2772	1009	11	y.	y.	PROPN
admet-2772	1009	12	fan	fan	PROPN
admet-2772	1009	13	,	,	PUNCT
admet-2772	1009	14	x.	x.	PROPN
admet-2772	1009	15	chen	chen	PROPN
admet-2772	1009	16	,	,	PUNCT
admet-2772	1009	17	y.	y.	PROPN
admet-2772	1009	18	yang	yang	PROPN
admet-2772	1009	19	,	,	PUNCT
admet-2772	1009	20	l.	l.	PROPN
admet-2772	1009	21	zhu	zhu	PROPN
admet-2772	1009	22	,	,	PUNCT
admet-2772	1009	23	j.	j.	PROPN
admet-2772	1009	24	zhao	zhao	PROPN
admet-2772	1009	25	,	,	PUNCT
admet-2772	1009	26	y.	y.	PROPN
admet-2772	1009	27	chen	chen	PROPN
admet-2772	1009	28	,	,	PUNCT
admet-2772	1009	29	y.	y.	PROPN
admet-2772	1009	30	zhang	zhang	PROPN
admet-2772	1009	31	.	.	PUNCT
admet-2772	1010	1	in	in	ADP
admet-2772	1010	2	silico	silico	NOUN
admet-2772	1010	3	prediction	prediction	NOUN
admet-2772	1010	4	of	of	ADP
admet-2772	1010	5	human	human	ADJ
admet-2772	1010	6	intravenous	intravenous	ADJ
admet-2772	1010	7	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	1010	8	parameters	parameter	NOUN
admet-2772	1010	9	with	with	ADP
admet-2772	1010	10	improved	improved	ADJ
admet-2772	1010	11	accuracy	accuracy	NOUN
admet-2772	1010	12	.	.	PUNCT
admet-2772	1011	1	journal	journal	PROPN
admet-2772	1011	2	of	of	ADP
admet-2772	1011	3	chemical	chemical	ADJ
admet-2772	1011	4	information	information	NOUN
admet-2772	1011	5	and	and	CCONJ
admet-2772	1011	6	modeling	model	VERB
admet-2772	1011	7	59	59	NUM
admet-2772	1011	8	(	(	PUNCT
admet-2772	1011	9	2019	2019	NUM
admet-2772	1011	10	)	)	PUNCT
admet-2772	1011	11	3968	3968	NUM
admet-2772	1011	12	-	-	SYM
admet-2772	1011	13	3980	3980	NUM
admet-2772	1011	14	.	.	PUNCT
admet-2772	1012	1	https://doi.org/10.1021/acs.jcim.9b00300	https://doi.org/10.1021/acs.jcim.9b00300	NOUN
admet-2772	1013	1	[	[	X
admet-2772	1013	2	102	102	NUM
admet-2772	1013	3	]	]	X
admet-2772	1013	4	w.	w.	PROPN
admet-2772	1013	5	guo	guo	PROPN
admet-2772	1013	6	,	,	PUNCT
admet-2772	1013	7	j.	j.	PROPN
admet-2772	1013	8	liu	liu	PROPN
admet-2772	1013	9	,	,	PUNCT
admet-2772	1013	10	f.	f.	PROPN
admet-2772	1013	11	dong	dong	PROPN
admet-2772	1013	12	,	,	PUNCT
admet-2772	1013	13	m.	m.	NOUN
admet-2772	1013	14	song	song	NOUN
admet-2772	1013	15	,	,	PUNCT
admet-2772	1013	16	z.	z.	PROPN
admet-2772	1013	17	li	li	PROPN
admet-2772	1013	18	,	,	PUNCT
admet-2772	1013	19	m.k.h	m.k.h	PROPN
admet-2772	1013	20	.	.	PROPN
admet-2772	1013	21	khan	khan	PROPN
admet-2772	1013	22	,	,	PUNCT
admet-2772	1013	23	t.a	t.a	PROPN
admet-2772	1013	24	.	.	PROPN
admet-2772	1013	25	patterson	patterson	PROPN
admet-2772	1013	26	,	,	PUNCT
admet-2772	1013	27	h.	h.	PROPN
admet-2772	1013	28	hong	hong	PROPN
admet-2772	1013	29	.	.	PUNCT
admet-2772	1014	1	review	review	NOUN
admet-2772	1014	2	of	of	ADP
admet-2772	1014	3	machine	machine	NOUN
admet-2772	1014	4	learning	learning	NOUN
admet-2772	1014	5	and	and	CCONJ
admet-2772	1014	6	deep	deep	ADJ
admet-2772	1014	7	learning	learning	NOUN
admet-2772	1014	8	models	model	NOUN
admet-2772	1014	9	for	for	ADP
admet-2772	1014	10	toxicity	toxicity	NOUN
admet-2772	1014	11	prediction	prediction	NOUN
admet-2772	1014	12	.	.	PUNCT
admet-2772	1015	1	experimental	experimental	ADJ
admet-2772	1015	2	biology	biology	NOUN
admet-2772	1015	3	and	and	CCONJ
admet-2772	1015	4	medicine	medicine	NOUN
admet-2772	1015	5	248	248	NUM
admet-2772	1015	6	(	(	PUNCT
admet-2772	1015	7	2023	2023	NUM
admet-2772	1015	8	)	)	PUNCT
admet-2772	1015	9	1952	1952	NUM
admet-2772	1015	10	-	-	SYM
admet-2772	1015	11	1973	1973	NUM
admet-2772	1015	12	.	.	PUNCT
admet-2772	1016	1	https://doi.org/10.1177/15353702231209421	https://doi.org/10.1177/15353702231209421	NOUN
admet-2772	1017	1	[	[	X
admet-2772	1017	2	103	103	NUM
admet-2772	1017	3	]	]	PUNCT
admet-2772	1017	4	p.	p.	PROPN
admet-2772	1017	5	rana	rana	PROPN
admet-2772	1017	6	,	,	PUNCT
admet-2772	1017	7	s.	s.	PROPN
admet-2772	1017	8	kogut	kogut	PROPN
admet-2772	1017	9	,	,	PUNCT
admet-2772	1017	10	x.	x.	PROPN
admet-2772	1017	11	wen	wen	PROPN
admet-2772	1017	12	,	,	PUNCT
admet-2772	1017	13	f.	f.	PROPN
admet-2772	1017	14	akhlaghi	akhlaghi	PROPN
admet-2772	1017	15	,	,	PUNCT
admet-2772	1017	16	m.d	m.d	PROPN
admet-2772	1017	17	.	.	PROPN
admet-2772	1017	18	aleo	aleo	PROPN
admet-2772	1017	19	.	.	PUNCT
admet-2772	1018	1	most	most	ADJ
admet-2772	1018	2	influential	influential	ADJ
admet-2772	1018	3	physicochemical	physicochemical	ADJ
admet-2772	1018	4	and	and	CCONJ
admet-2772	1018	5	in	in	ADP
admet-2772	1018	6	vitro	vitro	X
admet-2772	1018	7	assay	assay	NOUN
admet-2772	1018	8	descriptors	descriptor	NOUN
admet-2772	1018	9	for	for	ADP
admet-2772	1018	10	hepatotoxicity	hepatotoxicity	NOUN
admet-2772	1018	11	and	and	CCONJ
admet-2772	1018	12	nephrotoxicity	nephrotoxicity	NOUN
admet-2772	1018	13	prediction	prediction	NOUN
admet-2772	1018	14	.	.	PUNCT
admet-2772	1019	1	chemical	chemical	ADJ
admet-2772	1019	2	research	research	NOUN
admet-2772	1019	3	in	in	ADP
admet-2772	1019	4	toxicology	toxicology	NOUN
admet-2772	1019	5	33	33	NUM
admet-2772	1019	6	(	(	PUNCT
admet-2772	1019	7	2020	2020	NUM
admet-2772	1019	8	)	)	PUNCT
admet-2772	1019	9	1780	1780	NUM
admet-2772	1019	10	-	-	SYM
admet-2772	1019	11	1790	1790	NUM
admet-2772	1019	12	.	.	PUNCT
admet-2772	1020	1	https://doi.org/10.1021/acs.chemrestox.0c00040	https://doi.org/10.1021/acs.chemrestox.0c00040	PUNCT
admet-2772	1021	1	[	[	X
admet-2772	1021	2	104	104	NUM
admet-2772	1021	3	]	]	X
admet-2772	1021	4	m.z.i	m.z.i	NOUN
admet-2772	1021	5	.	.	PUNCT
admet-2772	1021	6	khan	khan	PROPN
admet-2772	1021	7	,	,	PUNCT
admet-2772	1021	8	j.n	j.n	PROPN
admet-2772	1021	9	.	.	PROPN
admet-2772	1021	10	ren	ren	PROPN
admet-2772	1021	11	,	,	PUNCT
admet-2772	1021	12	c.	c.	PROPN
admet-2772	1021	13	cao	cao	PROPN
admet-2772	1021	14	,	,	PUNCT
admet-2772	1021	15	h.y.x	h.y.x	PROPN
admet-2772	1021	16	.	.	PUNCT
admet-2772	1022	1	ye	ye	PROPN
admet-2772	1022	2	,	,	PUNCT
admet-2772	1022	3	h.	h.	PROPN
admet-2772	1022	4	wang	wang	PROPN
admet-2772	1022	5	,	,	PUNCT
admet-2772	1022	6	y.m	y.m	PROPN
admet-2772	1022	7	.	.	PROPN
admet-2772	1022	8	guo	guo	PROPN
admet-2772	1022	9	,	,	PUNCT
admet-2772	1022	10	j.r	j.r	PROPN
admet-2772	1022	11	.	.	PROPN
admet-2772	1022	12	yang	yang	PROPN
admet-2772	1022	13	,	,	PUNCT
admet-2772	1022	14	j.z	j.z	PROPN
admet-2772	1022	15	.	.	PROPN
admet-2772	1022	16	chen	chen	PROPN
admet-2772	1022	17	.	.	PUNCT
admet-2772	1023	1	comprehensive	comprehensive	ADJ
admet-2772	1023	2	hepatotoxicity	hepatotoxicity	NOUN
admet-2772	1023	3	prediction	prediction	NOUN
admet-2772	1023	4	:	:	PUNCT
admet-2772	1023	5	ensemble	ensemble	ADJ
admet-2772	1023	6	model	model	NOUN
admet-2772	1023	7	integrating	integrate	VERB
admet-2772	1023	8	machine	machine	NOUN
admet-2772	1023	9	learning	learning	NOUN
admet-2772	1023	10	and	and	CCONJ
admet-2772	1023	11	deep	deep	ADJ
admet-2772	1023	12	learning	learning	NOUN
admet-2772	1023	13	.	.	PUNCT
admet-2772	1024	1	frontiers	frontier	NOUN
admet-2772	1024	2	in	in	ADP
admet-2772	1024	3	pharmacology	pharmacology	NOUN
admet-2772	1024	4	15	15	NUM
admet-2772	1024	5	(	(	PUNCT
admet-2772	1024	6	2024	2024	NUM
admet-2772	1024	7	)	)	PUNCT
admet-2772	1024	8	1441587	1441587	NUM
admet-2772	1024	9	.	.	PUNCT
admet-2772	1025	1	https://doi.org/10.3389/fphar.2024.1441587	https://doi.org/10.3389/fphar.2024.1441587	PROPN
admet-2772	1025	2	[	[	X
admet-2772	1025	3	105	105	NUM
admet-2772	1025	4	]	]	X
admet-2772	1025	5	r.	r.	PROPN
admet-2772	1025	6	ancuceanu	ancuceanu	PROPN
admet-2772	1025	7	,	,	PUNCT
admet-2772	1025	8	m.v	m.v	PROPN
admet-2772	1025	9	.	.	PROPN
admet-2772	1025	10	hovanet	hovanet	PROPN
admet-2772	1025	11	,	,	PUNCT
admet-2772	1025	12	a.i	a.i	PROPN
admet-2772	1025	13	.	.	PROPN
admet-2772	1025	14	anghel	anghel	PROPN
admet-2772	1025	15	,	,	PUNCT
admet-2772	1025	16	f.	f.	PROPN
admet-2772	1025	17	furtunescu	furtunescu	PROPN
admet-2772	1025	18	,	,	PUNCT
admet-2772	1025	19	m.	m.	NOUN
admet-2772	1025	20	neagu	neagu	NOUN
admet-2772	1025	21	,	,	PUNCT
admet-2772	1025	22	c.	c.	PROPN
admet-2772	1025	23	constantin	constantin	PROPN
admet-2772	1025	24	,	,	PUNCT
admet-2772	1025	25	m.	m.	NOUN
admet-2772	1025	26	dinu	dinu	PROPN
admet-2772	1025	27	.	.	PUNCT
admet-2772	1026	1	computational	computational	ADJ
admet-2772	1026	2	models	model	NOUN
admet-2772	1026	3	using	use	VERB
admet-2772	1026	4	multiple	multiple	ADJ
admet-2772	1026	5	machine	machine	NOUN
admet-2772	1026	6	learning	learn	VERB
admet-2772	1026	7	algorithms	algorithm	NOUN
admet-2772	1026	8	for	for	ADP
admet-2772	1026	9	predicting	predict	VERB
admet-2772	1026	10	drug	drug	NOUN
admet-2772	1026	11	hepatotoxicity	hepatotoxicity	NOUN
admet-2772	1026	12	with	with	ADP
admet-2772	1026	13	the	the	DET
admet-2772	1026	14	dilirank	dilirank	NOUN
admet-2772	1026	15	dataset	dataset	NOUN
admet-2772	1026	16	.	.	PUNCT
admet-2772	1027	1	international	international	ADJ
admet-2772	1027	2	journal	journal	NOUN
admet-2772	1027	3	of	of	ADP
admet-2772	1027	4	molecular	molecular	ADJ
admet-2772	1027	5	sciences	science	NOUN
admet-2772	1027	6	21(6	21(6	NUM
admet-2772	1027	7	)	)	PUNCT
admet-2772	1027	8	(	(	PUNCT
admet-2772	1027	9	2020	2020	NUM
admet-2772	1027	10	)	)	PUNCT
admet-2772	1027	11	2114	2114	NUM
admet-2772	1027	12	.	.	PUNCT
admet-2772	1028	1	https://doi.org/10.3390/ijms21062114	https://doi.org/10.3390/ijms21062114	PROPN
admet-2772	1029	1	[	[	X
admet-2772	1029	2	106	106	X
admet-2772	1029	3	]	]	X
admet-2772	1029	4	y.	y.	PROPN
admet-2772	1029	5	lu	lu	PROPN
admet-2772	1029	6	,	,	PUNCT
admet-2772	1029	7	l.	l.	PROPN
admet-2772	1029	8	liu	liu	PROPN
admet-2772	1029	9	,	,	PUNCT
admet-2772	1029	10	d.	d.	PROPN
admet-2772	1029	11	lu	lu	PROPN
admet-2772	1029	12	,	,	PUNCT
admet-2772	1029	13	y.	y.	PROPN
admet-2772	1029	14	cai	cai	PROPN
admet-2772	1029	15	,	,	PUNCT
admet-2772	1029	16	m.	m.	NOUN
admet-2772	1029	17	zheng	zheng	PROPN
admet-2772	1029	18	,	,	PUNCT
admet-2772	1029	19	x.	x.	PROPN
admet-2772	1029	20	luo	luo	PROPN
admet-2772	1029	21	,	,	PUNCT
admet-2772	1029	22	h.	h.	PROPN
admet-2772	1029	23	jiang	jiang	PROPN
admet-2772	1029	24	,	,	PUNCT
admet-2772	1029	25	k.	k.	PROPN
admet-2772	1029	26	chen	chen	PROPN
admet-2772	1029	27	.	.	PUNCT
admet-2772	1030	1	predicting	predict	VERB
admet-2772	1030	2	hepatotoxicity	hepatotoxicity	NOUN
admet-2772	1030	3	of	of	ADP
admet-2772	1030	4	drug	drug	NOUN
admet-2772	1030	5	metabolites	metabolite	NOUN
admet-2772	1030	6	via	via	ADP
admet-2772	1030	7	an	an	DET
admet-2772	1030	8	ensemble	ensemble	ADJ
admet-2772	1030	9	approach	approach	NOUN
admet-2772	1030	10	based	base	VERB
admet-2772	1030	11	on	on	ADP
admet-2772	1030	12	support	support	NOUN
admet-2772	1030	13	vector	vector	NOUN
admet-2772	1030	14	machine	machine	NOUN
admet-2772	1030	15	.	.	PUNCT
admet-2772	1031	1	combinatorial	combinatorial	ADJ
admet-2772	1031	2	chemistry	chemistry	NOUN
admet-2772	1031	3	&	&	CCONJ
admet-2772	1031	4	high	high	ADJ
admet-2772	1031	5	throughput	throughput	NOUN
admet-2772	1031	6	screening	screen	VERB
admet-2772	1031	7	20	20	NUM
admet-2772	1031	8	(	(	PUNCT
admet-2772	1031	9	2017	2017	NUM
admet-2772	1031	10	)	)	PUNCT
admet-2772	1031	11	839	839	NUM
admet-2772	1031	12	-	-	NUM
admet-2772	1031	13	849	849	NUM
admet-2772	1031	14	.	.	PUNCT
admet-2772	1031	15	https://doi.org/10.2174/1386207320666171121113255	https://doi.org/10.2174/1386207320666171121113255	PUNCT
admet-2772	1032	1	[	[	X
admet-2772	1032	2	107	107	NUM
admet-2772	1032	3	]	]	X
admet-2772	1032	4	l.w	l.w	PROPN
admet-2772	1032	5	.	.	PROPN
admet-2772	1032	6	chiu	chiu	PROPN
admet-2772	1032	7	,	,	PUNCT
admet-2772	1032	8	y.e	y.e	PROPN
admet-2772	1032	9	.	.	PROPN
admet-2772	1032	10	ku	ku	PROPN
admet-2772	1032	11	,	,	PUNCT
admet-2772	1032	12	f.y	f.y	PROPN
admet-2772	1032	13	.	.	PROPN
admet-2772	1032	14	chan	chan	PROPN
admet-2772	1032	15	,	,	PUNCT
admet-2772	1032	16	w.n	w.n	PROPN
admet-2772	1032	17	.	.	PROPN
admet-2772	1032	18	lie	lie	PROPN
admet-2772	1032	19	,	,	PUNCT
admet-2772	1032	20	h.j	h.j	PROPN
admet-2772	1032	21	.	.	PROPN
admet-2772	1032	22	chao	chao	PROPN
admet-2772	1032	23	,	,	PUNCT
admet-2772	1032	24	s.y	s.y	PROPN
admet-2772	1032	25	.	.	PROPN
admet-2772	1032	26	wang	wang	PROPN
admet-2772	1032	27	,	,	PUNCT
admet-2772	1032	28	w.c	w.c	PROPN
admet-2772	1032	29	.	.	PROPN
admet-2772	1032	30	shen	shen	PROPN
admet-2772	1032	31	,	,	PUNCT
admet-2772	1032	32	h.y	h.y	PROPN
admet-2772	1032	33	.	.	PROPN
admet-2772	1032	34	chen	chen	PROPN
admet-2772	1032	35	.	.	PUNCT
admet-2772	1033	1	machine	machine	NOUN
admet-2772	1033	2	learning	learn	VERB
admet-2772	1033	3	algorithms	algorithm	NOUN
admet-2772	1033	4	to	to	PART
admet-2772	1033	5	predict	predict	VERB
admet-2772	1033	6	colistin	colistin	NOUN
admet-2772	1033	7	-	-	PUNCT
admet-2772	1033	8	induced	induce	VERB
admet-2772	1033	9	nephrotoxicity	nephrotoxicity	NOUN
admet-2772	1033	10	from	from	ADP
admet-2772	1033	11	electronic	electronic	ADJ
admet-2772	1033	12	health	health	NOUN
admet-2772	1033	13	records	record	NOUN
admet-2772	1033	14	in	in	ADP
admet-2772	1033	15	patients	patient	NOUN
admet-2772	1033	16	with	with	ADP
admet-2772	1033	17	multidrug	multidrug	NOUN
admet-2772	1033	18	-	-	PUNCT
admet-2772	1033	19	resistant	resistant	ADJ
admet-2772	1033	20	gram	gram	NOUN
admet-2772	1033	21	-	-	PUNCT
admet-2772	1033	22	negative	negative	ADJ
admet-2772	1033	23	infection	infection	NOUN
admet-2772	1033	24	.	.	PUNCT
admet-2772	1034	1	international	international	ADJ
admet-2772	1034	2	journal	journal	PROPN
admet-2772	1034	3	of	of	ADP
admet-2772	1034	4	antimicrobial	antimicrobial	ADJ
admet-2772	1034	5	agents	agent	NOUN
admet-2772	1034	6	64	64	NUM
admet-2772	1034	7	(	(	PUNCT
admet-2772	1034	8	2024	2024	NUM
admet-2772	1034	9	)	)	PUNCT
admet-2772	1034	10	107175	107175	NUM
admet-2772	1034	11	.	.	PUNCT
admet-2772	1035	1	https://doi.org/10.1016/j.ijantimicag.2024.107175	https://doi.org/10.1016/j.ijantimicag.2024.107175	PROPN
admet-2772	1036	1	[	[	X
admet-2772	1036	2	108	108	NUM
admet-2772	1036	3	]	]	X
admet-2772	1036	4	j.y	j.y	PROPN
admet-2772	1036	5	.	.	PROPN
admet-2772	1036	6	ryu	ryu	PROPN
admet-2772	1036	7	,	,	PUNCT
admet-2772	1036	8	w.d	w.d	PROPN
admet-2772	1036	9	.	.	PROPN
admet-2772	1036	10	jang	jang	PROPN
admet-2772	1036	11	,	,	PUNCT
admet-2772	1036	12	j.	j.	PROPN
admet-2772	1036	13	jang	jang	PROPN
admet-2772	1036	14	,	,	PUNCT
admet-2772	1036	15	k.s	k.s	PROPN
admet-2772	1036	16	.	.	PUNCT
admet-2772	1037	1	oh	oh	INTJ
admet-2772	1037	2	.	.	PUNCT
admet-2772	1038	1	predaot	predaot	NOUN
admet-2772	1038	2	:	:	PUNCT
admet-2772	1038	3	a	a	DET
admet-2772	1038	4	computational	computational	ADJ
admet-2772	1038	5	framework	framework	NOUN
admet-2772	1038	6	for	for	ADP
admet-2772	1038	7	prediction	prediction	NOUN
admet-2772	1038	8	of	of	ADP
admet-2772	1038	9	acute	acute	ADJ
admet-2772	1038	10	oral	oral	ADJ
admet-2772	1038	11	toxicity	toxicity	NOUN
admet-2772	1038	12	based	base	VERB
admet-2772	1038	13	on	on	ADP
admet-2772	1038	14	multiple	multiple	ADJ
admet-2772	1038	15	random	random	ADJ
admet-2772	1038	16	forest	forest	NOUN
admet-2772	1038	17	models	model	NOUN
admet-2772	1038	18	.	.	PUNCT
admet-2772	1039	1	bmc	bmc	ADJ
admet-2772	1039	2	bioinformatics	bioinformatics	NOUN
admet-2772	1039	3	24	24	NUM
admet-2772	1039	4	(	(	PUNCT
admet-2772	1039	5	2023	2023	NUM
admet-2772	1039	6	)	)	PUNCT
admet-2772	1039	7	66	66	NUM
admet-2772	1039	8	.	.	PUNCT
admet-2772	1040	1	https://doi.org/10.1186/s12859-023-05176-5	https://doi.org/10.1186/s12859-023-05176-5	NUM
admet-2772	1040	2	[	[	X
admet-2772	1040	3	109	109	NUM
admet-2772	1040	4	]	]	PUNCT
admet-2772	1040	5	f.	f.	PROPN
admet-2772	1040	6	mostafa	mostafa	PROPN
admet-2772	1040	7	,	,	PUNCT
admet-2772	1040	8	v.	v.	ADP
admet-2772	1040	9	howle	howle	ADV
admet-2772	1040	10	,	,	PUNCT
admet-2772	1040	11	m.	m.	PROPN
admet-2772	1040	12	chen	chen	PROPN
admet-2772	1040	13	.	.	PUNCT
admet-2772	1041	1	machine	machine	NOUN
admet-2772	1041	2	learning	learn	VERB
admet-2772	1041	3	to	to	PART
admet-2772	1041	4	predict	predict	VERB
admet-2772	1041	5	drug	drug	NOUN
admet-2772	1041	6	-	-	PUNCT
admet-2772	1041	7	induced	induce	VERB
admet-2772	1041	8	liver	liver	NOUN
admet-2772	1041	9	injury	injury	NOUN
admet-2772	1041	10	and	and	CCONJ
admet-2772	1041	11	its	its	PRON
admet-2772	1041	12	validation	validation	NOUN
admet-2772	1041	13	on	on	ADP
admet-2772	1041	14	failed	fail	VERB
admet-2772	1041	15	drug	drug	NOUN
admet-2772	1041	16	candidates	candidate	NOUN
admet-2772	1041	17	in	in	ADP
admet-2772	1041	18	development	development	NOUN
admet-2772	1041	19	†.	†.	PART
admet-2772	1041	20	toxics	toxic	NOUN
admet-2772	1041	21	12(6	12(6	NUM
admet-2772	1041	22	)	)	PUNCT
admet-2772	1041	23	(	(	PUNCT
admet-2772	1041	24	2024	2024	NUM
admet-2772	1041	25	)	)	PUNCT
admet-2772	1041	26	385	385	NUM
admet-2772	1041	27	.	.	PUNCT
admet-2772	1042	1	https://doi.org/10.3390/toxics12060385	https://doi.org/10.3390/toxics12060385	PROPN
admet-2772	1043	1	[	[	X
admet-2772	1043	2	110	110	NUM
admet-2772	1043	3	]	]	X
admet-2772	1043	4	c.	c.	PROPN
admet-2772	1043	5	cai	cai	PROPN
admet-2772	1043	6	,	,	PUNCT
admet-2772	1043	7	p.	p.	PROPN
admet-2772	1043	8	guo	guo	PROPN
admet-2772	1043	9	,	,	PUNCT
admet-2772	1043	10	y.	y.	PROPN
admet-2772	1043	11	zhou	zhou	PROPN
admet-2772	1043	12	,	,	PUNCT
admet-2772	1043	13	j.	j.	PROPN
admet-2772	1043	14	zhou	zhou	PROPN
admet-2772	1043	15	,	,	PUNCT
admet-2772	1043	16	q.	q.	PROPN
admet-2772	1043	17	wang	wang	PROPN
admet-2772	1043	18	,	,	PUNCT
admet-2772	1043	19	f.	f.	PROPN
admet-2772	1043	20	zhang	zhang	PROPN
admet-2772	1043	21	,	,	PUNCT
admet-2772	1043	22	j.	j.	PROPN
admet-2772	1043	23	fang	fang	PROPN
admet-2772	1043	24	,	,	PUNCT
admet-2772	1043	25	f.	f.	PROPN
admet-2772	1043	26	cheng	cheng	PROPN
admet-2772	1043	27	.	.	PUNCT
admet-2772	1044	1	deep	deep	ADJ
admet-2772	1044	2	learning	learning	NOUN
admet-2772	1044	3	-	-	PUNCT
admet-2772	1044	4	based	base	VERB
admet-2772	1044	5	prediction	prediction	NOUN
admet-2772	1044	6	of	of	ADP
admet-2772	1044	7	drug	drug	NOUN
admet-2772	1044	8	-	-	PUNCT
admet-2772	1044	9	induced	induce	VERB
admet-2772	1044	10	cardiotoxicity	cardiotoxicity	NOUN
admet-2772	1044	11	.	.	PUNCT
admet-2772	1045	1	journal	journal	PROPN
admet-2772	1045	2	of	of	ADP
admet-2772	1045	3	chemical	chemical	ADJ
admet-2772	1045	4	information	information	NOUN
admet-2772	1045	5	and	and	CCONJ
admet-2772	1045	6	modeling	model	VERB
admet-2772	1045	7	59	59	NUM
admet-2772	1045	8	(	(	PUNCT
admet-2772	1045	9	2019	2019	NUM
admet-2772	1045	10	)	)	PUNCT
admet-2772	1045	11	1073	1073	NUM
admet-2772	1045	12	-	-	SYM
admet-2772	1045	13	1084	1084	NUM
admet-2772	1045	14	.	.	PUNCT
admet-2772	1046	1	https://doi.org/10.1021/acs.jcim.8b00769	https://doi.org/10.1021/acs.jcim.8b00769	NOUN
admet-2772	1047	1	[	[	X
admet-2772	1047	2	111	111	NUM
admet-2772	1047	3	]	]	PUNCT
admet-2772	1047	4	d.	d.	PROPN
admet-2772	1047	5	fan	fan	PROPN
admet-2772	1047	6	,	,	PUNCT
admet-2772	1047	7	h.	h.	PROPN
admet-2772	1047	8	yang	yang	PROPN
admet-2772	1047	9	,	,	PUNCT
admet-2772	1047	10	f.	f.	PROPN
admet-2772	1047	11	li	li	PROPN
admet-2772	1047	12	,	,	PUNCT
admet-2772	1047	13	l.	l.	PROPN
admet-2772	1047	14	sun	sun	PROPN
admet-2772	1047	15	,	,	PUNCT
admet-2772	1047	16	p.	p.	PROPN
admet-2772	1047	17	di	di	PROPN
admet-2772	1047	18	,	,	PUNCT
admet-2772	1047	19	w.	w.	PROPN
admet-2772	1047	20	li	li	PROPN
admet-2772	1047	21	,	,	PUNCT
admet-2772	1047	22	y.	y.	PROPN
admet-2772	1047	23	tang	tang	PROPN
admet-2772	1047	24	,	,	PUNCT
admet-2772	1047	25	g.	g.	PROPN
admet-2772	1047	26	liu	liu	PROPN
admet-2772	1047	27	.	.	PUNCT
admet-2772	1048	1	in	in	ADP
admet-2772	1048	2	silico	silico	NOUN
admet-2772	1048	3	prediction	prediction	NOUN
admet-2772	1048	4	of	of	ADP
admet-2772	1048	5	chemical	chemical	ADJ
admet-2772	1048	6	genotoxicity	genotoxicity	NOUN
admet-2772	1048	7	using	use	VERB
admet-2772	1048	8	machine	machine	NOUN
admet-2772	1048	9	learning	learning	NOUN
admet-2772	1048	10	methods	method	NOUN
admet-2772	1048	11	and	and	CCONJ
admet-2772	1048	12	structural	structural	ADJ
admet-2772	1048	13	alerts	alert	NOUN
admet-2772	1048	14	.	.	PUNCT
admet-2772	1049	1	toxicology	toxicology	NOUN
admet-2772	1049	2	research	research	NOUN
admet-2772	1049	3	7	7	NUM
admet-2772	1049	4	(	(	PUNCT
admet-2772	1049	5	2018	2018	NUM
admet-2772	1049	6	)	)	PUNCT
admet-2772	1049	7	211	211	NUM
admet-2772	1049	8	-	-	SYM
admet-2772	1049	9	220	220	NUM
admet-2772	1049	10	.	.	PUNCT
admet-2772	1050	1	https://doi.org/10.1039/c7tx00259a	https://doi.org/10.1039/c7tx00259a	PUNCT
admet-2772	1051	1	[	[	X
admet-2772	1051	2	112	112	NUM
admet-2772	1051	3	]	]	X
admet-2772	1051	4	n.k	n.k	PROPN
admet-2772	1051	5	.	.	PROPN
admet-2772	1051	6	shinada	shinada	PROPN
admet-2772	1051	7	,	,	PUNCT
admet-2772	1051	8	n.	n.	PROPN
admet-2772	1051	9	koyama	koyama	PROPN
admet-2772	1051	10	,	,	PUNCT
admet-2772	1051	11	m.	m.	NOUN
admet-2772	1051	12	ikemori	ikemori	PROPN
admet-2772	1051	13	,	,	PUNCT
admet-2772	1051	14	t.	t.	PROPN
admet-2772	1051	15	nishioka	nishioka	PROPN
admet-2772	1051	16	,	,	PUNCT
admet-2772	1051	17	s.	s.	PROPN
admet-2772	1051	18	hitaoka	hitaoka	PROPN
admet-2772	1051	19	,	,	PUNCT
admet-2772	1051	20	a.	a.	NOUN
admet-2772	1051	21	hakura	hakura	PROPN
admet-2772	1051	22	,	,	PUNCT
admet-2772	1051	23	s.	s.	PROPN
admet-2772	1051	24	asakura	asakura	PROPN
admet-2772	1051	25	,	,	PUNCT
admet-2772	1051	26	y.	y.	PROPN
admet-2772	1051	27	matsuoka	matsuoka	PROPN
admet-2772	1051	28	,	,	PUNCT
admet-2772	1051	29	s.k	s.k	PROPN
admet-2772	1051	30	.	.	PROPN
admet-2772	1051	31	palaniappan	palaniappan	PROPN
admet-2772	1051	32	.	.	PUNCT
admet-2772	1052	1	optimizing	optimize	VERB
admet-2772	1052	2	machine	machine	NOUN
admet-2772	1052	3	-	-	PUNCT
admet-2772	1052	4	learning	learn	VERB
admet-2772	1052	5	models	model	NOUN
admet-2772	1052	6	for	for	ADP
admet-2772	1052	7	mutagenicity	mutagenicity	NOUN
admet-2772	1052	8	prediction	prediction	NOUN
admet-2772	1052	9	through	through	ADP
admet-2772	1052	10	better	well	ADJ
admet-2772	1052	11	feature	feature	NOUN
admet-2772	1052	12	selection	selection	NOUN
admet-2772	1052	13	.	.	PUNCT
admet-2772	1053	1	mutagenesis	mutagenesis	NOUN
admet-2772	1053	2	37	37	NUM
admet-2772	1053	3	(	(	PUNCT
admet-2772	1053	4	2022	2022	NUM
admet-2772	1053	5	)	)	PUNCT
admet-2772	1053	6	191	191	NUM
admet-2772	1053	7	-	-	SYM
admet-2772	1053	8	202	202	NUM
admet-2772	1053	9	.	.	PUNCT
admet-2772	1054	1	https://doi.org/10.1093/mutage/geac010	https://doi.org/10.1093/mutage/geac010	NOUN
admet-2772	1055	1	[	[	X
admet-2772	1055	2	113	113	NUM
admet-2772	1055	3	]	]	PUNCT
admet-2772	1055	4	t.	t.	PROPN
admet-2772	1055	5	li	li	PROPN
admet-2772	1055	6	,	,	PUNCT
admet-2772	1055	7	w.	w.	PROPN
admet-2772	1055	8	tong	tong	PROPN
admet-2772	1055	9	,	,	PUNCT
admet-2772	1055	10	r.	r.	PROPN
admet-2772	1055	11	roberts	roberts	PROPN
admet-2772	1055	12	,	,	PUNCT
admet-2772	1055	13	z.	z.	PROPN
admet-2772	1055	14	liu	liu	PROPN
admet-2772	1055	15	,	,	PUNCT
admet-2772	1055	16	s.	s.	PROPN
admet-2772	1055	17	thakkar	thakkar	PROPN
admet-2772	1055	18	.	.	PUNCT
admet-2772	1056	1	deepcarc	deepcarc	PRON
admet-2772	1056	2	:	:	PUNCT
admet-2772	1056	3	deep	deep	ADJ
admet-2772	1056	4	learning	learning	NOUN
admet-2772	1056	5	-	-	PUNCT
admet-2772	1056	6	powered	power	VERB
admet-2772	1056	7	carcinogenicity	carcinogenicity	NOUN
admet-2772	1056	8	prediction	prediction	NOUN
admet-2772	1056	9	using	use	VERB
admet-2772	1056	10	model	model	NOUN
admet-2772	1056	11	-	-	PUNCT
admet-2772	1056	12	level	level	NOUN
admet-2772	1056	13	representation	representation	NOUN
admet-2772	1056	14	.	.	PUNCT
admet-2772	1057	1	frontiers	frontier	NOUN
admet-2772	1057	2	in	in	ADP
admet-2772	1057	3	artificial	artificial	ADJ
admet-2772	1057	4	intelligence	intelligence	NOUN
admet-2772	1057	5	4	4	NUM
admet-2772	1057	6	(	(	PUNCT
admet-2772	1057	7	2021	2021	NUM
admet-2772	1057	8	)	)	PUNCT
admet-2772	1057	9	757780	757780	NUM
admet-2772	1057	10	.	.	PUNCT
admet-2772	1058	1	https://doi.org/10.3389/frai.2021.757780	https://doi.org/10.3389/frai.2021.757780	PROPN
admet-2772	1059	1	[	[	X
admet-2772	1059	2	114	114	NUM
admet-2772	1059	3	]	]	PUNCT
admet-2772	1059	4	a.	a.	NOUN
admet-2772	1059	5	talebi	talebi	PROPN
admet-2772	1059	6	,	,	PUNCT
admet-2772	1059	7	a.	a.	NOUN
admet-2772	1059	8	bitarafan	bitarafan	PROPN
admet-2772	1059	9	-	-	PUNCT
admet-2772	1059	10	rajabi	rajabi	NOUN
admet-2772	1059	11	,	,	PUNCT
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admet-2772	1059	13	alizadeh	alizadeh	PROPN
admet-2772	1059	14	-	-	PUNCT
admet-2772	1059	15	asl	asl	PROPN
admet-2772	1059	16	,	,	PUNCT
admet-2772	1059	17	p.	p.	PROPN
admet-2772	1059	18	seilani	seilani	PROPN
admet-2772	1059	19	,	,	PUNCT
admet-2772	1059	20	b.	b.	PROPN
admet-2772	1059	21	khajetash	khajetash	PROPN
admet-2772	1059	22	,	,	PUNCT
admet-2772	1059	23	g.	g.	PROPN
admet-2772	1059	24	hajianfar	hajianfar	PROPN
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admet-2772	1059	27	tavakoli	tavakoli	PROPN
admet-2772	1059	28	.	.	PUNCT
admet-2772	1060	1	machine	machine	NOUN
admet-2772	1060	2	learning	learning	PROPN
admet-2772	1060	3	based	base	VERB
admet-2772	1060	4	radiomics	radiomic	NOUN
admet-2772	1060	5	model	model	NOUN
admet-2772	1060	6	to	to	PART
admet-2772	1060	7	predict	predict	VERB
admet-2772	1060	8	radiotherapy	radiotherapy	NOUN
admet-2772	1060	9	induced	induce	VERB
admet-2772	1060	10	cardiotoxicity	cardiotoxicity	NOUN
admet-2772	1060	11	in	in	ADP
admet-2772	1060	12	breast	breast	NOUN
admet-2772	1060	13	cancer	cancer	NOUN
admet-2772	1060	14	.	.	PUNCT
admet-2772	1061	1	journal	journal	PROPN
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admet-2772	1061	4	clinical	clinical	ADJ
admet-2772	1061	5	medical	medical	ADJ
admet-2772	1061	6	physics	physics	NOUN
admet-2772	1061	7	26(4	26(4	NUM
admet-2772	1061	8	)	)	PUNCT
admet-2772	1061	9	(	(	PUNCT
admet-2772	1061	10	2024	2024	NUM
admet-2772	1061	11	)	)	PUNCT
admet-2772	1061	12	e14614	e14614	NUM
admet-2772	1061	13	.	.	PUNCT
admet-2772	1062	1	https://doi.org/10.1002/acm2.14614	https://doi.org/10.1002/acm2.14614	X
admet-2772	1062	2	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	1063	1	https://doi.org/10.1016/j.jmgm.2010.10.003	https://doi.org/10.1016/j.jmgm.2010.10.003	ADJ
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admet-2772	1063	4	https://doi.org/10.1021/acs.chemrestox.0c00040	https://doi.org/10.1021/acs.chemrestox.0c00040	NOUN
admet-2772	1064	1	https://doi.org/10.3389/fphar.2024.1441587	https://doi.org/10.3389/fphar.2024.1441587	PROPN
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admet-2772	1064	4	https://doi.org/10.1016/j.ijantimicag.2024.107175	https://doi.org/10.1016/j.ijantimicag.2024.107175	PROPN
admet-2772	1064	5	https://doi.org/10.1186/s12859-023-05176-5	https://doi.org/10.1186/s12859-023-05176-5	PROPN
admet-2772	1064	6	https://doi.org/10.3390/toxics12060385	https://doi.org/10.3390/toxics12060385	PROPN
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admet-2772	1064	8	https://doi.org/10.1039/c7tx00259a	https://doi.org/10.1039/c7tx00259a	PROPN
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admet-2772	1064	10	https://doi.org/10.3389/frai.2021.757780	https://doi.org/10.3389/frai.2021.757780	PROPN
admet-2772	1064	11	https://doi.org/10.1002/acm2.14614	https://doi.org/10.1002/acm2.14614	PUNCT
admet-2772	1065	1	m.	m.	PROPN
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admet-2772	1065	3	et	et	PROPN
admet-2772	1065	4	al	al	PROPN
admet-2772	1065	5	.	.	PROPN
admet-2772	1065	6	admet	admet	PROPN
admet-2772	1065	7	&	&	CCONJ
admet-2772	1065	8	dmpk	dmpk	PROPN
admet-2772	1065	9	13(3	13(3	NUM
admet-2772	1065	10	)	)	PUNCT
admet-2772	1065	11	(	(	PUNCT
admet-2772	1065	12	2025	2025	NUM
admet-2772	1065	13	)	)	PUNCT
admet-2772	1065	14	2772	2772	NUM
admet-2772	1065	15	32	32	NUM
admet-2772	1066	1	[	[	SYM
admet-2772	1066	2	115	115	NUM
admet-2772	1066	3	]	]	PUNCT
admet-2772	1066	4	s.	s.	PROPN
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admet-2772	1066	6	,	,	PUNCT
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admet-2772	1066	8	.	.	PROPN
admet-2772	1066	9	de	de	PROPN
admet-2772	1066	10	sá	sá	PROPN
admet-2772	1066	11	,	,	PUNCT
admet-2772	1066	12	j.p.l	j.p.l	PROPN
admet-2772	1066	13	.	.	PUNCT
admet-2772	1066	14	velloso	velloso	PROPN
admet-2772	1066	15	,	,	PUNCT
admet-2772	1066	16	r.	r.	PROPN
admet-2772	1066	17	aljarf	aljarf	PROPN
admet-2772	1066	18	,	,	PUNCT
admet-2772	1066	19	d.e.v	d.e.v	PROPN
admet-2772	1066	20	.	.	PUNCT
admet-2772	1066	21	pires	pires	PROPN
admet-2772	1066	22	,	,	PUNCT
admet-2772	1066	23	d.b	d.b	PROPN
admet-2772	1066	24	.	.	PROPN
admet-2772	1066	25	ascher	ascher	PROPN
admet-2772	1066	26	.	.	PUNCT
admet-2772	1067	1	cardiotoxcsm	cardiotoxcsm	NOUN
admet-2772	1067	2	:	:	PUNCT
admet-2772	1067	3	a	a	DET
admet-2772	1067	4	web	web	NOUN
admet-2772	1067	5	server	server	NOUN
admet-2772	1067	6	for	for	ADP
admet-2772	1067	7	predicting	predict	VERB
admet-2772	1067	8	cardiotoxicity	cardiotoxicity	NOUN
admet-2772	1067	9	of	of	ADP
admet-2772	1067	10	small	small	ADJ
admet-2772	1067	11	molecules	molecule	NOUN
admet-2772	1067	12	.	.	PUNCT
admet-2772	1068	1	journal	journal	PROPN
admet-2772	1068	2	of	of	ADP
admet-2772	1068	3	chemical	chemical	ADJ
admet-2772	1068	4	information	information	NOUN
admet-2772	1068	5	and	and	CCONJ
admet-2772	1068	6	modeling	model	VERB
admet-2772	1068	7	62	62	NUM
admet-2772	1068	8	(	(	PUNCT
admet-2772	1068	9	2022	2022	NUM
admet-2772	1068	10	)	)	PUNCT
admet-2772	1068	11	4827	4827	NUM
admet-2772	1068	12	-	-	SYM
admet-2772	1068	13	4836	4836	NUM
admet-2772	1068	14	.	.	PUNCT
admet-2772	1069	1	https://doi.org/10.1021/acs.jcim.2c00822	https://doi.org/10.1021/acs.jcim.2c00822	NOUN
admet-2772	1070	1	[	[	X
admet-2772	1070	2	116	116	X
admet-2772	1070	3	]	]	X
admet-2772	1070	4	p.	p.	PROPN
admet-2772	1070	5	trairatphisan	trairatphisan	PROPN
admet-2772	1070	6	,	,	PUNCT
admet-2772	1070	7	l.	l.	PROPN
admet-2772	1070	8	dorsheimer	dorsheimer	PROPN
admet-2772	1070	9	,	,	PUNCT
admet-2772	1070	10	p.	p.	NOUN
admet-2772	1070	11	monecke	monecke	PROPN
admet-2772	1070	12	,	,	PUNCT
admet-2772	1070	13	j.	j.	PROPN
admet-2772	1070	14	wenzel	wenzel	PROPN
admet-2772	1070	15	,	,	PUNCT
admet-2772	1070	16	r.	r.	PROPN
admet-2772	1070	17	james	james	PROPN
admet-2772	1070	18	,	,	PUNCT
admet-2772	1070	19	a.	a.	NOUN
admet-2772	1070	20	czich	czich	PROPN
admet-2772	1070	21	,	,	PUNCT
admet-2772	1070	22	y.	y.	PROPN
admet-2772	1070	23	dietz	dietz	PROPN
admet-2772	1070	24	-	-	PUNCT
admet-2772	1070	25	baum	baum	PROPN
admet-2772	1070	26	,	,	PUNCT
admet-2772	1070	27	f.	f.	PROPN
admet-2772	1070	28	schmidt	schmidt	PROPN
admet-2772	1070	29	.	.	PUNCT
admet-2772	1071	1	machine	machine	NOUN
admet-2772	1071	2	learning	learning	NOUN
admet-2772	1071	3	enhances	enhance	VERB
admet-2772	1071	4	genotoxicity	genotoxicity	NOUN
admet-2772	1071	5	assessment	assessment	NOUN
admet-2772	1071	6	using	use	VERB
admet-2772	1071	7	multiflow	multiflow	NOUN
admet-2772	1071	8	®	®	NOUN
admet-2772	1071	9	dna	dna	PROPN
admet-2772	1071	10	damage	damage	NOUN
admet-2772	1071	11	assay	assay	VERB
admet-2772	1071	12	.	.	PUNCT
admet-2772	1072	1	environmental	environmental	ADJ
admet-2772	1072	2	and	and	CCONJ
admet-2772	1072	3	molecular	molecular	ADJ
admet-2772	1072	4	mutagenesis	mutagenesis	NOUN
admet-2772	1072	5	66	66	NUM
admet-2772	1072	6	(	(	PUNCT
admet-2772	1072	7	2024	2024	NUM
admet-2772	1072	8	)	)	PUNCT
admet-2772	1072	9	45	45	NUM
admet-2772	1072	10	-	-	SYM
admet-2772	1072	11	57	57	NUM
admet-2772	1072	12	.	.	PUNCT
admet-2772	1072	13	https://doi.org/10.1002/em.22648	https://doi.org/10.1002/em.22648	X
admet-2772	1073	1	[	[	X
admet-2772	1073	2	117	117	NUM
admet-2772	1073	3	]	]	X
admet-2772	1073	4	c.n	c.n	PROPN
admet-2772	1073	5	.	.	PROPN
admet-2772	1073	6	cavasotto	cavasotto	PROPN
admet-2772	1073	7	,	,	PUNCT
admet-2772	1073	8	v.	v.	PROPN
admet-2772	1073	9	scardino	scardino	PROPN
admet-2772	1073	10	.	.	PUNCT
admet-2772	1074	1	machine	machine	NOUN
admet-2772	1074	2	learning	learn	VERB
admet-2772	1074	3	toxicity	toxicity	NOUN
admet-2772	1074	4	prediction	prediction	NOUN
admet-2772	1074	5	:	:	PUNCT
admet-2772	1074	6	latest	late	ADJ
admet-2772	1074	7	advances	advance	NOUN
admet-2772	1074	8	by	by	ADP
admet-2772	1074	9	toxicity	toxicity	NOUN
admet-2772	1074	10	end	end	NOUN
admet-2772	1074	11	point	point	NOUN
admet-2772	1074	12	.	.	PUNCT
admet-2772	1075	1	acs	acs	PROPN
admet-2772	1075	2	omega	omega	NOUN
admet-2772	1075	3	7	7	NUM
admet-2772	1075	4	(	(	PUNCT
admet-2772	1075	5	2022	2022	NUM
admet-2772	1075	6	)	)	PUNCT
admet-2772	1075	7	47536	47536	NUM
admet-2772	1075	8	-	-	SYM
admet-2772	1075	9	47546	47546	NUM
admet-2772	1075	10	.	.	PUNCT
admet-2772	1076	1	https://doi.org/10.1021/acsomega.2c05693	https://doi.org/10.1021/acsomega.2c05693	PROPN
admet-2772	1076	2	[	[	X
admet-2772	1076	3	118	118	NUM
admet-2772	1076	4	]	]	PUNCT
admet-2772	1076	5	x.	x.	PROPN
admet-2772	1076	6	ma	ma	PROPN
admet-2772	1076	7	,	,	PUNCT
admet-2772	1076	8	r.	r.	PROPN
admet-2772	1076	9	wang	wang	PROPN
admet-2772	1076	10	,	,	PUNCT
admet-2772	1076	11	y.	y.	PROPN
admet-2772	1076	12	xue	xue	PROPN
admet-2772	1076	13	,	,	PUNCT
admet-2772	1076	14	z.	z.	PROPN
admet-2772	1076	15	li	li	PROPN
admet-2772	1076	16	,	,	PUNCT
admet-2772	1076	17	s.	s.	PROPN
admet-2772	1076	18	yang	yang	PROPN
admet-2772	1076	19	,	,	PUNCT
admet-2772	1076	20	y.	y.	PROPN
admet-2772	1076	21	wei	wei	PROPN
admet-2772	1076	22	,	,	PUNCT
admet-2772	1076	23	y.	y.	PROPN
admet-2772	1076	24	chen	chen	PROPN
admet-2772	1076	25	.	.	PUNCT
admet-2772	1077	1	advances	advance	NOUN
admet-2772	1077	2	in	in	ADP
admet-2772	1077	3	machine	machine	NOUN
admet-2772	1077	4	learning	learn	VERB
admet-2772	1077	5	prediction	prediction	NOUN
admet-2772	1077	6	of	of	ADP
admet-2772	1077	7	toxicological	toxicological	ADJ
admet-2772	1077	8	properties	property	NOUN
admet-2772	1077	9	and	and	CCONJ
admet-2772	1077	10	adverse	adverse	ADJ
admet-2772	1077	11	drug	drug	NOUN
admet-2772	1077	12	reactions	reaction	NOUN
admet-2772	1077	13	of	of	ADP
admet-2772	1077	14	pharmaceutical	pharmaceutical	ADJ
admet-2772	1077	15	agents	agent	NOUN
admet-2772	1077	16	.	.	PUNCT
admet-2772	1078	1	current	current	ADJ
admet-2772	1078	2	drug	drug	NOUN
admet-2772	1078	3	safety	safety	NOUN
admet-2772	1078	4	3	3	NUM
admet-2772	1078	5	(	(	PUNCT
admet-2772	1078	6	2008	2008	NUM
admet-2772	1078	7	)	)	PUNCT
admet-2772	1078	8	100	100	NUM
admet-2772	1078	9	-	-	SYM
admet-2772	1078	10	114	114	NUM
admet-2772	1078	11	.	.	PUNCT
admet-2772	1079	1	https://doi.org/10.2174/157488608784529224	https://doi.org/10.2174/157488608784529224	X
admet-2772	1080	1	[	[	X
admet-2772	1080	2	119	119	NUM
admet-2772	1080	3	]	]	X
admet-2772	1080	4	n.	n.	NOUN
admet-2772	1080	5	madhukar	madhukar	PROPN
admet-2772	1080	6	,	,	PUNCT
admet-2772	1080	7	k.	k.	PROPN
admet-2772	1080	8	gayvert	gayvert	PROPN
admet-2772	1080	9	,	,	PUNCT
admet-2772	1080	10	c.	c.	PROPN
admet-2772	1080	11	gilvary	gilvary	NOUN
admet-2772	1080	12	,	,	PUNCT
admet-2772	1080	13	o.	o.	PROPN
admet-2772	1080	14	elemento	elemento	PROPN
admet-2772	1080	15	.	.	PUNCT
admet-2772	1081	1	a	a	DET
admet-2772	1081	2	machine	machine	NOUN
admet-2772	1081	3	learning	learn	VERB
admet-2772	1081	4	approach	approach	NOUN
admet-2772	1081	5	predicts	predict	VERB
admet-2772	1081	6	tissuespecific	tissuespecific	NOUN
admet-2772	1081	7	drug	drug	NOUN
admet-2772	1081	8	adverse	adverse	ADJ
admet-2772	1081	9	events	event	NOUN
admet-2772	1081	10	.	.	PUNCT
admet-2772	1082	1	biorxiv	biorxiv	NOUN
admet-2772	1082	2	(	(	PUNCT
admet-2772	1082	3	2018	2018	NUM
admet-2772	1082	4	)	)	PUNCT
admet-2772	1082	5	.	.	PUNCT
admet-2772	1083	1	https://doi.org/10.1101/288332	https://doi.org/10.1101/288332	PROPN
admet-2772	1084	1	[	[	X
admet-2772	1084	2	120	120	NUM
admet-2772	1084	3	]	]	X
admet-2772	1084	4	d.	d.	PROPN
admet-2772	1084	5	naga	naga	PROPN
admet-2772	1084	6	,	,	PUNCT
admet-2772	1084	7	w.	w.	PROPN
admet-2772	1084	8	muster	muster	PROPN
admet-2772	1084	9	,	,	PUNCT
admet-2772	1084	10	e.	e.	PROPN
admet-2772	1084	11	musvasva	musvasva	PROPN
admet-2772	1084	12	,	,	PUNCT
admet-2772	1084	13	g.f	g.f	PROPN
admet-2772	1084	14	.	.	PROPN
admet-2772	1084	15	ecker	ecker	PROPN
admet-2772	1084	16	.	.	PUNCT
admet-2772	1085	1	off	off	ADP
admet-2772	1085	2	-	-	PUNCT
admet-2772	1085	3	targetp	targetp	NOUN
admet-2772	1085	4	ml	ml	ADP
admet-2772	1085	5	:	:	PUNCT
admet-2772	1085	6	an	an	DET
admet-2772	1085	7	open	open	ADJ
admet-2772	1085	8	source	source	NOUN
admet-2772	1085	9	machine	machine	NOUN
admet-2772	1085	10	learning	learn	VERB
admet-2772	1085	11	framework	framework	NOUN
admet-2772	1085	12	for	for	ADP
admet-2772	1085	13	off	off	ADP
admet-2772	1085	14	-	-	PUNCT
admet-2772	1085	15	target	target	NOUN
admet-2772	1085	16	panel	panel	NOUN
admet-2772	1085	17	safety	safety	NOUN
admet-2772	1085	18	assessment	assessment	NOUN
admet-2772	1085	19	of	of	ADP
admet-2772	1085	20	small	small	ADJ
admet-2772	1085	21	molecules	molecule	NOUN
admet-2772	1085	22	.	.	PUNCT
admet-2772	1086	1	journal	journal	PROPN
admet-2772	1086	2	of	of	ADP
admet-2772	1086	3	cheminformatics	cheminformatics	PROPN
admet-2772	1086	4	14	14	NUM
admet-2772	1086	5	(	(	PUNCT
admet-2772	1086	6	2022	2022	NUM
admet-2772	1086	7	)	)	PUNCT
admet-2772	1086	8	27	27	NUM
admet-2772	1086	9	.	.	PUNCT
admet-2772	1087	1	https://doi.org/10.1186/s13321-022-00603-w	https://doi.org/10.1186/s13321-022-00603-w	NOUN
admet-2772	1087	2	[	[	X
admet-2772	1087	3	121	121	NUM
admet-2772	1087	4	]	]	PUNCT
admet-2772	1087	5	l.	l.	PROPN
admet-2772	1087	6	tonoyan	tonoyan	PROPN
admet-2772	1087	7	,	,	PUNCT
admet-2772	1087	8	a.g	a.g	PROPN
admet-2772	1087	9	.	.	PROPN
admet-2772	1087	10	siraki	siraki	PROPN
admet-2772	1087	11	.	.	PUNCT
admet-2772	1088	1	machine	machine	NOUN
admet-2772	1088	2	learning	learn	VERB
admet-2772	1088	3	in	in	ADP
admet-2772	1088	4	toxicological	toxicological	ADJ
admet-2772	1088	5	sciences	science	NOUN
admet-2772	1088	6	:	:	PUNCT
admet-2772	1088	7	opportunities	opportunity	NOUN
admet-2772	1088	8	for	for	ADP
admet-2772	1088	9	assessing	assess	VERB
admet-2772	1088	10	drug	drug	NOUN
admet-2772	1088	11	toxicity	toxicity	NOUN
admet-2772	1088	12	.	.	PUNCT
admet-2772	1089	1	frontiers	frontier	NOUN
admet-2772	1089	2	in	in	ADP
admet-2772	1089	3	drug	drug	NOUN
admet-2772	1089	4	discovery	discovery	NOUN
admet-2772	1089	5	4	4	NUM
admet-2772	1089	6	(	(	PUNCT
admet-2772	1089	7	2024	2024	NUM
admet-2772	1089	8	)	)	PUNCT
admet-2772	1089	9	1336025	1336025	NUM
admet-2772	1089	10	.	.	PUNCT
admet-2772	1090	1	https://doi.org/10.3389/fddsv.2024.1336025	https://doi.org/10.3389/fddsv.2024.1336025	PROPN
admet-2772	1090	2	[	[	X
admet-2772	1090	3	122	122	NUM
admet-2772	1090	4	]	]	X
admet-2772	1090	5	s.	s.	PROPN
admet-2772	1090	6	okechukwuyem	okechukwuyem	VERB
admet-2772	1090	7	ojji	ojji	NOUN
admet-2772	1090	8	.	.	PUNCT
admet-2772	1091	1	emerging	emerge	VERB
admet-2772	1091	2	technology	technology	NOUN
admet-2772	1091	3	integration	integration	NOUN
admet-2772	1091	4	artificial	artificial	ADJ
admet-2772	1091	5	intelligence	intelligence	NOUN
admet-2772	1091	6	(	(	PUNCT
admet-2772	1091	7	ai	ai	NOUN
admet-2772	1091	8	)	)	PUNCT
admet-2772	1091	9	and	and	CCONJ
admet-2772	1091	10	machine	machine	NOUN
admet-2772	1091	11	learning	learning	NOUN
admet-2772	1091	12	(	(	PUNCT
admet-2772	1091	13	ml	ml	NOUN
admet-2772	1091	14	)	)	PUNCT
admet-2772	1091	15	for	for	ADP
admet-2772	1091	16	predictive	predictive	ADJ
admet-2772	1091	17	analysis	analysis	NOUN
admet-2772	1091	18	for	for	ADP
admet-2772	1091	19	safety	safety	NOUN
admet-2772	1091	20	and	and	CCONJ
admet-2772	1091	21	toxicity	toxicity	NOUN
admet-2772	1091	22	assessment	assessment	NOUN
admet-2772	1091	23	in	in	ADP
admet-2772	1091	24	environmental	environmental	ADJ
admet-2772	1091	25	toxicology	toxicology	NOUN
admet-2772	1091	26	.	.	PUNCT
admet-2772	1092	1	international	international	ADJ
admet-2772	1092	2	journal	journal	PROPN
admet-2772	1092	3	of	of	ADP
admet-2772	1092	4	scientific	scientific	ADJ
admet-2772	1092	5	research	research	NOUN
admet-2772	1092	6	and	and	CCONJ
admet-2772	1092	7	management	management	NOUN
admet-2772	1092	8	(	(	PUNCT
admet-2772	1092	9	ijsrm	ijsrm	PROPN
admet-2772	1092	10	)	)	PUNCT
admet-2772	1092	11	12	12	NUM
admet-2772	1092	12	(	(	PUNCT
admet-2772	1092	13	2024	2024	NUM
admet-2772	1092	14	)	)	PUNCT
admet-2772	1092	15	11821195	11821195	NUM
admet-2772	1092	16	.	.	PUNCT
admet-2772	1093	1	https://doi.org/10.18535/ijsrm/v12i05.ec03	https://doi.org/10.18535/ijsrm/v12i05.ec03	X
admet-2772	1094	1	[	[	X
admet-2772	1094	2	123	123	NUM
admet-2772	1094	3	]	]	PUNCT
admet-2772	1094	4	v.	v.	CCONJ
admet-2772	1094	5	blay	blay	PROPN
admet-2772	1094	6	,	,	PUNCT
admet-2772	1094	7	x.	x.	PROPN
admet-2772	1094	8	li	li	PROPN
admet-2772	1094	9	,	,	PUNCT
admet-2772	1094	10	j.	j.	PROPN
admet-2772	1094	11	gerlach	gerlach	PROPN
admet-2772	1094	12	,	,	PUNCT
admet-2772	1094	13	f.	f.	PROPN
admet-2772	1094	14	urbina	urbina	PROPN
admet-2772	1094	15	,	,	PUNCT
admet-2772	1094	16	s.	s.	PROPN
admet-2772	1094	17	ekins	ekin	NOUN
admet-2772	1094	18	.	.	PUNCT
admet-2772	1095	1	combining	combine	VERB
admet-2772	1095	2	dels	del	NOUN
admet-2772	1095	3	and	and	CCONJ
admet-2772	1095	4	machine	machine	NOUN
admet-2772	1095	5	learning	learn	VERB
admet-2772	1095	6	for	for	ADP
admet-2772	1095	7	toxicology	toxicology	NOUN
admet-2772	1095	8	prediction	prediction	NOUN
admet-2772	1095	9	.	.	PUNCT
admet-2772	1096	1	drug	drug	NOUN
admet-2772	1096	2	discovery	discovery	PROPN
admet-2772	1096	3	today	today	NOUN
admet-2772	1096	4	27	27	NUM
admet-2772	1096	5	(	(	PUNCT
admet-2772	1096	6	2022	2022	NUM
admet-2772	1096	7	)	)	PUNCT
admet-2772	1096	8	103351	103351	NUM
admet-2772	1096	9	.	.	PUNCT
admet-2772	1097	1	https://doi.org/10.1016/j.drudis.2022.103351	https://doi.org/10.1016/j.drudis.2022.103351	VERB
admet-2772	1098	1	[	[	X
admet-2772	1098	2	124	124	NUM
admet-2772	1098	3	]	]	PUNCT
admet-2772	1098	4	a.	a.	NOUN
admet-2772	1098	5	lavecchia	lavecchia	NOUN
admet-2772	1098	6	.	.	PUNCT
admet-2772	1099	1	deep	deep	ADJ
admet-2772	1099	2	learning	learning	NOUN
admet-2772	1099	3	in	in	ADP
admet-2772	1099	4	drug	drug	NOUN
admet-2772	1099	5	discovery	discovery	NOUN
admet-2772	1099	6	:	:	PUNCT
admet-2772	1099	7	opportunities	opportunity	NOUN
admet-2772	1099	8	,	,	PUNCT
admet-2772	1099	9	challenges	challenge	NOUN
admet-2772	1099	10	and	and	CCONJ
admet-2772	1099	11	future	future	ADJ
admet-2772	1099	12	prospects	prospect	NOUN
admet-2772	1099	13	.	.	PUNCT
admet-2772	1100	1	drug	drug	NOUN
admet-2772	1100	2	discovery	discovery	PROPN
admet-2772	1100	3	today	today	NOUN
admet-2772	1100	4	24	24	NUM
admet-2772	1100	5	(	(	PUNCT
admet-2772	1100	6	2019	2019	NUM
admet-2772	1100	7	)	)	PUNCT
admet-2772	1100	8	2017	2017	NUM
admet-2772	1100	9	-	-	SYM
admet-2772	1100	10	2032	2032	NUM
admet-2772	1100	11	.	.	PUNCT
admet-2772	1101	1	https://doi.org/10.1016/j.drudis.2019.07.006	https://doi.org/10.1016/j.drudis.2019.07.006	NOUN
admet-2772	1101	2	[	[	X
admet-2772	1101	3	125	125	NUM
admet-2772	1101	4	]	]	PUNCT
admet-2772	1101	5	h.	h.	PROPN
admet-2772	1101	6	chen	chen	PROPN
admet-2772	1101	7	,	,	PUNCT
admet-2772	1101	8	o.	o.	PROPN
admet-2772	1101	9	engkvist	engkvist	PROPN
admet-2772	1101	10	,	,	PUNCT
admet-2772	1101	11	y.	y.	PROPN
admet-2772	1101	12	wang	wang	PROPN
admet-2772	1101	13	,	,	PUNCT
admet-2772	1101	14	m.	m.	NOUN
admet-2772	1101	15	olivecrona	olivecrona	NOUN
admet-2772	1101	16	,	,	PUNCT
admet-2772	1101	17	t.	t.	PROPN
admet-2772	1101	18	blaschke	blaschke	PROPN
admet-2772	1101	19	.	.	PUNCT
admet-2772	1102	1	the	the	DET
admet-2772	1102	2	rise	rise	NOUN
admet-2772	1102	3	of	of	ADP
admet-2772	1102	4	deep	deep	ADJ
admet-2772	1102	5	learning	learning	NOUN
admet-2772	1102	6	in	in	ADP
admet-2772	1102	7	drug	drug	NOUN
admet-2772	1102	8	discovery	discovery	NOUN
admet-2772	1102	9	.	.	PUNCT
admet-2772	1103	1	drug	drug	NOUN
admet-2772	1103	2	discovery	discovery	PROPN
admet-2772	1103	3	today	today	NOUN
admet-2772	1103	4	23	23	NUM
admet-2772	1103	5	(	(	PUNCT
admet-2772	1103	6	2018	2018	NUM
admet-2772	1103	7	)	)	PUNCT
admet-2772	1103	8	1241	1241	NUM
admet-2772	1103	9	-	-	SYM
admet-2772	1103	10	1250	1250	NUM
admet-2772	1103	11	.	.	PUNCT
admet-2772	1104	1	https://doi.org/10.1016/j.drudis.2018.01.039	https://doi.org/10.1016/j.drudis.2018.01.039	NOUN
admet-2772	1104	2	[	[	X
admet-2772	1104	3	126	126	NUM
admet-2772	1104	4	]	]	X
admet-2772	1104	5	s.	s.	PROPN
admet-2772	1104	6	min	min	PROPN
admet-2772	1104	7	,	,	PUNCT
admet-2772	1104	8	b.	b.	PROPN
admet-2772	1104	9	lee	lee	PROPN
admet-2772	1104	10	,	,	PUNCT
admet-2772	1104	11	s.	s.	PROPN
admet-2772	1104	12	yoon	yoon	PROPN
admet-2772	1104	13	.	.	PUNCT
admet-2772	1105	1	deep	deep	ADJ
admet-2772	1105	2	learning	learning	NOUN
admet-2772	1105	3	in	in	ADP
admet-2772	1105	4	bioinformatics	bioinformatics	NOUN
admet-2772	1105	5	.	.	PUNCT
admet-2772	1106	1	briefings	briefing	NOUN
admet-2772	1106	2	in	in	ADP
admet-2772	1106	3	bioinformatics	bioinformatics	NOUN
admet-2772	1106	4	18	18	NUM
admet-2772	1106	5	(	(	PUNCT
admet-2772	1106	6	2017	2017	NUM
admet-2772	1106	7	)	)	PUNCT
admet-2772	1106	8	851869	851869	NUM
admet-2772	1106	9	.	.	PUNCT
admet-2772	1107	1	https://doi.org/10.1093/bib/bbw068	https://doi.org/10.1093/bib/bbw068	PROPN
admet-2772	1107	2	[	[	PUNCT
admet-2772	1107	3	127	127	NUM
admet-2772	1107	4	]	]	X
admet-2772	1107	5	h.	h.	PROPN
admet-2772	1107	6	belyadi	belyadi	PROPN
admet-2772	1107	7	,	,	PUNCT
admet-2772	1107	8	a.	a.	NOUN
admet-2772	1107	9	haghighat	haghighat	PROPN
admet-2772	1107	10	.	.	PUNCT
admet-2772	1108	1	supervised	supervised	ADJ
admet-2772	1108	2	learning	learning	NOUN
admet-2772	1108	3	.	.	PUNCT
admet-2772	1109	1	machine	machine	NOUN
admet-2772	1109	2	learning	learn	VERB
admet-2772	1109	3	guide	guide	NOUN
admet-2772	1109	4	for	for	ADP
admet-2772	1109	5	oil	oil	NOUN
admet-2772	1109	6	and	and	CCONJ
admet-2772	1109	7	gas	gas	NOUN
admet-2772	1109	8	using	use	VERB
admet-2772	1109	9	python	python	NOUN
admet-2772	1109	10	(	(	PUNCT
admet-2772	1109	11	2021	2021	NUM
admet-2772	1109	12	)	)	PUNCT
admet-2772	1109	13	169	169	NUM
admet-2772	1109	14	-	-	SYM
admet-2772	1109	15	295	295	NUM
admet-2772	1109	16	.	.	PUNCT
admet-2772	1110	1	https://doi.org/10.1016/b978-0-12-821929-4.00004-4	https://doi.org/10.1016/b978-0-12-821929-4.00004-4	PRON
admet-2772	1111	1	[	[	X
admet-2772	1111	2	128	128	NUM
admet-2772	1111	3	]	]	X
admet-2772	1111	4	i.v.d	i.v.d	PROPN
admet-2772	1111	5	.	.	PROPN
admet-2772	1111	6	srihith	srihith	PROPN
admet-2772	1111	7	,	,	PUNCT
admet-2772	1111	8	p.v	p.v	PROPN
admet-2772	1111	9	.	.	PROPN
admet-2772	1111	10	lakshmi	lakshmi	PROPN
admet-2772	1111	11	,	,	PUNCT
admet-2772	1111	12	a.d	a.d	PROPN
admet-2772	1111	13	.	.	PROPN
admet-2772	1111	14	donald	donald	PROPN
admet-2772	1111	15	,	,	PUNCT
admet-2772	1111	16	t.	t.	PROPN
admet-2772	1111	17	aditya	aditya	PROPN
admet-2772	1111	18	,	,	PUNCT
admet-2772	1111	19	t.a.s	t.a.s	PROPN
admet-2772	1111	20	.	.	PUNCT
admet-2772	1111	21	srinivas	srinivas	PROPN
admet-2772	1111	22	,	,	PUNCT
admet-2772	1111	23	g.	g.	PROPN
admet-2772	1111	24	thippanna	thippanna	PROPN
admet-2772	1111	25	.	.	PUNCT
admet-2772	1112	1	a	a	DET
admet-2772	1112	2	forest	forest	NOUN
admet-2772	1112	3	of	of	ADP
admet-2772	1112	4	possibilities	possibility	NOUN
admet-2772	1112	5	:	:	PUNCT
admet-2772	1112	6	decision	decision	NOUN
admet-2772	1112	7	trees	tree	NOUN
admet-2772	1112	8	and	and	CCONJ
admet-2772	1112	9	beyond	beyond	ADP
admet-2772	1112	10	.	.	PUNCT
admet-2772	1113	1	harb	harb	PROPN
admet-2772	1113	2	publication	publication	NOUN
admet-2772	1113	3	6	6	NUM
admet-2772	1113	4	(	(	PUNCT
admet-2772	1113	5	2023	2023	NUM
admet-2772	1113	6	)	)	PUNCT
admet-2772	1113	7	29	29	NUM
admet-2772	1113	8	-	-	SYM
admet-2772	1113	9	37	37	NUM
admet-2772	1113	10	.	.	PUNCT
admet-2772	1113	11	http://dx.doi.org/10.5281/zenodo.8372196	http://dx.doi.org/10.5281/zenodo.8372196	PROPN
admet-2772	1114	1	[	[	X
admet-2772	1114	2	129	129	NUM
admet-2772	1114	3	]	]	X
admet-2772	1114	4	d.s	d.s	PROPN
admet-2772	1114	5	.	.	PROPN
admet-2772	1114	6	palmer	palmer	PROPN
admet-2772	1114	7	,	,	PUNCT
admet-2772	1114	8	n.m	n.m	PROPN
admet-2772	1114	9	.	.	PROPN
admet-2772	1114	10	o’boyle	o’boyle	PROPN
admet-2772	1114	11	,	,	PUNCT
admet-2772	1114	12	r.c	r.c	PROPN
admet-2772	1114	13	.	.	PROPN
admet-2772	1114	14	glen	glen	PROPN
admet-2772	1114	15	,	,	PUNCT
admet-2772	1114	16	j.b.o	j.b.o	PROPN
admet-2772	1114	17	.	.	PROPN
admet-2772	1114	18	mitchell	mitchell	PROPN
admet-2772	1114	19	.	.	PUNCT
admet-2772	1115	1	random	random	ADJ
admet-2772	1115	2	forest	forest	NOUN
admet-2772	1115	3	models	model	NOUN
admet-2772	1115	4	to	to	PART
admet-2772	1115	5	predict	predict	VERB
admet-2772	1115	6	aqueous	aqueous	ADJ
admet-2772	1115	7	solubility	solubility	NOUN
admet-2772	1115	8	.	.	PUNCT
admet-2772	1116	1	journal	journal	PROPN
admet-2772	1116	2	of	of	ADP
admet-2772	1116	3	chemical	chemical	ADJ
admet-2772	1116	4	information	information	NOUN
admet-2772	1116	5	and	and	CCONJ
admet-2772	1116	6	modeling	model	VERB
admet-2772	1116	7	47	47	NUM
admet-2772	1116	8	(	(	PUNCT
admet-2772	1116	9	2007	2007	NUM
admet-2772	1116	10	)	)	PUNCT
admet-2772	1116	11	150	150	NUM
admet-2772	1116	12	-	-	SYM
admet-2772	1116	13	158	158	NUM
admet-2772	1116	14	.	.	PUNCT
admet-2772	1117	1	https://doi.org/10.1021/ci060164k	https://doi.org/10.1021/ci060164k	X
admet-2772	1118	1	[	[	X
admet-2772	1118	2	130	130	NUM
admet-2772	1118	3	]	]	X
admet-2772	1118	4	d.s	d.s	PROPN
admet-2772	1118	5	.	.	PROPN
admet-2772	1118	6	cao	cao	PROPN
admet-2772	1118	7	,	,	PUNCT
admet-2772	1118	8	y.n	y.n	PROPN
admet-2772	1118	9	.	.	PROPN
admet-2772	1118	10	yang	yang	PROPN
admet-2772	1118	11	,	,	PUNCT
admet-2772	1118	12	j.c	j.c	PROPN
admet-2772	1118	13	.	.	PROPN
admet-2772	1118	14	zhao	zhao	PROPN
admet-2772	1118	15	,	,	PUNCT
admet-2772	1118	16	j.	j.	PROPN
admet-2772	1118	17	yan	yan	PROPN
admet-2772	1118	18	,	,	PUNCT
admet-2772	1118	19	s.	s.	PROPN
admet-2772	1118	20	liu	liu	PROPN
admet-2772	1118	21	,	,	PUNCT
admet-2772	1118	22	q.n	q.n	PROPN
admet-2772	1118	23	.	.	PROPN
admet-2772	1118	24	hu	hu	PROPN
admet-2772	1118	25	,	,	PUNCT
admet-2772	1118	26	q.s	q.s	PROPN
admet-2772	1118	27	.	.	PROPN
admet-2772	1118	28	xu	xu	PROPN
admet-2772	1118	29	,	,	PUNCT
admet-2772	1118	30	y.z	y.z	PROPN
admet-2772	1118	31	.	.	PROPN
admet-2772	1118	32	liang	liang	PROPN
admet-2772	1118	33	.	.	PUNCT
admet-2772	1119	1	computer	computer	NOUN
admet-2772	1119	2	-	-	PUNCT
admet-2772	1119	3	aided	aid	VERB
admet-2772	1119	4	prediction	prediction	NOUN
admet-2772	1119	5	of	of	ADP
admet-2772	1119	6	toxicity	toxicity	NOUN
admet-2772	1119	7	with	with	ADP
admet-2772	1119	8	substructure	substructure	NOUN
admet-2772	1119	9	pattern	pattern	NOUN
admet-2772	1119	10	and	and	CCONJ
admet-2772	1119	11	random	random	ADJ
admet-2772	1119	12	forest	forest	NOUN
admet-2772	1119	13	.	.	PUNCT
admet-2772	1120	1	journal	journal	PROPN
admet-2772	1120	2	of	of	ADP
admet-2772	1120	3	chemometrics	chemometric	NOUN
admet-2772	1120	4	26	26	NUM
admet-2772	1120	5	(	(	PUNCT
admet-2772	1120	6	2012	2012	NUM
admet-2772	1120	7	)	)	PUNCT
admet-2772	1120	8	7	7	NUM
admet-2772	1120	9	-	-	SYM
admet-2772	1120	10	15	15	NUM
admet-2772	1120	11	.	.	PUNCT
admet-2772	1121	1	https://doi.org/10.1002/cem.1416	https://doi.org/10.1002/cem.1416	NOUN
admet-2772	1121	2	[	[	SYM
admet-2772	1121	3	131	131	NUM
admet-2772	1121	4	]	]	X
admet-2772	1121	5	d.s	d.s	PROPN
admet-2772	1121	6	.	.	PROPN
admet-2772	1121	7	cao	cao	PROPN
admet-2772	1121	8	,	,	PUNCT
admet-2772	1121	9	q.n	q.n	PROPN
admet-2772	1121	10	.	.	PROPN
admet-2772	1121	11	hu	hu	PROPN
admet-2772	1121	12	,	,	PUNCT
admet-2772	1121	13	q.s	q.s	PROPN
admet-2772	1121	14	.	.	PROPN
admet-2772	1121	15	xu	xu	PROPN
admet-2772	1121	16	,	,	PUNCT
admet-2772	1121	17	y.n	y.n	PROPN
admet-2772	1121	18	.	.	PROPN
admet-2772	1121	19	yang	yang	PROPN
admet-2772	1121	20	,	,	PUNCT
admet-2772	1121	21	j.c	j.c	PROPN
admet-2772	1121	22	.	.	PROPN
admet-2772	1121	23	zhao	zhao	PROPN
admet-2772	1121	24	,	,	PUNCT
admet-2772	1121	25	h.m	h.m	PROPN
admet-2772	1121	26	.	.	PROPN
admet-2772	1121	27	lu	lu	PROPN
admet-2772	1121	28	,	,	PUNCT
admet-2772	1121	29	l.x	l.x	PROPN
admet-2772	1121	30	.	.	PROPN
admet-2772	1122	1	zhang	zhang	PROPN
admet-2772	1122	2	,	,	PUNCT
admet-2772	1122	3	y.z	y.z	PROPN
admet-2772	1122	4	.	.	PROPN
admet-2772	1122	5	liang	liang	PROPN
admet-2772	1122	6	.	.	PUNCT
admet-2772	1123	1	in	in	ADP
admet-2772	1123	2	silico	silico	NOUN
admet-2772	1123	3	classification	classification	NOUN
admet-2772	1123	4	of	of	ADP
admet-2772	1123	5	human	human	ADJ
admet-2772	1123	6	maximum	maximum	ADJ
admet-2772	1123	7	recommended	recommend	VERB
admet-2772	1123	8	daily	daily	ADJ
admet-2772	1123	9	dose	dose	NOUN
admet-2772	1123	10	based	base	VERB
admet-2772	1123	11	on	on	ADP
admet-2772	1123	12	modified	modify	VERB
admet-2772	1123	13	random	random	ADJ
admet-2772	1123	14	forest	forest	NOUN
admet-2772	1123	15	and	and	CCONJ
admet-2772	1123	16	substructure	substructure	NOUN
admet-2772	1123	17	fingerprint	fingerprint	NOUN
admet-2772	1123	18	.	.	PUNCT
admet-2772	1124	1	analytica	analytica	PROPN
admet-2772	1124	2	chimica	chimica	PROPN
admet-2772	1124	3	acta	acta	PROPN
admet-2772	1124	4	692	692	NUM
admet-2772	1124	5	(	(	PUNCT
admet-2772	1124	6	2011	2011	NUM
admet-2772	1124	7	)	)	PUNCT
admet-2772	1124	8	50	50	NUM
admet-2772	1124	9	-	-	SYM
admet-2772	1124	10	56	56	NUM
admet-2772	1124	11	.	.	PUNCT
admet-2772	1125	1	https://doi.org/10.1016/j.aca.2011.02.010	https://doi.org/10.1016/j.aca.2011.02.010	NOUN
admet-2772	1126	1	[	[	X
admet-2772	1126	2	132	132	NUM
admet-2772	1126	3	]	]	X
admet-2772	1126	4	y.	y.	NOUN
admet-2772	1126	5	uesawa	uesawa	PROPN
admet-2772	1126	6	.	.	PUNCT
admet-2772	1127	1	rigorous	rigorous	ADJ
admet-2772	1127	2	selection	selection	NOUN
admet-2772	1127	3	of	of	ADP
admet-2772	1127	4	random	random	ADJ
admet-2772	1127	5	forest	forest	NOUN
admet-2772	1127	6	models	model	NOUN
admet-2772	1127	7	for	for	ADP
admet-2772	1127	8	identifying	identify	VERB
admet-2772	1127	9	compounds	compound	NOUN
admet-2772	1127	10	that	that	PRON
admet-2772	1127	11	activate	activate	VERB
admet-2772	1127	12	toxicity	toxicity	NOUN
admet-2772	1127	13	-	-	PUNCT
admet-2772	1127	14	related	relate	VERB
admet-2772	1127	15	pathways	pathway	NOUN
admet-2772	1127	16	.	.	PUNCT
admet-2772	1128	1	frontiers	frontier	NOUN
admet-2772	1128	2	in	in	ADP
admet-2772	1128	3	environmental	environmental	ADJ
admet-2772	1128	4	science	science	NOUN
admet-2772	1128	5	4	4	NUM
admet-2772	1128	6	(	(	PUNCT
admet-2772	1128	7	2016	2016	NUM
admet-2772	1128	8	)	)	PUNCT
admet-2772	1128	9	9	9	NUM
admet-2772	1128	10	.	.	PUNCT
admet-2772	1129	1	https://doi.org/10.3389/fenvs.2016.00009	https://doi.org/10.3389/fenvs.2016.00009	NOUN
admet-2772	1129	2	[	[	X
admet-2772	1129	3	133	133	NUM
admet-2772	1129	4	]	]	X
admet-2772	1129	5	m.m	m.m	PROPN
admet-2772	1129	6	.	.	PROPN
admet-2772	1129	7	suprijono	suprijono	PROPN
admet-2772	1129	8	,	,	PUNCT
admet-2772	1129	9	h.	h.	PROPN
admet-2772	1129	10	sujuti	sujuti	PROPN
admet-2772	1129	11	,	,	PUNCT
admet-2772	1129	12	d.	d.	PROPN
admet-2772	1129	13	kurnia	kurnia	PROPN
admet-2772	1129	14	,	,	PUNCT
admet-2772	1129	15	s.b	s.b	PROPN
admet-2772	1129	16	.	.	PROPN
admet-2772	1129	17	widjanarko	widjanarko	PROPN
admet-2772	1129	18	.	.	PUNCT
admet-2772	1130	1	absorption	absorption	NOUN
admet-2772	1130	2	,	,	PUNCT
admet-2772	1130	3	distribution	distribution	NOUN
admet-2772	1130	4	,	,	PUNCT
admet-2772	1130	5	metabolism	metabolism	NOUN
admet-2772	1130	6	,	,	PUNCT
admet-2772	1130	7	excretion	excretion	NOUN
admet-2772	1130	8	,	,	PUNCT
admet-2772	1130	9	and	and	CCONJ
admet-2772	1130	10	toxicity	toxicity	NOUN
admet-2772	1130	11	evaluation	evaluation	NOUN
admet-2772	1130	12	of	of	ADP
admet-2772	1130	13	papua	papua	PROPN
admet-2772	1130	14	red	red	ADJ
admet-2772	1130	15	fruit	fruit	NOUN
admet-2772	1130	16	flavonoids	flavonoid	NOUN
admet-2772	1130	17	through	through	ADP
admet-2772	1130	18	a	a	DET
admet-2772	1130	19	computational	computational	ADJ
admet-2772	1130	20	study	study	NOUN
admet-2772	1130	21	.	.	PUNCT
admet-2772	1131	1	in	in	ADP
admet-2772	1131	2	:	:	PUNCT
admet-2772	1131	3	https://doi.org/10.1021/acs.jcim.2c00822	https://doi.org/10.1021/acs.jcim.2c00822	NOUN
admet-2772	1131	4	https://doi.org/10.1002/em.22648	https://doi.org/10.1002/em.22648	PROPN
admet-2772	1131	5	https://doi.org/10.1021/acsomega.2c05693	https://doi.org/10.1021/acsomega.2c05693	VERB
admet-2772	1131	6	https://doi.org/10.2174/157488608784529224	https://doi.org/10.2174/157488608784529224	X
admet-2772	1131	7	https://doi.org/10.1101/288332	https://doi.org/10.1101/288332	PROPN
admet-2772	1131	8	https://doi.org/10.1186/s13321-022-00603-w	https://doi.org/10.1186/s13321-022-00603-w	NOUN
admet-2772	1131	9	https://doi.org/10.3389/fddsv.2024.1336025	https://doi.org/10.3389/fddsv.2024.1336025	PROPN
admet-2772	1131	10	https://doi.org/10.18535/ijsrm/v12i05.ec03	https://doi.org/10.18535/ijsrm/v12i05.ec03	X
admet-2772	1131	11	https://doi.org/10.1016/j.drudis.2022.103351	https://doi.org/10.1016/j.drudis.2022.103351	VERB
admet-2772	1131	12	https://doi.org/10.1016/j.drudis.2019.07.006	https://doi.org/10.1016/j.drudis.2019.07.006	ADJ
admet-2772	1131	13	https://doi.org/10.1016/j.drudis.2018.01.039	https://doi.org/10.1016/j.drudis.2018.01.039	NOUN
admet-2772	1131	14	https://doi.org/10.1093/bib/bbw068	https://doi.org/10.1093/bib/bbw068	VERB
admet-2772	1131	15	https://doi.org/10.1016/b978-0-12-821929-4.00004-4	https://doi.org/10.1016/b978-0-12-821929-4.00004-4	PROPN
admet-2772	1131	16	http://dx.doi.org/10.5281/zenodo.8372196	http://dx.doi.org/10.5281/zenodo.8372196	PROPN
admet-2772	1131	17	https://doi.org/10.1021/ci060164k	https://doi.org/10.1021/ci060164k	X
admet-2772	1131	18	https://doi.org/10.1002/cem.1416	https://doi.org/10.1002/cem.1416	PROPN
admet-2772	1131	19	https://doi.org/10.1016/j.aca.2011.02.010	https://doi.org/10.1016/j.aca.2011.02.010	NOUN
admet-2772	1131	20	https://doi.org/10.3389/fenvs.2016.00009	https://doi.org/10.3389/fenvs.2016.00009	PROPN
admet-2772	1131	21	admet	admet	PROPN
admet-2772	1131	22	&	&	CCONJ
admet-2772	1131	23	dmpk	dmpk	PROPN
admet-2772	1131	24	13(3	13(3	NUM
admet-2772	1131	25	)	)	PUNCT
admet-2772	1131	26	(	(	PUNCT
admet-2772	1131	27	2025	2025	NUM
admet-2772	1131	28	)	)	PUNCT
admet-2772	1131	29	2772	2772	NUM
admet-2772	1131	30	machine	machine	NOUN
admet-2772	1131	31	learning	learning	NOUN
admet-2772	1131	32	models	model	NOUN
admet-2772	1131	33	for	for	ADP
admet-2772	1131	34	admet	admet	ADJ
admet-2772	1131	35	prediction	prediction	NOUN
admet-2772	1131	36	in	in	ADP
admet-2772	1131	37	drug	drug	NOUN
admet-2772	1131	38	development	development	NOUN
admet-2772	1131	39	doi	doi	PROPN
admet-2772	1131	40	:	:	PUNCT
admet-2772	1131	41	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	X
admet-2772	1131	42	33	33	NUM
admet-2772	1131	43	iop	iop	PROPN
admet-2772	1131	44	conf	conf	NOUN
admet-2772	1131	45	.	.	PUNCT
admet-2772	1132	1	ser	ser	PROPN
admet-2772	1132	2	.	.	PROPN
admet-2772	1132	3	earth	earth	PROPN
admet-2772	1132	4	environ	environ	PROPN
admet-2772	1132	5	.	.	PUNCT
admet-2772	1133	1	sci	sci	PROPN
admet-2772	1133	2	.	.	PROPN
admet-2772	1133	3	,	,	PUNCT
admet-2772	1133	4	iop	iop	PROPN
admet-2772	1133	5	science	science	PROPN
admet-2772	1133	6	,	,	PUNCT
admet-2772	1133	7	malang	malang	PROPN
admet-2772	1133	8	east	east	PROPN
admet-2772	1133	9	java	java	PROPN
admet-2772	1133	10	indonesia	indonesia	PROPN
admet-2772	1133	11	,	,	PUNCT
admet-2772	1133	12	(	(	PUNCT
admet-2772	1133	13	2020	2020	NUM
admet-2772	1133	14	)	)	PUNCT
admet-2772	1133	15	https://doi.org/10.1088/1755-1315/475/1/012078	https://doi.org/10.1088/1755-1315/475/1/012078	NOUN
admet-2772	1133	16	[	[	X
admet-2772	1133	17	134	134	NUM
admet-2772	1133	18	]	]	X
admet-2772	1133	19	m.n	m.n	PROPN
admet-2772	1133	20	.	.	PROPN
admet-2772	1133	21	murty	murty	PROPN
admet-2772	1133	22	,	,	PUNCT
admet-2772	1133	23	r.	r.	PROPN
admet-2772	1133	24	raghava	raghava	PROPN
admet-2772	1133	25	.	.	PUNCT
admet-2772	1133	26	kernel	kernel	NOUN
admet-2772	1133	27	-	-	PUNCT
admet-2772	1133	28	based	base	VERB
admet-2772	1133	29	svm	svm	PROPN
admet-2772	1133	30	.	.	PROPN
admet-2772	1133	31	springerbriefs	springerbrief	NOUN
admet-2772	1133	32	in	in	ADP
admet-2772	1133	33	computer	computer	NOUN
admet-2772	1133	34	science	science	NOUN
admet-2772	1133	35	0	0	NUM
admet-2772	1133	36	(	(	PUNCT
admet-2772	1133	37	2016	2016	NUM
admet-2772	1133	38	)	)	PUNCT
admet-2772	1133	39	57	57	NUM
admet-2772	1133	40	-	-	SYM
admet-2772	1133	41	67	67	NUM
admet-2772	1133	42	.	.	PUNCT
admet-2772	1134	1	https://doi.org/10.1007/978-3-319-41063-0_5	https://doi.org/10.1007/978-3-319-41063-0_5	X
admet-2772	1135	1	[	[	X
admet-2772	1135	2	135	135	NUM
admet-2772	1135	3	]	]	X
admet-2772	1135	4	m.w.b	m.w.b	PROPN
admet-2772	1135	5	.	.	PROPN
admet-2772	1135	6	trotter	trotter	PROPN
admet-2772	1135	7	,	,	PUNCT
admet-2772	1135	8	s.b	s.b	PROPN
admet-2772	1135	9	.	.	PROPN
admet-2772	1135	10	holden	holden	PROPN
admet-2772	1135	11	.	.	PUNCT
admet-2772	1136	1	support	support	NOUN
admet-2772	1136	2	vector	vector	NOUN
admet-2772	1136	3	machines	machine	NOUN
admet-2772	1136	4	for	for	ADP
admet-2772	1136	5	adme	adme	NOUN
admet-2772	1136	6	property	property	NOUN
admet-2772	1136	7	classification	classification	NOUN
admet-2772	1136	8	.	.	PUNCT
admet-2772	1137	1	qsar	qsar	NOUN
admet-2772	1137	2	and	and	CCONJ
admet-2772	1137	3	combinatorial	combinatorial	ADJ
admet-2772	1137	4	science	science	NOUN
admet-2772	1137	5	22	22	NUM
admet-2772	1137	6	(	(	PUNCT
admet-2772	1137	7	2003	2003	NUM
admet-2772	1137	8	)	)	PUNCT
admet-2772	1137	9	533	533	NUM
admet-2772	1137	10	-	-	SYM
admet-2772	1137	11	548	548	NUM
admet-2772	1137	12	.	.	PUNCT
admet-2772	1138	1	https://doi.org/10.1002/qsar.200310006	https://doi.org/10.1002/qsar.200310006	ADJ
admet-2772	1138	2	[	[	X
admet-2772	1138	3	136	136	NUM
admet-2772	1138	4	]	]	PUNCT
admet-2772	1138	5	j.	j.	PROPN
admet-2772	1138	6	gola	gola	PROPN
admet-2772	1138	7	,	,	PUNCT
admet-2772	1138	8	o.	o.	PROPN
admet-2772	1138	9	obrezanova	obrezanova	PROPN
admet-2772	1138	10	,	,	PUNCT
admet-2772	1138	11	e.	e.	PROPN
admet-2772	1138	12	champness	champness	PROPN
admet-2772	1138	13	,	,	PUNCT
admet-2772	1138	14	m.	m.	PROPN
admet-2772	1138	15	segall	segall	PROPN
admet-2772	1138	16	.	.	PUNCT
admet-2772	1139	1	admet	admet	PROPN
admet-2772	1139	2	property	property	PROPN
admet-2772	1139	3	prediction	prediction	NOUN
admet-2772	1139	4	:	:	PUNCT
admet-2772	1139	5	the	the	DET
admet-2772	1139	6	state	state	NOUN
admet-2772	1139	7	of	of	ADP
admet-2772	1139	8	the	the	DET
admet-2772	1139	9	art	art	NOUN
admet-2772	1139	10	and	and	CCONJ
admet-2772	1139	11	current	current	ADJ
admet-2772	1139	12	challenges	challenge	NOUN
admet-2772	1139	13	.	.	PUNCT
admet-2772	1140	1	qsar	qsar	NOUN
admet-2772	1140	2	and	and	CCONJ
admet-2772	1140	3	combinatorial	combinatorial	ADJ
admet-2772	1140	4	science	science	NOUN
admet-2772	1140	5	25	25	NUM
admet-2772	1140	6	(	(	PUNCT
admet-2772	1140	7	2006	2006	NUM
admet-2772	1140	8	)	)	PUNCT
admet-2772	1140	9	1172	1172	NUM
admet-2772	1140	10	-	-	SYM
admet-2772	1140	11	1180	1180	NUM
admet-2772	1140	12	.	.	PUNCT
admet-2772	1141	1	https://doi.org/10.1002/qsar.200610093	https://doi.org/10.1002/qsar.200610093	PROPN
admet-2772	1142	1	[	[	X
admet-2772	1142	2	137	137	NUM
admet-2772	1142	3	]	]	X
admet-2772	1142	4	y.	y.	PROPN
admet-2772	1142	5	shi	shi	PROPN
admet-2772	1142	6	,	,	PUNCT
admet-2772	1142	7	k.	k.	PROPN
admet-2772	1142	8	yang	yang	PROPN
admet-2772	1142	9	,	,	PUNCT
admet-2772	1142	10	z.	z.	PROPN
admet-2772	1142	11	yang	yang	PROPN
admet-2772	1142	12	,	,	PUNCT
admet-2772	1142	13	y.	y.	PROPN
admet-2772	1142	14	zhou	zhou	PROPN
admet-2772	1142	15	.	.	PUNCT
admet-2772	1142	16	primer	primer	NOUN
admet-2772	1142	17	on	on	ADP
admet-2772	1142	18	artificial	artificial	ADJ
admet-2772	1142	19	intelligence	intelligence	NOUN
admet-2772	1142	20	.	.	PUNCT
admet-2772	1143	1	mobile	mobile	ADJ
admet-2772	1143	2	edge	edge	NOUN
admet-2772	1143	3	artificial	artificial	ADJ
admet-2772	1143	4	intelligence	intelligence	NOUN
admet-2772	1143	5	(	(	PUNCT
admet-2772	1143	6	2022	2022	NUM
admet-2772	1143	7	)	)	PUNCT
admet-2772	1143	8	7	7	NUM
admet-2772	1143	9	-	-	SYM
admet-2772	1143	10	36	36	NUM
admet-2772	1143	11	.	.	PUNCT
admet-2772	1144	1	https://doi.org/10.1016/b978-0-12-823817-2.00011-5	https://doi.org/10.1016/b978-0-12-823817-2.00011-5	NOUN
admet-2772	1145	1	[	[	X
admet-2772	1145	2	138	138	NUM
admet-2772	1145	3	]	]	X
admet-2772	1145	4	d.	d.	PROPN
admet-2772	1145	5	gadaleta	gadaleta	PROPN
admet-2772	1145	6	,	,	PUNCT
admet-2772	1145	7	f.	f.	PROPN
admet-2772	1145	8	pizzo	pizzo	PROPN
admet-2772	1145	9	,	,	PUNCT
admet-2772	1145	10	a.	a.	PROPN
admet-2772	1145	11	lombardo	lombardo	PROPN
admet-2772	1145	12	,	,	PUNCT
admet-2772	1145	13	a.	a.	NOUN
admet-2772	1145	14	carotti	carotti	PROPN
admet-2772	1145	15	,	,	PUNCT
admet-2772	1145	16	s.e	s.e	PROPN
admet-2772	1145	17	.	.	PROPN
admet-2772	1145	18	escher	escher	PROPN
admet-2772	1145	19	,	,	PUNCT
admet-2772	1145	20	o.	o.	PROPN
admet-2772	1145	21	nicolotti	nicolotti	PROPN
admet-2772	1145	22	,	,	PUNCT
admet-2772	1145	23	e.	e.	PROPN
admet-2772	1145	24	benfenati	benfenati	PROPN
admet-2772	1145	25	.	.	PUNCT
admet-2772	1146	1	a	a	DET
admet-2772	1146	2	k	k	PROPN
admet-2772	1146	3	-	-	PUNCT
admet-2772	1146	4	nn	nn	ADJ
admet-2772	1146	5	algorithm	algorithm	NOUN
admet-2772	1146	6	for	for	ADP
admet-2772	1146	7	predicting	predict	VERB
admet-2772	1146	8	oral	oral	ADJ
admet-2772	1146	9	sub	sub	ADJ
admet-2772	1146	10	-	-	ADJ
admet-2772	1146	11	chronic	chronic	ADJ
admet-2772	1146	12	toxicity	toxicity	NOUN
admet-2772	1146	13	in	in	ADP
admet-2772	1146	14	the	the	DET
admet-2772	1146	15	rat	rat	NOUN
admet-2772	1146	16	.	.	PUNCT
admet-2772	1146	17	altex	altex	PROPN
admet-2772	1146	18	31	31	NUM
admet-2772	1146	19	(	(	PUNCT
admet-2772	1146	20	2014	2014	NUM
admet-2772	1146	21	)	)	PUNCT
admet-2772	1146	22	423	423	NUM
admet-2772	1146	23	-	-	SYM
admet-2772	1146	24	432	432	NUM
admet-2772	1146	25	.	.	PUNCT
admet-2772	1147	1	https://doi.org/10.14573/altex.1405091	https://doi.org/10.14573/altex.1405091	ADJ
admet-2772	1147	2	[	[	X
admet-2772	1147	3	139	139	NUM
admet-2772	1147	4	]	]	X
admet-2772	1147	5	f.	f.	PROPN
admet-2772	1147	6	como	como	PROPN
admet-2772	1147	7	,	,	PUNCT
admet-2772	1147	8	e.	e.	PROPN
admet-2772	1147	9	carnesecchi	carnesecchi	PROPN
admet-2772	1147	10	,	,	PUNCT
admet-2772	1147	11	s.	s.	PROPN
admet-2772	1147	12	volani	volani	PROPN
admet-2772	1147	13	,	,	PUNCT
admet-2772	1147	14	j.l	j.l	PROPN
admet-2772	1147	15	.	.	PROPN
admet-2772	1147	16	dorne	dorne	PROPN
admet-2772	1147	17	,	,	PUNCT
admet-2772	1147	18	j.	j.	PROPN
admet-2772	1147	19	richardson	richardson	PROPN
admet-2772	1147	20	,	,	PUNCT
admet-2772	1147	21	a.	a.	NOUN
admet-2772	1147	22	bassan	bassan	NOUN
admet-2772	1147	23	,	,	PUNCT
admet-2772	1147	24	m.	m.	NOUN
admet-2772	1147	25	pavan	pavan	PROPN
admet-2772	1147	26	,	,	PUNCT
admet-2772	1147	27	e.	e.	PROPN
admet-2772	1147	28	benfenati	benfenati	PROPN
admet-2772	1147	29	.	.	PUNCT
admet-2772	1148	1	predicting	predict	VERB
admet-2772	1148	2	acute	acute	ADJ
admet-2772	1148	3	contact	contact	NOUN
admet-2772	1148	4	toxicity	toxicity	NOUN
admet-2772	1148	5	of	of	ADP
admet-2772	1148	6	pesticides	pesticide	NOUN
admet-2772	1148	7	in	in	ADP
admet-2772	1148	8	honeybees	honeybee	NOUN
admet-2772	1148	9	(	(	PUNCT
admet-2772	1148	10	apis	apis	PROPN
admet-2772	1148	11	mellifera	mellifera	PROPN
admet-2772	1148	12	)	)	PUNCT
admet-2772	1148	13	through	through	ADP
admet-2772	1148	14	a	a	DET
admet-2772	1148	15	k	k	NOUN
admet-2772	1148	16	-	-	PUNCT
admet-2772	1148	17	nearest	near	ADJ
admet-2772	1148	18	neighbor	neighbor	NOUN
admet-2772	1148	19	model	model	NOUN
admet-2772	1148	20	.	.	PUNCT
admet-2772	1149	1	chemosphere	chemosphere	PROPN
admet-2772	1149	2	166	166	NUM
admet-2772	1149	3	(	(	PUNCT
admet-2772	1149	4	2017	2017	NUM
admet-2772	1149	5	)	)	PUNCT
admet-2772	1149	6	438	438	NUM
admet-2772	1149	7	-	-	SYM
admet-2772	1149	8	444	444	NUM
admet-2772	1149	9	.	.	PUNCT
admet-2772	1150	1	https://doi.org/10.1016/j.chemosphere.2016.09.092	https://doi.org/10.1016/j.chemosphere.2016.09.092	NOUN
admet-2772	1150	2	[	[	X
admet-2772	1150	3	140	140	NUM
admet-2772	1150	4	]	]	X
admet-2772	1150	5	s.	s.	PROPN
admet-2772	1150	6	chavan	chavan	PROPN
admet-2772	1150	7	,	,	PUNCT
admet-2772	1150	8	r.	r.	PROPN
admet-2772	1150	9	friedman	friedman	PROPN
admet-2772	1150	10	,	,	PUNCT
admet-2772	1150	11	i.a	i.a	PROPN
admet-2772	1150	12	.	.	PROPN
admet-2772	1150	13	nicholls	nicholls	PROPN
admet-2772	1150	14	.	.	PUNCT
admet-2772	1151	1	acute	acute	ADJ
admet-2772	1151	2	toxicity	toxicity	NOUN
admet-2772	1151	3	-	-	PUNCT
admet-2772	1151	4	supported	support	VERB
admet-2772	1151	5	chronic	chronic	ADJ
admet-2772	1151	6	toxicity	toxicity	NOUN
admet-2772	1151	7	prediction	prediction	NOUN
admet-2772	1151	8	:	:	PUNCT
admet-2772	1151	9	a	a	DET
admet-2772	1151	10	knearest	knearest	NOUN
admet-2772	1151	11	neighbor	neighbor	NOUN
admet-2772	1151	12	coupled	couple	VERB
admet-2772	1151	13	read	read	NOUN
admet-2772	1151	14	-	-	PUNCT
admet-2772	1151	15	across	across	ADP
admet-2772	1151	16	strategy	strategy	NOUN
admet-2772	1151	17	.	.	PUNCT
admet-2772	1152	1	international	international	ADJ
admet-2772	1152	2	journal	journal	NOUN
admet-2772	1152	3	of	of	ADP
admet-2772	1152	4	molecular	molecular	ADJ
admet-2772	1152	5	sciences	science	NOUN
admet-2772	1152	6	16	16	NUM
admet-2772	1152	7	(	(	PUNCT
admet-2772	1152	8	2015	2015	NUM
admet-2772	1152	9	)	)	PUNCT
admet-2772	1152	10	11659	11659	NUM
admet-2772	1152	11	-	-	SYM
admet-2772	1152	12	11677	11677	NUM
admet-2772	1152	13	.	.	PUNCT
admet-2772	1153	1	https://doi.org/10.3390/ijms160511659	https://doi.org/10.3390/ijms160511659	NOUN
admet-2772	1154	1	[	[	X
admet-2772	1154	2	141	141	NUM
admet-2772	1154	3	]	]	PUNCT
admet-2772	1154	4	h.	h.	PROPN
admet-2772	1154	5	tian	tian	PROPN
admet-2772	1154	6	,	,	PUNCT
admet-2772	1154	7	r.	r.	PROPN
admet-2772	1154	8	ketkar	ketkar	PROPN
admet-2772	1154	9	,	,	PUNCT
admet-2772	1154	10	p.	p.	PROPN
admet-2772	1154	11	tao	tao	PROPN
admet-2772	1154	12	.	.	PUNCT
admet-2772	1155	1	admetboost	admetboost	PROPN
admet-2772	1155	2	:	:	PUNCT
admet-2772	1155	3	a	a	DET
admet-2772	1155	4	web	web	NOUN
admet-2772	1155	5	server	server	NOUN
admet-2772	1155	6	for	for	ADP
admet-2772	1155	7	accurate	accurate	ADJ
admet-2772	1155	8	admet	admet	PROPN
admet-2772	1155	9	prediction	prediction	NOUN
admet-2772	1155	10	.	.	PUNCT
admet-2772	1156	1	journal	journal	NOUN
admet-2772	1156	2	of	of	ADP
admet-2772	1156	3	molecular	molecular	ADJ
admet-2772	1156	4	modeling	modeling	NOUN
admet-2772	1156	5	28	28	NUM
admet-2772	1156	6	(	(	PUNCT
admet-2772	1156	7	2022	2022	NUM
admet-2772	1156	8	)	)	PUNCT
admet-2772	1156	9	408	408	NUM
admet-2772	1156	10	.	.	PUNCT
admet-2772	1157	1	https://doi.org/10.1007/s00894-022-05373-8	https://doi.org/10.1007/s00894-022-05373-8	NOUN
admet-2772	1158	1	[	[	X
admet-2772	1158	2	142	142	NUM
admet-2772	1158	3	]	]	PUNCT
admet-2772	1158	4	t.	t.	PROPN
admet-2772	1158	5	an	an	PROPN
admet-2772	1158	6	,	,	PUNCT
admet-2772	1158	7	y.	y.	PROPN
admet-2772	1158	8	chen	chen	PROPN
admet-2772	1158	9	,	,	PUNCT
admet-2772	1158	10	y.	y.	PROPN
admet-2772	1158	11	chen	chen	PROPN
admet-2772	1158	12	,	,	PUNCT
admet-2772	1158	13	l.	l.	PROPN
admet-2772	1158	14	ma	ma	PROPN
admet-2772	1158	15	,	,	PUNCT
admet-2772	1158	16	j.	j.	PROPN
admet-2772	1158	17	wang	wang	PROPN
admet-2772	1158	18	,	,	PUNCT
admet-2772	1158	19	j.	j.	PROPN
admet-2772	1158	20	zhao	zhao	PROPN
admet-2772	1158	21	.	.	PUNCT
admet-2772	1159	1	a	a	DET
admet-2772	1159	2	machine	machine	NOUN
admet-2772	1159	3	learning	learning	NOUN
admet-2772	1159	4	-	-	PUNCT
admet-2772	1159	5	based	base	VERB
admet-2772	1159	6	approach	approach	NOUN
admet-2772	1159	7	to	to	ADP
admet-2772	1159	8	erα	erα	NOUN
admet-2772	1159	9	bioactivity	bioactivity	NOUN
admet-2772	1159	10	and	and	CCONJ
admet-2772	1159	11	drug	drug	NOUN
admet-2772	1159	12	admet	admet	PROPN
admet-2772	1159	13	prediction	prediction	NOUN
admet-2772	1159	14	.	.	PUNCT
admet-2772	1160	1	frontiers	frontier	NOUN
admet-2772	1160	2	in	in	ADP
admet-2772	1160	3	genetics	genetic	NOUN
admet-2772	1160	4	13	13	NUM
admet-2772	1160	5	(	(	PUNCT
admet-2772	1160	6	2023	2023	NUM
admet-2772	1160	7	)	)	PUNCT
admet-2772	1160	8	1087273	1087273	NUM
admet-2772	1160	9	.	.	PUNCT
admet-2772	1161	1	https://doi.org/10.3389/fgene.2022.1087273	https://doi.org/10.3389/fgene.2022.1087273	PROPN
admet-2772	1162	1	[	[	X
admet-2772	1162	2	143	143	NUM
admet-2772	1162	3	]	]	X
admet-2772	1162	4	x.	x.	NOUN
admet-2772	1162	5	li	li	PROPN
admet-2772	1162	6	,	,	PUNCT
admet-2772	1162	7	l.	l.	PROPN
admet-2772	1162	8	tang	tang	PROPN
admet-2772	1162	9	,	,	PUNCT
admet-2772	1162	10	z.	z.	PROPN
admet-2772	1162	11	li	li	PROPN
admet-2772	1162	12	,	,	PUNCT
admet-2772	1162	13	d.	d.	PROPN
admet-2772	1162	14	qiu	qiu	PROPN
admet-2772	1162	15	,	,	PUNCT
admet-2772	1162	16	z.	z.	PROPN
admet-2772	1162	17	yang	yang	PROPN
admet-2772	1162	18	,	,	PUNCT
admet-2772	1162	19	b.	b.	PROPN
admet-2772	1162	20	li	li	PROPN
admet-2772	1162	21	.	.	PROPN
admet-2772	1162	22	prediction	prediction	NOUN
admet-2772	1162	23	of	of	ADP
admet-2772	1162	24	admet	admet	NOUN
admet-2772	1162	25	properties	property	NOUN
admet-2772	1162	26	of	of	ADP
admet-2772	1162	27	anti	anti	ADJ
admet-2772	1162	28	-	-	ADJ
admet-2772	1162	29	breast	breast	ADJ
admet-2772	1162	30	cancer	cancer	NOUN
admet-2772	1162	31	compounds	compound	NOUN
admet-2772	1162	32	using	use	VERB
admet-2772	1162	33	three	three	NUM
admet-2772	1162	34	machine	machine	NOUN
admet-2772	1162	35	learning	learn	VERB
admet-2772	1162	36	algorithms	algorithm	NOUN
admet-2772	1162	37	.	.	PUNCT
admet-2772	1163	1	molecules	molecule	NOUN
admet-2772	1163	2	28	28	NUM
admet-2772	1163	3	(	(	PUNCT
admet-2772	1163	4	2023	2023	NUM
admet-2772	1163	5	)	)	PUNCT
admet-2772	1163	6	2326	2326	NUM
admet-2772	1163	7	.	.	PUNCT
admet-2772	1164	1	https://doi.org/10.3390/molecules28052326	https://doi.org/10.3390/molecules28052326	NOUN
admet-2772	1165	1	[	[	X
admet-2772	1165	2	144	144	NUM
admet-2772	1165	3	]	]	X
admet-2772	1165	4	p.m.	p.m.	NOUN
admet-2772	1165	5	vassiliev	vassiliev	ADV
admet-2772	1165	6	,	,	PUNCT
admet-2772	1165	7	a.	a.	PROPN
admet-2772	1165	8	v.	v.	PROPN
admet-2772	1165	9	golubeva	golubeva	PROPN
admet-2772	1165	10	,	,	PUNCT
admet-2772	1165	11	a.r	a.r	PROPN
admet-2772	1165	12	.	.	PROPN
admet-2772	1165	13	koroleva	koroleva	PROPN
admet-2772	1165	14	,	,	PUNCT
admet-2772	1165	15	m.a	m.a	PROPN
admet-2772	1165	16	.	.	PROPN
admet-2772	1165	17	perfilev	perfilev	PROPN
admet-2772	1165	18	,	,	PUNCT
admet-2772	1165	19	a.n	a.n	PROPN
admet-2772	1165	20	.	.	PROPN
admet-2772	1165	21	kochetkov	kochetkov	PROPN
admet-2772	1165	22	.	.	PUNCT
admet-2772	1166	1	in	in	ADP
admet-2772	1166	2	silico	silico	NOUN
admet-2772	1166	3	prediction	prediction	NOUN
admet-2772	1166	4	of	of	ADP
admet-2772	1166	5	toxicological	toxicological	ADJ
admet-2772	1166	6	and	and	CCONJ
admet-2772	1166	7	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	1166	8	characteristics	characteristic	NOUN
admet-2772	1166	9	of	of	ADP
admet-2772	1166	10	medicinal	medicinal	ADJ
admet-2772	1166	11	compounds	compound	NOUN
admet-2772	1166	12	.	.	PUNCT
admet-2772	1167	1	safety	safety	NOUN
admet-2772	1167	2	and	and	CCONJ
admet-2772	1167	3	risk	risk	NOUN
admet-2772	1167	4	of	of	ADP
admet-2772	1167	5	pharmacotherapy	pharmacotherapy	NOUN
admet-2772	1167	6	11	11	NUM
admet-2772	1167	7	(	(	PUNCT
admet-2772	1167	8	2023	2023	NUM
admet-2772	1167	9	)	)	PUNCT
admet-2772	1167	10	390	390	NUM
admet-2772	1167	11	-	-	SYM
admet-2772	1167	12	408	408	NUM
admet-2772	1167	13	.	.	PUNCT
admet-2772	1168	1	https://doi.org/10.30895/2312-7821-2023-11-4-390-408	https://doi.org/10.30895/2312-7821-2023-11-4-390-408	PROPN
admet-2772	1169	1	[	[	X
admet-2772	1169	2	145	145	NUM
admet-2772	1169	3	]	]	PUNCT
admet-2772	1169	4	j.	j.	PROPN
admet-2772	1169	5	wenzel	wenzel	PROPN
admet-2772	1169	6	,	,	PUNCT
admet-2772	1169	7	h.	h.	PROPN
admet-2772	1169	8	matter	matter	NOUN
admet-2772	1169	9	,	,	PUNCT
admet-2772	1169	10	f.	f.	PROPN
admet-2772	1169	11	schmidt	schmidt	PROPN
admet-2772	1169	12	.	.	PUNCT
admet-2772	1170	1	predictive	predictive	ADJ
admet-2772	1170	2	multitask	multitask	PROPN
admet-2772	1170	3	deep	deep	ADJ
admet-2772	1170	4	neural	neural	ADJ
admet-2772	1170	5	network	network	NOUN
admet-2772	1170	6	models	model	NOUN
admet-2772	1170	7	for	for	ADP
admet-2772	1170	8	adme	adme	NOUN
admet-2772	1170	9	-	-	PUNCT
admet-2772	1170	10	tox	tox	NOUN
admet-2772	1170	11	properties	property	NOUN
admet-2772	1170	12	:	:	PUNCT
admet-2772	1170	13	learning	learn	VERB
admet-2772	1170	14	from	from	ADP
admet-2772	1170	15	large	large	ADJ
admet-2772	1170	16	data	datum	NOUN
admet-2772	1170	17	sets	set	NOUN
admet-2772	1170	18	.	.	PUNCT
admet-2772	1171	1	journal	journal	NOUN
admet-2772	1171	2	of	of	ADP
admet-2772	1171	3	chemical	chemical	ADJ
admet-2772	1171	4	information	information	NOUN
admet-2772	1171	5	and	and	CCONJ
admet-2772	1171	6	modeling	model	VERB
admet-2772	1171	7	59	59	NUM
admet-2772	1171	8	(	(	PUNCT
admet-2772	1171	9	2019	2019	NUM
admet-2772	1171	10	)	)	PUNCT
admet-2772	1171	11	1253	1253	NUM
admet-2772	1171	12	-	-	SYM
admet-2772	1171	13	1268	1268	NUM
admet-2772	1171	14	.	.	PUNCT
admet-2772	1172	1	https://doi.org/10.1021/acs.jcim.8b00785	https://doi.org/10.1021/acs.jcim.8b00785	PROPN
admet-2772	1172	2	[	[	X
admet-2772	1172	3	146	146	NUM
admet-2772	1172	4	]	]	X
admet-2772	1172	5	d.a	d.a	PROPN
admet-2772	1172	6	.	.	PROPN
admet-2772	1172	7	winkler	winkler	PROPN
admet-2772	1172	8	.	.	PUNCT
admet-2772	1173	1	neural	neural	ADJ
admet-2772	1173	2	networks	network	NOUN
admet-2772	1173	3	in	in	ADP
admet-2772	1173	4	adme	adme	NOUN
admet-2772	1173	5	and	and	CCONJ
admet-2772	1173	6	toxicity	toxicity	NOUN
admet-2772	1173	7	prediction	prediction	NOUN
admet-2772	1173	8	.	.	PUNCT
admet-2772	1174	1	drugs	drug	NOUN
admet-2772	1174	2	of	of	ADP
admet-2772	1174	3	the	the	DET
admet-2772	1174	4	future	future	ADJ
admet-2772	1174	5	29	29	NUM
admet-2772	1174	6	(	(	PUNCT
admet-2772	1174	7	2004	2004	NUM
admet-2772	1174	8	)	)	PUNCT
admet-2772	1174	9	10431057	10431057	NUM
admet-2772	1174	10	.	.	PUNCT
admet-2772	1175	1	https://doi.org/10.1358/dof.2004.029.10.863395	https://doi.org/10.1358/dof.2004.029.10.863395	PROPN
admet-2772	1176	1	[	[	X
admet-2772	1176	2	147	147	NUM
admet-2772	1176	3	]	]	X
admet-2772	1176	4	i.	i.	PROPN
admet-2772	1176	5	pantic	pantic	PROPN
admet-2772	1176	6	,	,	PUNCT
admet-2772	1176	7	j.	j.	PROPN
admet-2772	1176	8	paunovic	paunovic	PROPN
admet-2772	1176	9	,	,	PUNCT
admet-2772	1176	10	j.	j.	PROPN
admet-2772	1176	11	cumic	cumic	PROPN
admet-2772	1176	12	,	,	PUNCT
admet-2772	1176	13	s.	s.	PROPN
admet-2772	1176	14	valjarevic	valjarevic	PROPN
admet-2772	1176	15	,	,	PUNCT
admet-2772	1176	16	g.a	g.a	PROPN
admet-2772	1176	17	.	.	PROPN
admet-2772	1176	18	petroianu	petroianu	PROPN
admet-2772	1176	19	,	,	PUNCT
admet-2772	1176	20	p.r	p.r	PROPN
admet-2772	1176	21	.	.	PROPN
admet-2772	1176	22	corridon	corridon	PROPN
admet-2772	1176	23	.	.	PUNCT
admet-2772	1177	1	artificial	artificial	ADJ
admet-2772	1177	2	neural	neural	ADJ
admet-2772	1177	3	networks	network	NOUN
admet-2772	1177	4	in	in	ADP
admet-2772	1177	5	contemporary	contemporary	ADJ
admet-2772	1177	6	toxicology	toxicology	NOUN
admet-2772	1177	7	research	research	NOUN
admet-2772	1177	8	.	.	PUNCT
admet-2772	1178	1	chemico	chemico	ADJ
admet-2772	1178	2	-	-	ADJ
admet-2772	1178	3	biological	biological	ADJ
admet-2772	1178	4	interactions	interaction	NOUN
admet-2772	1178	5	369	369	NUM
admet-2772	1178	6	(	(	PUNCT
admet-2772	1178	7	2023	2023	NUM
admet-2772	1178	8	)	)	PUNCT
admet-2772	1178	9	110269	110269	NUM
admet-2772	1178	10	.	.	PUNCT
admet-2772	1179	1	https://doi.org/10.1016/j.cbi.2022.110269	https://doi.org/10.1016/j.cbi.2022.110269	PUNCT
admet-2772	1180	1	[	[	X
admet-2772	1180	2	148	148	NUM
admet-2772	1180	3	]	]	X
admet-2772	1180	4	n.	n.	PROPN
admet-2772	1180	5	schapin	schapin	PROPN
admet-2772	1180	6	,	,	PUNCT
admet-2772	1180	7	m.	m.	NOUN
admet-2772	1180	8	majewski	majewski	PROPN
admet-2772	1180	9	,	,	PUNCT
admet-2772	1180	10	a.	a.	NOUN
admet-2772	1180	11	varela	varela	PROPN
admet-2772	1180	12	-	-	PUNCT
admet-2772	1180	13	rial	rial	NOUN
admet-2772	1180	14	,	,	PUNCT
admet-2772	1180	15	c.	c.	PROPN
admet-2772	1180	16	arroniz	arroniz	PROPN
admet-2772	1180	17	,	,	PUNCT
admet-2772	1180	18	g.	g.	PROPN
admet-2772	1180	19	de	de	X
admet-2772	1180	20	fabritiis	fabritiis	NOUN
admet-2772	1180	21	.	.	PUNCT
admet-2772	1181	1	machine	machine	NOUN
admet-2772	1181	2	learning	learn	VERB
admet-2772	1181	3	small	small	ADJ
admet-2772	1181	4	molecule	molecule	NOUN
admet-2772	1181	5	properties	property	NOUN
admet-2772	1181	6	in	in	ADP
admet-2772	1181	7	drug	drug	NOUN
admet-2772	1181	8	discovery	discovery	NOUN
admet-2772	1181	9	.	.	PUNCT
admet-2772	1182	1	artificial	artificial	ADJ
admet-2772	1182	2	intelligence	intelligence	NOUN
admet-2772	1182	3	chemistry	chemistry	NOUN
admet-2772	1182	4	1	1	NUM
admet-2772	1182	5	(	(	PUNCT
admet-2772	1182	6	2023	2023	NUM
admet-2772	1182	7	)	)	PUNCT
admet-2772	1182	8	100020	100020	NUM
admet-2772	1182	9	.	.	PUNCT
admet-2772	1183	1	https://doi.org/10.1016/j.aichem.2023.100020	https://doi.org/10.1016/j.aichem.2023.100020	NOUN
admet-2772	1183	2	[	[	X
admet-2772	1183	3	149	149	NUM
admet-2772	1183	4	]	]	X
admet-2772	1183	5	p.	p.	NOUN
admet-2772	1183	6	schyman	schyman	NOUN
admet-2772	1183	7	,	,	PUNCT
admet-2772	1183	8	r.	r.	PROPN
admet-2772	1183	9	liu	liu	PROPN
admet-2772	1183	10	,	,	PUNCT
admet-2772	1183	11	v.	v.	PROPN
admet-2772	1183	12	desai	desai	PROPN
admet-2772	1183	13	,	,	PUNCT
admet-2772	1183	14	a.	a.	NOUN
admet-2772	1183	15	wallqvist	wallqvist	NOUN
admet-2772	1183	16	.	.	PUNCT
admet-2772	1184	1	vnn	vnn	NOUN
admet-2772	1184	2	web	web	NOUN
admet-2772	1184	3	server	server	NOUN
admet-2772	1184	4	for	for	ADP
admet-2772	1184	5	admet	admet	ADJ
admet-2772	1184	6	predictions	prediction	NOUN
admet-2772	1184	7	.	.	PUNCT
admet-2772	1185	1	frontiers	frontier	NOUN
admet-2772	1185	2	in	in	ADP
admet-2772	1185	3	pharmacology	pharmacology	NOUN
admet-2772	1185	4	8	8	NUM
admet-2772	1185	5	(	(	PUNCT
admet-2772	1185	6	2017	2017	NUM
admet-2772	1185	7	)	)	PUNCT
admet-2772	1185	8	889	889	NUM
admet-2772	1185	9	.	.	PUNCT
admet-2772	1186	1	https://doi.org/10.3389/fphar.2017.00889	https://doi.org/10.3389/fphar.2017.00889	PROPN
admet-2772	1186	2	[	[	X
admet-2772	1186	3	150	150	NUM
admet-2772	1186	4	]	]	PUNCT
admet-2772	1186	5	h.	h.	PROPN
admet-2772	1186	6	gonzález	gonzález	PROPN
admet-2772	1186	7	-	-	PUNCT
admet-2772	1186	8	díaz	díaz	NOUN
admet-2772	1186	9	.	.	PUNCT
admet-2772	1187	1	admet	admet	ADJ
admet-2772	1187	2	-	-	PUNCT
admet-2772	1187	3	multi	multi	ADJ
admet-2772	1187	4	-	-	ADJ
admet-2772	1187	5	output	output	ADJ
admet-2772	1187	6	cheminformatics	cheminformatic	NOUN
admet-2772	1187	7	models	model	NOUN
admet-2772	1187	8	for	for	ADP
admet-2772	1187	9	drug	drug	NOUN
admet-2772	1187	10	delivery	delivery	NOUN
admet-2772	1187	11	,	,	PUNCT
admet-2772	1187	12	interactomics	interactomic	NOUN
admet-2772	1187	13	,	,	PUNCT
admet-2772	1187	14	and	and	CCONJ
admet-2772	1187	15	nanotoxicology	nanotoxicology	NOUN
admet-2772	1187	16	.	.	PUNCT
admet-2772	1188	1	current	current	ADJ
admet-2772	1188	2	drug	drug	NOUN
admet-2772	1188	3	delivery	delivery	NOUN
admet-2772	1188	4	13	13	NUM
admet-2772	1188	5	(	(	PUNCT
admet-2772	1188	6	2016	2016	NUM
admet-2772	1188	7	)	)	PUNCT
admet-2772	1188	8	1	1	NUM
admet-2772	1188	9	.	.	PUNCT
admet-2772	1189	1	https://pubmed.ncbi.nlm.nih.gov/27417300/	https://pubmed.ncbi.nlm.nih.gov/27417300/	NOUN
admet-2772	1189	2	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	1189	3	https://doi.org/10.1088/1755-1315/475/1/012078	https://doi.org/10.1088/1755-1315/475/1/012078	PROPN
admet-2772	1189	4	https://doi.org/10.1007/978-3-319-41063-0_5	https://doi.org/10.1007/978-3-319-41063-0_5	X
admet-2772	1189	5	https://doi.org/10.1002/qsar.200310006	https://doi.org/10.1002/qsar.200310006	ADJ
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admet-2772	1189	7	https://doi.org/10.1016/b978-0-12-823817-2.00011-5	https://doi.org/10.1016/b978-0-12-823817-2.00011-5	PROPN
admet-2772	1189	8	https://doi.org/10.14573/altex.1405091	https://doi.org/10.14573/altex.1405091	VERB
admet-2772	1189	9	https://doi.org/10.1016/j.chemosphere.2016.09.092	https://doi.org/10.1016/j.chemosphere.2016.09.092	NOUN
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admet-2772	1189	11	https://doi.org/10.1007/s00894-022-05373-8	https://doi.org/10.1007/s00894-022-05373-8	NOUN
admet-2772	1190	1	https://doi.org/10.3389/fgene.2022.1087273	https://doi.org/10.3389/fgene.2022.1087273	PROPN
admet-2772	1190	2	https://doi.org/10.3390/molecules28052326	https://doi.org/10.3390/molecules28052326	NOUN
admet-2772	1190	3	https://doi.org/10.30895/2312-7821-2023-11-4-390-408	https://doi.org/10.30895/2312-7821-2023-11-4-390-408	PROPN
admet-2772	1190	4	https://doi.org/10.1021/acs.jcim.8b00785	https://doi.org/10.1021/acs.jcim.8b00785	X
admet-2772	1190	5	https://doi.org/10.1358/dof.2004.029.10.863395	https://doi.org/10.1358/dof.2004.029.10.863395	PROPN
admet-2772	1190	6	https://doi.org/10.1016/j.cbi.2022.110269	https://doi.org/10.1016/j.cbi.2022.110269	PROPN
admet-2772	1190	7	https://doi.org/10.1016/j.aichem.2023.100020	https://doi.org/10.1016/j.aichem.2023.100020	PROPN
admet-2772	1191	1	https://doi.org/10.3389/fphar.2017.00889	https://doi.org/10.3389/fphar.2017.00889	PROPN
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admet-2772	1191	3	m.	m.	NOUN
admet-2772	1191	4	venkataraman	venkataraman	NOUN
admet-2772	1191	5	et	et	PROPN
admet-2772	1191	6	al	al	PROPN
admet-2772	1191	7	.	.	PROPN
admet-2772	1191	8	admet	admet	PROPN
admet-2772	1191	9	&	&	CCONJ
admet-2772	1191	10	dmpk	dmpk	PROPN
admet-2772	1191	11	13(3	13(3	NUM
admet-2772	1191	12	)	)	PUNCT
admet-2772	1191	13	(	(	PUNCT
admet-2772	1191	14	2025	2025	NUM
admet-2772	1191	15	)	)	PUNCT
admet-2772	1191	16	2772	2772	NUM
admet-2772	1191	17	34	34	NUM
admet-2772	1192	1	[	[	X
admet-2772	1192	2	151	151	NUM
admet-2772	1192	3	]	]	X
admet-2772	1192	4	a.t	a.t	PROPN
admet-2772	1192	5	.	.	PROPN
admet-2772	1192	6	müller	müller	PROPN
admet-2772	1192	7	,	,	PUNCT
admet-2772	1192	8	j.a	j.a	PROPN
admet-2772	1192	9	.	.	PROPN
admet-2772	1192	10	hiss	hiss	PROPN
admet-2772	1192	11	,	,	PUNCT
admet-2772	1192	12	g.	g.	PROPN
admet-2772	1192	13	schneider	schneider	PROPN
admet-2772	1192	14	.	.	PUNCT
admet-2772	1193	1	recurrent	recurrent	ADJ
admet-2772	1193	2	neural	neural	ADJ
admet-2772	1193	3	network	network	NOUN
admet-2772	1193	4	model	model	NOUN
admet-2772	1193	5	for	for	ADP
admet-2772	1193	6	constructive	constructive	ADJ
admet-2772	1193	7	peptide	peptide	NOUN
admet-2772	1193	8	design	design	NOUN
admet-2772	1193	9	.	.	PUNCT
admet-2772	1194	1	journal	journal	PROPN
admet-2772	1194	2	of	of	ADP
admet-2772	1194	3	chemical	chemical	ADJ
admet-2772	1194	4	information	information	NOUN
admet-2772	1194	5	and	and	CCONJ
admet-2772	1194	6	modeling	model	VERB
admet-2772	1194	7	58	58	NUM
admet-2772	1194	8	(	(	PUNCT
admet-2772	1194	9	2018	2018	NUM
admet-2772	1194	10	)	)	PUNCT
admet-2772	1194	11	472	472	NUM
admet-2772	1194	12	-	-	SYM
admet-2772	1194	13	479	479	NUM
admet-2772	1194	14	.	.	PUNCT
admet-2772	1195	1	https://doi.org/10.1021/acs.jcim.7b00414	https://doi.org/10.1021/acs.jcim.7b00414	X
admet-2772	1195	2	[	[	X
admet-2772	1195	3	152	152	NUM
admet-2772	1195	4	]	]	PUNCT
admet-2772	1195	5	a.	a.	PROPN
admet-2772	1195	6	de	de	PROPN
admet-2772	1195	7	carlo	carlo	PROPN
admet-2772	1195	8	,	,	PUNCT
admet-2772	1195	9	d.	d.	PROPN
admet-2772	1195	10	ronchi	ronchi	PROPN
admet-2772	1195	11	,	,	PUNCT
admet-2772	1195	12	m.	m.	NOUN
admet-2772	1195	13	piastra	piastra	PROPN
admet-2772	1195	14	,	,	PUNCT
admet-2772	1195	15	e.m	e.m	PROPN
admet-2772	1195	16	.	.	PROPN
admet-2772	1195	17	tosca	tosca	PROPN
admet-2772	1195	18	,	,	PUNCT
admet-2772	1195	19	p.	p.	PROPN
admet-2772	1195	20	magni	magni	PROPN
admet-2772	1195	21	.	.	PUNCT
admet-2772	1196	1	predicting	predict	VERB
admet-2772	1196	2	admet	admet	PROPN
admet-2772	1196	3	properties	property	NOUN
admet-2772	1196	4	from	from	ADP
admet-2772	1196	5	molecule	molecule	NOUN
admet-2772	1196	6	smile	smile	NOUN
admet-2772	1196	7	:	:	PUNCT
admet-2772	1196	8	a	a	DET
admet-2772	1196	9	bottom	bottom	ADJ
admet-2772	1196	10	-	-	PUNCT
admet-2772	1196	11	up	up	ADP
admet-2772	1196	12	approach	approach	NOUN
admet-2772	1196	13	using	use	VERB
admet-2772	1196	14	attention	attention	NOUN
admet-2772	1196	15	-	-	PUNCT
admet-2772	1196	16	based	base	VERB
admet-2772	1196	17	graph	graph	NOUN
admet-2772	1196	18	neural	neural	ADJ
admet-2772	1196	19	networks	network	NOUN
admet-2772	1196	20	.	.	PUNCT
admet-2772	1197	1	pharmaceutics	pharmaceutic	NOUN
admet-2772	1197	2	16	16	NUM
admet-2772	1197	3	(	(	PUNCT
admet-2772	1197	4	2024	2024	NUM
admet-2772	1197	5	)	)	PUNCT
admet-2772	1197	6	776	776	NUM
admet-2772	1197	7	.	.	PUNCT
admet-2772	1197	8	https://doi.org/10.3390/pharmaceutics16060776	https://doi.org/10.3390/pharmaceutics16060776	NOUN
admet-2772	1198	1	[	[	X
admet-2772	1198	2	153	153	NUM
admet-2772	1198	3	]	]	PUNCT
admet-2772	1198	4	m.	m.	NOUN
admet-2772	1198	5	aburidi	aburidi	PROPN
admet-2772	1198	6	,	,	PUNCT
admet-2772	1198	7	r.	r.	PROPN
admet-2772	1198	8	marcia	marcia	PROPN
admet-2772	1198	9	.	.	PUNCT
admet-2772	1199	1	wasserstein	wasserstein	PROPN
admet-2772	1199	2	distance	distance	NOUN
admet-2772	1199	3	-	-	PUNCT
admet-2772	1199	4	based	base	VERB
admet-2772	1199	5	graph	graph	NOUN
admet-2772	1199	6	kernel	kernel	NOUN
admet-2772	1199	7	for	for	ADP
admet-2772	1199	8	enhancing	enhance	VERB
admet-2772	1199	9	drug	drug	NOUN
admet-2772	1199	10	safety	safety	NOUN
admet-2772	1199	11	and	and	CCONJ
admet-2772	1199	12	efficacy	efficacy	NOUN
admet-2772	1199	13	prediction	prediction	NOUN
admet-2772	1199	14	*	*	PUNCT
admet-2772	1199	15	.	.	PUNCT
admet-2772	1200	1	proceedings	proceeding	NOUN
admet-2772	1200	2	2024	2024	NUM
admet-2772	1200	3	ieee	ieee	PROPN
admet-2772	1200	4	1st	1st	PROPN
admet-2772	1200	5	international	international	ADJ
admet-2772	1200	6	conference	conference	NOUN
admet-2772	1200	7	on	on	ADP
admet-2772	1200	8	artificial	artificial	ADJ
admet-2772	1200	9	intelligence	intelligence	NOUN
admet-2772	1200	10	for	for	ADP
admet-2772	1200	11	medicine	medicine	NOUN
admet-2772	1200	12	,	,	PUNCT
admet-2772	1200	13	health	health	NOUN
admet-2772	1200	14	and	and	CCONJ
admet-2772	1200	15	care	care	NOUN
admet-2772	1200	16	,	,	PUNCT
admet-2772	1200	17	aimhc	aimhc	PROPN
admet-2772	1200	18	(	(	PUNCT
admet-2772	1200	19	2024	2024	NUM
admet-2772	1200	20	)	)	PUNCT
admet-2772	1200	21	113	113	NUM
admet-2772	1200	22	-	-	SYM
admet-2772	1200	23	119	119	NUM
admet-2772	1200	24	.	.	PUNCT
admet-2772	1201	1	https://doi.org/10.1109/aimhc59811.2024.00029	https://doi.org/10.1109/aimhc59811.2024.00029	PROPN
admet-2772	1201	2	[	[	X
admet-2772	1201	3	154	154	NUM
admet-2772	1201	4	]	]	X
admet-2772	1201	5	l.	l.	PROPN
admet-2772	1201	6	mescheder	mescheder	PROPN
admet-2772	1201	7	,	,	PUNCT
admet-2772	1201	8	s.	s.	PROPN
admet-2772	1201	9	nowozin	nowozin	PROPN
admet-2772	1201	10	,	,	PUNCT
admet-2772	1201	11	a.	a.	NOUN
admet-2772	1201	12	geiger	geiger	PROPN
admet-2772	1201	13	.	.	PUNCT
admet-2772	1202	1	adversarial	adversarial	ADJ
admet-2772	1202	2	variational	variational	ADJ
admet-2772	1202	3	bayes	baye	NOUN
admet-2772	1202	4	:	:	PUNCT
admet-2772	1202	5	unifying	unify	VERB
admet-2772	1202	6	variational	variational	ADJ
admet-2772	1202	7	autoencoders	autoencoder	NOUN
admet-2772	1202	8	and	and	CCONJ
admet-2772	1202	9	generative	generative	ADJ
admet-2772	1202	10	adversarial	adversarial	ADJ
admet-2772	1202	11	networks	network	NOUN
admet-2772	1202	12	.	.	PUNCT
admet-2772	1203	1	arxiv	arxiv	PROPN
admet-2772	1203	2	(	(	PUNCT
admet-2772	1203	3	2017	2017	NUM
admet-2772	1203	4	)	)	PUNCT
admet-2772	1203	5	.	.	PUNCT
admet-2772	1204	1	http://dx.doi.org/10.48550/arxiv.1701.04722	http://dx.doi.org/10.48550/arxiv.1701.04722	NOUN
admet-2772	1205	1	[	[	X
admet-2772	1205	2	155	155	NUM
admet-2772	1205	3	]	]	PUNCT
admet-2772	1205	4	a.	a.	NOUN
admet-2772	1205	5	genevay	genevay	NOUN
admet-2772	1205	6	,	,	PUNCT
admet-2772	1205	7	g.	g.	PROPN
admet-2772	1205	8	peyré	peyré	PROPN
admet-2772	1205	9	,	,	PUNCT
admet-2772	1205	10	m.	m.	NOUN
admet-2772	1205	11	cuturi	cuturi	PROPN
admet-2772	1205	12	.	.	PUNCT
admet-2772	1206	1	gan	gan	PROPN
admet-2772	1206	2	and	and	CCONJ
admet-2772	1206	3	vae	vae	PROPN
admet-2772	1206	4	from	from	ADP
admet-2772	1206	5	an	an	DET
admet-2772	1206	6	optimal	optimal	ADJ
admet-2772	1206	7	transport	transport	NOUN
admet-2772	1206	8	point	point	NOUN
admet-2772	1206	9	of	of	ADP
admet-2772	1206	10	view	view	NOUN
admet-2772	1206	11	.	.	PUNCT
admet-2772	1207	1	(	(	PUNCT
admet-2772	1207	2	2017	2017	NUM
admet-2772	1207	3	)	)	PUNCT
admet-2772	1207	4	.	.	PUNCT
admet-2772	1208	1	http://arxiv.org/abs/1706.01807	http://arxiv.org/abs/1706.01807	ADJ
admet-2772	1209	1	[	[	X
admet-2772	1209	2	156	156	NUM
admet-2772	1209	3	]	]	PUNCT
admet-2772	1209	4	k.	k.	PROPN
admet-2772	1210	1	tsaioun	tsaioun	PROPN
admet-2772	1210	2	,	,	PUNCT
admet-2772	1210	3	b.j	b.j	PROPN
admet-2772	1210	4	.	.	PROPN
admet-2772	1210	5	blaauboer	blaauboer	PROPN
admet-2772	1210	6	,	,	PUNCT
admet-2772	1210	7	t.	t.	PROPN
admet-2772	1210	8	hartung	hartung	PROPN
admet-2772	1210	9	.	.	PUNCT
admet-2772	1211	1	evidence	evidence	NOUN
admet-2772	1211	2	-	-	PUNCT
admet-2772	1211	3	based	base	VERB
admet-2772	1211	4	absorption	absorption	NOUN
admet-2772	1211	5	,	,	PUNCT
admet-2772	1211	6	distribution	distribution	NOUN
admet-2772	1211	7	,	,	PUNCT
admet-2772	1211	8	metabolism	metabolism	NOUN
admet-2772	1211	9	,	,	PUNCT
admet-2772	1211	10	excretion	excretion	NOUN
admet-2772	1211	11	(	(	PUNCT
admet-2772	1211	12	adme	adme	NOUN
admet-2772	1211	13	)	)	PUNCT
admet-2772	1211	14	and	and	CCONJ
admet-2772	1211	15	its	its	PRON
admet-2772	1211	16	interplay	interplay	NOUN
admet-2772	1211	17	with	with	ADP
admet-2772	1211	18	alternative	alternative	ADJ
admet-2772	1211	19	toxicity	toxicity	NOUN
admet-2772	1211	20	methods	method	NOUN
admet-2772	1211	21	.	.	PUNCT
admet-2772	1212	1	altex	altex	PROPN
admet-2772	1212	2	33	33	NUM
admet-2772	1212	3	(	(	PUNCT
admet-2772	1212	4	2016	2016	NUM
admet-2772	1212	5	)	)	PUNCT
admet-2772	1212	6	343	343	NUM
admet-2772	1212	7	-	-	SYM
admet-2772	1212	8	358	358	NUM
admet-2772	1212	9	.	.	PUNCT
admet-2772	1213	1	https://doi.org/10.14573/altex.1610101	https://doi.org/10.14573/altex.1610101	X
admet-2772	1214	1	[	[	X
admet-2772	1214	2	157	157	NUM
admet-2772	1214	3	]	]	X
admet-2772	1214	4	l.k	l.k	PROPN
admet-2772	1214	5	.	.	PROPN
admet-2772	1214	6	vora	vora	PROPN
admet-2772	1214	7	,	,	PUNCT
admet-2772	1214	8	a.d	a.d	PROPN
admet-2772	1214	9	.	.	PROPN
admet-2772	1214	10	gholap	gholap	PROPN
admet-2772	1214	11	,	,	PUNCT
admet-2772	1214	12	k.	k.	PROPN
admet-2772	1214	13	jetha	jetha	PROPN
admet-2772	1214	14	,	,	PUNCT
admet-2772	1214	15	r.r.s	r.r.s	PROPN
admet-2772	1214	16	.	.	PUNCT
admet-2772	1215	1	thakur	thakur	PROPN
admet-2772	1215	2	,	,	PUNCT
admet-2772	1215	3	h.k	h.k	PROPN
admet-2772	1215	4	.	.	PROPN
admet-2772	1215	5	solanki	solanki	PROPN
admet-2772	1215	6	,	,	PUNCT
admet-2772	1215	7	v.p	v.p	PROPN
admet-2772	1215	8	.	.	PROPN
admet-2772	1215	9	chavda	chavda	PROPN
admet-2772	1215	10	.	.	PUNCT
admet-2772	1216	1	artificial	artificial	ADJ
admet-2772	1216	2	intelligence	intelligence	NOUN
admet-2772	1216	3	in	in	ADP
admet-2772	1216	4	pharmaceutical	pharmaceutical	NOUN
admet-2772	1216	5	technology	technology	NOUN
admet-2772	1216	6	and	and	CCONJ
admet-2772	1216	7	drug	drug	NOUN
admet-2772	1216	8	delivery	delivery	NOUN
admet-2772	1216	9	design	design	NOUN
admet-2772	1216	10	.	.	PUNCT
admet-2772	1217	1	pharmaceutics	pharmaceutic	NOUN
admet-2772	1217	2	15	15	NUM
admet-2772	1217	3	(	(	PUNCT
admet-2772	1217	4	2023	2023	NUM
admet-2772	1217	5	)	)	PUNCT
admet-2772	1217	6	1916	1916	NUM
admet-2772	1217	7	.	.	PUNCT
admet-2772	1218	1	https://doi.org/10.3390/pharmaceutics15071916	https://doi.org/10.3390/pharmaceutics15071916	PROPN
admet-2772	1218	2	[	[	X
admet-2772	1218	3	158	158	NUM
admet-2772	1218	4	]	]	X
admet-2772	1218	5	j.	j.	PROPN
admet-2772	1218	6	kim	kim	PROPN
admet-2772	1218	7	,	,	PUNCT
admet-2772	1218	8	w.	w.	PROPN
admet-2772	1218	9	chang	chang	PROPN
admet-2772	1218	10	,	,	PUNCT
admet-2772	1218	11	h.	h.	PROPN
admet-2772	1219	1	ji	ji	PROPN
admet-2772	1219	2	,	,	PUNCT
admet-2772	1219	3	i.s	i.s	PROPN
admet-2772	1219	4	.	.	PROPN
admet-2772	1219	5	joung	joung	PROPN
admet-2772	1219	6	.	.	PUNCT
admet-2772	1220	1	quantum	quantum	NOUN
admet-2772	1220	2	-	-	PUNCT
admet-2772	1220	3	informed	inform	VERB
admet-2772	1220	4	molecular	molecular	ADJ
admet-2772	1220	5	representation	representation	NOUN
admet-2772	1220	6	learning	learning	NOUN
admet-2772	1220	7	enhancing	enhance	VERB
admet-2772	1220	8	admet	admet	PROPN
admet-2772	1220	9	property	property	NOUN
admet-2772	1220	10	prediction	prediction	NOUN
admet-2772	1220	11	.	.	PUNCT
admet-2772	1221	1	journal	journal	PROPN
admet-2772	1221	2	of	of	ADP
admet-2772	1221	3	chemical	chemical	ADJ
admet-2772	1221	4	information	information	NOUN
admet-2772	1221	5	and	and	CCONJ
admet-2772	1221	6	modeling	model	VERB
admet-2772	1221	7	64	64	NUM
admet-2772	1221	8	(	(	PUNCT
admet-2772	1221	9	2024	2024	NUM
admet-2772	1221	10	)	)	PUNCT
admet-2772	1221	11	5028	5028	NUM
admet-2772	1221	12	-	-	SYM
admet-2772	1221	13	5040	5040	NUM
admet-2772	1221	14	.	.	PUNCT
admet-2772	1222	1	https://doi.org/10.1021/acs.jcim.4c00772	https://doi.org/10.1021/acs.jcim.4c00772	PRON
admet-2772	1222	2	[	[	X
admet-2772	1222	3	159	159	NUM
admet-2772	1222	4	]	]	X
admet-2772	1222	5	c.	c.	PROPN
admet-2772	1222	6	hu	hu	PROPN
admet-2772	1222	7	,	,	PUNCT
admet-2772	1222	8	k.	k.	PROPN
admet-2772	1222	9	v.	v.	PROPN
admet-2772	1222	10	saboo	saboo	PROPN
admet-2772	1222	11	,	,	PUNCT
admet-2772	1222	12	a.h	a.h	PROPN
admet-2772	1222	13	.	.	PROPN
admet-2772	1222	14	ali	ali	PROPN
admet-2772	1222	15	,	,	PUNCT
admet-2772	1222	16	b.d	b.d	PROPN
admet-2772	1222	17	.	.	PROPN
admet-2772	1222	18	juran	juran	PROPN
admet-2772	1222	19	,	,	PUNCT
admet-2772	1222	20	k.n	k.n	PROPN
admet-2772	1222	21	.	.	PROPN
admet-2772	1222	22	lazaridis	lazaridis	PROPN
admet-2772	1222	23	,	,	PUNCT
admet-2772	1222	24	r.k	r.k	PROPN
admet-2772	1222	25	.	.	PROPN
admet-2772	1222	26	iyer	iyer	PROPN
admet-2772	1222	27	.	.	PUNCT
admet-2772	1223	1	remedi	remedi	PROPN
admet-2772	1223	2	:	:	PUNCT
admet-2772	1223	3	reinforcement	reinforcement	NOUN
admet-2772	1223	4	learningdriven	learningdriven	NOUN
admet-2772	1223	5	adaptive	adaptive	ADJ
admet-2772	1223	6	metabolism	metabolism	NOUN
admet-2772	1223	7	modeling	modeling	NOUN
admet-2772	1223	8	of	of	ADP
admet-2772	1223	9	primary	primary	ADJ
admet-2772	1223	10	sclerosing	sclerose	VERB
admet-2772	1223	11	cholangitis	cholangitis	NOUN
admet-2772	1223	12	disease	disease	NOUN
admet-2772	1223	13	progression	progression	NOUN
admet-2772	1223	14	.	.	PUNCT
admet-2772	1224	1	proceedings	proceeding	NOUN
admet-2772	1224	2	of	of	ADP
admet-2772	1224	3	machine	machine	NOUN
admet-2772	1224	4	learning	learn	VERB
admet-2772	1224	5	research	research	NOUN
admet-2772	1224	6	225	225	NUM
admet-2772	1224	7	(	(	PUNCT
admet-2772	1224	8	2023	2023	NUM
admet-2772	1224	9	)	)	PUNCT
admet-2772	1224	10	157	157	NUM
admet-2772	1224	11	-	-	SYM
admet-2772	1224	12	189	189	NUM
admet-2772	1224	13	.	.	PUNCT
admet-2772	1225	1	https://doi.org/10.48550/arxiv.2310.01426	https://doi.org/10.48550/arxiv.2310.01426	PROPN
admet-2772	1226	1	[	[	X
admet-2772	1226	2	160	160	NUM
admet-2772	1226	3	]	]	X
admet-2772	1226	4	r.k	r.k	PROPN
admet-2772	1226	5	.	.	PROPN
admet-2772	1226	6	tan	tan	PROPN
admet-2772	1226	7	,	,	PUNCT
admet-2772	1226	8	y.	y.	PROPN
admet-2772	1226	9	liu	liu	PROPN
admet-2772	1226	10	,	,	PUNCT
admet-2772	1226	11	l.	l.	PROPN
admet-2772	1226	12	xie	xie	PROPN
admet-2772	1226	13	.	.	PUNCT
admet-2772	1227	1	reinforcement	reinforcement	NOUN
admet-2772	1227	2	learning	learning	NOUN
admet-2772	1227	3	for	for	ADP
admet-2772	1227	4	systems	system	NOUN
admet-2772	1227	5	pharmacology	pharmacology	NOUN
admet-2772	1227	6	-	-	PUNCT
admet-2772	1227	7	oriented	orient	VERB
admet-2772	1227	8	and	and	CCONJ
admet-2772	1227	9	personalized	personalized	ADJ
admet-2772	1227	10	drug	drug	NOUN
admet-2772	1227	11	design	design	NOUN
admet-2772	1227	12	.	.	PUNCT
admet-2772	1228	1	expert	expert	ADJ
admet-2772	1228	2	opinion	opinion	NOUN
admet-2772	1228	3	on	on	ADP
admet-2772	1228	4	drug	drug	NOUN
admet-2772	1228	5	discovery	discovery	NOUN
admet-2772	1228	6	17	17	NUM
admet-2772	1228	7	(	(	PUNCT
admet-2772	1228	8	2022	2022	NUM
admet-2772	1228	9	)	)	PUNCT
admet-2772	1228	10	849	849	NUM
admet-2772	1228	11	-	-	SYM
admet-2772	1228	12	863	863	NUM
admet-2772	1228	13	.	.	PUNCT
admet-2772	1229	1	https://doi.org/10.1080/17460441.2022.2072288	https://doi.org/10.1080/17460441.2022.2072288	NOUN
admet-2772	1230	1	[	[	X
admet-2772	1230	2	161	161	NUM
admet-2772	1230	3	]	]	PUNCT
admet-2772	1230	4	s.	s.	PROPN
admet-2772	1230	5	park	park	PROPN
admet-2772	1230	6	,	,	PUNCT
admet-2772	1230	7	y.h	y.h	PROPN
admet-2772	1230	8	.	.	PROPN
admet-2772	1230	9	ko	ko	PROPN
admet-2772	1230	10	,	,	PUNCT
admet-2772	1230	11	b.	b.	PROPN
admet-2772	1230	12	lee	lee	PROPN
admet-2772	1230	13	,	,	PUNCT
admet-2772	1230	14	b.	b.	PROPN
admet-2772	1230	15	shin	shin	PROPN
admet-2772	1230	16	,	,	PUNCT
admet-2772	1230	17	b.r	b.r	PROPN
admet-2772	1230	18	.	.	PROPN
admet-2772	1230	19	beck	beck	PROPN
admet-2772	1230	20	.	.	PUNCT
admet-2772	1231	1	abstract	abstract	ADJ
admet-2772	1231	2	35	35	NUM
admet-2772	1231	3	:	:	PUNCT
admet-2772	1231	4	molecular	molecular	ADJ
admet-2772	1231	5	optimization	optimization	NOUN
admet-2772	1231	6	of	of	ADP
admet-2772	1231	7	phase	phase	NOUN
admet-2772	1231	8	iii	iii	NUM
admet-2772	1231	9	trial	trial	NOUN
admet-2772	1231	10	failed	fail	VERB
admet-2772	1231	11	anticancer	anticancer	NOUN
admet-2772	1231	12	drugs	drug	NOUN
admet-2772	1231	13	using	use	VERB
admet-2772	1231	14	target	target	NOUN
admet-2772	1231	15	affinity	affinity	NOUN
admet-2772	1231	16	and	and	CCONJ
admet-2772	1231	17	toxicity	toxicity	NOUN
admet-2772	1231	18	-	-	PUNCT
admet-2772	1231	19	centered	center	VERB
admet-2772	1231	20	multiple	multiple	ADJ
admet-2772	1231	21	properties	property	NOUN
admet-2772	1231	22	reinforcement	reinforcement	NOUN
admet-2772	1231	23	learning	learning	NOUN
admet-2772	1231	24	.	.	PUNCT
admet-2772	1232	1	clinical	clinical	ADJ
admet-2772	1232	2	cancer	cancer	NOUN
admet-2772	1232	3	research	research	NOUN
admet-2772	1232	4	26	26	NUM
admet-2772	1232	5	(	(	PUNCT
admet-2772	1232	6	2020	2020	NUM
admet-2772	1232	7	)	)	PUNCT
admet-2772	1232	8	35	35	NUM
admet-2772	1232	9	-	-	SYM
admet-2772	1232	10	35	35	NUM
admet-2772	1232	11	.	.	PUNCT
admet-2772	1232	12	https://doi.org/10.1158/15573265.advprecmed20-35	https://doi.org/10.1158/15573265.advprecmed20-35	X
admet-2772	1233	1	[	[	X
admet-2772	1233	2	162	162	NUM
admet-2772	1233	3	]	]	X
admet-2772	1233	4	d.	d.	PROPN
admet-2772	1233	5	yuan	yuan	PROPN
admet-2772	1233	6	,	,	PUNCT
admet-2772	1233	7	h.	h.	PROPN
admet-2772	1233	8	he	he	PROPN
admet-2772	1233	9	,	,	PUNCT
admet-2772	1233	10	y.	y.	PROPN
admet-2772	1233	11	wu	wu	PROPN
admet-2772	1233	12	,	,	PUNCT
admet-2772	1233	13	j.	j.	PROPN
admet-2772	1233	14	fan	fan	PROPN
admet-2772	1233	15	,	,	PUNCT
admet-2772	1233	16	y.	y.	PROPN
admet-2772	1233	17	cao	cao	PROPN
admet-2772	1233	18	.	.	PUNCT
admet-2772	1234	1	physiologically	physiologically	ADV
admet-2772	1234	2	based	base	VERB
admet-2772	1234	3	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	1234	4	modeling	modeling	NOUN
admet-2772	1234	5	of	of	ADP
admet-2772	1234	6	nanoparticles	nanoparticle	NOUN
admet-2772	1234	7	.	.	PUNCT
admet-2772	1235	1	journal	journal	NOUN
admet-2772	1235	2	of	of	ADP
admet-2772	1235	3	pharmaceutical	pharmaceutical	PROPN
admet-2772	1235	4	sciences	science	NOUN
admet-2772	1235	5	108	108	NUM
admet-2772	1235	6	(	(	PUNCT
admet-2772	1235	7	2019	2019	NUM
admet-2772	1235	8	)	)	PUNCT
admet-2772	1235	9	58	58	NUM
admet-2772	1235	10	-	-	SYM
admet-2772	1235	11	72	72	NUM
admet-2772	1235	12	.	.	PUNCT
admet-2772	1236	1	https://doi.org/10.1016/j.xphs.2018.10.037	https://doi.org/10.1016/j.xphs.2018.10.037	NOUN
admet-2772	1236	2	[	[	X
admet-2772	1236	3	163	163	NUM
admet-2772	1236	4	]	]	X
admet-2772	1236	5	d.	d.	PROPN
admet-2772	1236	6	deepika	deepika	PROPN
admet-2772	1236	7	,	,	PUNCT
admet-2772	1236	8	v.	v.	PROPN
admet-2772	1236	9	kumar	kumar	PROPN
admet-2772	1236	10	.	.	PUNCT
admet-2772	1237	1	the	the	DET
admet-2772	1237	2	role	role	NOUN
admet-2772	1237	3	of	of	ADP
admet-2772	1237	4	“	"	PUNCT
admet-2772	1237	5	physiologically	physiologically	ADV
admet-2772	1237	6	based	base	VERB
admet-2772	1237	7	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	1237	8	model	model	NOUN
admet-2772	1237	9	(	(	PUNCT
admet-2772	1237	10	pbpk	pbpk	NOUN
admet-2772	1237	11	)	)	PUNCT
admet-2772	1237	12	”	"	PUNCT
admet-2772	1237	13	new	new	ADJ
admet-2772	1237	14	approach	approach	NOUN
admet-2772	1237	15	methodology	methodology	NOUN
admet-2772	1237	16	(	(	PUNCT
admet-2772	1237	17	nam	nam	NOUN
admet-2772	1237	18	)	)	PUNCT
admet-2772	1237	19	in	in	ADP
admet-2772	1237	20	pharmaceuticals	pharmaceutical	NOUN
admet-2772	1237	21	and	and	CCONJ
admet-2772	1237	22	environmental	environmental	ADJ
admet-2772	1237	23	chemical	chemical	NOUN
admet-2772	1237	24	risk	risk	NOUN
admet-2772	1237	25	assessment	assessment	NOUN
admet-2772	1237	26	.	.	PUNCT
admet-2772	1238	1	international	international	ADJ
admet-2772	1238	2	journal	journal	PROPN
admet-2772	1238	3	of	of	ADP
admet-2772	1238	4	environmental	environmental	ADJ
admet-2772	1238	5	research	research	NOUN
admet-2772	1238	6	and	and	CCONJ
admet-2772	1238	7	public	public	ADJ
admet-2772	1238	8	health	health	NOUN
admet-2772	1238	9	20	20	NUM
admet-2772	1238	10	(	(	PUNCT
admet-2772	1238	11	2023	2023	NUM
admet-2772	1238	12	)	)	PUNCT
admet-2772	1238	13	3473	3473	NUM
admet-2772	1238	14	.	.	PUNCT
admet-2772	1239	1	https://doi.org/10.3390/ijerph20043473	https://doi.org/10.3390/ijerph20043473	PROPN
admet-2772	1239	2	[	[	X
admet-2772	1239	3	164	164	NUM
admet-2772	1239	4	]	]	X
admet-2772	1239	5	y.	y.	PROPN
admet-2772	1239	6	kamiya	kamiya	PROPN
admet-2772	1239	7	,	,	PUNCT
admet-2772	1239	8	k.	k.	PROPN
admet-2772	1239	9	handa	handa	PROPN
admet-2772	1239	10	,	,	PUNCT
admet-2772	1239	11	t.	t.	PROPN
admet-2772	1239	12	miura	miura	PROPN
admet-2772	1239	13	,	,	PUNCT
admet-2772	1239	14	m.	m.	PROPN
admet-2772	1239	15	yanagi	yanagi	PROPN
admet-2772	1239	16	,	,	PUNCT
admet-2772	1239	17	k.	k.	PROPN
admet-2772	1239	18	shigeta	shigeta	PROPN
admet-2772	1239	19	,	,	PUNCT
admet-2772	1239	20	s.	s.	PROPN
admet-2772	1239	21	hina	hina	PROPN
admet-2772	1239	22	,	,	PUNCT
admet-2772	1239	23	m.	m.	PROPN
admet-2772	1239	24	shimizu	shimizu	PROPN
admet-2772	1239	25	,	,	PUNCT
admet-2772	1239	26	m.	m.	PROPN
admet-2772	1239	27	kitajima	kitajima	PROPN
admet-2772	1239	28	,	,	PUNCT
admet-2772	1239	29	f.	f.	PROPN
admet-2772	1239	30	shono	shono	PROPN
admet-2772	1239	31	,	,	PUNCT
admet-2772	1239	32	k.	k.	PROPN
admet-2772	1239	33	funatsu	funatsu	PROPN
admet-2772	1239	34	,	,	PUNCT
admet-2772	1239	35	h.	h.	PROPN
admet-2772	1239	36	yamazaki	yamazaki	PROPN
admet-2772	1239	37	.	.	PUNCT
admet-2772	1240	1	in	in	ADP
admet-2772	1240	2	silico	silico	NOUN
admet-2772	1240	3	prediction	prediction	NOUN
admet-2772	1240	4	of	of	ADP
admet-2772	1240	5	input	input	NOUN
admet-2772	1240	6	parameters	parameter	NOUN
admet-2772	1240	7	for	for	ADP
admet-2772	1240	8	simplified	simplified	ADJ
admet-2772	1240	9	physiologically	physiologically	ADV
admet-2772	1240	10	based	base	VERB
admet-2772	1240	11	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	1240	12	models	model	NOUN
admet-2772	1240	13	for	for	ADP
admet-2772	1240	14	estimating	estimate	VERB
admet-2772	1240	15	plasma	plasma	NOUN
admet-2772	1240	16	,	,	PUNCT
admet-2772	1240	17	liver	liver	NOUN
admet-2772	1240	18	,	,	PUNCT
admet-2772	1240	19	and	and	CCONJ
admet-2772	1240	20	kidney	kidney	NOUN
admet-2772	1240	21	exposures	exposure	NOUN
admet-2772	1240	22	in	in	ADP
admet-2772	1240	23	rats	rat	NOUN
admet-2772	1240	24	after	after	ADP
admet-2772	1240	25	oral	oral	ADJ
admet-2772	1240	26	doses	dose	NOUN
admet-2772	1240	27	of	of	ADP
admet-2772	1240	28	246	246	NUM
admet-2772	1240	29	disparate	disparate	ADJ
admet-2772	1240	30	chemicals	chemical	NOUN
admet-2772	1240	31	.	.	PUNCT
admet-2772	1241	1	chemical	chemical	ADJ
admet-2772	1241	2	research	research	NOUN
admet-2772	1241	3	in	in	ADP
admet-2772	1241	4	toxicology	toxicology	NOUN
admet-2772	1241	5	34	34	NUM
admet-2772	1241	6	(	(	PUNCT
admet-2772	1241	7	2021	2021	NUM
admet-2772	1241	8	)	)	PUNCT
admet-2772	1241	9	507	507	NUM
admet-2772	1241	10	-	-	SYM
admet-2772	1241	11	513	513	NUM
admet-2772	1241	12	.	.	PUNCT
admet-2772	1242	1	https://doi.org/10.1021/acs.chemrestox.0c00336	https://doi.org/10.1021/acs.chemrestox.0c00336	NOUN
admet-2772	1243	1	[	[	X
admet-2772	1243	2	165	165	NUM
admet-2772	1243	3	]	]	PUNCT
admet-2772	1243	4	w.c	w.c	PROPN
admet-2772	1243	5	.	.	PROPN
admet-2772	1243	6	chou	chou	PROPN
admet-2772	1243	7	,	,	PUNCT
admet-2772	1243	8	z.	z.	PROPN
admet-2772	1243	9	lin	lin	PROPN
admet-2772	1243	10	.	.	PUNCT
admet-2772	1243	11	machine	machine	NOUN
admet-2772	1243	12	learning	learning	NOUN
admet-2772	1243	13	and	and	CCONJ
admet-2772	1243	14	artificial	artificial	ADJ
admet-2772	1243	15	intelligence	intelligence	NOUN
admet-2772	1243	16	in	in	ADP
admet-2772	1243	17	physiologically	physiologically	ADV
admet-2772	1243	18	based	base	VERB
admet-2772	1243	19	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	1243	20	modeling	modeling	NOUN
admet-2772	1243	21	.	.	PUNCT
admet-2772	1244	1	toxicological	toxicological	ADJ
admet-2772	1244	2	sciences	science	NOUN
admet-2772	1244	3	191	191	NUM
admet-2772	1244	4	(	(	PUNCT
admet-2772	1244	5	2023	2023	NUM
admet-2772	1244	6	)	)	PUNCT
admet-2772	1244	7	1	1	NUM
admet-2772	1244	8	-	-	SYM
admet-2772	1244	9	14	14	NUM
admet-2772	1244	10	.	.	PUNCT
admet-2772	1245	1	https://doi.org/10.1093/toxsci/kfac101	https://doi.org/10.1093/toxsci/kfac101	PROPN
admet-2772	1245	2	https://doi.org/10.1021/acs.jcim.7b00414	https://doi.org/10.1021/acs.jcim.7b00414	PUNCT
admet-2772	1245	3	https://doi.org/10.3390/pharmaceutics16060776	https://doi.org/10.3390/pharmaceutics16060776	PROPN
admet-2772	1245	4	https://doi.org/10.1109/aimhc59811.2024.00029	https://doi.org/10.1109/aimhc59811.2024.00029	PROPN
admet-2772	1245	5	http://dx.doi.org/10.48550/arxiv.1701.04722	http://dx.doi.org/10.48550/arxiv.1701.04722	NOUN
admet-2772	1245	6	http://arxiv.org/abs/1706.01807	http://arxiv.org/abs/1706.01807	VERB
admet-2772	1245	7	https://doi.org/10.14573/altex.1610101	https://doi.org/10.14573/altex.1610101	PROPN
admet-2772	1245	8	https://doi.org/10.3390/pharmaceutics15071916	https://doi.org/10.3390/pharmaceutics15071916	PROPN
admet-2772	1245	9	https://doi.org/10.1021/acs.jcim.4c00772	https://doi.org/10.1021/acs.jcim.4c00772	NOUN
admet-2772	1245	10	https://doi.org/10.48550/arxiv.2310.01426	https://doi.org/10.48550/arxiv.2310.01426	PROPN
admet-2772	1245	11	https://doi.org/10.1080/17460441.2022.2072288	https://doi.org/10.1080/17460441.2022.2072288	PROPN
admet-2772	1245	12	https://doi.org/10.1158/1557-3265.advprecmed20-35	https://doi.org/10.1158/1557-3265.advprecmed20-35	NOUN
admet-2772	1245	13	https://doi.org/10.1158/1557-3265.advprecmed20-35	https://doi.org/10.1158/1557-3265.advprecmed20-35	VERB
admet-2772	1245	14	https://doi.org/10.1016/j.xphs.2018.10.037	https://doi.org/10.1016/j.xphs.2018.10.037	PROPN
admet-2772	1245	15	https://doi.org/10.3390/ijerph20043473	https://doi.org/10.3390/ijerph20043473	VERB
admet-2772	1245	16	https://doi.org/10.1021/acs.chemrestox.0c00336	https://doi.org/10.1021/acs.chemrestox.0c00336	NOUN
admet-2772	1245	17	https://doi.org/10.1093/toxsci/kfac101	https://doi.org/10.1093/toxsci/kfac101	PROPN
admet-2772	1245	18	admet	admet	PROPN
admet-2772	1245	19	&	&	CCONJ
admet-2772	1245	20	dmpk	dmpk	PROPN
admet-2772	1245	21	13(3	13(3	NUM
admet-2772	1245	22	)	)	PUNCT
admet-2772	1245	23	(	(	PUNCT
admet-2772	1245	24	2025	2025	NUM
admet-2772	1245	25	)	)	PUNCT
admet-2772	1245	26	2772	2772	NUM
admet-2772	1245	27	machine	machine	NOUN
admet-2772	1245	28	learning	learning	NOUN
admet-2772	1245	29	models	model	NOUN
admet-2772	1245	30	for	for	ADP
admet-2772	1245	31	admet	admet	ADJ
admet-2772	1245	32	prediction	prediction	NOUN
admet-2772	1245	33	in	in	ADP
admet-2772	1245	34	drug	drug	NOUN
admet-2772	1245	35	development	development	NOUN
admet-2772	1245	36	doi	doi	PROPN
admet-2772	1245	37	:	:	PUNCT
admet-2772	1245	38	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	1245	39	35	35	NUM
admet-2772	1245	40	[	[	SYM
admet-2772	1245	41	166	166	NUM
admet-2772	1245	42	]	]	X
admet-2772	1245	43	y.	y.	PROPN
admet-2772	1245	44	li	li	PROPN
admet-2772	1245	45	,	,	PUNCT
admet-2772	1245	46	z.	z.	PROPN
admet-2772	1245	47	wang	wang	PROPN
admet-2772	1245	48	,	,	PUNCT
admet-2772	1245	49	y.	y.	PROPN
admet-2772	1245	50	li	li	PROPN
admet-2772	1245	51	,	,	PUNCT
admet-2772	1245	52	j.	j.	PROPN
admet-2772	1245	53	du	du	PROPN
admet-2772	1245	54	,	,	PUNCT
admet-2772	1245	55	x.	x.	PROPN
admet-2772	1245	56	gao	gao	PROPN
admet-2772	1245	57	,	,	PUNCT
admet-2772	1245	58	y.	y.	PROPN
admet-2772	1245	59	li	li	PROPN
admet-2772	1245	60	,	,	PUNCT
admet-2772	1245	61	l.	l.	PROPN
admet-2772	1245	62	lai	lai	PROPN
admet-2772	1245	63	.	.	PUNCT
admet-2772	1246	1	a	a	DET
admet-2772	1246	2	combination	combination	NOUN
admet-2772	1246	3	of	of	ADP
admet-2772	1246	4	machine	machine	NOUN
admet-2772	1246	5	learning	learning	NOUN
admet-2772	1246	6	and	and	CCONJ
admet-2772	1246	7	pbpk	pbpk	NOUN
admet-2772	1246	8	modeling	model	VERB
admet-2772	1246	9	approach	approach	NOUN
admet-2772	1246	10	for	for	ADP
admet-2772	1246	11	pharmacokinetics	pharmacokinetic	NOUN
admet-2772	1246	12	prediction	prediction	NOUN
admet-2772	1246	13	of	of	ADP
admet-2772	1246	14	small	small	ADJ
admet-2772	1246	15	molecules	molecule	NOUN
admet-2772	1246	16	in	in	ADP
admet-2772	1246	17	humans	human	NOUN
admet-2772	1246	18	.	.	PUNCT
admet-2772	1247	1	pharmaceutical	pharmaceutical	NOUN
admet-2772	1247	2	research	research	NOUN
admet-2772	1247	3	41	41	NUM
admet-2772	1247	4	(	(	PUNCT
admet-2772	1247	5	2024	2024	NUM
admet-2772	1247	6	)	)	PUNCT
admet-2772	1247	7	1369	1369	NUM
admet-2772	1247	8	-	-	SYM
admet-2772	1247	9	1379	1379	NUM
admet-2772	1247	10	.	.	PUNCT
admet-2772	1248	1	https://doi.org/10.1007/s11095-024-03725-y	https://doi.org/10.1007/s11095-024-03725-y	X
admet-2772	1249	1	[	[	X
admet-2772	1249	2	167	167	NUM
admet-2772	1249	3	]	]	PUNCT
admet-2772	1249	4	d.	d.	PROPN
admet-2772	1249	5	naga	naga	PROPN
admet-2772	1249	6	,	,	PUNCT
admet-2772	1249	7	n.	n.	PROPN
admet-2772	1249	8	parrott	parrott	PROPN
admet-2772	1249	9	,	,	PUNCT
admet-2772	1249	10	g.f	g.f	PROPN
admet-2772	1249	11	.	.	PROPN
admet-2772	1249	12	ecker	ecker	PROPN
admet-2772	1249	13	,	,	PUNCT
admet-2772	1249	14	a.	a.	PROPN
admet-2772	1249	15	olivares	olivare	NOUN
admet-2772	1249	16	-	-	PUNCT
admet-2772	1249	17	morales	morale	NOUN
admet-2772	1249	18	.	.	PUNCT
admet-2772	1250	1	evaluation	evaluation	NOUN
admet-2772	1250	2	of	of	ADP
admet-2772	1250	3	the	the	DET
admet-2772	1250	4	success	success	NOUN
admet-2772	1250	5	of	of	ADP
admet-2772	1250	6	high	high	ADJ
admet-2772	1250	7	-	-	PUNCT
admet-2772	1250	8	throughput	throughput	NOUN
admet-2772	1250	9	physiologically	physiologically	ADV
admet-2772	1250	10	based	base	VERB
admet-2772	1250	11	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	1250	12	(	(	PUNCT
admet-2772	1250	13	ht	ht	NOUN
admet-2772	1250	14	-	-	PUNCT
admet-2772	1250	15	pbpk	pbpk	ADJ
admet-2772	1250	16	)	)	PUNCT
admet-2772	1250	17	modeling	model	VERB
admet-2772	1250	18	predictions	prediction	NOUN
admet-2772	1250	19	to	to	PART
admet-2772	1250	20	inform	inform	VERB
admet-2772	1250	21	early	early	ADJ
admet-2772	1250	22	drug	drug	NOUN
admet-2772	1250	23	discovery	discovery	NOUN
admet-2772	1250	24	.	.	PUNCT
admet-2772	1251	1	molecular	molecular	ADJ
admet-2772	1251	2	pharmaceutics	pharmaceutic	NOUN
admet-2772	1251	3	19	19	NUM
admet-2772	1251	4	(	(	PUNCT
admet-2772	1251	5	2022	2022	NUM
admet-2772	1251	6	)	)	PUNCT
admet-2772	1251	7	2203	2203	NUM
admet-2772	1251	8	-	-	SYM
admet-2772	1251	9	2216	2216	NUM
admet-2772	1251	10	.	.	PUNCT
admet-2772	1252	1	https://doi.org/10.1021/acs.molpharmaceut.2c00040	https://doi.org/10.1021/acs.molpharmaceut.2c00040	NOUN
admet-2772	1253	1	[	[	X
admet-2772	1253	2	168	168	NUM
admet-2772	1253	3	]	]	PUNCT
admet-2772	1253	4	s.	s.	PROPN
admet-2772	1253	5	habiballah	habiballah	PROPN
admet-2772	1253	6	,	,	PUNCT
admet-2772	1253	7	b.	b.	PROPN
admet-2772	1253	8	reisfeld	reisfeld	PROPN
admet-2772	1253	9	.	.	PUNCT
admet-2772	1254	1	adapting	adapt	VERB
admet-2772	1254	2	physiologically	physiologically	ADV
admet-2772	1254	3	-	-	PUNCT
admet-2772	1254	4	based	base	VERB
admet-2772	1254	5	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	1254	6	models	model	NOUN
admet-2772	1254	7	for	for	ADP
admet-2772	1254	8	machine	machine	NOUN
admet-2772	1254	9	learning	learn	VERB
admet-2772	1254	10	applications	application	NOUN
admet-2772	1254	11	.	.	PUNCT
admet-2772	1255	1	scientific	scientific	ADJ
admet-2772	1255	2	reports	report	NOUN
admet-2772	1255	3	13	13	NUM
admet-2772	1255	4	(	(	PUNCT
admet-2772	1255	5	2023	2023	NUM
admet-2772	1255	6	)	)	PUNCT
admet-2772	1255	7	14934	14934	NUM
admet-2772	1255	8	.	.	PUNCT
admet-2772	1256	1	https://doi.org/10.1038/s41598-02342165-3	https://doi.org/10.1038/s41598-02342165-3	PROPN
admet-2772	1257	1	[	[	X
admet-2772	1257	2	169	169	NUM
admet-2772	1257	3	]	]	X
admet-2772	1257	4	y.	y.	PROPN
admet-2772	1257	5	zhang	zhang	PROPN
admet-2772	1257	6	,	,	PUNCT
admet-2772	1257	7	q.	q.	PROPN
admet-2772	1257	8	yang	yang	PROPN
admet-2772	1257	9	.	.	PUNCT
admet-2772	1258	1	an	an	DET
admet-2772	1258	2	overview	overview	NOUN
admet-2772	1258	3	of	of	ADP
admet-2772	1258	4	multi	multi	ADJ
admet-2772	1258	5	-	-	ADJ
admet-2772	1258	6	task	task	ADJ
admet-2772	1258	7	learning	learning	NOUN
admet-2772	1258	8	.	.	PUNCT
admet-2772	1259	1	national	national	PROPN
admet-2772	1259	2	science	science	PROPN
admet-2772	1259	3	review	review	PROPN
admet-2772	1259	4	5	5	NUM
admet-2772	1259	5	(	(	PUNCT
admet-2772	1259	6	2018	2018	NUM
admet-2772	1259	7	)	)	PUNCT
admet-2772	1259	8	30	30	NUM
admet-2772	1259	9	-	-	SYM
admet-2772	1259	10	43	43	NUM
admet-2772	1259	11	.	.	PUNCT
admet-2772	1260	1	https://doi.org/10.1093/nsr/nwx105	https://doi.org/10.1093/nsr/nwx105	PROPN
admet-2772	1261	1	[	[	X
admet-2772	1261	2	170	170	NUM
admet-2772	1261	3	]	]	PUNCT
admet-2772	1261	4	s.	s.	PROPN
admet-2772	1261	5	zhang	zhang	PROPN
admet-2772	1261	6	,	,	PUNCT
admet-2772	1261	7	x.	x.	PROPN
admet-2772	1261	8	luo	luo	PROPN
admet-2772	1261	9	,	,	PUNCT
admet-2772	1261	10	b.	b.	PROPN
admet-2772	1261	11	mai	mai	PROPN
admet-2772	1261	12	.	.	PUNCT
admet-2772	1262	1	multi	multi	ADJ
admet-2772	1262	2	-	-	ADJ
admet-2772	1262	3	task	task	ADJ
admet-2772	1262	4	machine	machine	NOUN
admet-2772	1262	5	learning	learning	NOUN
admet-2772	1262	6	models	model	NOUN
admet-2772	1262	7	for	for	ADP
admet-2772	1262	8	simultaneous	simultaneous	ADJ
admet-2772	1262	9	prediction	prediction	NOUN
admet-2772	1262	10	of	of	ADP
admet-2772	1262	11	tissueto	tissueto	NOUN
admet-2772	1262	12	-	-	PUNCT
admet-2772	1262	13	blood	blood	NOUN
admet-2772	1262	14	partition	partition	NOUN
admet-2772	1262	15	coefficients	coefficient	NOUN
admet-2772	1262	16	of	of	ADP
admet-2772	1262	17	chemicals	chemical	NOUN
admet-2772	1262	18	in	in	ADP
admet-2772	1262	19	mammals	mammal	NOUN
admet-2772	1262	20	.	.	PUNCT
admet-2772	1263	1	environmental	environmental	ADJ
admet-2772	1263	2	research	research	NOUN
admet-2772	1263	3	241	241	NUM
admet-2772	1263	4	(	(	PUNCT
admet-2772	1263	5	2024	2024	NUM
admet-2772	1263	6	)	)	PUNCT
admet-2772	1263	7	117603	117603	NUM
admet-2772	1263	8	.	.	PUNCT
admet-2772	1264	1	https://doi.org/10.1016/j.envres.2023.117603	https://doi.org/10.1016/j.envres.2023.117603	NOUN
admet-2772	1264	2	[	[	X
admet-2772	1264	3	171	171	NUM
admet-2772	1264	4	]	]	X
admet-2772	1264	5	m.	m.	PROPN
admet-2772	1264	6	walter	walter	PROPN
admet-2772	1264	7	,	,	PUNCT
admet-2772	1264	8	j.m	j.m	PROPN
admet-2772	1264	9	.	.	PROPN
admet-2772	1264	10	borghardt	borghardt	NOUN
admet-2772	1264	11	,	,	PUNCT
admet-2772	1264	12	l.	l.	PROPN
admet-2772	1264	13	humbeck	humbeck	PROPN
admet-2772	1264	14	,	,	PUNCT
admet-2772	1264	15	m.	m.	NOUN
admet-2772	1264	16	skalic	skalic	PROPN
admet-2772	1264	17	.	.	PUNCT
admet-2772	1265	1	multi	multi	ADJ
admet-2772	1265	2	-	-	NOUN
admet-2772	1265	3	task	task	ADJ
admet-2772	1265	4	adme	adme	NOUN
admet-2772	1265	5	/	/	SYM
admet-2772	1265	6	pk	pk	NOUN
admet-2772	1265	7	prediction	prediction	NOUN
admet-2772	1265	8	at	at	ADP
admet-2772	1265	9	industrial	industrial	ADJ
admet-2772	1265	10	scale	scale	NOUN
admet-2772	1265	11	:	:	PUNCT
admet-2772	1265	12	leveraging	leverage	VERB
admet-2772	1265	13	large	large	ADJ
admet-2772	1265	14	and	and	CCONJ
admet-2772	1265	15	diverse	diverse	ADJ
admet-2772	1265	16	experimental	experimental	ADJ
admet-2772	1265	17	datasets	dataset	NOUN
admet-2772	1265	18	.	.	PUNCT
admet-2772	1266	1	chemrxiv	chemrxiv	PROPN
admet-2772	1266	2	(	(	PUNCT
admet-2772	1266	3	2024	2024	NUM
admet-2772	1266	4	)	)	PUNCT
admet-2772	1266	5	e202400079	e202400079	PROPN
admet-2772	1266	6	.	.	PROPN
admet-2772	1266	7	https://doi.org/10.1002/minf.202400079	https://doi.org/10.1002/minf.202400079	PROPN
admet-2772	1267	1	[	[	X
admet-2772	1267	2	172	172	NUM
admet-2772	1267	3	]	]	PUNCT
admet-2772	1267	4	z.	z.	PROPN
admet-2772	1267	5	zhao	zhao	PROPN
admet-2772	1267	6	,	,	PUNCT
admet-2772	1267	7	l.	l.	PROPN
admet-2772	1267	8	alzubaidi	alzubaidi	PROPN
admet-2772	1267	9	,	,	PUNCT
admet-2772	1267	10	j.	j.	PROPN
admet-2772	1267	11	zhang	zhang	PROPN
admet-2772	1267	12	,	,	PUNCT
admet-2772	1267	13	y.	y.	PROPN
admet-2772	1267	14	duan	duan	PROPN
admet-2772	1267	15	,	,	PUNCT
admet-2772	1267	16	y.	y.	PROPN
admet-2772	1267	17	gu	gu	PROPN
admet-2772	1267	18	.	.	PUNCT
admet-2772	1268	1	a	a	DET
admet-2772	1268	2	comparison	comparison	NOUN
admet-2772	1268	3	review	review	NOUN
admet-2772	1268	4	of	of	ADP
admet-2772	1268	5	transfer	transfer	NOUN
admet-2772	1268	6	learning	learning	NOUN
admet-2772	1268	7	and	and	CCONJ
admet-2772	1268	8	selfsupervised	selfsupervise	VERB
admet-2772	1268	9	learning	learning	NOUN
admet-2772	1268	10	:	:	PUNCT
admet-2772	1268	11	definitions	definition	NOUN
admet-2772	1268	12	,	,	PUNCT
admet-2772	1268	13	applications	application	NOUN
admet-2772	1268	14	,	,	PUNCT
admet-2772	1268	15	advantages	advantage	NOUN
admet-2772	1268	16	and	and	CCONJ
admet-2772	1268	17	limitations	limitation	NOUN
admet-2772	1268	18	.	.	PUNCT
admet-2772	1269	1	expert	expert	NOUN
admet-2772	1269	2	systems	system	NOUN
admet-2772	1269	3	with	with	ADP
admet-2772	1269	4	applications	application	NOUN
admet-2772	1269	5	242	242	NUM
admet-2772	1269	6	(	(	PUNCT
admet-2772	1269	7	2024	2024	NUM
admet-2772	1269	8	)	)	PUNCT
admet-2772	1269	9	122807	122807	NUM
admet-2772	1269	10	.	.	PUNCT
admet-2772	1270	1	https://doi.org/10.1016/j.eswa.2023.122807	https://doi.org/10.1016/j.eswa.2023.122807	PROPN
admet-2772	1270	2	[	[	X
admet-2772	1270	3	173	173	NUM
admet-2772	1270	4	]	]	X
admet-2772	1270	5	z.	z.	PROPN
admet-2772	1270	6	ye	ye	PROPN
admet-2772	1270	7	,	,	PUNCT
admet-2772	1270	8	y.	y.	PROPN
admet-2772	1270	9	yang	yang	PROPN
admet-2772	1270	10	,	,	PUNCT
admet-2772	1270	11	x.	x.	PROPN
admet-2772	1270	12	li	li	PROPN
admet-2772	1270	13	,	,	PUNCT
admet-2772	1270	14	d.	d.	PROPN
admet-2772	1270	15	cao	cao	PROPN
admet-2772	1270	16	,	,	PUNCT
admet-2772	1270	17	d.	d.	PROPN
admet-2772	1270	18	ouyang	ouyang	PROPN
admet-2772	1270	19	.	.	PUNCT
admet-2772	1271	1	an	an	DET
admet-2772	1271	2	integrated	integrate	VERB
admet-2772	1271	3	transfer	transfer	NOUN
admet-2772	1271	4	learning	learning	NOUN
admet-2772	1271	5	and	and	CCONJ
admet-2772	1271	6	multitask	multitask	PROPN
admet-2772	1271	7	learning	learn	VERB
admet-2772	1271	8	approach	approach	NOUN
admet-2772	1271	9	for	for	ADP
admet-2772	1271	10	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	1271	11	parameter	parameter	NOUN
admet-2772	1271	12	prediction	prediction	NOUN
admet-2772	1271	13	.	.	PUNCT
admet-2772	1272	1	molecular	molecular	ADJ
admet-2772	1272	2	pharmaceutics	pharmaceutic	NOUN
admet-2772	1272	3	16	16	NUM
admet-2772	1272	4	(	(	PUNCT
admet-2772	1272	5	2019	2019	NUM
admet-2772	1272	6	)	)	PUNCT
admet-2772	1272	7	533	533	NUM
admet-2772	1272	8	-	-	SYM
admet-2772	1272	9	541	541	NUM
admet-2772	1272	10	.	.	PUNCT
admet-2772	1273	1	https://doi.org/10.1021/acs.molpharmaceut.8b00816	https://doi.org/10.1021/acs.molpharmaceut.8b00816	PRON
admet-2772	1274	1	[	[	X
admet-2772	1274	2	174	174	NUM
admet-2772	1274	3	]	]	PUNCT
admet-2772	1274	4	k.	k.	PROPN
admet-2772	1274	5	abbasi	abbasi	PROPN
admet-2772	1274	6	,	,	PUNCT
admet-2772	1274	7	a.	a.	PROPN
admet-2772	1274	8	poso	poso	PROPN
admet-2772	1274	9	,	,	PUNCT
admet-2772	1274	10	j.	j.	PROPN
admet-2772	1274	11	ghasemi	ghasemi	PROPN
admet-2772	1274	12	,	,	PUNCT
admet-2772	1274	13	m.	m.	NOUN
admet-2772	1274	14	amanlou	amanlou	NOUN
admet-2772	1274	15	,	,	PUNCT
admet-2772	1274	16	a.	a.	NOUN
admet-2772	1274	17	masoudi	masoudi	PROPN
admet-2772	1274	18	-	-	PUNCT
admet-2772	1274	19	nejad	nejad	PROPN
admet-2772	1274	20	.	.	PUNCT
admet-2772	1275	1	deep	deep	ADJ
admet-2772	1275	2	transferable	transferable	ADJ
admet-2772	1275	3	compound	compound	NOUN
admet-2772	1275	4	representation	representation	NOUN
admet-2772	1275	5	across	across	ADP
admet-2772	1275	6	domains	domain	NOUN
admet-2772	1275	7	and	and	CCONJ
admet-2772	1275	8	tasks	task	NOUN
admet-2772	1275	9	for	for	ADP
admet-2772	1275	10	low	low	ADJ
admet-2772	1275	11	data	datum	NOUN
admet-2772	1275	12	drug	drug	NOUN
admet-2772	1275	13	discovery	discovery	NOUN
admet-2772	1275	14	.	.	PUNCT
admet-2772	1276	1	journal	journal	PROPN
admet-2772	1276	2	of	of	ADP
admet-2772	1276	3	chemical	chemical	ADJ
admet-2772	1276	4	information	information	NOUN
admet-2772	1276	5	and	and	CCONJ
admet-2772	1276	6	modeling	modeling	NOUN
admet-2772	1276	7	(	(	PUNCT
admet-2772	1276	8	2019	2019	NUM
admet-2772	1276	9	)	)	PUNCT
admet-2772	1276	10	4528	4528	NUM
admet-2772	1276	11	-	-	SYM
admet-2772	1276	12	4539	4539	NUM
admet-2772	1276	13	.	.	PUNCT
admet-2772	1277	1	https://doi.org/10.1021/acs.jcim.9b00626	https://doi.org/10.1021/acs.jcim.9b00626	X
admet-2772	1278	1	[	[	X
admet-2772	1278	2	175	175	NUM
admet-2772	1278	3	]	]	PUNCT
admet-2772	1278	4	s.	s.	PROPN
admet-2772	1278	5	wang	wang	PROPN
admet-2772	1278	6	,	,	PUNCT
admet-2772	1278	7	y.	y.	PROPN
admet-2772	1278	8	guo	guo	PROPN
admet-2772	1278	9	,	,	PUNCT
admet-2772	1278	10	y.	y.	PROPN
admet-2772	1278	11	wang	wang	PROPN
admet-2772	1278	12	,	,	PUNCT
admet-2772	1278	13	h.	h.	PROPN
admet-2772	1278	14	sun	sun	PROPN
admet-2772	1278	15	,	,	PUNCT
admet-2772	1278	16	j.	j.	PROPN
admet-2772	1278	17	huang	huang	PROPN
admet-2772	1278	18	.	.	PROPN
admet-2772	1279	1	smiles	smile	NOUN
admet-2772	1279	2	-	-	PUNCT
admet-2772	1279	3	bert	bert	ADJ
admet-2772	1279	4	:	:	PUNCT
admet-2772	1279	5	large	large	ADJ
admet-2772	1279	6	scale	scale	NOUN
admet-2772	1279	7	unsupervised	unsupervised	ADJ
admet-2772	1279	8	pre	pre	NOUN
admet-2772	1279	9	-	-	NOUN
admet-2772	1279	10	training	training	NOUN
admet-2772	1279	11	for	for	ADP
admet-2772	1279	12	molecular	molecular	ADJ
admet-2772	1279	13	property	property	NOUN
admet-2772	1279	14	prediction	prediction	NOUN
admet-2772	1279	15	.	.	PUNCT
admet-2772	1280	1	acm	acm	PROPN
admet-2772	1280	2	-	-	PUNCT
admet-2772	1280	3	bcb	bcb	PROPN
admet-2772	1280	4	2019	2019	NUM
admet-2772	1280	5	proceedings	proceeding	NOUN
admet-2772	1280	6	of	of	ADP
admet-2772	1280	7	the	the	DET
admet-2772	1280	8	10th	10th	ADJ
admet-2772	1280	9	acm	acm	PROPN
admet-2772	1280	10	international	international	ADJ
admet-2772	1280	11	conference	conference	NOUN
admet-2772	1280	12	on	on	ADP
admet-2772	1280	13	bioinformatics	bioinformatics	NOUN
admet-2772	1280	14	,	,	PUNCT
admet-2772	1280	15	computational	computational	ADJ
admet-2772	1280	16	biology	biology	NOUN
admet-2772	1280	17	and	and	CCONJ
admet-2772	1280	18	health	health	NOUN
admet-2772	1280	19	informatics	informatic	NOUN
admet-2772	1280	20	(	(	PUNCT
admet-2772	1280	21	2019	2019	NUM
admet-2772	1280	22	)	)	PUNCT
admet-2772	1280	23	429	429	NUM
admet-2772	1280	24	-	-	SYM
admet-2772	1280	25	436	436	NUM
admet-2772	1280	26	.	.	PUNCT
admet-2772	1281	1	https://doi.org/10.1145/3307339.3342186	https://doi.org/10.1145/3307339.3342186	X
admet-2772	1282	1	[	[	X
admet-2772	1282	2	176	176	X
admet-2772	1282	3	]	]	PUNCT
admet-2772	1282	4	x.	x.	NOUN
admet-2772	1282	5	li	li	PROPN
admet-2772	1282	6	,	,	PUNCT
admet-2772	1282	7	d.	d.	PROPN
admet-2772	1282	8	fourches	fourches	PROPN
admet-2772	1282	9	.	.	PUNCT
admet-2772	1283	1	inductive	inductive	ADJ
admet-2772	1283	2	transfer	transfer	NOUN
admet-2772	1283	3	learning	learning	NOUN
admet-2772	1283	4	for	for	ADP
admet-2772	1283	5	molecular	molecular	ADJ
admet-2772	1283	6	activity	activity	NOUN
admet-2772	1283	7	prediction	prediction	NOUN
admet-2772	1283	8	:	:	PUNCT
admet-2772	1283	9	next	next	ADJ
admet-2772	1283	10	-	-	PUNCT
admet-2772	1283	11	gen	gen	NOUN
admet-2772	1283	12	qsar	qsar	NOUN
admet-2772	1283	13	models	model	NOUN
admet-2772	1283	14	with	with	ADP
admet-2772	1283	15	molpmofit	molpmofit	NOUN
admet-2772	1283	16	.	.	PUNCT
admet-2772	1284	1	journal	journal	PROPN
admet-2772	1284	2	of	of	ADP
admet-2772	1284	3	cheminformatics	cheminformatic	NOUN
admet-2772	1284	4	12	12	NUM
admet-2772	1284	5	(	(	PUNCT
admet-2772	1284	6	2020	2020	NUM
admet-2772	1284	7	)	)	PUNCT
admet-2772	1284	8	27	27	NUM
admet-2772	1284	9	.	.	PUNCT
admet-2772	1285	1	https://doi.org/10.1186/s13321-020-00430-x	https://doi.org/10.1186/s13321-020-00430-x	NOUN
admet-2772	1285	2	[	[	X
admet-2772	1285	3	177	177	NUM
admet-2772	1285	4	]	]	PUNCT
admet-2772	1285	5	s.	s.	PROPN
admet-2772	1285	6	zhang	zhang	PROPN
admet-2772	1285	7	,	,	PUNCT
admet-2772	1285	8	z.	z.	PROPN
admet-2772	1285	9	yan	yan	PROPN
admet-2772	1285	10	,	,	PUNCT
admet-2772	1285	11	y.	y.	PROPN
admet-2772	1285	12	huang	huang	PROPN
admet-2772	1285	13	,	,	PUNCT
admet-2772	1285	14	l.	l.	PROPN
admet-2772	1285	15	liu	liu	PROPN
admet-2772	1285	16	,	,	PUNCT
admet-2772	1285	17	d.	d.	PROPN
admet-2772	1285	18	he	he	PRON
admet-2772	1285	19	,	,	PUNCT
admet-2772	1285	20	w.	w.	PROPN
admet-2772	1285	21	wang	wang	PROPN
admet-2772	1285	22	,	,	PUNCT
admet-2772	1285	23	x.	x.	PROPN
admet-2772	1285	24	fang	fang	PROPN
admet-2772	1285	25	,	,	PUNCT
admet-2772	1285	26	x.	x.	PROPN
admet-2772	1285	27	zhang	zhang	PROPN
admet-2772	1285	28	,	,	PUNCT
admet-2772	1285	29	f.	f.	PROPN
admet-2772	1285	30	wang	wang	PROPN
admet-2772	1285	31	,	,	PUNCT
admet-2772	1285	32	h.	h.	PROPN
admet-2772	1285	33	wu	wu	PROPN
admet-2772	1285	34	,	,	PUNCT
admet-2772	1285	35	h.	h.	PROPN
admet-2772	1285	36	wang	wang	PROPN
admet-2772	1285	37	.	.	PUNCT
admet-2772	1286	1	helixadmet	helixadmet	PROPN
admet-2772	1286	2	:	:	PUNCT
admet-2772	1286	3	a	a	DET
admet-2772	1286	4	robust	robust	ADJ
admet-2772	1286	5	and	and	CCONJ
admet-2772	1286	6	endpoint	endpoint	VERB
admet-2772	1286	7	extensible	extensible	ADJ
admet-2772	1286	8	admet	admet	NOUN
admet-2772	1286	9	system	system	NOUN
admet-2772	1286	10	incorporating	incorporate	VERB
admet-2772	1286	11	self	self	NOUN
admet-2772	1286	12	-	-	PUNCT
admet-2772	1286	13	supervised	supervise	VERB
admet-2772	1286	14	knowledge	knowledge	NOUN
admet-2772	1286	15	transfer	transfer	NOUN
admet-2772	1286	16	.	.	PUNCT
admet-2772	1287	1	bioinformatics	bioinformatic	NOUN
admet-2772	1287	2	38	38	NUM
admet-2772	1287	3	(	(	PUNCT
admet-2772	1287	4	2022	2022	NUM
admet-2772	1287	5	)	)	PUNCT
admet-2772	1287	6	3444	3444	NUM
admet-2772	1287	7	-	-	SYM
admet-2772	1287	8	3453	3453	NUM
admet-2772	1287	9	.	.	PUNCT
admet-2772	1288	1	https://doi.org/10.1093/bioinformatics/btac342	https://doi.org/10.1093/bioinformatics/btac342	NOUN
admet-2772	1289	1	[	[	X
admet-2772	1289	2	178	178	NUM
admet-2772	1289	3	]	]	X
admet-2772	1289	4	w.	w.	PROPN
admet-2772	1289	5	jung	jung	PROPN
admet-2772	1289	6	,	,	PUNCT
admet-2772	1289	7	s.	s.	PROPN
admet-2772	1289	8	goo	goo	PROPN
admet-2772	1289	9	,	,	PUNCT
admet-2772	1289	10	t.	t.	PROPN
admet-2772	1289	11	hwang	hwang	PROPN
admet-2772	1289	12	,	,	PUNCT
admet-2772	1289	13	h.	h.	PROPN
admet-2772	1289	14	lee	lee	PROPN
admet-2772	1289	15	,	,	PUNCT
admet-2772	1289	16	y.k	y.k	PROPN
admet-2772	1289	17	.	.	PROPN
admet-2772	1289	18	kim	kim	PROPN
admet-2772	1289	19	,	,	PUNCT
admet-2772	1289	20	j.w	j.w	PROPN
admet-2772	1289	21	.	.	PUNCT
admet-2772	1289	22	chae	chae	PROPN
admet-2772	1289	23	,	,	PUNCT
admet-2772	1289	24	h.y	h.y	PROPN
admet-2772	1289	25	.	.	PROPN
admet-2772	1289	26	yun	yun	PROPN
admet-2772	1289	27	,	,	PUNCT
admet-2772	1289	28	s.	s.	PROPN
admet-2772	1289	29	jung	jung	PROPN
admet-2772	1289	30	.	.	PUNCT
admet-2772	1290	1	absorption	absorption	NOUN
admet-2772	1290	2	distribution	distribution	NOUN
admet-2772	1290	3	metabolism	metabolism	NOUN
admet-2772	1290	4	excretion	excretion	NOUN
admet-2772	1290	5	and	and	CCONJ
admet-2772	1290	6	toxicity	toxicity	NOUN
admet-2772	1290	7	property	property	NOUN
admet-2772	1290	8	prediction	prediction	NOUN
admet-2772	1290	9	utilizing	utilize	VERB
admet-2772	1290	10	a	a	DET
admet-2772	1290	11	pre	pre	ADJ
admet-2772	1290	12	-	-	ADJ
admet-2772	1290	13	trained	train	VERB
admet-2772	1290	14	natural	natural	ADJ
admet-2772	1290	15	language	language	NOUN
admet-2772	1290	16	processing	processing	NOUN
admet-2772	1290	17	model	model	NOUN
admet-2772	1290	18	and	and	CCONJ
admet-2772	1290	19	its	its	PRON
admet-2772	1290	20	applications	application	NOUN
admet-2772	1290	21	in	in	ADP
admet-2772	1290	22	early	early	ADJ
admet-2772	1290	23	-	-	PUNCT
admet-2772	1290	24	stage	stage	NOUN
admet-2772	1290	25	drug	drug	NOUN
admet-2772	1290	26	development	development	NOUN
admet-2772	1290	27	.	.	PUNCT
admet-2772	1291	1	pharmaceuticals	pharmaceutical	NOUN
admet-2772	1291	2	17	17	NUM
admet-2772	1291	3	(	(	PUNCT
admet-2772	1291	4	2024	2024	NUM
admet-2772	1291	5	)	)	PUNCT
admet-2772	1291	6	382	382	NUM
admet-2772	1291	7	.	.	PUNCT
admet-2772	1292	1	https://doi.org/10.3390/ph17030382	https://doi.org/10.3390/ph17030382	X
admet-2772	1293	1	[	[	X
admet-2772	1293	2	179	179	NUM
admet-2772	1293	3	]	]	PUNCT
admet-2772	1293	4	j.	j.	PROPN
admet-2772	1293	5	wenzel	wenzel	PROPN
admet-2772	1293	6	,	,	PUNCT
admet-2772	1293	7	h.	h.	PROPN
admet-2772	1293	8	matter	matter	NOUN
admet-2772	1293	9	,	,	PUNCT
admet-2772	1293	10	f.	f.	PROPN
admet-2772	1293	11	schmidt	schmidt	PROPN
admet-2772	1293	12	.	.	PUNCT
admet-2772	1294	1	predictive	predictive	ADJ
admet-2772	1294	2	multitask	multitask	PROPN
admet-2772	1294	3	deep	deep	ADJ
admet-2772	1294	4	neural	neural	ADJ
admet-2772	1294	5	network	network	NOUN
admet-2772	1294	6	models	model	NOUN
admet-2772	1294	7	for	for	ADP
admet-2772	1294	8	adme	adme	NOUN
admet-2772	1294	9	-	-	PUNCT
admet-2772	1294	10	tox	tox	NOUN
admet-2772	1294	11	properties	property	NOUN
admet-2772	1294	12	:	:	PUNCT
admet-2772	1294	13	learning	learn	VERB
admet-2772	1294	14	from	from	ADP
admet-2772	1294	15	large	large	ADJ
admet-2772	1294	16	data	datum	NOUN
admet-2772	1294	17	sets	set	NOUN
admet-2772	1294	18	.	.	PUNCT
admet-2772	1295	1	journal	journal	NOUN
admet-2772	1295	2	of	of	ADP
admet-2772	1295	3	chemical	chemical	ADJ
admet-2772	1295	4	information	information	NOUN
admet-2772	1295	5	and	and	CCONJ
admet-2772	1295	6	modeling	model	VERB
admet-2772	1295	7	59	59	NUM
admet-2772	1295	8	(	(	PUNCT
admet-2772	1295	9	2019	2019	NUM
admet-2772	1295	10	)	)	PUNCT
admet-2772	1295	11	1253	1253	NUM
admet-2772	1295	12	-	-	SYM
admet-2772	1295	13	1268	1268	NUM
admet-2772	1295	14	.	.	PUNCT
admet-2772	1296	1	https://doi.org/10.4155/fmc-2021-0138	https://doi.org/10.4155/fmc-2021-0138	PROPN
admet-2772	1297	1	[	[	X
admet-2772	1297	2	180	180	NUM
admet-2772	1297	3	]	]	PUNCT
admet-2772	1297	4	w.	w.	PROPN
admet-2772	1297	5	saeed	saeed	PROPN
admet-2772	1297	6	,	,	PUNCT
admet-2772	1297	7	c.	c.	PROPN
admet-2772	1297	8	omlin	omlin	PROPN
admet-2772	1297	9	.	.	PUNCT
admet-2772	1298	1	explainable	explainable	ADJ
admet-2772	1298	2	ai	ai	PROPN
admet-2772	1298	3	(	(	PUNCT
admet-2772	1298	4	xai	xai	PROPN
admet-2772	1298	5	):	):	PUNCT
admet-2772	1298	6	a	a	DET
admet-2772	1298	7	systematic	systematic	ADJ
admet-2772	1298	8	meta	meta	NOUN
admet-2772	1298	9	-	-	PUNCT
admet-2772	1298	10	survey	survey	NOUN
admet-2772	1298	11	of	of	ADP
admet-2772	1298	12	current	current	ADJ
admet-2772	1298	13	challenges	challenge	NOUN
admet-2772	1298	14	and	and	CCONJ
admet-2772	1298	15	future	future	ADJ
admet-2772	1298	16	opportunities	opportunity	NOUN
admet-2772	1298	17	.	.	PUNCT
admet-2772	1299	1	knowledge	knowledge	NOUN
admet-2772	1299	2	-	-	PUNCT
admet-2772	1299	3	based	base	VERB
admet-2772	1299	4	systems	system	NOUN
admet-2772	1299	5	263	263	NUM
admet-2772	1299	6	(	(	PUNCT
admet-2772	1299	7	2023	2023	NUM
admet-2772	1299	8	)	)	PUNCT
admet-2772	1299	9	110273	110273	NUM
admet-2772	1299	10	.	.	PUNCT
admet-2772	1300	1	https://doi.org/10.1016/j.knosys.2023.110273	https://doi.org/10.1016/j.knosys.2023.110273	PROPN
admet-2772	1301	1	[	[	X
admet-2772	1301	2	181	181	NUM
admet-2772	1301	3	]	]	X
admet-2772	1301	4	r.	r.	PROPN
admet-2772	1301	5	alizadehsani	alizadehsani	PROPN
admet-2772	1301	6	,	,	PUNCT
admet-2772	1301	7	s.s	s.s	PROPN
admet-2772	1301	8	.	.	PROPN
admet-2772	1301	9	oyelere	oyelere	PROPN
admet-2772	1301	10	,	,	PUNCT
admet-2772	1301	11	s.	s.	PROPN
admet-2772	1301	12	hussain	hussain	PROPN
admet-2772	1301	13	,	,	PUNCT
admet-2772	1301	14	s.k	s.k	PROPN
admet-2772	1301	15	.	.	PROPN
admet-2772	1301	16	jagatheesaperumal	jagatheesaperumal	PROPN
admet-2772	1301	17	,	,	PUNCT
admet-2772	1301	18	r.r	r.r	PROPN
admet-2772	1301	19	.	.	PROPN
admet-2772	1301	20	calixto	calixto	PROPN
admet-2772	1301	21	,	,	PUNCT
admet-2772	1301	22	m.	m.	NOUN
admet-2772	1301	23	rahouti	rahouti	NOUN
admet-2772	1301	24	,	,	PUNCT
admet-2772	1301	25	m.	m.	NOUN
admet-2772	1301	26	roshanzamir	roshanzamir	NOUN
admet-2772	1301	27	,	,	PUNCT
admet-2772	1301	28	v.h.c	v.h.c	NOUN
admet-2772	1301	29	.	.	PROPN
admet-2772	1301	30	de	de	X
admet-2772	1301	31	albuquerque	albuquerque	NOUN
admet-2772	1301	32	.	.	PUNCT
admet-2772	1302	1	explainable	explainable	ADJ
admet-2772	1302	2	artificial	artificial	ADJ
admet-2772	1302	3	intelligence	intelligence	NOUN
admet-2772	1302	4	for	for	ADP
admet-2772	1302	5	drug	drug	NOUN
admet-2772	1302	6	discovery	discovery	NOUN
admet-2772	1302	7	and	and	CCONJ
admet-2772	1302	8	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
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admet-2772	1303	1	https://doi.org/10.1021/acs.molpharmaceut.2c00040	https://doi.org/10.1021/acs.molpharmaceut.2c00040	NUM
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admet-2772	1303	3	https://doi.org/10.1038/s41598-023-42165-3	https://doi.org/10.1038/s41598-023-42165-3	PROPN
admet-2772	1304	1	https://doi.org/10.1093/nsr/nwx105	https://doi.org/10.1093/nsr/nwx105	PROPN
admet-2772	1304	2	https://doi.org/10.1016/j.envres.2023.117603	https://doi.org/10.1016/j.envres.2023.117603	PROPN
admet-2772	1304	3	https://doi.org/10.1002/minf.202400079	https://doi.org/10.1002/minf.202400079	NOUN
admet-2772	1304	4	https://doi.org/10.1016/j.eswa.2023.122807	https://doi.org/10.1016/j.eswa.2023.122807	PROPN
admet-2772	1304	5	https://doi.org/10.1021/acs.molpharmaceut.8b00816	https://doi.org/10.1021/acs.molpharmaceut.8b00816	PROPN
admet-2772	1304	6	https://doi.org/10.1021/acs.jcim.9b00626	https://doi.org/10.1021/acs.jcim.9b00626	PROPN
admet-2772	1304	7	https://doi.org/10.1145/3307339.3342186	https://doi.org/10.1145/3307339.3342186	VERB
admet-2772	1304	8	https://doi.org/10.1186/s13321-020-00430-x	https://doi.org/10.1186/s13321-020-00430-x	PROPN
admet-2772	1304	9	https://doi.org/10.1093/bioinformatics/btac342	https://doi.org/10.1093/bioinformatics/btac342	PROPN
admet-2772	1304	10	https://doi.org/10.3390/ph17030382	https://doi.org/10.3390/ph17030382	NOUN
admet-2772	1305	1	https://doi.org/10.4155/fmc-2021-0138	https://doi.org/10.4155/fmc-2021-0138	PROPN
admet-2772	1305	2	https://doi.org/10.1016/j.knosys.2023.110273	https://doi.org/10.1016/j.knosys.2023.110273	PROPN
admet-2772	1305	3	m.	m.	NOUN
admet-2772	1305	4	venkataraman	venkataraman	PROPN
admet-2772	1305	5	et	et	PROPN
admet-2772	1305	6	al	al	PROPN
admet-2772	1305	7	.	.	PROPN
admet-2772	1305	8	admet	admet	PROPN
admet-2772	1305	9	&	&	CCONJ
admet-2772	1305	10	dmpk	dmpk	PROPN
admet-2772	1305	11	13(3	13(3	NUM
admet-2772	1305	12	)	)	PUNCT
admet-2772	1305	13	(	(	PUNCT
admet-2772	1305	14	2025	2025	NUM
admet-2772	1305	15	)	)	PUNCT
admet-2772	1305	16	2772	2772	NUM
admet-2772	1305	17	36	36	NUM
admet-2772	1305	18	development	development	NOUN
admet-2772	1305	19	:	:	PUNCT
admet-2772	1305	20	a	a	DET
admet-2772	1305	21	comprehensive	comprehensive	ADJ
admet-2772	1305	22	survey	survey	NOUN
admet-2772	1305	23	.	.	PUNCT
admet-2772	1306	1	ieee	ieee	NOUN
admet-2772	1306	2	access	access	NOUN
admet-2772	1306	3	12	12	NUM
admet-2772	1306	4	(	(	PUNCT
admet-2772	1306	5	2024	2024	NUM
admet-2772	1306	6	)	)	PUNCT
admet-2772	1306	7	35796	35796	NUM
admet-2772	1306	8	-	-	SYM
admet-2772	1306	9	35812	35812	NUM
admet-2772	1306	10	.	.	PUNCT
admet-2772	1307	1	https://doi.org/10.1109/access.2024.3373195	https://doi.org/10.1109/access.2024.3373195	PROPN
admet-2772	1307	2	[	[	X
admet-2772	1307	3	182	182	NUM
admet-2772	1307	4	]	]	PUNCT
admet-2772	1307	5	a.	a.	NOUN
admet-2772	1307	6	mcgrath	mcgrath	PROPN
admet-2772	1307	7	.	.	PUNCT
admet-2772	1308	1	what	what	PRON
admet-2772	1308	2	is	be	AUX
admet-2772	1308	3	ai	ai	VERB
admet-2772	1308	4	interpretability	interpretability	NOUN
admet-2772	1308	5	?	?	PUNCT
admet-2772	1309	1	ibm	ibm	PROPN
admet-2772	1309	2	(	(	PUNCT
admet-2772	1309	3	2024	2024	NUM
admet-2772	1309	4	)	)	PUNCT
admet-2772	1309	5	.	.	PUNCT
admet-2772	1310	1	https://www.ibm.com/think/topics/interpretability	https://www.ibm.com/think/topics/interpretability	NOUN
admet-2772	1311	1	[	[	X
admet-2772	1311	2	183	183	NUM
admet-2772	1311	3	]	]	X
admet-2772	1311	4	v.	v.	PROPN
admet-2772	1311	5	vimbi	vimbi	PROPN
admet-2772	1311	6	,	,	PUNCT
admet-2772	1311	7	n.	n.	PROPN
admet-2772	1311	8	shaffi	shaffi	PROPN
admet-2772	1311	9	,	,	PUNCT
admet-2772	1311	10	m.	m.	NOUN
admet-2772	1311	11	mahmud	mahmud	PROPN
admet-2772	1311	12	.	.	PUNCT
admet-2772	1312	1	interpreting	interpret	VERB
admet-2772	1312	2	artificial	artificial	ADJ
admet-2772	1312	3	intelligence	intelligence	NOUN
admet-2772	1312	4	models	model	NOUN
admet-2772	1312	5	:	:	PUNCT
admet-2772	1312	6	a	a	DET
admet-2772	1312	7	systematic	systematic	ADJ
admet-2772	1312	8	review	review	NOUN
admet-2772	1312	9	on	on	ADP
admet-2772	1312	10	the	the	DET
admet-2772	1312	11	application	application	NOUN
admet-2772	1312	12	of	of	ADP
admet-2772	1312	13	lime	lime	NOUN
admet-2772	1312	14	and	and	CCONJ
admet-2772	1312	15	shap	shap	PROPN
admet-2772	1312	16	in	in	ADP
admet-2772	1312	17	alzheimer	alzheimer	PROPN
admet-2772	1312	18	’s	’s	PART
admet-2772	1312	19	disease	disease	NOUN
admet-2772	1312	20	detection	detection	NOUN
admet-2772	1312	21	.	.	PUNCT
admet-2772	1313	1	brain	brain	NOUN
admet-2772	1313	2	informatics	informatic	NOUN
admet-2772	1313	3	11	11	NUM
admet-2772	1313	4	(	(	PUNCT
admet-2772	1313	5	2024	2024	NUM
admet-2772	1313	6	)	)	PUNCT
admet-2772	1313	7	10	10	NUM
admet-2772	1313	8	.	.	PUNCT
admet-2772	1314	1	https://doi.org/10.1186/s40708-024-00222-1	https://doi.org/10.1186/s40708-024-00222-1	PROPN
admet-2772	1315	1	[	[	X
admet-2772	1315	2	184	184	X
admet-2772	1315	3	]	]	PUNCT
admet-2772	1315	4	j.	j.	PROPN
admet-2772	1315	5	patterson	patterson	PROPN
admet-2772	1315	6	,	,	PUNCT
admet-2772	1315	7	n.	n.	PROPN
admet-2772	1315	8	tatonetti	tatonetti	PROPN
admet-2772	1315	9	.	.	PUNCT
admet-2772	1316	1	kg	kg	NOUN
admet-2772	1316	2	-	-	PUNCT
admet-2772	1316	3	lime	lime	NOUN
admet-2772	1316	4	:	:	PUNCT
admet-2772	1316	5	predicting	predict	VERB
admet-2772	1316	6	individualized	individualized	ADJ
admet-2772	1316	7	risk	risk	NOUN
admet-2772	1316	8	of	of	ADP
admet-2772	1316	9	adverse	adverse	ADJ
admet-2772	1316	10	drug	drug	NOUN
admet-2772	1316	11	events	event	NOUN
admet-2772	1316	12	for	for	ADP
admet-2772	1316	13	multiple	multiple	ADJ
admet-2772	1316	14	sclerosis	sclerosis	NOUN
admet-2772	1316	15	disease	disease	NOUN
admet-2772	1316	16	-	-	PUNCT
admet-2772	1316	17	modifying	modify	VERB
admet-2772	1316	18	therapy	therapy	NOUN
admet-2772	1316	19	.	.	PUNCT
admet-2772	1317	1	journal	journal	NOUN
admet-2772	1317	2	of	of	ADP
admet-2772	1317	3	the	the	DET
admet-2772	1317	4	american	american	PROPN
admet-2772	1317	5	medical	medical	PROPN
admet-2772	1317	6	informatics	informatics	PROPN
admet-2772	1317	7	association	association	PROPN
admet-2772	1317	8	31	31	NUM
admet-2772	1317	9	(	(	PUNCT
admet-2772	1317	10	2024	2024	NUM
admet-2772	1317	11	)	)	PUNCT
admet-2772	1317	12	1693	1693	NUM
admet-2772	1317	13	-	-	SYM
admet-2772	1317	14	1703	1703	NUM
admet-2772	1317	15	.	.	PUNCT
admet-2772	1318	1	https://doi.org/10.1093/jamia/ocae155	https://doi.org/10.1093/jamia/ocae155	X
admet-2772	1319	1	[	[	X
admet-2772	1319	2	185	185	NUM
admet-2772	1319	3	]	]	PUNCT
admet-2772	1319	4	f.	f.	PROPN
admet-2772	1319	5	gabbay	gabbay	PROPN
admet-2772	1319	6	,	,	PUNCT
admet-2772	1319	7	s.	s.	PROPN
admet-2772	1319	8	bar	bar	PROPN
admet-2772	1319	9	-	-	PUNCT
admet-2772	1319	10	lev	lev	NOUN
admet-2772	1319	11	,	,	PUNCT
admet-2772	1319	12	o.	o.	PROPN
admet-2772	1319	13	montano	montano	PROPN
admet-2772	1319	14	,	,	PUNCT
admet-2772	1319	15	n.	n.	PROPN
admet-2772	1319	16	hadad	hadad	PROPN
admet-2772	1319	17	.	.	PUNCT
admet-2772	1320	1	a	a	DET
admet-2772	1320	2	lime	lime	NOUN
admet-2772	1320	3	-	-	PUNCT
admet-2772	1320	4	based	base	VERB
admet-2772	1320	5	explainable	explainable	ADJ
admet-2772	1320	6	machine	machine	NOUN
admet-2772	1320	7	learning	learning	NOUN
admet-2772	1320	8	model	model	NOUN
admet-2772	1320	9	for	for	ADP
admet-2772	1320	10	predicting	predict	VERB
admet-2772	1320	11	the	the	DET
admet-2772	1320	12	severity	severity	NOUN
admet-2772	1320	13	level	level	NOUN
admet-2772	1320	14	of	of	ADP
admet-2772	1320	15	covid-19	covid-19	PROPN
admet-2772	1320	16	diagnosed	diagnose	VERB
admet-2772	1320	17	patients	patient	NOUN
admet-2772	1320	18	.	.	PUNCT
admet-2772	1321	1	applied	apply	VERB
admet-2772	1321	2	sciences	sciences	PROPN
admet-2772	1321	3	(	(	PUNCT
admet-2772	1321	4	switzerland	switzerland	PROPN
admet-2772	1321	5	)	)	PUNCT
admet-2772	1321	6	11	11	NUM
admet-2772	1321	7	(	(	PUNCT
admet-2772	1321	8	2021	2021	NUM
admet-2772	1321	9	)	)	PUNCT
admet-2772	1321	10	10417	10417	NUM
admet-2772	1321	11	.	.	PUNCT
admet-2772	1322	1	https://doi.org/10.3390/app112110417	https://doi.org/10.3390/app112110417	X
admet-2772	1323	1	[	[	X
admet-2772	1323	2	186	186	NUM
admet-2772	1323	3	]	]	PUNCT
admet-2772	1323	4	s.	s.	PROPN
admet-2772	1323	5	singh	singh	PROPN
admet-2772	1323	6	,	,	PUNCT
admet-2772	1323	7	r.	r.	PROPN
admet-2772	1323	8	kumar	kumar	PROPN
admet-2772	1323	9	,	,	PUNCT
admet-2772	1323	10	s.	s.	PROPN
admet-2772	1323	11	payra	payra	PROPN
admet-2772	1323	12	,	,	PUNCT
admet-2772	1323	13	s.k	s.k	PROPN
admet-2772	1323	14	.	.	PROPN
admet-2772	1323	15	singh	singh	PROPN
admet-2772	1323	16	.	.	PUNCT
admet-2772	1324	1	artificial	artificial	ADJ
admet-2772	1324	2	intelligence	intelligence	NOUN
admet-2772	1324	3	and	and	CCONJ
admet-2772	1324	4	machine	machine	NOUN
admet-2772	1324	5	learning	learning	NOUN
admet-2772	1324	6	in	in	ADP
admet-2772	1324	7	pharmacological	pharmacological	ADJ
admet-2772	1324	8	research	research	NOUN
admet-2772	1324	9	:	:	PUNCT
admet-2772	1324	10	bridging	bridge	VERB
admet-2772	1324	11	the	the	DET
admet-2772	1324	12	gap	gap	NOUN
admet-2772	1324	13	between	between	ADP
admet-2772	1324	14	data	datum	NOUN
admet-2772	1324	15	and	and	CCONJ
admet-2772	1324	16	drug	drug	NOUN
admet-2772	1324	17	discovery	discovery	NOUN
admet-2772	1324	18	.	.	PUNCT
admet-2772	1325	1	cureus	cureus	PROPN
admet-2772	1325	2	15(8	15(8	NUM
admet-2772	1325	3	)	)	PUNCT
admet-2772	1325	4	(	(	PUNCT
admet-2772	1325	5	2023	2023	NUM
admet-2772	1325	6	)	)	PUNCT
admet-2772	1326	1	e44359	e44359	NOUN
admet-2772	1326	2	.	.	PUNCT
admet-2772	1326	3	https://doi.org/10.7759/cureus.44359	https://doi.org/10.7759/cureus.44359	PROPN
admet-2772	1327	1	[	[	X
admet-2772	1327	2	187	187	NUM
admet-2772	1327	3	]	]	X
admet-2772	1327	4	t.z	t.z	PROPN
admet-2772	1327	5	.	.	PROPN
admet-2772	1327	6	long	long	PROPN
admet-2772	1327	7	,	,	PUNCT
admet-2772	1327	8	d.j	d.j	PROPN
admet-2772	1327	9	.	.	PROPN
admet-2772	1327	10	jiang	jiang	PROPN
admet-2772	1327	11	,	,	PUNCT
admet-2772	1327	12	s.h	s.h	PROPN
admet-2772	1327	13	.	.	PROPN
admet-2772	1327	14	shi	shi	PROPN
admet-2772	1327	15	,	,	PUNCT
admet-2772	1327	16	y.c	y.c	PROPN
admet-2772	1327	17	.	.	PROPN
admet-2772	1327	18	deng	deng	PROPN
admet-2772	1327	19	,	,	PUNCT
admet-2772	1327	20	w.x	w.x	PROPN
admet-2772	1327	21	.	.	PROPN
admet-2772	1327	22	wang	wang	PROPN
admet-2772	1327	23	,	,	PUNCT
admet-2772	1327	24	d.s	d.s	PROPN
admet-2772	1327	25	.	.	PROPN
admet-2772	1327	26	cao	cao	PROPN
admet-2772	1327	27	.	.	PUNCT
admet-2772	1328	1	enhancing	enhance	VERB
admet-2772	1328	2	multi	multi	ADJ
admet-2772	1328	3	-	-	ADJ
admet-2772	1328	4	species	species	ADJ
admet-2772	1328	5	liver	liver	NOUN
admet-2772	1328	6	microsomal	microsomal	ADJ
admet-2772	1328	7	stability	stability	NOUN
admet-2772	1328	8	prediction	prediction	NOUN
admet-2772	1328	9	through	through	ADP
admet-2772	1328	10	artificial	artificial	ADJ
admet-2772	1328	11	intelligence	intelligence	NOUN
admet-2772	1328	12	.	.	PUNCT
admet-2772	1329	1	journal	journal	PROPN
admet-2772	1329	2	of	of	ADP
admet-2772	1329	3	chemical	chemical	ADJ
admet-2772	1329	4	information	information	NOUN
admet-2772	1329	5	and	and	CCONJ
admet-2772	1329	6	modeling	model	VERB
admet-2772	1329	7	64	64	NUM
admet-2772	1329	8	(	(	PUNCT
admet-2772	1329	9	2024	2024	NUM
admet-2772	1329	10	)	)	PUNCT
admet-2772	1329	11	3222	3222	NUM
admet-2772	1329	12	-	-	SYM
admet-2772	1329	13	3236	3236	NUM
admet-2772	1329	14	.	.	PUNCT
admet-2772	1330	1	https://doi.org/10.1021/acs.jcim.4c00159	https://doi.org/10.1021/acs.jcim.4c00159	VERB
admet-2772	1330	2	[	[	X
admet-2772	1330	3	188	188	NUM
admet-2772	1330	4	]	]	PUNCT
admet-2772	1330	5	c.	c.	PROPN
admet-2772	1330	6	könig	könig	PROPN
admet-2772	1330	7	,	,	PUNCT
admet-2772	1330	8	a.	a.	NOUN
admet-2772	1330	9	vellido	vellido	NOUN
admet-2772	1330	10	.	.	PUNCT
admet-2772	1331	1	understanding	understand	VERB
admet-2772	1331	2	predictions	prediction	NOUN
admet-2772	1331	3	of	of	ADP
admet-2772	1331	4	drug	drug	NOUN
admet-2772	1331	5	profiles	profile	NOUN
admet-2772	1331	6	using	use	VERB
admet-2772	1331	7	explainable	explainable	ADJ
admet-2772	1331	8	machine	machine	NOUN
admet-2772	1331	9	learning	learning	NOUN
admet-2772	1331	10	models	model	NOUN
admet-2772	1331	11	.	.	PUNCT
admet-2772	1332	1	biodata	biodata	PROPN
admet-2772	1332	2	mining	mining	PROPN
admet-2772	1332	3	17	17	NUM
admet-2772	1332	4	(	(	PUNCT
admet-2772	1332	5	2024	2024	NUM
admet-2772	1332	6	)	)	PUNCT
admet-2772	1332	7	25	25	NUM
admet-2772	1332	8	.	.	PUNCT
admet-2772	1333	1	https://doi.org/10.1186/s13040-024-00378-w	https://doi.org/10.1186/s13040-024-00378-w	NOUN
admet-2772	1333	2	[	[	X
admet-2772	1333	3	189	189	NUM
admet-2772	1333	4	]	]	X
admet-2772	1333	5	r.	r.	PROPN
admet-2772	1333	6	rodríguez	rodríguez	PROPN
admet-2772	1333	7	-	-	PUNCT
admet-2772	1333	8	pérez	pérez	NOUN
admet-2772	1333	9	,	,	PUNCT
admet-2772	1333	10	j.	j.	PROPN
admet-2772	1333	11	bajorath	bajorath	PROPN
admet-2772	1333	12	.	.	PUNCT
admet-2772	1334	1	interpretation	interpretation	NOUN
admet-2772	1334	2	of	of	ADP
admet-2772	1334	3	machine	machine	NOUN
admet-2772	1334	4	learning	learning	NOUN
admet-2772	1334	5	models	model	NOUN
admet-2772	1334	6	using	use	VERB
admet-2772	1334	7	shapley	shapley	ADJ
admet-2772	1334	8	values	value	NOUN
admet-2772	1334	9	:	:	PUNCT
admet-2772	1334	10	application	application	NOUN
admet-2772	1334	11	to	to	PART
admet-2772	1334	12	compound	compound	VERB
admet-2772	1334	13	potency	potency	NOUN
admet-2772	1334	14	and	and	CCONJ
admet-2772	1334	15	multi	multi	ADJ
admet-2772	1334	16	-	-	ADJ
admet-2772	1334	17	target	target	ADJ
admet-2772	1334	18	activity	activity	NOUN
admet-2772	1334	19	predictions	prediction	NOUN
admet-2772	1334	20	.	.	PUNCT
admet-2772	1335	1	journal	journal	NOUN
admet-2772	1335	2	of	of	ADP
admet-2772	1335	3	computer	computer	NOUN
admet-2772	1335	4	-	-	PUNCT
admet-2772	1335	5	aided	aid	VERB
admet-2772	1335	6	molecular	molecular	ADJ
admet-2772	1335	7	design	design	NOUN
admet-2772	1335	8	34	34	NUM
admet-2772	1335	9	(	(	PUNCT
admet-2772	1335	10	2020	2020	NUM
admet-2772	1335	11	)	)	PUNCT
admet-2772	1335	12	1013	1013	NUM
admet-2772	1335	13	-	-	SYM
admet-2772	1335	14	1026	1026	NUM
admet-2772	1335	15	.	.	PUNCT
admet-2772	1336	1	https://doi.org/10.1007/s10822-020-00314-0	https://doi.org/10.1007/s10822-020-00314-0	NUM
admet-2772	1337	1	[	[	X
admet-2772	1337	2	190	190	NUM
admet-2772	1337	3	]	]	PUNCT
admet-2772	1337	4	s.	s.	PROPN
admet-2772	1337	5	marshall	marshall	PROPN
admet-2772	1337	6	,	,	PUNCT
admet-2772	1337	7	r.	r.	PROPN
admet-2772	1337	8	madabushi	madabushi	PROPN
admet-2772	1337	9	,	,	PUNCT
admet-2772	1337	10	e.	e.	PROPN
admet-2772	1337	11	manolis	manolis	PROPN
admet-2772	1337	12	,	,	PUNCT
admet-2772	1337	13	k.	k.	PROPN
admet-2772	1337	14	krudys	krudys	PROPN
admet-2772	1337	15	,	,	PUNCT
admet-2772	1337	16	a.	a.	NOUN
admet-2772	1337	17	staab	staab	PROPN
admet-2772	1337	18	,	,	PUNCT
admet-2772	1337	19	k.	k.	PROPN
admet-2772	1337	20	dykstra	dykstra	PROPN
admet-2772	1337	21	,	,	PUNCT
admet-2772	1338	1	s.a.g	s.a.g	PROPN
admet-2772	1338	2	.	.	PUNCT
admet-2772	1338	3	visser	visser	PROPN
admet-2772	1338	4	.	.	PUNCT
admet-2772	1339	1	model	model	NOUN
admet-2772	1339	2	-	-	PUNCT
admet-2772	1339	3	informed	inform	VERB
admet-2772	1339	4	drug	drug	NOUN
admet-2772	1339	5	discovery	discovery	NOUN
admet-2772	1339	6	and	and	CCONJ
admet-2772	1339	7	development	development	NOUN
admet-2772	1339	8	:	:	PUNCT
admet-2772	1339	9	current	current	ADJ
admet-2772	1339	10	industry	industry	NOUN
admet-2772	1339	11	good	good	ADJ
admet-2772	1339	12	practice	practice	NOUN
admet-2772	1339	13	and	and	CCONJ
admet-2772	1339	14	regulatory	regulatory	ADJ
admet-2772	1339	15	expectations	expectation	NOUN
admet-2772	1339	16	and	and	CCONJ
admet-2772	1339	17	future	future	ADJ
admet-2772	1339	18	perspectives	perspective	NOUN
admet-2772	1339	19	.	.	PUNCT
admet-2772	1340	1	cpt	cpt	NOUN
admet-2772	1340	2	:	:	PUNCT
admet-2772	1340	3	pharmacometrics	pharmacometric	NOUN
admet-2772	1340	4	and	and	CCONJ
admet-2772	1340	5	systems	system	NOUN
admet-2772	1340	6	pharmacology	pharmacology	NOUN
admet-2772	1340	7	8	8	NUM
admet-2772	1340	8	(	(	PUNCT
admet-2772	1340	9	2019	2019	NUM
admet-2772	1340	10	)	)	PUNCT
admet-2772	1340	11	87	87	NUM
admet-2772	1340	12	-	-	SYM
admet-2772	1340	13	96	96	NUM
admet-2772	1340	14	.	.	PUNCT
admet-2772	1341	1	https://doi.org/10.1002/psp4.12372	https://doi.org/10.1002/psp4.12372	X
admet-2772	1341	2	[	[	X
admet-2772	1341	3	191	191	NUM
admet-2772	1341	4	]	]	X
admet-2772	1341	5	n.	n.	PROPN
admet-2772	1341	6	terranova	terranova	PROPN
admet-2772	1341	7	,	,	PUNCT
admet-2772	1341	8	d.	d.	PROPN
admet-2772	1341	9	renard	renard	PROPN
admet-2772	1341	10	,	,	PUNCT
admet-2772	1341	11	m.h	m.h	PROPN
admet-2772	1341	12	.	.	PROPN
admet-2772	1341	13	shahin	shahin	PROPN
admet-2772	1341	14	,	,	PUNCT
admet-2772	1341	15	s.	s.	PROPN
admet-2772	1341	16	menon	menon	PROPN
admet-2772	1341	17	,	,	PUNCT
admet-2772	1341	18	y.	y.	PROPN
admet-2772	1341	19	cao	cao	PROPN
admet-2772	1341	20	,	,	PUNCT
admet-2772	1341	21	c.e.c.a	c.e.c.a	PROPN
admet-2772	1341	22	.	.	PUNCT
admet-2772	1342	1	hop	hop	PROPN
admet-2772	1342	2	,	,	PUNCT
admet-2772	1342	3	s.	s.	PROPN
admet-2772	1342	4	hayes	hayes	PROPN
admet-2772	1342	5	,	,	PUNCT
admet-2772	1342	6	k.	k.	PROPN
admet-2772	1342	7	madrasi	madrasi	PROPN
admet-2772	1342	8	,	,	PUNCT
admet-2772	1342	9	s.	s.	PROPN
admet-2772	1342	10	stodtmann	stodtmann	PROPN
admet-2772	1342	11	,	,	PUNCT
admet-2772	1342	12	t.	t.	NOUN
admet-2772	1342	13	tensfeldt	tensfeldt	PROPN
admet-2772	1342	14	,	,	PUNCT
admet-2772	1342	15	p.	p.	PROPN
admet-2772	1342	16	vaddady	vaddady	NOUN
admet-2772	1342	17	,	,	PUNCT
admet-2772	1342	18	n.	n.	NOUN
admet-2772	1342	19	ellinwood	ellinwood	PROPN
admet-2772	1342	20	,	,	PUNCT
admet-2772	1342	21	j.	j.	PROPN
admet-2772	1342	22	lu	lu	PROPN
admet-2772	1342	23	.	.	PUNCT
admet-2772	1343	1	artificial	artificial	ADJ
admet-2772	1343	2	intelligence	intelligence	NOUN
admet-2772	1343	3	for	for	ADP
admet-2772	1343	4	quantitative	quantitative	ADJ
admet-2772	1343	5	modeling	modeling	NOUN
admet-2772	1343	6	in	in	ADP
admet-2772	1343	7	drug	drug	NOUN
admet-2772	1343	8	discovery	discovery	NOUN
admet-2772	1343	9	and	and	CCONJ
admet-2772	1343	10	development	development	NOUN
admet-2772	1343	11	:	:	PUNCT
admet-2772	1343	12	an	an	DET
admet-2772	1343	13	innovation	innovation	NOUN
admet-2772	1343	14	and	and	CCONJ
admet-2772	1343	15	quality	quality	NOUN
admet-2772	1343	16	consortium	consortium	NOUN
admet-2772	1343	17	perspective	perspective	NOUN
admet-2772	1343	18	on	on	ADP
admet-2772	1343	19	use	use	NOUN
admet-2772	1343	20	cases	case	NOUN
admet-2772	1343	21	and	and	CCONJ
admet-2772	1343	22	best	good	ADJ
admet-2772	1343	23	practices	practice	NOUN
admet-2772	1343	24	.	.	PUNCT
admet-2772	1344	1	clinical	clinical	ADJ
admet-2772	1344	2	pharmacology	pharmacology	NOUN
admet-2772	1344	3	and	and	CCONJ
admet-2772	1344	4	therapeutics	therapeutic	NOUN
admet-2772	1344	5	115	115	NUM
admet-2772	1344	6	(	(	PUNCT
admet-2772	1344	7	2024	2024	NUM
admet-2772	1344	8	)	)	PUNCT
admet-2772	1344	9	658	658	NUM
admet-2772	1344	10	-	-	SYM
admet-2772	1344	11	672	672	NUM
admet-2772	1344	12	.	.	PUNCT
admet-2772	1345	1	https://doi.org/10.1002/cpt.3053	https://doi.org/10.1002/cpt.3053	NOUN
admet-2772	1346	1	[	[	X
admet-2772	1346	2	192	192	NUM
admet-2772	1346	3	]	]	X
admet-2772	1346	4	s.h	s.h	PROPN
admet-2772	1346	5	.	.	PROPN
admet-2772	1346	6	kang	kang	PROPN
admet-2772	1346	7	,	,	PUNCT
admet-2772	1346	8	m.r	m.r	PROPN
admet-2772	1346	9	.	.	PROPN
admet-2772	1346	10	poynton	poynton	PROPN
admet-2772	1346	11	,	,	PUNCT
admet-2772	1346	12	k.m	k.m	PROPN
admet-2772	1346	13	.	.	PROPN
admet-2772	1346	14	kim	kim	PROPN
admet-2772	1346	15	,	,	PUNCT
admet-2772	1346	16	h.	h.	PROPN
admet-2772	1346	17	lee	lee	PROPN
admet-2772	1346	18	,	,	PUNCT
admet-2772	1346	19	d.h	d.h	PROPN
admet-2772	1346	20	.	.	PROPN
admet-2772	1346	21	kim	kim	PROPN
admet-2772	1346	22	,	,	PUNCT
admet-2772	1346	23	s.h	s.h	PROPN
admet-2772	1346	24	.	.	PROPN
admet-2772	1346	25	lee	lee	PROPN
admet-2772	1346	26	,	,	PUNCT
admet-2772	1346	27	k.s	k.s	PROPN
admet-2772	1346	28	.	.	PROPN
admet-2772	1346	29	bae	bae	PROPN
admet-2772	1346	30	,	,	PUNCT
admet-2772	1346	31	o.	o.	PROPN
admet-2772	1346	32	linares	linare	NOUN
admet-2772	1346	33	,	,	PUNCT
admet-2772	1346	34	s.e	s.e	PROPN
admet-2772	1346	35	.	.	PROPN
admet-2772	1346	36	kern	kern	PROPN
admet-2772	1346	37	,	,	PUNCT
admet-2772	1346	38	g.j	g.j	PROPN
admet-2772	1346	39	.	.	PROPN
admet-2772	1346	40	noh	noh	PROPN
admet-2772	1346	41	.	.	PUNCT
admet-2772	1347	1	population	population	NOUN
admet-2772	1347	2	pharmacokinetic	pharmacokinetic	ADJ
admet-2772	1347	3	and	and	CCONJ
admet-2772	1347	4	pharmacodynamic	pharmacodynamic	ADJ
admet-2772	1347	5	models	model	NOUN
admet-2772	1347	6	of	of	ADP
admet-2772	1347	7	remifentanil	remifentanil	NOUN
admet-2772	1347	8	in	in	ADP
admet-2772	1347	9	healthy	healthy	ADJ
admet-2772	1347	10	volunteers	volunteer	NOUN
admet-2772	1347	11	using	use	VERB
admet-2772	1347	12	artificial	artificial	ADJ
admet-2772	1347	13	neural	neural	ADJ
admet-2772	1347	14	network	network	NOUN
admet-2772	1347	15	analysis	analysis	NOUN
admet-2772	1347	16	.	.	PUNCT
admet-2772	1348	1	british	british	ADJ
admet-2772	1348	2	journal	journal	PROPN
admet-2772	1348	3	of	of	ADP
admet-2772	1348	4	clinical	clinical	ADJ
admet-2772	1348	5	pharmacology	pharmacology	NOUN
admet-2772	1348	6	64	64	NUM
admet-2772	1348	7	(	(	PUNCT
admet-2772	1348	8	2007	2007	NUM
admet-2772	1348	9	)	)	PUNCT
admet-2772	1348	10	3	3	NUM
admet-2772	1348	11	-	-	SYM
admet-2772	1348	12	13	13	NUM
admet-2772	1348	13	.	.	PUNCT
admet-2772	1349	1	https://doi.org/10.1111/j.1365-2125.2007.02845.x	https://doi.org/10.1111/j.1365-2125.2007.02845.x	NOUN
admet-2772	1350	1	[	[	X
admet-2772	1350	2	193	193	NUM
admet-2772	1350	3	]	]	X
admet-2772	1350	4	b.	b.	PROPN
admet-2772	1350	5	canault	canault	PROPN
admet-2772	1350	6	,	,	PUNCT
admet-2772	1350	7	s.	s.	PROPN
admet-2772	1350	8	bourg	bourg	PROPN
admet-2772	1350	9	,	,	PUNCT
admet-2772	1350	10	p.	p.	NOUN
admet-2772	1350	11	vayer	vayer	NOUN
admet-2772	1350	12	,	,	PUNCT
admet-2772	1350	13	p.	p.	NOUN
admet-2772	1350	14	bonnet	bonnet	NOUN
admet-2772	1350	15	.	.	PUNCT
admet-2772	1351	1	comprehensive	comprehensive	ADJ
admet-2772	1351	2	network	network	NOUN
admet-2772	1351	3	map	map	NOUN
admet-2772	1351	4	of	of	ADP
admet-2772	1351	5	adme	adme	NOUN
admet-2772	1351	6	-	-	PUNCT
admet-2772	1351	7	tox	tox	NOUN
admet-2772	1351	8	databases	database	NOUN
admet-2772	1351	9	.	.	PUNCT
admet-2772	1352	1	molecular	molecular	ADJ
admet-2772	1352	2	informatics	informatic	NOUN
admet-2772	1352	3	36	36	NUM
admet-2772	1352	4	(	(	PUNCT
admet-2772	1352	5	2017	2017	NUM
admet-2772	1352	6	)	)	PUNCT
admet-2772	1352	7	1700029	1700029	NUM
admet-2772	1352	8	.	.	PUNCT
admet-2772	1353	1	https://doi.org/10.1002/minf.201700029	https://doi.org/10.1002/minf.201700029	PROPN
admet-2772	1354	1	[	[	X
admet-2772	1354	2	194	194	NUM
admet-2772	1354	3	]	]	PUNCT
admet-2772	1354	4	s.	s.	PROPN
admet-2772	1354	5	ekins	ekins	PROPN
admet-2772	1354	6	,	,	PUNCT
admet-2772	1354	7	a.j	a.j	PROPN
admet-2772	1354	8	.	.	PROPN
admet-2772	1354	9	williams	williams	PROPN
admet-2772	1354	10	.	.	PUNCT
admet-2772	1355	1	precompetitive	precompetitive	ADJ
admet-2772	1355	2	preclinical	preclinical	ADJ
admet-2772	1355	3	adme	adme	NOUN
admet-2772	1355	4	/	/	SYM
admet-2772	1355	5	tox	tox	NOUN
admet-2772	1355	6	data	datum	NOUN
admet-2772	1355	7	:	:	PUNCT
admet-2772	1355	8	set	set	VERB
admet-2772	1355	9	it	it	PRON
admet-2772	1355	10	free	free	ADJ
admet-2772	1355	11	on	on	ADP
admet-2772	1355	12	the	the	DET
admet-2772	1355	13	web	web	NOUN
admet-2772	1355	14	to	to	PART
admet-2772	1355	15	facilitate	facilitate	VERB
admet-2772	1355	16	computational	computational	ADJ
admet-2772	1355	17	model	model	NOUN
admet-2772	1355	18	building	building	NOUN
admet-2772	1355	19	and	and	CCONJ
admet-2772	1355	20	assist	assist	VERB
admet-2772	1355	21	drug	drug	NOUN
admet-2772	1355	22	development	development	NOUN
admet-2772	1355	23	.	.	PUNCT
admet-2772	1356	1	lab	lab	NOUN
admet-2772	1356	2	on	on	ADP
admet-2772	1356	3	a	a	DET
admet-2772	1356	4	chip	chip	NOUN
admet-2772	1356	5	10	10	NUM
admet-2772	1356	6	(	(	PUNCT
admet-2772	1356	7	2010	2010	NUM
admet-2772	1356	8	)	)	PUNCT
admet-2772	1356	9	13	13	NUM
admet-2772	1356	10	-	-	SYM
admet-2772	1356	11	22	22	NUM
admet-2772	1356	12	.	.	PUNCT
admet-2772	1357	1	https://doi.org/10.1039/b917760b	https://doi.org/10.1039/b917760b	X
admet-2772	1358	1	[	[	X
admet-2772	1358	2	195	195	NUM
admet-2772	1358	3	]	]	X
admet-2772	1358	4	g.	g.	PROPN
admet-2772	1358	5	pawar	pawar	PROPN
admet-2772	1358	6	,	,	PUNCT
admet-2772	1358	7	j.c	j.c	PROPN
admet-2772	1358	8	.	.	PROPN
admet-2772	1358	9	madden	madden	PROPN
admet-2772	1358	10	,	,	PUNCT
admet-2772	1358	11	d.	d.	PROPN
admet-2772	1358	12	ebbrell	ebbrell	PROPN
admet-2772	1358	13	,	,	PUNCT
admet-2772	1358	14	j.w	j.w	PROPN
admet-2772	1358	15	.	.	PROPN
admet-2772	1358	16	firman	firman	PROPN
admet-2772	1358	17	,	,	PUNCT
admet-2772	1358	18	m.t.d	m.t.d	PROPN
admet-2772	1358	19	.	.	PUNCT
admet-2772	1358	20	cronin	cronin	PROPN
admet-2772	1358	21	.	.	PUNCT
admet-2772	1359	1	in	in	ADP
admet-2772	1359	2	silico	silico	NOUN
admet-2772	1359	3	toxicology	toxicology	NOUN
admet-2772	1359	4	data	datum	NOUN
admet-2772	1359	5	resources	resource	NOUN
admet-2772	1359	6	to	to	PART
admet-2772	1359	7	support	support	VERB
admet-2772	1359	8	read	read	NOUN
admet-2772	1359	9	-	-	PUNCT
admet-2772	1359	10	across	across	ADP
admet-2772	1359	11	and	and	CCONJ
admet-2772	1359	12	(	(	PUNCT
admet-2772	1359	13	q)sar	q)sar	PROPN
admet-2772	1359	14	.	.	PUNCT
admet-2772	1360	1	frontiers	frontier	NOUN
admet-2772	1360	2	in	in	ADP
admet-2772	1360	3	pharmacology	pharmacology	NOUN
admet-2772	1360	4	10	10	NUM
admet-2772	1360	5	(	(	PUNCT
admet-2772	1360	6	2019	2019	NUM
admet-2772	1360	7	)	)	PUNCT
admet-2772	1360	8	561	561	NUM
admet-2772	1360	9	.	.	PUNCT
admet-2772	1361	1	https://doi.org/10.3389/fphar.2019.00561	https://doi.org/10.3389/fphar.2019.00561	PROPN
admet-2772	1362	1	[	[	X
admet-2772	1362	2	196	196	NUM
admet-2772	1362	3	]	]	X
admet-2772	1362	4	m.a	m.a	PROPN
admet-2772	1362	5	.	.	PROPN
admet-2772	1362	6	miteva	miteva	PROPN
admet-2772	1362	7	,	,	PUNCT
admet-2772	1362	8	s.	s.	PROPN
admet-2772	1362	9	violas	violas	PROPN
admet-2772	1362	10	,	,	PUNCT
admet-2772	1362	11	m.	m.	NOUN
admet-2772	1362	12	montes	montes	PROPN
admet-2772	1362	13	,	,	PUNCT
admet-2772	1362	14	d.	d.	PROPN
admet-2772	1362	15	gomez	gomez	PROPN
admet-2772	1362	16	,	,	PUNCT
admet-2772	1362	17	p.	p.	PROPN
admet-2772	1362	18	tuffery	tuffery	PROPN
admet-2772	1362	19	,	,	PUNCT
admet-2772	1362	20	b.o	b.o	PROPN
admet-2772	1362	21	.	.	PROPN
admet-2772	1362	22	villoutreix	villoutreix	PROPN
admet-2772	1362	23	.	.	PUNCT
admet-2772	1363	1	faf	faf	NOUN
admet-2772	1363	2	-	-	PUNCT
admet-2772	1363	3	drugs	drug	NOUN
admet-2772	1363	4	:	:	PUNCT
admet-2772	1363	5	free	free	ADJ
admet-2772	1363	6	adme	adme	NOUN
admet-2772	1363	7	/	/	SYM
admet-2772	1363	8	tox	tox	NOUN
admet-2772	1363	9	filtering	filtering	NOUN
admet-2772	1363	10	of	of	ADP
admet-2772	1363	11	compound	compound	NOUN
admet-2772	1363	12	collections	collection	NOUN
admet-2772	1363	13	.	.	PUNCT
admet-2772	1364	1	nucleic	nucleic	ADJ
admet-2772	1364	2	acids	acid	NOUN
admet-2772	1364	3	research	research	NOUN
admet-2772	1364	4	34	34	NUM
admet-2772	1364	5	(	(	PUNCT
admet-2772	1364	6	2006	2006	NUM
admet-2772	1364	7	)	)	PUNCT
admet-2772	1364	8	w738	w738	PROPN
admet-2772	1364	9	-	-	PUNCT
admet-2772	1364	10	w744	w744	PROPN
admet-2772	1364	11	.	.	PUNCT
admet-2772	1365	1	https://doi.org/10.1093/nar/gkl065	https://doi.org/10.1093/nar/gkl065	PROPN
admet-2772	1365	2	https://doi.org/10.1109/access.2024.3373195	https://doi.org/10.1109/access.2024.3373195	PROPN
admet-2772	1365	3	https://www.ibm.com/think/topics/interpretability	https://www.ibm.com/think/topics/interpretability	NOUN
admet-2772	1365	4	https://doi.org/10.1186/s40708-024-00222-1	https://doi.org/10.1186/s40708-024-00222-1	PROPN
admet-2772	1365	5	https://doi.org/10.1093/jamia/ocae155	https://doi.org/10.1093/jamia/ocae155	INTJ
admet-2772	1366	1	https://doi.org/10.3390/app112110417	https://doi.org/10.3390/app112110417	PROPN
admet-2772	1366	2	https://doi.org/10.7759/cureus.44359	https://doi.org/10.7759/cureus.44359	PROPN
admet-2772	1366	3	https://doi.org/10.1021/acs.jcim.4c00159	https://doi.org/10.1021/acs.jcim.4c00159	VERB
admet-2772	1366	4	https://doi.org/10.1186/s13040-024-00378-w	https://doi.org/10.1186/s13040-024-00378-w	PROPN
admet-2772	1366	5	https://doi.org/10.1007/s10822-020-00314-0	https://doi.org/10.1007/s10822-020-00314-0	NUM
admet-2772	1366	6	https://doi.org/10.1002/psp4.12372	https://doi.org/10.1002/psp4.12372	VERB
admet-2772	1366	7	https://doi.org/10.1002/cpt.3053	https://doi.org/10.1002/cpt.3053	ADJ
admet-2772	1366	8	https://doi.org/10.1111/j.1365-2125.2007.02845.x	https://doi.org/10.1111/j.1365-2125.2007.02845.x	NOUN
admet-2772	1366	9	https://doi.org/10.1002/minf.201700029	https://doi.org/10.1002/minf.201700029	NOUN
admet-2772	1367	1	https://doi.org/10.1039/b917760b	https://doi.org/10.1039/b917760b	PROPN
admet-2772	1368	1	https://doi.org/10.3389/fphar.2019.00561	https://doi.org/10.3389/fphar.2019.00561	PROPN
admet-2772	1368	2	https://doi.org/10.1093/nar/gkl065	https://doi.org/10.1093/nar/gkl065	PROPN
admet-2772	1368	3	admet	admet	PROPN
admet-2772	1368	4	&	&	CCONJ
admet-2772	1368	5	dmpk	dmpk	PROPN
admet-2772	1368	6	13(3	13(3	NUM
admet-2772	1368	7	)	)	PUNCT
admet-2772	1368	8	(	(	PUNCT
admet-2772	1368	9	2025	2025	NUM
admet-2772	1368	10	)	)	PUNCT
admet-2772	1368	11	2772	2772	NUM
admet-2772	1368	12	machine	machine	NOUN
admet-2772	1368	13	learning	learning	NOUN
admet-2772	1368	14	models	model	NOUN
admet-2772	1368	15	for	for	ADP
admet-2772	1368	16	admet	admet	ADJ
admet-2772	1368	17	prediction	prediction	NOUN
admet-2772	1368	18	in	in	ADP
admet-2772	1368	19	drug	drug	NOUN
admet-2772	1368	20	development	development	NOUN
admet-2772	1368	21	doi	doi	PROPN
admet-2772	1368	22	:	:	PUNCT
admet-2772	1368	23	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	1368	24	37	37	NUM
admet-2772	1368	25	[	[	SYM
admet-2772	1368	26	197	197	NUM
admet-2772	1368	27	]	]	X
admet-2772	1368	28	d.	d.	PROPN
admet-2772	1368	29	rao	rao	PROPN
admet-2772	1368	30	,	,	PUNCT
admet-2772	1368	31	v.n	v.n	PROPN
admet-2772	1368	32	.	.	PROPN
admet-2772	1368	33	gudivada	gudivada	PROPN
admet-2772	1368	34	,	,	PUNCT
admet-2772	1368	35	v.	v.	PROPN
admet-2772	1368	36	v.	v.	ADP
admet-2772	1368	37	raghavan	raghavan	PROPN
admet-2772	1368	38	.	.	PROPN
admet-2772	1369	1	data	data	PROPN
admet-2772	1369	2	quality	quality	NOUN
admet-2772	1369	3	issues	issue	NOUN
admet-2772	1369	4	in	in	ADP
admet-2772	1369	5	big	big	ADJ
admet-2772	1369	6	data	datum	NOUN
admet-2772	1369	7	.	.	PUNCT
admet-2772	1370	1	proceedings	proceeding	NOUN
admet-2772	1370	2	2015	2015	NUM
admet-2772	1370	3	ieee	ieee	PROPN
admet-2772	1370	4	international	international	ADJ
admet-2772	1370	5	conference	conference	NOUN
admet-2772	1370	6	on	on	ADP
admet-2772	1370	7	big	big	ADJ
admet-2772	1370	8	data	datum	NOUN
admet-2772	1370	9	,	,	PUNCT
admet-2772	1370	10	ieee	ieee	NOUN
admet-2772	1370	11	big	big	ADJ
admet-2772	1370	12	data	datum	NOUN
admet-2772	1370	13	(	(	PUNCT
admet-2772	1370	14	2015	2015	NUM
admet-2772	1370	15	)	)	PUNCT
admet-2772	1370	16	2654	2654	NUM
admet-2772	1370	17	-	-	SYM
admet-2772	1370	18	2660	2660	NUM
admet-2772	1370	19	.	.	PUNCT
admet-2772	1371	1	https://doi.org/10.1109/bigdata.2015.7364065	https://doi.org/10.1109/bigdata.2015.7364065	PROPN
admet-2772	1372	1	[	[	X
admet-2772	1372	2	198	198	NUM
admet-2772	1372	3	]	]	PUNCT
admet-2772	1372	4	w.	w.	PROPN
admet-2772	1372	5	fan	fan	PROPN
admet-2772	1372	6	,	,	PUNCT
admet-2772	1372	7	f.	f.	PROPN
admet-2772	1372	8	geerts	geerts	PROPN
admet-2772	1372	9	.	.	PUNCT
admet-2772	1373	1	foundations	foundation	NOUN
admet-2772	1373	2	of	of	ADP
admet-2772	1373	3	data	datum	NOUN
admet-2772	1373	4	quality	quality	NOUN
admet-2772	1373	5	management	management	NOUN
admet-2772	1373	6	,	,	PUNCT
admet-2772	1373	7	1st	1st	ADJ
admet-2772	1373	8	ed	ed	NOUN
admet-2772	1373	9	.	.	PROPN
admet-2772	1373	10	,	,	PUNCT
admet-2772	1373	11	springer	springer	NOUN
admet-2772	1373	12	nature	nature	PROPN
admet-2772	1373	13	link	link	PROPN
admet-2772	1373	14	,	,	PUNCT
admet-2772	1373	15	(	(	PUNCT
admet-2772	1373	16	2012	2012	NUM
admet-2772	1373	17	)	)	PUNCT
admet-2772	1374	1	https://doi.org/10.1007/978-3-031-01892-3	https://doi.org/10.1007/978-3-031-01892-3	PROPN
admet-2772	1375	1	[	[	X
admet-2772	1375	2	199	199	NUM
admet-2772	1375	3	]	]	PUNCT
admet-2772	1375	4	k.	k.	PROPN
admet-2772	1375	5	natarajan	natarajan	PROPN
admet-2772	1375	6	,	,	PUNCT
admet-2772	1375	7	j.	j.	PROPN
admet-2772	1375	8	li	li	PROPN
admet-2772	1375	9	,	,	PUNCT
admet-2772	1375	10	a.	a.	NOUN
admet-2772	1375	11	koronios	koronios	PROPN
admet-2772	1375	12	.	.	PUNCT
admet-2772	1376	1	data	datum	NOUN
admet-2772	1376	2	mining	mining	NOUN
admet-2772	1376	3	techniques	technique	NOUN
admet-2772	1376	4	for	for	ADP
admet-2772	1376	5	data	datum	NOUN
admet-2772	1376	6	cleaning	cleaning	NOUN
admet-2772	1376	7	.	.	PUNCT
admet-2772	1377	1	engineering	engineering	NOUN
admet-2772	1377	2	asset	asset	NOUN
admet-2772	1377	3	lifecycle	lifecycle	NOUN
admet-2772	1377	4	management	management	NOUN
admet-2772	1377	5	proceedings	proceeding	NOUN
admet-2772	1377	6	of	of	ADP
admet-2772	1377	7	the	the	DET
admet-2772	1377	8	4th	4th	ADJ
admet-2772	1377	9	world	world	NOUN
admet-2772	1377	10	congress	congress	PROPN
admet-2772	1377	11	on	on	ADP
admet-2772	1377	12	engineering	engineering	NOUN
admet-2772	1377	13	asset	asset	NOUN
admet-2772	1377	14	management	management	NOUN
admet-2772	1377	15	,	,	PUNCT
admet-2772	1377	16	wceam	wceam	NOUN
admet-2772	1377	17	(	(	PUNCT
admet-2772	1377	18	2009	2009	NUM
admet-2772	1377	19	)	)	PUNCT
admet-2772	1377	20	796	796	NUM
admet-2772	1377	21	-	-	SYM
admet-2772	1377	22	804	804	NUM
admet-2772	1377	23	.	.	PUNCT
admet-2772	1378	1	https://doi.org/10.1007/978-0-85729-320-6_91	https://doi.org/10.1007/978-0-85729-320-6_91	PROPN
admet-2772	1379	1	[	[	X
admet-2772	1379	2	200	200	NUM
admet-2772	1379	3	]	]	PUNCT
admet-2772	1379	4	c.	c.	PROPN
admet-2772	1379	5	batini	batini	PROPN
admet-2772	1379	6	,	,	PUNCT
admet-2772	1379	7	m.	m.	PROPN
admet-2772	1379	8	scannapieco	scannapieco	PROPN
admet-2772	1379	9	.	.	PUNCT
admet-2772	1380	1	data	data	PROPN
admet-2772	1380	2	quality	quality	PROPN
admet-2772	1380	3	:	:	PUNCT
admet-2772	1380	4	concepts	concept	NOUN
admet-2772	1380	5	,	,	PUNCT
admet-2772	1380	6	methodologies	methodology	NOUN
admet-2772	1380	7	and	and	CCONJ
admet-2772	1380	8	techniques	technique	NOUN
admet-2772	1380	9	.	.	PUNCT
admet-2772	1381	1	springer	springer	NOUN
admet-2772	1381	2	1	1	NUM
admet-2772	1381	3	(	(	PUNCT
admet-2772	1381	4	2006	2006	NUM
admet-2772	1381	5	)	)	PUNCT
admet-2772	1381	6	161	161	NUM
admet-2772	1381	7	-	-	SYM
admet-2772	1381	8	200	200	NUM
admet-2772	1381	9	.	.	PUNCT
admet-2772	1382	1	http://dx.doi.org/10.1007/3-540-33173-5	http://dx.doi.org/10.1007/3-540-33173-5	NOUN
admet-2772	1383	1	[	[	X
admet-2772	1383	2	201	201	NUM
admet-2772	1383	3	]	]	X
admet-2772	1383	4	m.	m.	NOUN
admet-2772	1383	5	picard	picard	PROPN
admet-2772	1383	6	,	,	PUNCT
admet-2772	1383	7	m.p	m.p	PROPN
admet-2772	1383	8	.	.	PROPN
admet-2772	1383	9	scott	scott	PROPN
admet-2772	1383	10	-	-	PUNCT
admet-2772	1383	11	boyer	boyer	PROPN
admet-2772	1383	12	,	,	PUNCT
admet-2772	1383	13	a.	a.	PROPN
admet-2772	1383	14	bodein	bodein	PROPN
admet-2772	1383	15	,	,	PUNCT
admet-2772	1383	16	o.	o.	ADJ
admet-2772	1383	17	périn	périn	NOUN
admet-2772	1383	18	,	,	PUNCT
admet-2772	1383	19	a.	a.	NOUN
admet-2772	1383	20	droit	droit	NOUN
admet-2772	1383	21	.	.	PUNCT
admet-2772	1384	1	integration	integration	NOUN
admet-2772	1384	2	strategies	strategy	NOUN
admet-2772	1384	3	of	of	ADP
admet-2772	1384	4	multi	multi	ADJ
admet-2772	1384	5	-	-	ADJ
admet-2772	1384	6	omics	omics	ADJ
admet-2772	1384	7	data	datum	NOUN
admet-2772	1384	8	for	for	ADP
admet-2772	1384	9	machine	machine	NOUN
admet-2772	1384	10	learning	learn	VERB
admet-2772	1384	11	analysis	analysis	NOUN
admet-2772	1384	12	.	.	PUNCT
admet-2772	1385	1	computational	computational	ADJ
admet-2772	1385	2	and	and	CCONJ
admet-2772	1385	3	structural	structural	ADJ
admet-2772	1385	4	biotechnology	biotechnology	NOUN
admet-2772	1385	5	journal	journal	NOUN
admet-2772	1385	6	19	19	NUM
admet-2772	1385	7	(	(	PUNCT
admet-2772	1385	8	2021	2021	NUM
admet-2772	1385	9	)	)	PUNCT
admet-2772	1385	10	37353746	37353746	NUM
admet-2772	1385	11	.	.	PUNCT
admet-2772	1386	1	https://doi.org/10.1016/j.csbj.2021.06.030	https://doi.org/10.1016/j.csbj.2021.06.030	X
admet-2772	1386	2	[	[	X
admet-2772	1386	3	202	202	NUM
admet-2772	1386	4	]	]	X
admet-2772	1386	5	h.	h.	PROPN
admet-2772	1386	6	bansal	bansal	PROPN
admet-2772	1386	7	,	,	PUNCT
admet-2772	1386	8	h.	h.	PROPN
admet-2772	1386	9	luthra	luthra	PROPN
admet-2772	1386	10	,	,	PUNCT
admet-2772	1386	11	s.r	s.r	PROPN
admet-2772	1386	12	.	.	PROPN
admet-2772	1386	13	raghuram	raghuram	PROPN
admet-2772	1386	14	.	.	PUNCT
admet-2772	1387	1	a	a	DET
admet-2772	1387	2	review	review	NOUN
admet-2772	1387	3	on	on	ADP
admet-2772	1387	4	machine	machine	NOUN
admet-2772	1387	5	learning	learning	NOUN
admet-2772	1387	6	aided	aid	VERB
admet-2772	1387	7	multi	multi	ADJ
admet-2772	1387	8	-	-	ADJ
admet-2772	1387	9	omics	omics	ADJ
admet-2772	1387	10	data	data	NOUN
admet-2772	1387	11	integration	integration	NOUN
admet-2772	1387	12	techniques	technique	NOUN
admet-2772	1387	13	for	for	ADP
admet-2772	1387	14	healthcare	healthcare	NOUN
admet-2772	1387	15	.	.	PUNCT
admet-2772	1388	1	studies	study	NOUN
admet-2772	1388	2	in	in	ADP
admet-2772	1388	3	big	big	ADJ
admet-2772	1388	4	data	datum	NOUN
admet-2772	1388	5	132	132	NUM
admet-2772	1388	6	(	(	PUNCT
admet-2772	1388	7	2023	2023	NUM
admet-2772	1388	8	)	)	PUNCT
admet-2772	1388	9	211	211	NUM
admet-2772	1388	10	-	-	SYM
admet-2772	1388	11	239	239	NUM
admet-2772	1388	12	.	.	PUNCT
admet-2772	1389	1	https://doi.org/10.1007/978-3-031-38325-0_10	https://doi.org/10.1007/978-3-031-38325-0_10	NOUN
admet-2772	1389	2	[	[	X
admet-2772	1389	3	203	203	NUM
admet-2772	1389	4	]	]	PUNCT
admet-2772	1389	5	m.	m.	NOUN
admet-2772	1389	6	akhmedov	akhmedov	PROPN
admet-2772	1389	7	,	,	PUNCT
admet-2772	1389	8	a.	a.	PROPN
admet-2772	1389	9	arribas	arribas	PROPN
admet-2772	1389	10	,	,	PUNCT
admet-2772	1389	11	r.	r.	PROPN
admet-2772	1389	12	montemanni	montemanni	PROPN
admet-2772	1389	13	,	,	PUNCT
admet-2772	1389	14	f.	f.	PROPN
admet-2772	1389	15	bertoni	bertoni	PROPN
admet-2772	1389	16	,	,	PUNCT
admet-2772	1389	17	k.	k.	PROPN
admet-2772	1389	18	ivo	ivo	PROPN
admet-2772	1389	19	.	.	PUNCT
admet-2772	1390	1	omicsnet	omicsnet	NOUN
admet-2772	1390	2	:	:	PUNCT
admet-2772	1390	3	integration	integration	NOUN
admet-2772	1390	4	of	of	ADP
admet-2772	1390	5	multi	multi	ADJ
admet-2772	1390	6	-	-	ADJ
admet-2772	1390	7	omics	omics	ADJ
admet-2772	1390	8	data	datum	NOUN
admet-2772	1390	9	using	use	VERB
admet-2772	1390	10	path	path	NOUN
admet-2772	1390	11	analysis	analysis	NOUN
admet-2772	1390	12	in	in	ADP
admet-2772	1390	13	multilayer	multilayer	ADJ
admet-2772	1390	14	networks	network	NOUN
admet-2772	1390	15	.	.	PUNCT
admet-2772	1391	1	biorxiv	biorxiv	NOUN
admet-2772	1391	2	(	(	PUNCT
admet-2772	1391	3	2017	2017	NUM
admet-2772	1391	4	)	)	PUNCT
admet-2772	1391	5	.	.	PUNCT
admet-2772	1392	1	https://doi.org/10.1101/238766	https://doi.org/10.1101/238766	NOUN
admet-2772	1393	1	[	[	X
admet-2772	1393	2	204	204	NUM
admet-2772	1393	3	]	]	X
admet-2772	1393	4	i.	i.	PROPN
admet-2772	1393	5	subramanian	subramanian	PROPN
admet-2772	1393	6	,	,	PUNCT
admet-2772	1393	7	s.	s.	PROPN
admet-2772	1393	8	verma	verma	PROPN
admet-2772	1393	9	,	,	PUNCT
admet-2772	1393	10	s.	s.	PROPN
admet-2772	1393	11	kumar	kumar	PROPN
admet-2772	1393	12	,	,	PUNCT
admet-2772	1393	13	a.	a.	PROPN
admet-2772	1393	14	jere	jere	PROPN
admet-2772	1393	15	,	,	PUNCT
admet-2772	1393	16	k.	k.	PROPN
admet-2772	1393	17	anamika	anamika	PROPN
admet-2772	1393	18	.	.	PUNCT
admet-2772	1394	1	multi	multi	ADJ
admet-2772	1394	2	-	-	ADJ
admet-2772	1394	3	omics	omics	ADJ
admet-2772	1394	4	data	datum	NOUN
admet-2772	1394	5	integration	integration	NOUN
admet-2772	1394	6	,	,	PUNCT
admet-2772	1394	7	interpretation	interpretation	NOUN
admet-2772	1394	8	,	,	PUNCT
admet-2772	1394	9	and	and	CCONJ
admet-2772	1394	10	its	its	PRON
admet-2772	1394	11	application	application	NOUN
admet-2772	1394	12	.	.	PUNCT
admet-2772	1395	1	bioinformatics	bioinformatic	NOUN
admet-2772	1395	2	and	and	CCONJ
admet-2772	1395	3	biology	biology	NOUN
admet-2772	1395	4	insights	insight	NOUN
admet-2772	1395	5	14	14	NUM
admet-2772	1395	6	(	(	PUNCT
admet-2772	1395	7	2020	2020	NUM
admet-2772	1395	8	)	)	PUNCT
admet-2772	1395	9	16	16	NUM
admet-2772	1395	10	-	-	SYM
admet-2772	1395	11	21	21	NUM
admet-2772	1395	12	.	.	PUNCT
admet-2772	1396	1	https://doi.org/10.1177/1177932219899051	https://doi.org/10.1177/1177932219899051	VERB
admet-2772	1397	1	[	[	X
admet-2772	1397	2	205	205	NUM
admet-2772	1397	3	]	]	X
admet-2772	1397	4	p.k	p.k	PROPN
admet-2772	1397	5	.	.	PROPN
admet-2772	1397	6	davis	davis	PROPN
admet-2772	1397	7	,	,	PUNCT
admet-2772	1397	8	a.	a.	NOUN
admet-2772	1397	9	o’mahony	o’mahony	PROPN
admet-2772	1397	10	,	,	PUNCT
admet-2772	1397	11	j.	j.	PROPN
admet-2772	1397	12	pfautz	pfautz	PROPN
admet-2772	1397	13	.	.	PUNCT
admet-2772	1398	1	social	social	ADJ
admet-2772	1398	2	-	-	PUNCT
admet-2772	1398	3	behavioral	behavioral	ADJ
admet-2772	1398	4	modeling	modeling	NOUN
admet-2772	1398	5	for	for	ADP
admet-2772	1398	6	complex	complex	ADJ
admet-2772	1398	7	systems	system	NOUN
admet-2772	1398	8	.	.	PUNCT
admet-2772	1399	1	socialbehavioral	socialbehavioral	ADJ
admet-2772	1399	2	modeling	modeling	NOUN
admet-2772	1399	3	for	for	ADP
admet-2772	1399	4	complex	complex	ADJ
admet-2772	1399	5	systems	system	NOUN
admet-2772	1399	6	(	(	PUNCT
admet-2772	1399	7	2019	2019	NUM
admet-2772	1399	8	)	)	PUNCT
admet-2772	1399	9	1	1	NUM
admet-2772	1399	10	-	-	SYM
admet-2772	1399	11	947	947	NUM
admet-2772	1399	12	.	.	PUNCT
admet-2772	1400	1	https://doi.org/10.1002/9781119485001	https://doi.org/10.1002/9781119485001	X
admet-2772	1401	1	[	[	X
admet-2772	1401	2	206	206	NUM
admet-2772	1401	3	]	]	PUNCT
admet-2772	1401	4	a.	a.	NOUN
admet-2772	1401	5	pardo	pardo	PROPN
admet-2772	1401	6	,	,	PUNCT
admet-2772	1401	7	g.	g.	PROPN
admet-2772	1401	8	siemens	siemens	PROPN
admet-2772	1401	9	.	.	PROPN
admet-2772	1401	10	ethical	ethical	PROPN
admet-2772	1401	11	and	and	CCONJ
admet-2772	1401	12	privacy	privacy	NOUN
admet-2772	1401	13	principles	principle	NOUN
admet-2772	1401	14	for	for	ADP
admet-2772	1401	15	learning	learn	VERB
admet-2772	1401	16	analytics	analytic	NOUN
admet-2772	1401	17	.	.	PUNCT
admet-2772	1402	1	british	british	ADJ
admet-2772	1402	2	journal	journal	PROPN
admet-2772	1402	3	of	of	ADP
admet-2772	1402	4	educational	educational	ADJ
admet-2772	1402	5	technology	technology	NOUN
admet-2772	1402	6	45	45	NUM
admet-2772	1402	7	(	(	PUNCT
admet-2772	1402	8	2014	2014	NUM
admet-2772	1402	9	)	)	PUNCT
admet-2772	1402	10	438	438	NUM
admet-2772	1402	11	-	-	SYM
admet-2772	1402	12	450	450	NUM
admet-2772	1402	13	.	.	PUNCT
admet-2772	1403	1	https://doi.org/10.1111/bjet.12152	https://doi.org/10.1111/bjet.12152	NOUN
admet-2772	1404	1	[	[	X
admet-2772	1404	2	207	207	NUM
admet-2772	1404	3	]	]	PUNCT
admet-2772	1404	4	j.	j.	PROPN
admet-2772	1404	5	francom	francom	PROPN
admet-2772	1404	6	.	.	PUNCT
admet-2772	1405	1	rfid	rfid	PROPN
admet-2772	1405	2	:	:	PUNCT
admet-2772	1405	3	a	a	DET
admet-2772	1405	4	survey	survey	NOUN
admet-2772	1405	5	of	of	ADP
admet-2772	1405	6	ethical	ethical	ADJ
admet-2772	1405	7	and	and	CCONJ
admet-2772	1405	8	privacy	privacy	NOUN
admet-2772	1405	9	concerns	concern	NOUN
admet-2772	1405	10	.	.	PUNCT
admet-2772	1406	1	issues	issue	NOUN
admet-2772	1406	2	in	in	ADP
admet-2772	1406	3	information	information	NOUN
admet-2772	1406	4	systems	system	NOUN
admet-2772	1406	5	8(2	8(2	NUM
admet-2772	1406	6	)	)	PUNCT
admet-2772	1406	7	(	(	PUNCT
admet-2772	1406	8	2007	2007	NUM
admet-2772	1406	9	)	)	PUNCT
admet-2772	1406	10	336	336	NUM
admet-2772	1406	11	-	-	SYM
admet-2772	1406	12	340	340	NUM
admet-2772	1406	13	.	.	PUNCT
admet-2772	1407	1	https://doi.org/10.48009/2_iis_2007_336-340	https://doi.org/10.48009/2_iis_2007_336-340	PROPN
admet-2772	1408	1	[	[	X
admet-2772	1408	2	208	208	NUM
admet-2772	1408	3	]	]	X
admet-2772	1408	4	p.	p.	PROPN
admet-2772	1408	5	wisniewski	wisniewski	PROPN
admet-2772	1408	6	,	,	PUNCT
admet-2772	1408	7	j.	j.	PROPN
admet-2772	1408	8	vitak	vitak	PROPN
admet-2772	1408	9	,	,	PUNCT
admet-2772	1408	10	x.	x.	NOUN
admet-2772	1408	11	page	page	NOUN
admet-2772	1408	12	,	,	PUNCT
admet-2772	1408	13	b.	b.	PROPN
admet-2772	1408	14	knijnenburg	knijnenburg	PROPN
admet-2772	1408	15	,	,	PUNCT
admet-2772	1408	16	y.	y.	PROPN
admet-2772	1408	17	wang	wang	PROPN
admet-2772	1408	18	,	,	PUNCT
admet-2772	1408	19	c.	c.	PROPN
admet-2772	1408	20	fiesler	fiesler	PROPN
admet-2772	1408	21	.	.	PUNCT
admet-2772	1409	1	in	in	ADP
admet-2772	1409	2	whose	whose	DET
admet-2772	1409	3	best	good	ADJ
admet-2772	1409	4	interest	interest	NOUN
admet-2772	1409	5	?	?	PUNCT
admet-2772	1409	6	exploring	explore	VERB
admet-2772	1409	7	the	the	DET
admet-2772	1409	8	real	real	ADJ
admet-2772	1409	9	,	,	PUNCT
admet-2772	1409	10	potential	potential	ADJ
admet-2772	1409	11	,	,	PUNCT
admet-2772	1409	12	and	and	CCONJ
admet-2772	1409	13	imagined	imagine	VERB
admet-2772	1409	14	ethical	ethical	ADJ
admet-2772	1409	15	concerns	concern	NOUN
admet-2772	1409	16	in	in	ADP
admet-2772	1409	17	privacy	privacy	NOUN
admet-2772	1409	18	-	-	PUNCT
admet-2772	1409	19	focused	focus	VERB
admet-2772	1409	20	agenda	agenda	NOUN
admet-2772	1409	21	.	.	PUNCT
admet-2772	1410	1	cscw	cscw	VERB
admet-2772	1410	2	2017	2017	NUM
admet-2772	1410	3	companion	companion	NOUN
admet-2772	1410	4	of	of	ADP
admet-2772	1410	5	the	the	DET
admet-2772	1410	6	2017	2017	NUM
admet-2772	1410	7	acm	acm	NOUN
admet-2772	1410	8	conference	conference	NOUN
admet-2772	1410	9	on	on	ADP
admet-2772	1410	10	computer	computer	NOUN
admet-2772	1410	11	supported	support	VERB
admet-2772	1410	12	cooperative	cooperative	ADJ
admet-2772	1410	13	work	work	NOUN
admet-2772	1410	14	and	and	CCONJ
admet-2772	1410	15	social	social	ADJ
admet-2772	1410	16	computing	computing	NOUN
admet-2772	1410	17	(	(	PUNCT
admet-2772	1410	18	2017	2017	NUM
admet-2772	1410	19	)	)	PUNCT
admet-2772	1410	20	377	377	NUM
admet-2772	1410	21	-	-	SYM
admet-2772	1410	22	382	382	NUM
admet-2772	1410	23	.	.	PUNCT
admet-2772	1410	24	https://doi.org/10.1145/3022198.3022660	https://doi.org/10.1145/3022198.3022660	NOUN
admet-2772	1411	1	[	[	X
admet-2772	1411	2	209	209	NUM
admet-2772	1411	3	]	]	PUNCT
admet-2772	1411	4	a.	a.	NOUN
admet-2772	1411	5	nayarisseri	nayarisseri	PROPN
admet-2772	1411	6	,	,	PUNCT
admet-2772	1411	7	r.	r.	PROPN
admet-2772	1411	8	khandelwal	khandelwal	PROPN
admet-2772	1411	9	,	,	PUNCT
admet-2772	1411	10	p.	p.	PROPN
admet-2772	1411	11	tanwar	tanwar	PROPN
admet-2772	1411	12	,	,	PUNCT
admet-2772	1411	13	m.	m.	PROPN
admet-2772	1411	14	madhavi	madhavi	PROPN
admet-2772	1411	15	,	,	PUNCT
admet-2772	1411	16	d.	d.	PROPN
admet-2772	1411	17	sharma	sharma	PROPN
admet-2772	1411	18	,	,	PUNCT
admet-2772	1411	19	g.	g.	PROPN
admet-2772	1411	20	thakur	thakur	PROPN
admet-2772	1411	21	,	,	PUNCT
admet-2772	1411	22	a.	a.	PROPN
admet-2772	1411	23	speck	speck	NOUN
admet-2772	1411	24	-	-	PUNCT
admet-2772	1411	25	planche	planche	NOUN
admet-2772	1411	26	,	,	PUNCT
admet-2772	1411	27	s.k	s.k	PROPN
admet-2772	1411	28	.	.	PROPN
admet-2772	1411	29	singh	singh	PROPN
admet-2772	1411	30	.	.	PUNCT
admet-2772	1412	1	artificial	artificial	ADJ
admet-2772	1412	2	intelligence	intelligence	NOUN
admet-2772	1412	3	,	,	PUNCT
admet-2772	1412	4	big	big	ADJ
admet-2772	1412	5	data	datum	NOUN
admet-2772	1412	6	and	and	CCONJ
admet-2772	1412	7	machine	machine	NOUN
admet-2772	1412	8	learning	learning	NOUN
admet-2772	1412	9	approaches	approach	NOUN
admet-2772	1412	10	in	in	ADP
admet-2772	1412	11	precision	precision	NOUN
admet-2772	1412	12	medicine	medicine	NOUN
admet-2772	1412	13	&	&	CCONJ
admet-2772	1412	14	drug	drug	PROPN
admet-2772	1412	15	discovery	discovery	PROPN
admet-2772	1412	16	.	.	PUNCT
admet-2772	1413	1	current	current	ADJ
admet-2772	1413	2	drug	drug	NOUN
admet-2772	1413	3	targets	target	NOUN
admet-2772	1413	4	22	22	NUM
admet-2772	1413	5	(	(	PUNCT
admet-2772	1413	6	2021	2021	NUM
admet-2772	1413	7	)	)	PUNCT
admet-2772	1413	8	631	631	NUM
admet-2772	1413	9	-	-	PUNCT
admet-2772	1413	10	655	655	NUM
admet-2772	1413	11	.	.	PUNCT
admet-2772	1414	1	https://doi.org/10.2174/1389450122999210104205732	https://doi.org/10.2174/1389450122999210104205732	PRON
admet-2772	1415	1	[	[	X
admet-2772	1415	2	210	210	NUM
admet-2772	1415	3	]	]	X
admet-2772	1415	4	v.g	v.g	PROPN
admet-2772	1415	5	.	.	PROPN
admet-2772	1415	6	maltarollo	maltarollo	PROPN
admet-2772	1415	7	,	,	PUNCT
admet-2772	1415	8	j.c	j.c	PROPN
admet-2772	1415	9	.	.	PROPN
admet-2772	1415	10	gertrudes	gertrudes	PROPN
admet-2772	1415	11	,	,	PUNCT
admet-2772	1415	12	p.r	p.r	PROPN
admet-2772	1415	13	.	.	PROPN
admet-2772	1415	14	oliveira	oliveira	PROPN
admet-2772	1415	15	,	,	PUNCT
admet-2772	1415	16	k.m	k.m	PROPN
admet-2772	1415	17	.	.	PROPN
admet-2772	1415	18	honorio	honorio	PROPN
admet-2772	1415	19	.	.	PUNCT
admet-2772	1416	1	applying	apply	VERB
admet-2772	1416	2	machine	machine	NOUN
admet-2772	1416	3	learning	learn	VERB
admet-2772	1416	4	techniques	technique	NOUN
admet-2772	1416	5	for	for	ADP
admet-2772	1416	6	adme	adme	NOUN
admet-2772	1416	7	-	-	PUNCT
admet-2772	1416	8	tox	tox	NOUN
admet-2772	1416	9	prediction	prediction	NOUN
admet-2772	1416	10	:	:	PUNCT
admet-2772	1416	11	a	a	DET
admet-2772	1416	12	review	review	NOUN
admet-2772	1416	13	.	.	PUNCT
admet-2772	1417	1	expert	expert	ADJ
admet-2772	1417	2	opinion	opinion	NOUN
admet-2772	1417	3	on	on	ADP
admet-2772	1417	4	drug	drug	NOUN
admet-2772	1417	5	metabolism	metabolism	NOUN
admet-2772	1417	6	and	and	CCONJ
admet-2772	1417	7	toxicology	toxicology	NOUN
admet-2772	1417	8	11	11	NUM
admet-2772	1417	9	(	(	PUNCT
admet-2772	1417	10	2015	2015	NUM
admet-2772	1417	11	)	)	PUNCT
admet-2772	1417	12	259	259	NUM
admet-2772	1417	13	-	-	SYM
admet-2772	1417	14	271	271	NUM
admet-2772	1417	15	.	.	PUNCT
admet-2772	1417	16	https://doi.org/10.1517/17425255.2015.980814	https://doi.org/10.1517/17425255.2015.980814	X
admet-2772	1418	1	[	[	X
admet-2772	1418	2	211	211	NUM
admet-2772	1418	3	]	]	X
admet-2772	1418	4	y.	y.	NOUN
admet-2772	1418	5	bidault	bidault	PROPN
admet-2772	1418	6	.	.	PUNCT
admet-2772	1419	1	a	a	DET
admet-2772	1419	2	flexible	flexible	ADJ
admet-2772	1419	3	approach	approach	NOUN
admet-2772	1419	4	for	for	ADP
admet-2772	1419	5	optimising	optimise	VERB
admet-2772	1419	6	in	in	ADP
admet-2772	1419	7	silico	silico	NOUN
admet-2772	1419	8	adme	adme	NOUN
admet-2772	1419	9	/	/	SYM
admet-2772	1419	10	tox	tox	NOUN
admet-2772	1419	11	characterisation	characterisation	NOUN
admet-2772	1419	12	of	of	ADP
admet-2772	1419	13	lead	lead	ADJ
admet-2772	1419	14	candidates	candidate	NOUN
admet-2772	1419	15	.	.	PUNCT
admet-2772	1420	1	expert	expert	ADJ
admet-2772	1420	2	opinion	opinion	NOUN
admet-2772	1420	3	on	on	ADP
admet-2772	1420	4	drug	drug	NOUN
admet-2772	1420	5	metabolism	metabolism	NOUN
admet-2772	1420	6	and	and	CCONJ
admet-2772	1420	7	toxicology	toxicology	NOUN
admet-2772	1420	8	2	2	NUM
admet-2772	1420	9	(	(	PUNCT
admet-2772	1420	10	2006	2006	NUM
admet-2772	1420	11	)	)	PUNCT
admet-2772	1420	12	157	157	NUM
admet-2772	1420	13	-	-	SYM
admet-2772	1420	14	168	168	NUM
admet-2772	1420	15	.	.	PUNCT
admet-2772	1421	1	https://doi.org/10.1517/17425255.2.1.157	https://doi.org/10.1517/17425255.2.1.157	NOUN
admet-2772	1422	1	[	[	X
admet-2772	1422	2	212	212	NUM
admet-2772	1422	3	]	]	PUNCT
admet-2772	1422	4	j.g.m	j.g.m	NOUN
admet-2772	1422	5	.	.	PUNCT
admet-2772	1423	1	bessems	bessems	PROPN
admet-2772	1423	2	,	,	PUNCT
admet-2772	1423	3	l.	l.	PROPN
admet-2772	1423	4	geraets	geraets	PROPN
admet-2772	1423	5	.	.	PUNCT
admet-2772	1424	1	proper	proper	ADJ
admet-2772	1424	2	knowledge	knowledge	NOUN
admet-2772	1424	3	on	on	ADP
admet-2772	1424	4	toxicokinetics	toxicokinetic	NOUN
admet-2772	1424	5	improves	improve	VERB
admet-2772	1424	6	human	human	ADJ
admet-2772	1424	7	hazard	hazard	NOUN
admet-2772	1424	8	testing	testing	NOUN
admet-2772	1424	9	and	and	CCONJ
admet-2772	1424	10	subsequent	subsequent	ADJ
admet-2772	1424	11	health	health	NOUN
admet-2772	1424	12	risk	risk	NOUN
admet-2772	1424	13	characterisation	characterisation	NOUN
admet-2772	1424	14	.	.	PUNCT
admet-2772	1425	1	a	a	DET
admet-2772	1425	2	case	case	NOUN
admet-2772	1425	3	study	study	NOUN
admet-2772	1425	4	approach	approach	NOUN
admet-2772	1425	5	.	.	PUNCT
admet-2772	1426	1	regulatory	regulatory	ADJ
admet-2772	1426	2	toxicology	toxicology	NOUN
admet-2772	1426	3	and	and	CCONJ
admet-2772	1426	4	pharmacology	pharmacology	NOUN
admet-2772	1426	5	67	67	NUM
admet-2772	1426	6	(	(	PUNCT
admet-2772	1426	7	2013	2013	NUM
admet-2772	1426	8	)	)	PUNCT
admet-2772	1426	9	325	325	NUM
admet-2772	1426	10	-	-	SYM
admet-2772	1426	11	334	334	NUM
admet-2772	1426	12	.	.	PUNCT
admet-2772	1427	1	https://doi.org/10.1016/j.yrtph.2013.08.010	https://doi.org/10.1016/j.yrtph.2013.08.010	PROPN
admet-2772	1427	2	[	[	X
admet-2772	1427	3	213	213	NUM
admet-2772	1427	4	]	]	X
admet-2772	1427	5	s.n	s.n	PROPN
admet-2772	1427	6	.	.	NOUN
admet-2772	1427	7	deftereos	deftereo	NOUN
admet-2772	1427	8	,	,	PUNCT
admet-2772	1427	9	c.	c.	PROPN
admet-2772	1427	10	andronis	andronis	PROPN
admet-2772	1427	11	,	,	PUNCT
admet-2772	1427	12	e.j	e.j	PROPN
admet-2772	1427	13	.	.	PROPN
admet-2772	1427	14	friedla	friedla	PROPN
admet-2772	1427	15	,	,	PUNCT
admet-2772	1427	16	a.	a.	NOUN
admet-2772	1427	17	persidis	persidis	PROPN
admet-2772	1427	18	,	,	PUNCT
admet-2772	1427	19	a.	a.	NOUN
admet-2772	1427	20	persidis	persidis	PROPN
admet-2772	1427	21	.	.	PUNCT
admet-2772	1428	1	drug	drug	NOUN
admet-2772	1428	2	repurposing	repurpose	VERB
admet-2772	1428	3	and	and	CCONJ
admet-2772	1428	4	adverse	adverse	ADJ
admet-2772	1428	5	event	event	NOUN
admet-2772	1428	6	prediction	prediction	NOUN
admet-2772	1428	7	using	use	VERB
admet-2772	1428	8	high	high	ADJ
admet-2772	1428	9	-	-	PUNCT
admet-2772	1428	10	throughput	throughput	NOUN
admet-2772	1428	11	literature	literature	NOUN
admet-2772	1428	12	analysis	analysis	NOUN
admet-2772	1428	13	.	.	PUNCT
admet-2772	1429	1	wiley	wiley	PROPN
admet-2772	1429	2	interdisciplinary	interdisciplinary	ADJ
admet-2772	1429	3	reviews	review	NOUN
admet-2772	1429	4	:	:	PUNCT
admet-2772	1429	5	systems	system	NOUN
admet-2772	1429	6	biology	biology	NOUN
admet-2772	1429	7	and	and	CCONJ
admet-2772	1429	8	medicine	medicine	NOUN
admet-2772	1429	9	3	3	NUM
admet-2772	1429	10	(	(	PUNCT
admet-2772	1429	11	2011	2011	NUM
admet-2772	1429	12	)	)	PUNCT
admet-2772	1429	13	323	323	NUM
admet-2772	1429	14	-	-	SYM
admet-2772	1429	15	334	334	NUM
admet-2772	1429	16	.	.	PUNCT
admet-2772	1430	1	https://doi.org/10.1002/wsbm.147	https://doi.org/10.1002/wsbm.147	NOUN
admet-2772	1431	1	[	[	X
admet-2772	1431	2	214	214	NUM
admet-2772	1431	3	]	]	PUNCT
admet-2772	1431	4	l.	l.	PROPN
admet-2772	1431	5	mucke	mucke	PROPN
admet-2772	1431	6	.	.	PUNCT
admet-2772	1432	1	ec-03	ec-03	X
admet-2772	1432	2	-	-	PUNCT
admet-2772	1432	3	04	04	NUM
admet-2772	1432	4	:	:	PUNCT
admet-2772	1432	5	tau	tau	NOUN
admet-2772	1432	6	-	-	PUNCT
admet-2772	1432	7	dependent	dependent	ADJ
admet-2772	1432	8	signaling	signaling	ADJ
admet-2772	1432	9	and	and	CCONJ
admet-2772	1432	10	neuronal	neuronal	ADJ
admet-2772	1432	11	network	network	NOUN
admet-2772	1432	12	hyperexcitability	hyperexcitability	NOUN
admet-2772	1432	13	.	.	PUNCT
admet-2772	1433	1	alzheimer	alzheimer	PROPN
admet-2772	1433	2	’s	’s	PART
admet-2772	1433	3	&	&	CCONJ
admet-2772	1433	4	dementia	dementia	PROPN
admet-2772	1433	5	12	12	NUM
admet-2772	1433	6	(	(	PUNCT
admet-2772	1433	7	2016	2016	NUM
admet-2772	1433	8	)	)	PUNCT
admet-2772	1434	1	p269	p269	PROPN
admet-2772	1434	2	.	.	PUNCT
admet-2772	1435	1	https://doi.org/10.1016/j.jalz.2016.06.2382	https://doi.org/10.1016/j.jalz.2016.06.2382	NOUN
admet-2772	1435	2	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	1436	1	https://doi.org/10.1109/bigdata.2015.7364065	https://doi.org/10.1109/bigdata.2015.7364065	PROPN
admet-2772	1436	2	https://doi.org/10.1007/978-3-031-01892-3	https://doi.org/10.1007/978-3-031-01892-3	PROPN
admet-2772	1436	3	https://doi.org/10.1007/978-0-85729-320-6_91	https://doi.org/10.1007/978-0-85729-320-6_91	PROPN
admet-2772	1436	4	http://dx.doi.org/10.1007/3-540-33173-5	http://dx.doi.org/10.1007/3-540-33173-5	PROPN
admet-2772	1436	5	https://doi.org/10.1016/j.csbj.2021.06.030	https://doi.org/10.1016/j.csbj.2021.06.030	NOUN
admet-2772	1436	6	https://doi.org/10.1007/978-3-031-38325-0_10	https://doi.org/10.1007/978-3-031-38325-0_10	NOUN
admet-2772	1436	7	https://doi.org/10.1101/238766	https://doi.org/10.1101/238766	NOUN
admet-2772	1436	8	https://doi.org/10.1177/1177932219899051	https://doi.org/10.1177/1177932219899051	NOUN
admet-2772	1436	9	https://doi.org/10.1002/9781119485001	https://doi.org/10.1002/9781119485001	NOUN
admet-2772	1436	10	https://doi.org/10.1111/bjet.12152	https://doi.org/10.1111/bjet.12152	NOUN
admet-2772	1436	11	https://doi.org/10.48009/2_iis_2007_336-340	https://doi.org/10.48009/2_iis_2007_336-340	VERB
admet-2772	1436	12	https://doi.org/10.1145/3022198.3022660	https://doi.org/10.1145/3022198.3022660	NOUN
admet-2772	1436	13	https://doi.org/10.2174/1389450122999210104205732	https://doi.org/10.2174/1389450122999210104205732	ADP
admet-2772	1436	14	https://doi.org/10.1517/17425255.2015.980814	https://doi.org/10.1517/17425255.2015.980814	PROPN
admet-2772	1436	15	https://doi.org/10.1517/17425255.2.1.157	https://doi.org/10.1517/17425255.2.1.157	PROPN
admet-2772	1436	16	https://doi.org/10.1016/j.yrtph.2013.08.010	https://doi.org/10.1016/j.yrtph.2013.08.010	PROPN
admet-2772	1436	17	https://doi.org/10.1002/wsbm.147	https://doi.org/10.1002/wsbm.147	PRON
admet-2772	1437	1	https://doi.org/10.1016/j.jalz.2016.06.2382	https://doi.org/10.1016/j.jalz.2016.06.2382	NOUN
admet-2772	1437	2	m.	m.	NOUN
admet-2772	1437	3	venkataraman	venkataraman	PROPN
admet-2772	1437	4	et	et	PROPN
admet-2772	1437	5	al	al	PROPN
admet-2772	1437	6	.	.	PROPN
admet-2772	1437	7	admet	admet	PROPN
admet-2772	1437	8	&	&	CCONJ
admet-2772	1437	9	dmpk	dmpk	PROPN
admet-2772	1437	10	13(3	13(3	NUM
admet-2772	1437	11	)	)	PUNCT
admet-2772	1437	12	(	(	PUNCT
admet-2772	1437	13	2025	2025	NUM
admet-2772	1437	14	)	)	PUNCT
admet-2772	1437	15	2772	2772	NUM
admet-2772	1437	16	38	38	NUM
admet-2772	1438	1	[	[	X
admet-2772	1438	2	215	215	NUM
admet-2772	1438	3	]	]	X
admet-2772	1438	4	f.	f.	PROPN
admet-2772	1438	5	farouk	farouk	PROPN
admet-2772	1438	6	,	,	PUNCT
admet-2772	1438	7	r.	r.	PROPN
admet-2772	1438	8	shamma	shamma	PROPN
admet-2772	1438	9	.	.	PUNCT
admet-2772	1439	1	chemical	chemical	ADJ
admet-2772	1439	2	structure	structure	NOUN
admet-2772	1439	3	modifications	modification	NOUN
admet-2772	1439	4	and	and	CCONJ
admet-2772	1439	5	nano	nano	NOUN
admet-2772	1439	6	-	-	PUNCT
admet-2772	1439	7	technology	technology	NOUN
admet-2772	1439	8	applications	application	NOUN
admet-2772	1439	9	for	for	ADP
admet-2772	1439	10	improving	improve	VERB
admet-2772	1439	11	adme	adme	NOUN
admet-2772	1439	12	-	-	PUNCT
admet-2772	1439	13	tox	tox	NOUN
admet-2772	1439	14	properties	property	NOUN
admet-2772	1439	15	,	,	PUNCT
admet-2772	1439	16	a	a	DET
admet-2772	1439	17	review	review	NOUN
admet-2772	1439	18	.	.	PUNCT
admet-2772	1440	1	archiv	archiv	PROPN
admet-2772	1440	2	der	der	PROPN
admet-2772	1440	3	pharmazie	pharmazie	PROPN
admet-2772	1440	4	352	352	NUM
admet-2772	1440	5	(	(	PUNCT
admet-2772	1440	6	2019	2019	NUM
admet-2772	1440	7	)	)	PUNCT
admet-2772	1440	8	1800213	1800213	NUM
admet-2772	1440	9	.	.	PUNCT
admet-2772	1441	1	https://doi.org/10.1002/ardp.201800213	https://doi.org/10.1002/ardp.201800213	NOUN
admet-2772	1441	2	[	[	X
admet-2772	1441	3	216	216	NUM
admet-2772	1441	4	]	]	X
admet-2772	1441	5	g.	g.	PROPN
admet-2772	1441	6	szakács	szakács	PROPN
admet-2772	1441	7	,	,	PUNCT
admet-2772	1441	8	a.	a.	NOUN
admet-2772	1441	9	váradi	váradi	PROPN
admet-2772	1441	10	,	,	PUNCT
admet-2772	1441	11	c.	c.	PROPN
admet-2772	1441	12	özvegy	özvegy	PROPN
admet-2772	1441	13	-	-	PUNCT
admet-2772	1441	14	laczka	laczka	PROPN
admet-2772	1441	15	,	,	PUNCT
admet-2772	1441	16	b.	b.	PROPN
admet-2772	1441	17	sarkadi	sarkadi	PROPN
admet-2772	1441	18	.	.	PUNCT
admet-2772	1442	1	the	the	DET
admet-2772	1442	2	role	role	NOUN
admet-2772	1442	3	of	of	ADP
admet-2772	1442	4	abc	abc	PROPN
admet-2772	1442	5	transporters	transporter	NOUN
admet-2772	1442	6	in	in	ADP
admet-2772	1442	7	drug	drug	NOUN
admet-2772	1442	8	absorption	absorption	NOUN
admet-2772	1442	9	,	,	PUNCT
admet-2772	1442	10	distribution	distribution	NOUN
admet-2772	1442	11	,	,	PUNCT
admet-2772	1442	12	metabolism	metabolism	NOUN
admet-2772	1442	13	,	,	PUNCT
admet-2772	1442	14	excretion	excretion	NOUN
admet-2772	1442	15	and	and	CCONJ
admet-2772	1442	16	toxicity	toxicity	NOUN
admet-2772	1442	17	(	(	PUNCT
admet-2772	1442	18	adme	adme	NOUN
admet-2772	1442	19	-	-	PUNCT
admet-2772	1442	20	tox	tox	NOUN
admet-2772	1442	21	)	)	PUNCT
admet-2772	1442	22	.	.	PUNCT
admet-2772	1443	1	drug	drug	NOUN
admet-2772	1443	2	discovery	discovery	PROPN
admet-2772	1443	3	today	today	NOUN
admet-2772	1443	4	13	13	NUM
admet-2772	1443	5	(	(	PUNCT
admet-2772	1443	6	2008	2008	NUM
admet-2772	1443	7	)	)	PUNCT
admet-2772	1443	8	379393	379393	NUM
admet-2772	1443	9	.	.	PUNCT
admet-2772	1444	1	https://doi.org/10.1016/j.drudis.2007.12.010	https://doi.org/10.1016/j.drudis.2007.12.010	NOUN
admet-2772	1445	1	[	[	X
admet-2772	1445	2	217	217	NUM
admet-2772	1445	3	]	]	PUNCT
admet-2772	1445	4	c.	c.	PROPN
admet-2772	1445	5	kim	kim	PROPN
admet-2772	1445	6	,	,	PUNCT
admet-2772	1445	7	j.	j.	PROPN
admet-2772	1445	8	jeong	jeong	PROPN
admet-2772	1445	9	,	,	PUNCT
admet-2772	1445	10	j.	j.	PROPN
admet-2772	1445	11	choi	choi	PROPN
admet-2772	1445	12	.	.	PUNCT
admet-2772	1446	1	effects	effect	NOUN
admet-2772	1446	2	of	of	ADP
admet-2772	1446	3	class	class	NOUN
admet-2772	1446	4	imbalance	imbalance	NOUN
admet-2772	1446	5	and	and	CCONJ
admet-2772	1446	6	data	datum	NOUN
admet-2772	1446	7	scarcity	scarcity	NOUN
admet-2772	1446	8	on	on	ADP
admet-2772	1446	9	the	the	DET
admet-2772	1446	10	performance	performance	NOUN
admet-2772	1446	11	of	of	ADP
admet-2772	1446	12	binary	binary	ADJ
admet-2772	1446	13	classification	classification	NOUN
admet-2772	1446	14	machine	machine	NOUN
admet-2772	1446	15	learning	learning	NOUN
admet-2772	1446	16	models	model	NOUN
admet-2772	1446	17	developed	develop	VERB
admet-2772	1446	18	based	base	VERB
admet-2772	1446	19	on	on	ADP
admet-2772	1446	20	toxcast	toxcast	NOUN
admet-2772	1446	21	/	/	SYM
admet-2772	1446	22	tox21	tox21	PROPN
admet-2772	1446	23	assay	assay	PROPN
admet-2772	1446	24	data	data	PROPN
admet-2772	1446	25	.	.	PUNCT
admet-2772	1447	1	chemical	chemical	ADJ
admet-2772	1447	2	research	research	NOUN
admet-2772	1447	3	in	in	ADP
admet-2772	1447	4	toxicology	toxicology	NOUN
admet-2772	1447	5	35	35	NUM
admet-2772	1447	6	(	(	PUNCT
admet-2772	1447	7	2022	2022	NUM
admet-2772	1447	8	)	)	PUNCT
admet-2772	1447	9	2219	2219	NUM
admet-2772	1447	10	-	-	SYM
admet-2772	1447	11	2226	2226	NUM
admet-2772	1447	12	.	.	PUNCT
admet-2772	1448	1	https://doi.org/10.1021/acs.chemrestox.2c00189	https://doi.org/10.1021/acs.chemrestox.2c00189	PROPN
admet-2772	1448	2	[	[	X
admet-2772	1448	3	218	218	NUM
admet-2772	1448	4	]	]	X
admet-2772	1448	5	y.o	y.o	PROPN
admet-2772	1448	6	.	.	PROPN
admet-2772	1448	7	lee	lee	PROPN
admet-2772	1448	8	,	,	PUNCT
admet-2772	1448	9	y.j	y.j	PROPN
admet-2772	1448	10	.	.	PUNCT
admet-2772	1448	11	kim	kim	PROPN
admet-2772	1448	12	.	.	PUNCT
admet-2772	1449	1	the	the	DET
admet-2772	1449	2	effect	effect	NOUN
admet-2772	1449	3	of	of	ADP
admet-2772	1449	4	resampling	resample	VERB
admet-2772	1449	5	on	on	ADP
admet-2772	1449	6	data	datum	NOUN
admet-2772	1449	7	-	-	PUNCT
admet-2772	1449	8	imbalanced	imbalance	VERB
admet-2772	1449	9	conditions	condition	NOUN
admet-2772	1449	10	for	for	ADP
admet-2772	1449	11	prediction	prediction	NOUN
admet-2772	1449	12	towards	towards	ADP
admet-2772	1449	13	nuclear	nuclear	ADJ
admet-2772	1449	14	receptor	receptor	NOUN
admet-2772	1449	15	profiling	profiling	NOUN
admet-2772	1449	16	using	use	VERB
admet-2772	1449	17	deep	deep	ADJ
admet-2772	1449	18	learning	learning	NOUN
admet-2772	1449	19	.	.	PUNCT
admet-2772	1450	1	molecular	molecular	ADJ
admet-2772	1450	2	informatics	informatic	NOUN
admet-2772	1450	3	39	39	NUM
admet-2772	1450	4	(	(	PUNCT
admet-2772	1450	5	2020	2020	NUM
admet-2772	1450	6	)	)	PUNCT
admet-2772	1450	7	1900131	1900131	NUM
admet-2772	1450	8	.	.	PUNCT
admet-2772	1451	1	https://doi.org/10.1002/minf.201900131	https://doi.org/10.1002/minf.201900131	X
admet-2772	1452	1	[	[	X
admet-2772	1452	2	219	219	NUM
admet-2772	1452	3	]	]	PUNCT
admet-2772	1452	4	l.	l.	PROPN
admet-2772	1452	5	tao	tao	PROPN
admet-2772	1452	6	,	,	PUNCT
admet-2772	1452	7	p.	p.	PROPN
admet-2772	1452	8	zhang	zhang	PROPN
admet-2772	1452	9	,	,	PUNCT
admet-2772	1452	10	c.	c.	PROPN
admet-2772	1452	11	qin	qin	PROPN
admet-2772	1452	12	,	,	PUNCT
admet-2772	1452	13	s.y	s.y	PROPN
admet-2772	1452	14	.	.	PROPN
admet-2772	1452	15	chen	chen	PROPN
admet-2772	1452	16	,	,	PUNCT
admet-2772	1452	17	c.	c.	PROPN
admet-2772	1452	18	zhang	zhang	PROPN
admet-2772	1452	19	,	,	PUNCT
admet-2772	1452	20	z.	z.	PROPN
admet-2772	1452	21	chen	chen	PROPN
admet-2772	1452	22	,	,	PUNCT
admet-2772	1452	23	f.	f.	PROPN
admet-2772	1452	24	zhu	zhu	PROPN
admet-2772	1452	25	,	,	PUNCT
admet-2772	1452	26	s.y	s.y	PROPN
admet-2772	1452	27	.	.	PROPN
admet-2772	1452	28	yang	yang	PROPN
admet-2772	1452	29	,	,	PUNCT
admet-2772	1452	30	y.q	y.q	PROPN
admet-2772	1452	31	.	.	PROPN
admet-2772	1452	32	wei	wei	PROPN
admet-2772	1452	33	,	,	PUNCT
admet-2772	1452	34	y.z	y.z	PROPN
admet-2772	1452	35	.	.	PROPN
admet-2772	1452	36	chen	chen	PROPN
admet-2772	1452	37	.	.	PUNCT
admet-2772	1453	1	recent	recent	ADJ
admet-2772	1453	2	progresses	progress	NOUN
admet-2772	1453	3	in	in	ADP
admet-2772	1453	4	the	the	DET
admet-2772	1453	5	exploration	exploration	NOUN
admet-2772	1453	6	of	of	ADP
admet-2772	1453	7	machine	machine	NOUN
admet-2772	1453	8	learning	learning	NOUN
admet-2772	1453	9	methods	method	NOUN
admet-2772	1453	10	as	as	ADP
admet-2772	1453	11	in	in	ADP
admet-2772	1453	12	-	-	PUNCT
admet-2772	1453	13	silico	silico	NOUN
admet-2772	1453	14	adme	adme	NOUN
admet-2772	1453	15	prediction	prediction	NOUN
admet-2772	1453	16	tools	tool	NOUN
admet-2772	1453	17	.	.	PUNCT
admet-2772	1454	1	advanced	advanced	ADJ
admet-2772	1454	2	drug	drug	NOUN
admet-2772	1454	3	delivery	delivery	NOUN
admet-2772	1454	4	reviews	review	VERB
admet-2772	1454	5	86	86	NUM
admet-2772	1454	6	(	(	PUNCT
admet-2772	1454	7	2015	2015	NUM
admet-2772	1454	8	)	)	PUNCT
admet-2772	1454	9	83	83	NUM
admet-2772	1454	10	-	-	SYM
admet-2772	1454	11	100	100	NUM
admet-2772	1454	12	.	.	PUNCT
admet-2772	1455	1	https://doi.org/10.1016/j.addr.2015.03.014	https://doi.org/10.1016/j.addr.2015.03.014	VERB
admet-2772	1455	2	[	[	X
admet-2772	1455	3	220	220	NUM
admet-2772	1455	4	]	]	PUNCT
admet-2772	1455	5	x.	x.	NOUN
admet-2772	1455	6	sun	sun	PROPN
admet-2772	1455	7	,	,	PUNCT
admet-2772	1455	8	j.	j.	PROPN
admet-2772	1455	9	zhu	zhu	PROPN
admet-2772	1455	10	,	,	PUNCT
admet-2772	1455	11	b.	b.	PROPN
admet-2772	1455	12	chen	chen	PROPN
admet-2772	1455	13	,	,	PUNCT
admet-2772	1455	14	h.	h.	PROPN
admet-2772	1455	15	you	you	PRON
admet-2772	1455	16	,	,	PUNCT
admet-2772	1455	17	h.	h.	PROPN
admet-2772	1455	18	xu	xu	PROPN
admet-2772	1455	19	.	.	PUNCT
admet-2772	1456	1	a	a	DET
admet-2772	1456	2	feature	feature	NOUN
admet-2772	1456	3	transferring	transfer	VERB
admet-2772	1456	4	workflow	workflow	NOUN
admet-2772	1456	5	between	between	ADP
admet-2772	1456	6	data	datum	NOUN
admet-2772	1456	7	-	-	PUNCT
admet-2772	1456	8	poor	poor	ADJ
admet-2772	1456	9	compounds	compound	NOUN
admet-2772	1456	10	in	in	ADP
admet-2772	1456	11	various	various	ADJ
admet-2772	1456	12	tasks	task	NOUN
admet-2772	1456	13	.	.	PUNCT
admet-2772	1457	1	plos	plos	PROPN
admet-2772	1457	2	one	one	NUM
admet-2772	1457	3	17	17	NUM
admet-2772	1457	4	(	(	PUNCT
admet-2772	1457	5	2022	2022	NUM
admet-2772	1457	6	)	)	PUNCT
admet-2772	1457	7	e0266088	e0266088	NOUN
admet-2772	1457	8	.	.	PUNCT
admet-2772	1458	1	https://doi.org/10.1371/journal.pone.0266088	https://doi.org/10.1371/journal.pone.0266088	NOUN
admet-2772	1459	1	[	[	X
admet-2772	1459	2	221	221	NUM
admet-2772	1459	3	]	]	PUNCT
admet-2772	1459	4	l.	l.	PROPN
admet-2772	1459	5	alzubaidi	alzubaidi	PROPN
admet-2772	1459	6	,	,	PUNCT
admet-2772	1459	7	j.	j.	PROPN
admet-2772	1459	8	bai	bai	PROPN
admet-2772	1459	9	,	,	PUNCT
admet-2772	1459	10	a.	a.	PROPN
admet-2772	1459	11	al	al	PROPN
admet-2772	1459	12	-	-	PUNCT
admet-2772	1459	13	sabaawi	sabaawi	PROPN
admet-2772	1459	14	,	,	PUNCT
admet-2772	1459	15	j.	j.	PROPN
admet-2772	1459	16	santamaría	santamaría	PROPN
admet-2772	1459	17	,	,	PUNCT
admet-2772	1459	18	a.s	a.s	PROPN
admet-2772	1459	19	.	.	PROPN
admet-2772	1459	20	albahri	albahri	PROPN
admet-2772	1459	21	,	,	PUNCT
admet-2772	1459	22	b.s.n	b.s.n	PROPN
admet-2772	1459	23	.	.	PUNCT
admet-2772	1460	1	al	al	PROPN
admet-2772	1460	2	-	-	PUNCT
admet-2772	1460	3	dabbagh	dabbagh	PROPN
admet-2772	1460	4	,	,	PUNCT
admet-2772	1460	5	m.a	m.a	PROPN
admet-2772	1460	6	.	.	PROPN
admet-2772	1460	7	fadhel	fadhel	PROPN
admet-2772	1460	8	,	,	PUNCT
admet-2772	1460	9	m.	m.	PROPN
admet-2772	1460	10	manoufali	manoufali	PROPN
admet-2772	1460	11	,	,	PUNCT
admet-2772	1460	12	j.	j.	PROPN
admet-2772	1460	13	zhang	zhang	PROPN
admet-2772	1460	14	,	,	PUNCT
admet-2772	1460	15	a.h	a.h	PROPN
admet-2772	1460	16	.	.	PROPN
admet-2772	1460	17	al	al	PROPN
admet-2772	1460	18	-	-	PUNCT
admet-2772	1460	19	timemy	timemy	PROPN
admet-2772	1460	20	,	,	PUNCT
admet-2772	1460	21	y.	y.	PROPN
admet-2772	1460	22	duan	duan	PROPN
admet-2772	1460	23	,	,	PUNCT
admet-2772	1460	24	a.	a.	PROPN
admet-2772	1460	25	abdullah	abdullah	PROPN
admet-2772	1460	26	,	,	PUNCT
admet-2772	1460	27	l.	l.	PROPN
admet-2772	1460	28	farhan	farhan	PROPN
admet-2772	1460	29	,	,	PUNCT
admet-2772	1460	30	y.	y.	PROPN
admet-2772	1460	31	lu	lu	PROPN
admet-2772	1460	32	,	,	PUNCT
admet-2772	1460	33	a.	a.	PROPN
admet-2772	1460	34	gupta	gupta	PROPN
admet-2772	1460	35	,	,	PUNCT
admet-2772	1460	36	f.	f.	PROPN
admet-2772	1460	37	albu	albu	PROPN
admet-2772	1460	38	,	,	PUNCT
admet-2772	1460	39	a.	a.	PROPN
admet-2772	1460	40	abbosh	abbosh	PROPN
admet-2772	1460	41	,	,	PUNCT
admet-2772	1460	42	y.	y.	PROPN
admet-2772	1460	43	gu	gu	PROPN
admet-2772	1460	44	.	.	PUNCT
admet-2772	1461	1	a	a	DET
admet-2772	1461	2	survey	survey	NOUN
admet-2772	1461	3	on	on	ADP
admet-2772	1461	4	deep	deep	ADJ
admet-2772	1461	5	learning	learning	NOUN
admet-2772	1461	6	tools	tool	NOUN
admet-2772	1461	7	dealing	deal	VERB
admet-2772	1461	8	with	with	ADP
admet-2772	1461	9	data	datum	NOUN
admet-2772	1461	10	scarcity	scarcity	NOUN
admet-2772	1461	11	:	:	PUNCT
admet-2772	1461	12	definitions	definition	NOUN
admet-2772	1461	13	,	,	PUNCT
admet-2772	1461	14	challenges	challenge	NOUN
admet-2772	1461	15	,	,	PUNCT
admet-2772	1461	16	solutions	solution	NOUN
admet-2772	1461	17	,	,	PUNCT
admet-2772	1461	18	tips	tip	NOUN
admet-2772	1461	19	,	,	PUNCT
admet-2772	1461	20	and	and	CCONJ
admet-2772	1461	21	applications	application	NOUN
admet-2772	1461	22	.	.	PUNCT
admet-2772	1462	1	journal	journal	NOUN
admet-2772	1462	2	of	of	ADP
admet-2772	1462	3	big	big	ADJ
admet-2772	1462	4	data	datum	NOUN
admet-2772	1462	5	10	10	NUM
admet-2772	1462	6	(	(	PUNCT
admet-2772	1462	7	2023	2023	NUM
admet-2772	1462	8	)	)	PUNCT
admet-2772	1462	9	46	46	NUM
admet-2772	1462	10	.	.	PUNCT
admet-2772	1463	1	https://doi.org/10.1186/s40537023-00727-2	https://doi.org/10.1186/s40537023-00727-2	NOUN
admet-2772	1464	1	[	[	X
admet-2772	1464	2	222	222	NUM
admet-2772	1464	3	]	]	X
admet-2772	1464	4	d.a	d.a	PROPN
admet-2772	1464	5	.	.	PROPN
admet-2772	1464	6	dablain	dablain	PROPN
admet-2772	1464	7	,	,	PUNCT
admet-2772	1464	8	c.	c.	PROPN
admet-2772	1464	9	bellinger	bellinger	PROPN
admet-2772	1464	10	,	,	PUNCT
admet-2772	1464	11	b.	b.	PROPN
admet-2772	1464	12	krawczyk	krawczyk	PROPN
admet-2772	1464	13	,	,	PUNCT
admet-2772	1464	14	d.w	d.w	PROPN
admet-2772	1464	15	.	.	PROPN
admet-2772	1465	1	aha	aha	PROPN
admet-2772	1465	2	,	,	PUNCT
admet-2772	1465	3	n.	n.	PROPN
admet-2772	1465	4	v.	v.	PROPN
admet-2772	1465	5	chawla	chawla	PROPN
admet-2772	1465	6	.	.	PUNCT
admet-2772	1466	1	interpretable	interpretable	ADJ
admet-2772	1466	2	ml	ml	NOUN
admet-2772	1466	3	for	for	ADP
admet-2772	1466	4	imbalanced	imbalanced	ADJ
admet-2772	1466	5	data	datum	NOUN
admet-2772	1466	6	.	.	PUNCT
admet-2772	1467	1	arxiv	arxiv	PROPN
admet-2772	1467	2	(	(	PUNCT
admet-2772	1467	3	2022	2022	NUM
admet-2772	1467	4	)	)	PUNCT
admet-2772	1467	5	.	.	PUNCT
admet-2772	1468	1	http://arxiv.org/abs/2212.07743	http://arxiv.org/abs/2212.07743	PROPN
admet-2772	1469	1	[	[	X
admet-2772	1469	2	223	223	NUM
admet-2772	1469	3	]	]	X
admet-2772	1469	4	y.	y.	PROPN
admet-2772	1469	5	chen	chen	PROPN
admet-2772	1469	6	,	,	PUNCT
admet-2772	1469	7	r.	r.	PROPN
admet-2772	1469	8	calabrese	calabrese	PROPN
admet-2772	1469	9	,	,	PUNCT
admet-2772	1469	10	b.	b.	PROPN
admet-2772	1469	11	martin	martin	PROPN
admet-2772	1469	12	-	-	PUNCT
admet-2772	1469	13	barragan	barragan	PROPN
admet-2772	1469	14	.	.	PUNCT
admet-2772	1470	1	interpretable	interpretable	ADJ
admet-2772	1470	2	machine	machine	NOUN
admet-2772	1470	3	learning	learn	VERB
admet-2772	1470	4	for	for	ADP
admet-2772	1470	5	imbalanced	imbalanced	ADJ
admet-2772	1470	6	credit	credit	NOUN
admet-2772	1470	7	scoring	scoring	NOUN
admet-2772	1470	8	datasets	dataset	NOUN
admet-2772	1470	9	.	.	PUNCT
admet-2772	1471	1	european	european	ADJ
admet-2772	1471	2	journal	journal	PROPN
admet-2772	1471	3	of	of	ADP
admet-2772	1471	4	operational	operational	ADJ
admet-2772	1471	5	research	research	NOUN
admet-2772	1471	6	312	312	NUM
admet-2772	1471	7	(	(	PUNCT
admet-2772	1471	8	2024	2024	NUM
admet-2772	1471	9	)	)	PUNCT
admet-2772	1471	10	357	357	NUM
admet-2772	1471	11	-	-	SYM
admet-2772	1471	12	372	372	NUM
admet-2772	1471	13	.	.	PUNCT
admet-2772	1472	1	https://doi.org/10.1016/j.ejor.2023.06.036	https://doi.org/10.1016/j.ejor.2023.06.036	PROPN
admet-2772	1473	1	[	[	X
admet-2772	1473	2	224	224	NUM
admet-2772	1473	3	]	]	X
admet-2772	1473	4	c.h	c.h	PROPN
admet-2772	1473	5	.	.	PROPN
admet-2772	1473	6	chang	chang	PROPN
admet-2772	1473	7	,	,	PUNCT
admet-2772	1473	8	s.	s.	PROPN
admet-2772	1473	9	tan	tan	PROPN
admet-2772	1473	10	,	,	PUNCT
admet-2772	1473	11	b.	b.	PROPN
admet-2772	1473	12	lengerich	lengerich	PROPN
admet-2772	1473	13	,	,	PUNCT
admet-2772	1473	14	a.	a.	PROPN
admet-2772	1473	15	goldenberg	goldenberg	PROPN
admet-2772	1473	16	,	,	PUNCT
admet-2772	1473	17	r.	r.	PROPN
admet-2772	1473	18	caruana	caruana	PROPN
admet-2772	1473	19	.	.	PUNCT
admet-2772	1474	1	how	how	SCONJ
admet-2772	1474	2	interpretable	interpretable	ADJ
admet-2772	1474	3	and	and	CCONJ
admet-2772	1474	4	trustworthy	trustworthy	ADJ
admet-2772	1474	5	are	be	AUX
admet-2772	1474	6	gams	gam	NOUN
admet-2772	1474	7	?	?	PUNCT
admet-2772	1475	1	proceedings	proceeding	NOUN
admet-2772	1475	2	of	of	ADP
admet-2772	1475	3	the	the	DET
admet-2772	1475	4	acm	acm	PROPN
admet-2772	1475	5	sigkdd	sigkdd	PROPN
admet-2772	1475	6	international	international	ADJ
admet-2772	1475	7	conference	conference	NOUN
admet-2772	1475	8	on	on	ADP
admet-2772	1475	9	knowledge	knowledge	NOUN
admet-2772	1475	10	discovery	discovery	PROPN
admet-2772	1475	11	and	and	CCONJ
admet-2772	1475	12	data	datum	NOUN
admet-2772	1475	13	mining	mining	NOUN
admet-2772	1475	14	(	(	PUNCT
admet-2772	1475	15	2021	2021	NUM
admet-2772	1475	16	)	)	PUNCT
admet-2772	1475	17	95	95	NUM
admet-2772	1475	18	-	-	SYM
admet-2772	1475	19	105	105	NUM
admet-2772	1475	20	.	.	PUNCT
admet-2772	1476	1	https://doi.org/10.1145/3447548.3467453	https://doi.org/10.1145/3447548.3467453	NOUN
admet-2772	1476	2	[	[	X
admet-2772	1476	3	225	225	NUM
admet-2772	1476	4	]	]	X
admet-2772	1476	5	y.	y.	PROPN
admet-2772	1476	6	liu	liu	PROPN
admet-2772	1476	7	,	,	PUNCT
admet-2772	1476	8	x.	x.	PROPN
admet-2772	1476	9	yu	yu	PROPN
admet-2772	1476	10	.	.	PROPN
admet-2772	1476	11	farthest	farth	ADJ
admet-2772	1476	12	point	point	NOUN
admet-2772	1476	13	sampling	sample	VERB
admet-2772	1476	14	in	in	ADP
admet-2772	1476	15	property	property	NOUN
admet-2772	1476	16	designated	designate	VERB
admet-2772	1476	17	chemical	chemical	NOUN
admet-2772	1476	18	feature	feature	NOUN
admet-2772	1476	19	space	space	NOUN
admet-2772	1476	20	as	as	ADP
admet-2772	1476	21	a	a	DET
admet-2772	1476	22	general	general	ADJ
admet-2772	1476	23	strategy	strategy	NOUN
admet-2772	1476	24	for	for	ADP
admet-2772	1476	25	enhancing	enhance	VERB
admet-2772	1476	26	the	the	DET
admet-2772	1476	27	machine	machine	NOUN
admet-2772	1476	28	learning	learning	NOUN
admet-2772	1476	29	model	model	NOUN
admet-2772	1476	30	performance	performance	NOUN
admet-2772	1476	31	for	for	ADP
admet-2772	1476	32	small	small	ADJ
admet-2772	1476	33	scale	scale	NOUN
admet-2772	1476	34	chemical	chemical	NOUN
admet-2772	1476	35	dataset	dataset	NOUN
admet-2772	1476	36	.	.	PUNCT
admet-2772	1477	1	(	(	PUNCT
admet-2772	1477	2	2024	2024	NUM
admet-2772	1477	3	)	)	PUNCT
admet-2772	1477	4	.	.	PUNCT
admet-2772	1478	1	http://arxiv.org/abs/2404.11348	http://arxiv.org/abs/2404.11348	PROPN
admet-2772	1479	1	[	[	X
admet-2772	1479	2	226	226	NUM
admet-2772	1479	3	]	]	X
admet-2772	1479	4	n.c	n.c	PROPN
admet-2772	1479	5	.	.	PROPN
admet-2772	1479	6	iovanac	iovanac	PROPN
admet-2772	1479	7	,	,	PUNCT
admet-2772	1479	8	b.m	b.m	PROPN
admet-2772	1479	9	.	.	PROPN
admet-2772	1479	10	savoie	savoie	PROPN
admet-2772	1479	11	.	.	PUNCT
admet-2772	1479	12	improved	improve	VERB
admet-2772	1479	13	chemical	chemical	NOUN
admet-2772	1479	14	prediction	prediction	NOUN
admet-2772	1479	15	from	from	ADP
admet-2772	1479	16	scarce	scarce	ADJ
admet-2772	1479	17	data	datum	NOUN
admet-2772	1479	18	sets	set	NOUN
admet-2772	1479	19	via	via	ADP
admet-2772	1479	20	latent	latent	ADJ
admet-2772	1479	21	space	space	NOUN
admet-2772	1479	22	enrichment	enrichment	NOUN
admet-2772	1479	23	.	.	PUNCT
admet-2772	1480	1	journal	journal	PROPN
admet-2772	1480	2	of	of	ADP
admet-2772	1480	3	physical	physical	ADJ
admet-2772	1480	4	chemistry	chemistry	NOUN
admet-2772	1480	5	a	a	DET
admet-2772	1480	6	123	123	NUM
admet-2772	1480	7	(	(	PUNCT
admet-2772	1480	8	2019	2019	NUM
admet-2772	1480	9	)	)	PUNCT
admet-2772	1480	10	4295	4295	NUM
admet-2772	1480	11	-	-	SYM
admet-2772	1480	12	4302	4302	NUM
admet-2772	1480	13	.	.	PUNCT
admet-2772	1481	1	https://doi.org/10.1021/acs.jpca.9b01398	https://doi.org/10.1021/acs.jpca.9b01398	X
admet-2772	1482	1	[	[	X
admet-2772	1482	2	227	227	NUM
admet-2772	1482	3	]	]	PUNCT
admet-2772	1482	4	d.	d.	PROPN
admet-2772	1482	5	lemm	lemm	PROPN
admet-2772	1482	6	,	,	PUNCT
admet-2772	1482	7	g.f	g.f	PROPN
admet-2772	1482	8	.	.	PROPN
admet-2772	1482	9	von	von	PROPN
admet-2772	1482	10	rudorff	rudorff	PROPN
admet-2772	1482	11	,	,	PUNCT
admet-2772	1482	12	o.a	o.a	PROPN
admet-2772	1482	13	.	.	PROPN
admet-2772	1482	14	von	von	PROPN
admet-2772	1482	15	lilienfeld	lilienfeld	PROPN
admet-2772	1482	16	.	.	PUNCT
admet-2772	1483	1	improved	improve	VERB
admet-2772	1483	2	decision	decision	NOUN
admet-2772	1483	3	making	make	VERB
admet-2772	1483	4	with	with	ADP
admet-2772	1483	5	similarity	similarity	NOUN
admet-2772	1483	6	based	base	VERB
admet-2772	1483	7	machine	machine	NOUN
admet-2772	1483	8	learning	learning	NOUN
admet-2772	1483	9	.	.	PUNCT
admet-2772	1484	1	(	(	PUNCT
admet-2772	1484	2	2022	2022	NUM
admet-2772	1484	3	)	)	PUNCT
admet-2772	1484	4	.	.	PUNCT
admet-2772	1485	1	http://arxiv.org/abs/2205.05633	http://arxiv.org/abs/2205.05633	NOUN
admet-2772	1486	1	[	[	X
admet-2772	1486	2	228	228	NUM
admet-2772	1486	3	]	]	X
admet-2772	1486	4	d.	d.	PROPN
admet-2772	1486	5	wade	wade	PROPN
admet-2772	1486	6	,	,	PUNCT
admet-2772	1486	7	a.	a.	PROPN
admet-2772	1486	8	wilson	wilson	PROPN
admet-2772	1486	9	,	,	PUNCT
admet-2772	1486	10	a.	a.	PROPN
admet-2772	1486	11	reddy	reddy	PROPN
admet-2772	1486	12	,	,	PUNCT
admet-2772	1486	13	r.	r.	PROPN
admet-2772	1486	14	bharadwaj	bharadwaj	PROPN
admet-2772	1486	15	.	.	PUNCT
admet-2772	1487	1	validating	validate	VERB
admet-2772	1487	2	machine	machine	NOUN
admet-2772	1487	3	-	-	PUNCT
admet-2772	1487	4	learned	learn	VERB
admet-2772	1487	5	diagnostic	diagnostic	ADJ
admet-2772	1487	6	classifiers	classifier	NOUN
admet-2772	1487	7	in	in	ADP
admet-2772	1487	8	safety	safety	NOUN
admet-2772	1487	9	critical	critical	ADJ
admet-2772	1487	10	applications	application	NOUN
admet-2772	1487	11	with	with	ADP
admet-2772	1487	12	imbalanced	imbalanced	ADJ
admet-2772	1487	13	populations	population	NOUN
admet-2772	1487	14	.	.	PUNCT
admet-2772	1488	1	proceedings	proceeding	NOUN
admet-2772	1488	2	of	of	ADP
admet-2772	1488	3	the	the	DET
admet-2772	1488	4	annual	annual	ADJ
admet-2772	1488	5	conference	conference	NOUN
admet-2772	1488	6	of	of	ADP
admet-2772	1488	7	the	the	DET
admet-2772	1488	8	prognostics	prognostic	NOUN
admet-2772	1488	9	and	and	CCONJ
admet-2772	1488	10	health	health	NOUN
admet-2772	1488	11	management	management	NOUN
admet-2772	1488	12	society	society	NOUN
admet-2772	1488	13	,	,	PUNCT
admet-2772	1488	14	phm	phm	PROPN
admet-2772	1488	15	(	(	PUNCT
admet-2772	1488	16	2018	2018	NUM
admet-2772	1488	17	)	)	PUNCT
admet-2772	1488	18	.	.	PUNCT
admet-2772	1489	1	https://doi.org/10.36001/phmconf.2018.v10i1.192	https://doi.org/10.36001/phmconf.2018.v10i1.192	VERB
admet-2772	1490	1	[	[	X
admet-2772	1490	2	229	229	NUM
admet-2772	1490	3	]	]	X
admet-2772	1490	4	j.d	j.d	PROPN
admet-2772	1490	5	.	.	PROPN
admet-2772	1490	6	walker	walker	PROPN
admet-2772	1490	7	,	,	PUNCT
admet-2772	1490	8	l.	l.	PROPN
admet-2772	1490	9	carlsen	carlsen	PROPN
admet-2772	1490	10	,	,	PUNCT
admet-2772	1490	11	j.	j.	PROPN
admet-2772	1490	12	jaworska	jaworska	PROPN
admet-2772	1490	13	.	.	PUNCT
admet-2772	1491	1	improving	improve	VERB
admet-2772	1491	2	opportunities	opportunity	NOUN
admet-2772	1491	3	for	for	ADP
admet-2772	1491	4	regulatory	regulatory	ADJ
admet-2772	1491	5	acceptance	acceptance	NOUN
admet-2772	1491	6	of	of	ADP
admet-2772	1491	7	qsars	qsar	NOUN
admet-2772	1491	8	:	:	PUNCT
admet-2772	1491	9	the	the	DET
admet-2772	1491	10	importance	importance	NOUN
admet-2772	1491	11	of	of	ADP
admet-2772	1491	12	model	model	NOUN
admet-2772	1491	13	domain	domain	NOUN
admet-2772	1491	14	,	,	PUNCT
admet-2772	1491	15	uncertainty	uncertainty	NOUN
admet-2772	1491	16	,	,	PUNCT
admet-2772	1491	17	validity	validity	NOUN
admet-2772	1491	18	and	and	CCONJ
admet-2772	1491	19	predictability	predictability	NOUN
admet-2772	1491	20	.	.	PUNCT
admet-2772	1492	1	qsar	qsar	NOUN
admet-2772	1492	2	and	and	CCONJ
admet-2772	1492	3	combinatorial	combinatorial	ADJ
admet-2772	1492	4	science	science	NOUN
admet-2772	1492	5	22	22	NUM
admet-2772	1492	6	(	(	PUNCT
admet-2772	1492	7	2003	2003	NUM
admet-2772	1492	8	)	)	PUNCT
admet-2772	1492	9	346	346	NUM
admet-2772	1492	10	-	-	SYM
admet-2772	1492	11	350	350	NUM
admet-2772	1492	12	.	.	PUNCT
admet-2772	1492	13	https://doi.org/10.1002/qsar.200390024	https://doi.org/10.1002/qsar.200390024	ADJ
admet-2772	1493	1	[	[	X
admet-2772	1493	2	230	230	NUM
admet-2772	1493	3	]	]	PUNCT
admet-2772	1493	4	y.	y.	PROPN
admet-2772	1493	5	wang	wang	PROPN
admet-2772	1493	6	,	,	PUNCT
admet-2772	1493	7	k.	k.	PROPN
admet-2772	1493	8	wang	wang	PROPN
admet-2772	1493	9	,	,	PUNCT
admet-2772	1493	10	c.	c.	PROPN
admet-2772	1493	11	zhang	zhang	PROPN
admet-2772	1493	12	.	.	PUNCT
admet-2772	1494	1	applications	application	NOUN
admet-2772	1494	2	of	of	ADP
admet-2772	1494	3	artificial	artificial	ADJ
admet-2772	1494	4	intelligence	intelligence	NOUN
admet-2772	1494	5	/	/	SYM
admet-2772	1494	6	machine	machine	NOUN
admet-2772	1494	7	learning	learn	VERB
admet-2772	1494	8	to	to	ADP
admet-2772	1494	9	highperformance	highperformance	NOUN
admet-2772	1494	10	composites	composite	NOUN
admet-2772	1494	11	.	.	PUNCT
admet-2772	1495	1	composites	composite	VERB
admet-2772	1495	2	part	part	NOUN
admet-2772	1495	3	b	b	NOUN
admet-2772	1495	4	:	:	PUNCT
admet-2772	1495	5	engineering	engineer	VERB
admet-2772	1495	6	285	285	NUM
admet-2772	1495	7	(	(	PUNCT
admet-2772	1495	8	2024	2024	NUM
admet-2772	1495	9	)	)	PUNCT
admet-2772	1495	10	111740	111740	NUM
admet-2772	1495	11	.	.	PUNCT
admet-2772	1496	1	https://doi.org/10.1016/j.compositesb.2024.111740	https://doi.org/10.1016/j.compositesb.2024.111740	NOUN
admet-2772	1496	2	https://doi.org/10.1002/ardp.201800213	https://doi.org/10.1002/ardp.201800213	NOUN
admet-2772	1496	3	https://doi.org/10.1016/j.drudis.2007.12.010	https://doi.org/10.1016/j.drudis.2007.12.010	NOUN
admet-2772	1496	4	https://doi.org/10.1021/acs.chemrestox.2c00189	https://doi.org/10.1021/acs.chemrestox.2c00189	PROPN
admet-2772	1496	5	https://doi.org/10.1002/minf.201900131	https://doi.org/10.1002/minf.201900131	NOUN
admet-2772	1496	6	https://doi.org/10.1016/j.addr.2015.03.014	https://doi.org/10.1016/j.addr.2015.03.014	VERB
admet-2772	1496	7	https://doi.org/10.1371/journal.pone.0266088	https://doi.org/10.1371/journal.pone.0266088	NOUN
admet-2772	1496	8	https://doi.org/10.1186/s40537-023-00727-2	https://doi.org/10.1186/s40537-023-00727-2	NUM
admet-2772	1496	9	https://doi.org/10.1186/s40537-023-00727-2	https://doi.org/10.1186/s40537-023-00727-2	NUM
admet-2772	1496	10	http://arxiv.org/abs/2212.07743	http://arxiv.org/abs/2212.07743	NOUN
admet-2772	1496	11	https://doi.org/10.1016/j.ejor.2023.06.036	https://doi.org/10.1016/j.ejor.2023.06.036	PROPN
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admet-2772	1496	18	https://doi.org/10.1016/j.compositesb.2024.111740	https://doi.org/10.1016/j.compositesb.2024.111740	PROPN
admet-2772	1496	19	admet	admet	PROPN
admet-2772	1496	20	&	&	CCONJ
admet-2772	1496	21	dmpk	dmpk	PROPN
admet-2772	1496	22	13(3	13(3	NUM
admet-2772	1496	23	)	)	PUNCT
admet-2772	1496	24	(	(	PUNCT
admet-2772	1496	25	2025	2025	NUM
admet-2772	1496	26	)	)	PUNCT
admet-2772	1496	27	2772	2772	NUM
admet-2772	1496	28	machine	machine	NOUN
admet-2772	1496	29	learning	learning	NOUN
admet-2772	1496	30	models	model	NOUN
admet-2772	1496	31	for	for	ADP
admet-2772	1496	32	admet	admet	ADJ
admet-2772	1496	33	prediction	prediction	NOUN
admet-2772	1496	34	in	in	ADP
admet-2772	1496	35	drug	drug	NOUN
admet-2772	1496	36	development	development	NOUN
admet-2772	1496	37	doi	doi	PROPN
admet-2772	1496	38	:	:	PUNCT
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admet-2772	1496	40	39	39	NUM
admet-2772	1496	41	[	[	SYM
admet-2772	1496	42	231	231	NUM
admet-2772	1496	43	]	]	X
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admet-2772	1496	45	.	.	PROPN
admet-2772	1496	46	janet	janet	PROPN
admet-2772	1496	47	,	,	PUNCT
admet-2772	1496	48	l.	l.	PROPN
admet-2772	1496	49	mervin	mervin	PROPN
admet-2772	1496	50	,	,	PUNCT
admet-2772	1496	51	o.	o.	PROPN
admet-2772	1496	52	engkvist	engkvist	PROPN
admet-2772	1496	53	.	.	PUNCT
admet-2772	1497	1	artificial	artificial	ADJ
admet-2772	1497	2	intelligence	intelligence	NOUN
admet-2772	1497	3	in	in	ADP
admet-2772	1497	4	molecular	molecular	ADJ
admet-2772	1497	5	de	de	X
admet-2772	1497	6	novo	novo	NOUN
admet-2772	1497	7	design	design	NOUN
admet-2772	1497	8	:	:	PUNCT
admet-2772	1497	9	integration	integration	NOUN
admet-2772	1497	10	with	with	ADP
admet-2772	1497	11	experiment	experiment	NOUN
admet-2772	1497	12	.	.	PUNCT
admet-2772	1498	1	current	current	ADJ
admet-2772	1498	2	opinion	opinion	NOUN
admet-2772	1498	3	in	in	ADP
admet-2772	1498	4	structural	structural	ADJ
admet-2772	1498	5	biology	biology	NOUN
admet-2772	1498	6	80	80	NUM
admet-2772	1498	7	(	(	PUNCT
admet-2772	1498	8	2023	2023	NUM
admet-2772	1498	9	)	)	PUNCT
admet-2772	1498	10	.	.	PUNCT
admet-2772	1499	1	https://doi.org/10.1016/j.sbi.2023.102575	https://doi.org/10.1016/j.sbi.2023.102575	PROPN
admet-2772	1500	1	[	[	X
admet-2772	1500	2	232	232	NUM
admet-2772	1500	3	]	]	PUNCT
admet-2772	1500	4	s.	s.	PROPN
admet-2772	1500	5	capponi	capponi	PROPN
admet-2772	1500	6	,	,	PUNCT
admet-2772	1500	7	k.g	k.g	PROPN
admet-2772	1500	8	.	.	PROPN
admet-2772	1500	9	daniels	daniels	PROPN
admet-2772	1500	10	.	.	PUNCT
admet-2772	1501	1	harnessing	harness	VERB
admet-2772	1501	2	the	the	DET
admet-2772	1501	3	power	power	NOUN
admet-2772	1501	4	of	of	ADP
admet-2772	1501	5	artificial	artificial	ADJ
admet-2772	1501	6	intelligence	intelligence	NOUN
admet-2772	1501	7	to	to	PART
admet-2772	1501	8	advance	advance	VERB
admet-2772	1501	9	cell	cell	NOUN
admet-2772	1501	10	therapy	therapy	NOUN
admet-2772	1501	11	.	.	PUNCT
admet-2772	1502	1	immunological	immunological	ADJ
admet-2772	1502	2	reviews	review	NOUN
admet-2772	1502	3	320	320	NUM
admet-2772	1502	4	(	(	PUNCT
admet-2772	1502	5	2023	2023	NUM
admet-2772	1502	6	)	)	PUNCT
admet-2772	1502	7	147	147	NUM
admet-2772	1502	8	-	-	SYM
admet-2772	1502	9	165	165	NUM
admet-2772	1502	10	.	.	PUNCT
admet-2772	1503	1	https://doi.org/10.1111/imr.13236	https://doi.org/10.1111/imr.13236	PROPN
admet-2772	1503	2	[	[	X
admet-2772	1503	3	233	233	NUM
admet-2772	1503	4	]	]	X
admet-2772	1503	5	y.	y.	PROPN
admet-2772	1503	6	hu	hu	PROPN
admet-2772	1503	7	,	,	PUNCT
admet-2772	1503	8	w.	w.	PROPN
admet-2772	1503	9	li	li	PROPN
admet-2772	1503	10	,	,	PUNCT
admet-2772	1503	11	d.	d.	PROPN
admet-2772	1503	12	wright	wright	PROPN
admet-2772	1503	13	,	,	PUNCT
admet-2772	1503	14	o.	o.	PROPN
admet-2772	1503	15	aydin	aydin	PROPN
admet-2772	1503	16	,	,	PUNCT
admet-2772	1503	17	d.	d.	PROPN
admet-2772	1503	18	wilson	wilson	PROPN
admet-2772	1503	19	,	,	PUNCT
admet-2772	1503	20	o.	o.	PROPN
admet-2772	1503	21	maher	maher	PROPN
admet-2772	1503	22	,	,	PUNCT
admet-2772	1503	23	m.	m.	PROPN
admet-2772	1503	24	raad	raad	PROPN
admet-2772	1503	25	.	.	PUNCT
admet-2772	1504	1	artificial	artificial	ADJ
admet-2772	1504	2	intelligence	intelligence	NOUN
admet-2772	1504	3	approaches	approach	NOUN
admet-2772	1504	4	.	.	PUNCT
admet-2772	1505	1	geographic	geographic	ADJ
admet-2772	1505	2	information	information	NOUN
admet-2772	1505	3	science	science	PROPN
admet-2772	1505	4	&	&	CCONJ
admet-2772	1505	5	technology	technology	PROPN
admet-2772	1505	6	body	body	NOUN
admet-2772	1505	7	of	of	ADP
admet-2772	1505	8	knowledge	knowledge	NOUN
admet-2772	1505	9	2019	2019	NUM
admet-2772	1505	10	(	(	PUNCT
admet-2772	1505	11	2019	2019	NUM
admet-2772	1505	12	)	)	PUNCT
admet-2772	1505	13	102575	102575	NUM
admet-2772	1505	14	.	.	PUNCT
admet-2772	1506	1	https://doi.org/10.22224/gistbok/2019.3.4	https://doi.org/10.22224/gistbok/2019.3.4	NOUN
admet-2772	1507	1	[	[	X
admet-2772	1507	2	234	234	NUM
admet-2772	1507	3	]	]	X
admet-2772	1507	4	j.e.t	j.e.t	PROPN
admet-2772	1507	5	.	.	PUNCT
admet-2772	1507	6	taylor	taylor	PROPN
admet-2772	1507	7	,	,	PUNCT
admet-2772	1507	8	g.w	g.w	PROPN
admet-2772	1507	9	.	.	PROPN
admet-2772	1507	10	taylor	taylor	PROPN
admet-2772	1507	11	.	.	PUNCT
admet-2772	1508	1	artificial	artificial	ADJ
admet-2772	1508	2	cognition	cognition	NOUN
admet-2772	1508	3	:	:	PUNCT
admet-2772	1508	4	how	how	SCONJ
admet-2772	1508	5	experimental	experimental	ADJ
admet-2772	1508	6	psychology	psychology	NOUN
admet-2772	1508	7	can	can	AUX
admet-2772	1508	8	help	help	VERB
admet-2772	1508	9	generate	generate	VERB
admet-2772	1508	10	explainable	explainable	ADJ
admet-2772	1508	11	artificial	artificial	ADJ
admet-2772	1508	12	intelligence	intelligence	NOUN
admet-2772	1508	13	.	.	PUNCT
admet-2772	1509	1	psychonomic	psychonomic	ADJ
admet-2772	1509	2	bulletin	bulletin	NOUN
admet-2772	1509	3	and	and	CCONJ
admet-2772	1509	4	review	review	VERB
admet-2772	1509	5	28	28	NUM
admet-2772	1509	6	(	(	PUNCT
admet-2772	1509	7	2021	2021	NUM
admet-2772	1509	8	)	)	PUNCT
admet-2772	1509	9	454	454	NUM
admet-2772	1509	10	-	-	SYM
admet-2772	1509	11	475	475	NUM
admet-2772	1509	12	.	.	PUNCT
admet-2772	1510	1	https://doi.org/10.3758/s13423-020-01825-5	https://doi.org/10.3758/s13423-020-01825-5	NUM
admet-2772	1511	1	[	[	X
admet-2772	1511	2	235	235	NUM
admet-2772	1511	3	]	]	PUNCT
admet-2772	1511	4	f.	f.	PROPN
admet-2772	1511	5	gossen	gossen	PROPN
admet-2772	1511	6	,	,	PUNCT
admet-2772	1511	7	t.	t.	PROPN
admet-2772	1511	8	margaria	margaria	PROPN
admet-2772	1511	9	,	,	PUNCT
admet-2772	1511	10	b.	b.	PROPN
admet-2772	1511	11	steffen	steffen	PROPN
admet-2772	1511	12	.	.	PUNCT
admet-2772	1512	1	formal	formal	ADJ
admet-2772	1512	2	methods	method	NOUN
admet-2772	1512	3	boost	boost	VERB
admet-2772	1512	4	experimental	experimental	ADJ
admet-2772	1512	5	performance	performance	NOUN
admet-2772	1512	6	for	for	ADP
admet-2772	1512	7	explainable	explainable	ADJ
admet-2772	1512	8	ai	ai	NOUN
admet-2772	1512	9	.	.	PUNCT
admet-2772	1513	1	it	it	PRON
admet-2772	1513	2	professional	professional	VERB
admet-2772	1513	3	23	23	NUM
admet-2772	1513	4	(	(	PUNCT
admet-2772	1513	5	2021	2021	NUM
admet-2772	1513	6	)	)	PUNCT
admet-2772	1513	7	8	8	NUM
admet-2772	1513	8	-	-	SYM
admet-2772	1513	9	12	12	NUM
admet-2772	1513	10	.	.	PUNCT
admet-2772	1514	1	https://doi.org/10.1109/mitp.2021.3123495	https://doi.org/10.1109/mitp.2021.3123495	PROPN
admet-2772	1514	2	[	[	X
admet-2772	1514	3	236	236	NUM
admet-2772	1514	4	]	]	PUNCT
admet-2772	1514	5	d.	d.	PROPN
admet-2772	1514	6	hemment	hemment	PROPN
admet-2772	1514	7	,	,	PUNCT
admet-2772	1514	8	d.	d.	PROPN
admet-2772	1514	9	murray	murray	PROPN
admet-2772	1514	10	-	-	PUNCT
admet-2772	1514	11	rust	rust	PROPN
admet-2772	1514	12	,	,	PUNCT
admet-2772	1514	13	v.	v.	X
admet-2772	1514	14	belle	belle	PROPN
admet-2772	1514	15	,	,	PUNCT
admet-2772	1514	16	r.	r.	PROPN
admet-2772	1514	17	aylett	aylett	PROPN
admet-2772	1514	18	,	,	PUNCT
admet-2772	1514	19	...	...	PUNCT
admet-2772	1514	20	experiential	experiential	ADJ
admet-2772	1514	21	ai	ai	NOUN
admet-2772	1514	22	:	:	PUNCT
admet-2772	1514	23	a	a	DET
admet-2772	1514	24	transdisciplinary	transdisciplinary	ADJ
admet-2772	1514	25	framework	framework	NOUN
admet-2772	1514	26	for	for	ADP
admet-2772	1514	27	legibility	legibility	NOUN
admet-2772	1514	28	and	and	CCONJ
admet-2772	1514	29	agency	agency	NOUN
admet-2772	1514	30	in	in	ADP
admet-2772	1514	31	ai	ai	PROPN
admet-2772	1514	32	.	.	PUNCT
admet-2772	1515	1	arxiv	arxiv	PROPN
admet-2772	1515	2	preprint	preprint	PROPN
admet-2772	1515	3	arxiv	arxiv	PROPN
admet-2772	1515	4	…	…	PUNCT
admet-2772	1515	5	(	(	PUNCT
admet-2772	1515	6	2023	2023	NUM
admet-2772	1515	7	)	)	PUNCT
admet-2772	1515	8	.	.	PUNCT
admet-2772	1516	1	https://doi.org/10.48550/arxiv.2306.00635	https://doi.org/10.48550/arxiv.2306.00635	PROPN
admet-2772	1517	1	[	[	X
admet-2772	1517	2	237	237	NUM
admet-2772	1517	3	]	]	SYM
admet-2772	1517	4	m.t	m.t	PROPN
admet-2772	1517	5	.	.	PROPN
admet-2772	1517	6	hosain	hosain	PROPN
admet-2772	1517	7	,	,	PUNCT
admet-2772	1517	8	j.r	j.r	PROPN
admet-2772	1517	9	.	.	PROPN
admet-2772	1517	10	jim	jim	PROPN
admet-2772	1517	11	,	,	PUNCT
admet-2772	1517	12	m.f	m.f	PROPN
admet-2772	1517	13	.	.	PROPN
admet-2772	1517	14	mridha	mridha	PROPN
admet-2772	1517	15	,	,	PUNCT
admet-2772	1517	16	m.m	m.m	PROPN
admet-2772	1517	17	.	.	PROPN
admet-2772	1517	18	kabir	kabir	PROPN
admet-2772	1517	19	.	.	PUNCT
admet-2772	1518	1	explainable	explainable	ADJ
admet-2772	1518	2	ai	ai	PROPN
admet-2772	1518	3	approaches	approach	NOUN
admet-2772	1518	4	in	in	ADP
admet-2772	1518	5	deep	deep	ADJ
admet-2772	1518	6	learning	learning	NOUN
admet-2772	1518	7	:	:	PUNCT
admet-2772	1518	8	advancements	advancement	NOUN
admet-2772	1518	9	,	,	PUNCT
admet-2772	1518	10	applications	application	NOUN
admet-2772	1518	11	and	and	CCONJ
admet-2772	1518	12	challenges	challenge	NOUN
admet-2772	1518	13	.	.	PUNCT
admet-2772	1519	1	computers	computer	NOUN
admet-2772	1519	2	and	and	CCONJ
admet-2772	1519	3	electrical	electrical	ADJ
admet-2772	1519	4	engineering	engineering	NOUN
admet-2772	1519	5	117	117	NUM
admet-2772	1519	6	(	(	PUNCT
admet-2772	1519	7	2024	2024	NUM
admet-2772	1519	8	)	)	PUNCT
admet-2772	1519	9	109246	109246	NUM
admet-2772	1519	10	.	.	PUNCT
admet-2772	1520	1	https://doi.org/10.1016/j.compeleceng.2024.109246	https://doi.org/10.1016/j.compeleceng.2024.109246	PROPN
admet-2772	1520	2	[	[	X
admet-2772	1520	3	238	238	NUM
admet-2772	1520	4	]	]	X
admet-2772	1520	5	y.	y.	PROPN
admet-2772	1520	6	cao	cao	PROPN
admet-2772	1520	7	,	,	PUNCT
admet-2772	1520	8	j.	j.	PROPN
admet-2772	1520	9	romero	romero	PROPN
admet-2772	1520	10	,	,	PUNCT
admet-2772	1520	11	a.	a.	NOUN
admet-2772	1520	12	aspuru	aspuru	ADJ
admet-2772	1520	13	-	-	PUNCT
admet-2772	1520	14	guzik	guzik	NOUN
admet-2772	1520	15	.	.	PUNCT
admet-2772	1521	1	potential	potential	NOUN
admet-2772	1521	2	of	of	ADP
admet-2772	1521	3	quantum	quantum	NOUN
admet-2772	1521	4	computing	computing	NOUN
admet-2772	1521	5	for	for	ADP
admet-2772	1521	6	drug	drug	NOUN
admet-2772	1521	7	discovery	discovery	NOUN
admet-2772	1521	8	.	.	PUNCT
admet-2772	1522	1	ibm	ibm	PROPN
admet-2772	1522	2	journal	journal	PROPN
admet-2772	1522	3	of	of	ADP
admet-2772	1522	4	research	research	NOUN
admet-2772	1522	5	and	and	CCONJ
admet-2772	1522	6	development	development	NOUN
admet-2772	1522	7	62	62	NUM
admet-2772	1522	8	(	(	PUNCT
admet-2772	1522	9	2018	2018	NUM
admet-2772	1522	10	)	)	PUNCT
admet-2772	1522	11	6:1	6:1	NUM
admet-2772	1522	12	-	-	NOUN
admet-2772	1522	13	6:20	6:20	NUM
admet-2772	1522	14	.	.	PUNCT
admet-2772	1523	1	https://doi.org/10.1147/jrd.2018.2888987	https://doi.org/10.1147/jrd.2018.2888987	PROPN
admet-2772	1524	1	[	[	X
admet-2772	1524	2	239	239	NUM
admet-2772	1524	3	]	]	PUNCT
admet-2772	1524	4	m.	m.	NOUN
admet-2772	1524	5	avramouli	avramouli	PROPN
admet-2772	1524	6	,	,	PUNCT
admet-2772	1524	7	i.k	i.k	PROPN
admet-2772	1524	8	.	.	PROPN
admet-2772	1524	9	savvas	savvas	PROPN
admet-2772	1524	10	,	,	PUNCT
admet-2772	1524	11	a.	a.	NOUN
admet-2772	1524	12	vasilaki	vasilaki	PROPN
admet-2772	1524	13	,	,	PUNCT
admet-2772	1524	14	g.	g.	PROPN
admet-2772	1524	15	garani	garani	PROPN
admet-2772	1524	16	.	.	PUNCT
admet-2772	1525	1	unlocking	unlock	VERB
admet-2772	1525	2	the	the	DET
admet-2772	1525	3	potential	potential	NOUN
admet-2772	1525	4	of	of	ADP
admet-2772	1525	5	quantum	quantum	NOUN
admet-2772	1525	6	machine	machine	NOUN
admet-2772	1525	7	learning	learn	VERB
admet-2772	1525	8	to	to	PART
admet-2772	1525	9	advance	advance	VERB
admet-2772	1525	10	drug	drug	NOUN
admet-2772	1525	11	discovery	discovery	NOUN
admet-2772	1525	12	.	.	PUNCT
admet-2772	1526	1	electronics	electronic	NOUN
admet-2772	1526	2	(	(	PUNCT
admet-2772	1526	3	switzerland	switzerland	PROPN
admet-2772	1526	4	)	)	PUNCT
admet-2772	1526	5	12	12	NUM
admet-2772	1526	6	(	(	PUNCT
admet-2772	1526	7	2023	2023	NUM
admet-2772	1526	8	)	)	PUNCT
admet-2772	1526	9	2402	2402	NUM
admet-2772	1526	10	.	.	PUNCT
admet-2772	1527	1	https://doi.org/10.3390/electronics12112402	https://doi.org/10.3390/electronics12112402	PROPN
admet-2772	1528	1	[	[	X
admet-2772	1528	2	240	240	NUM
admet-2772	1528	3	]	]	X
admet-2772	1528	4	s.k	s.k	PROPN
admet-2772	1528	5	.	.	PROPN
admet-2772	1528	6	kandula	kandula	PROPN
admet-2772	1528	7	,	,	PUNCT
admet-2772	1528	8	n.	n.	PROPN
admet-2772	1528	9	katam	katam	PROPN
admet-2772	1528	10	,	,	PUNCT
admet-2772	1528	11	p.r	p.r	PROPN
admet-2772	1528	12	.	.	PROPN
admet-2772	1528	13	kangari	kangari	PROPN
admet-2772	1528	14	,	,	PUNCT
admet-2772	1528	15	a.	a.	PROPN
admet-2772	1528	16	hijmal	hijmal	PROPN
admet-2772	1528	17	,	,	PUNCT
admet-2772	1528	18	r.	r.	PROPN
admet-2772	1528	19	gurrala	gurrala	PROPN
admet-2772	1528	20	,	,	PUNCT
admet-2772	1528	21	m.	m.	NOUN
admet-2772	1528	22	mahmoud	mahmoud	PROPN
admet-2772	1528	23	.	.	PUNCT
admet-2772	1529	1	quantum	quantum	PROPN
admet-2772	1529	2	computing	computing	NOUN
admet-2772	1529	3	potentials	potential	NOUN
admet-2772	1529	4	for	for	ADP
admet-2772	1529	5	drug	drug	NOUN
admet-2772	1529	6	discovery	discovery	NOUN
admet-2772	1529	7	.	.	PUNCT
admet-2772	1530	1	proceedings	proceeding	NOUN
admet-2772	1530	2	2023	2023	NUM
admet-2772	1530	3	international	international	ADJ
admet-2772	1530	4	conference	conference	NOUN
admet-2772	1530	5	on	on	ADP
admet-2772	1530	6	computational	computational	ADJ
admet-2772	1530	7	science	science	NOUN
admet-2772	1530	8	and	and	CCONJ
admet-2772	1530	9	computational	computational	ADJ
admet-2772	1530	10	intelligence	intelligence	NOUN
admet-2772	1530	11	,	,	PUNCT
admet-2772	1530	12	csci	csci	NOUN
admet-2772	1530	13	2023	2023	NUM
admet-2772	1530	14	(	(	PUNCT
admet-2772	1530	15	2023	2023	NUM
admet-2772	1530	16	)	)	PUNCT
admet-2772	1530	17	1467	1467	NUM
admet-2772	1530	18	-	-	SYM
admet-2772	1530	19	1473	1473	NUM
admet-2772	1530	20	.	.	PUNCT
admet-2772	1531	1	https://doi.org/10.1109/csci62032.2023.00240	https://doi.org/10.1109/csci62032.2023.00240	PROPN
admet-2772	1531	2	[	[	X
admet-2772	1531	3	241	241	NUM
admet-2772	1531	4	]	]	X
admet-2772	1531	5	p.h	p.h	PROPN
admet-2772	1531	6	.	.	PROPN
admet-2772	1531	7	wang	wang	PROPN
admet-2772	1531	8	,	,	PUNCT
admet-2772	1531	9	j.h	j.h	PROPN
admet-2772	1531	10	.	.	PROPN
admet-2772	1531	11	chen	chen	PROPN
admet-2772	1531	12	,	,	PUNCT
admet-2772	1531	13	y.y	y.y	PROPN
admet-2772	1531	14	.	.	PROPN
admet-2772	1531	15	yang	yang	PROPN
admet-2772	1531	16	,	,	PUNCT
admet-2772	1531	17	c.	c.	PROPN
admet-2772	1531	18	lee	lee	PROPN
admet-2772	1531	19	,	,	PUNCT
admet-2772	1531	20	y.j	y.j	PROPN
admet-2772	1531	21	.	.	PROPN
admet-2772	1531	22	tseng	tseng	PROPN
admet-2772	1531	23	.	.	PUNCT
admet-2772	1532	1	recent	recent	ADJ
admet-2772	1532	2	advances	advance	NOUN
admet-2772	1532	3	in	in	ADP
admet-2772	1532	4	quantum	quantum	NOUN
admet-2772	1532	5	computing	computing	NOUN
admet-2772	1532	6	for	for	ADP
admet-2772	1532	7	drug	drug	NOUN
admet-2772	1532	8	discovery	discovery	NOUN
admet-2772	1532	9	and	and	CCONJ
admet-2772	1532	10	development	development	NOUN
admet-2772	1532	11	.	.	PUNCT
admet-2772	1533	1	ieee	ieee	PROPN
admet-2772	1533	2	nanotechnology	nanotechnology	PROPN
admet-2772	1533	3	magazine	magazine	PROPN
admet-2772	1533	4	17	17	NUM
admet-2772	1533	5	(	(	PUNCT
admet-2772	1533	6	2023	2023	NUM
admet-2772	1533	7	)	)	PUNCT
admet-2772	1533	8	26	26	NUM
admet-2772	1533	9	-	-	SYM
admet-2772	1533	10	30	30	NUM
admet-2772	1533	11	.	.	PUNCT
admet-2772	1534	1	https://doi.org/10.1109/mnano.2023.3249499	https://doi.org/10.1109/mnano.2023.3249499	PROPN
admet-2772	1535	1	[	[	X
admet-2772	1535	2	242	242	NUM
admet-2772	1535	3	]	]	X
admet-2772	1535	4	k.	k.	PROPN
admet-2772	1535	5	louhichi	louhichi	PROPN
admet-2772	1535	6	,	,	PUNCT
admet-2772	1535	7	i.	i.	PROPN
admet-2772	1535	8	abdelghani	abdelghani	PROPN
admet-2772	1535	9	,	,	PUNCT
admet-2772	1535	10	h.	h.	PROPN
admet-2772	1535	11	jdidi	jdidi	PROPN
admet-2772	1535	12	,	,	PUNCT
admet-2772	1535	13	y.	y.	PROPN
admet-2772	1535	14	boukhris	boukhris	PROPN
admet-2772	1535	15	,	,	PUNCT
admet-2772	1535	16	b.	b.	PROPN
admet-2772	1535	17	roch	roch	PROPN
admet-2772	1535	18	,	,	PUNCT
admet-2772	1535	19	c.	c.	PROPN
admet-2772	1535	20	françois	françois	PROPN
admet-2772	1535	21	,	,	PUNCT
admet-2772	1535	22	m.	m.	PROPN
admet-2772	1535	23	toumi	toumi	PROPN
admet-2772	1535	24	,	,	PUNCT
admet-2772	1535	25	a.	a.	NOUN
admet-2772	1535	26	bakhutashvili	bakhutashvili	NOUN
admet-2772	1535	27	.	.	PUNCT
admet-2772	1536	1	msr8	msr8	PROPN
admet-2772	1536	2	revolutionizing	revolutionize	VERB
admet-2772	1536	3	drug	drug	NOUN
admet-2772	1536	4	discovery	discovery	NOUN
admet-2772	1536	5	and	and	CCONJ
admet-2772	1536	6	preclinical	preclinical	ADJ
admet-2772	1536	7	research	research	NOUN
admet-2772	1536	8	via	via	ADP
admet-2772	1536	9	artificial	artificial	ADJ
admet-2772	1536	10	intelligence	intelligence	NOUN
admet-2772	1536	11	:	:	PUNCT
admet-2772	1536	12	a	a	DET
admet-2772	1536	13	targeted	target	VERB
admet-2772	1536	14	literature	literature	NOUN
admet-2772	1536	15	review	review	NOUN
admet-2772	1536	16	.	.	PUNCT
admet-2772	1537	1	value	value	NOUN
admet-2772	1537	2	in	in	ADP
admet-2772	1537	3	health	health	NOUN
admet-2772	1537	4	25	25	NUM
admet-2772	1537	5	(	(	PUNCT
admet-2772	1537	6	2022	2022	NUM
admet-2772	1537	7	)	)	PUNCT
admet-2772	1537	8	s518	s518	PROPN
admet-2772	1537	9	-	-	PUNCT
admet-2772	1537	10	s519	s519	PROPN
admet-2772	1537	11	.	.	PUNCT
admet-2772	1538	1	https://doi.org/10.1016/j.jval.2022.04.1215	https://doi.org/10.1016/j.jval.2022.04.1215	VERB
admet-2772	1539	1	[	[	X
admet-2772	1539	2	243	243	NUM
admet-2772	1539	3	]	]	X
admet-2772	1539	4	n.	n.	PROPN
admet-2772	1539	5	stephenson	stephenson	PROPN
admet-2772	1539	6	,	,	PUNCT
admet-2772	1539	7	e.	e.	PROPN
admet-2772	1539	8	shane	shane	PROPN
admet-2772	1539	9	,	,	PUNCT
admet-2772	1539	10	j.	j.	PROPN
admet-2772	1539	11	chase	chase	PROPN
admet-2772	1539	12	,	,	PUNCT
admet-2772	1539	13	j.	j.	PROPN
admet-2772	1539	14	rowland	rowland	PROPN
admet-2772	1539	15	,	,	PUNCT
admet-2772	1539	16	d.	d.	PROPN
admet-2772	1539	17	ries	ries	PROPN
admet-2772	1539	18	,	,	PUNCT
admet-2772	1539	19	n.	n.	PROPN
admet-2772	1539	20	justice	justice	PROPN
admet-2772	1539	21	,	,	PUNCT
admet-2772	1539	22	j.	j.	PROPN
admet-2772	1539	23	zhang	zhang	PROPN
admet-2772	1539	24	,	,	PUNCT
admet-2772	1539	25	l.	l.	PROPN
admet-2772	1539	26	chan	chan	PROPN
admet-2772	1539	27	,	,	PUNCT
admet-2772	1539	28	r.	r.	PROPN
admet-2772	1539	29	cao	cao	PROPN
admet-2772	1539	30	.	.	PUNCT
admet-2772	1540	1	survey	survey	NOUN
admet-2772	1540	2	of	of	ADP
admet-2772	1540	3	machine	machine	NOUN
admet-2772	1540	4	learning	learn	VERB
admet-2772	1540	5	techniques	technique	NOUN
admet-2772	1540	6	in	in	ADP
admet-2772	1540	7	drug	drug	NOUN
admet-2772	1540	8	discovery	discovery	NOUN
admet-2772	1540	9	.	.	PUNCT
admet-2772	1541	1	current	current	ADJ
admet-2772	1541	2	drug	drug	NOUN
admet-2772	1541	3	metabolism	metabolism	NOUN
admet-2772	1541	4	20	20	NUM
admet-2772	1541	5	(	(	PUNCT
admet-2772	1541	6	2018	2018	NUM
admet-2772	1541	7	)	)	PUNCT
admet-2772	1541	8	185	185	NUM
admet-2772	1541	9	-	-	SYM
admet-2772	1541	10	193	193	NUM
admet-2772	1541	11	.	.	PUNCT
admet-2772	1542	1	https://doi.org/10.2174/1389200219666180820112457	https://doi.org/10.2174/1389200219666180820112457	PRON
admet-2772	1543	1	[	[	X
admet-2772	1543	2	244	244	NUM
admet-2772	1543	3	]	]	PUNCT
admet-2772	1543	4	m.	m.	NOUN
admet-2772	1543	5	baranwal	baranwal	PROPN
admet-2772	1543	6	,	,	PUNCT
admet-2772	1543	7	a.	a.	NOUN
admet-2772	1543	8	magner	magner	NOUN
admet-2772	1543	9	,	,	PUNCT
admet-2772	1543	10	p.	p.	NOUN
admet-2772	1543	11	elvati	elvati	PROPN
admet-2772	1543	12	,	,	PUNCT
admet-2772	1543	13	j.	j.	PROPN
admet-2772	1543	14	saldinger	saldinger	PROPN
admet-2772	1543	15	,	,	PUNCT
admet-2772	1543	16	a.	a.	NOUN
admet-2772	1543	17	violi	violi	PROPN
admet-2772	1543	18	,	,	PUNCT
admet-2772	1543	19	a.	a.	NOUN
admet-2772	1543	20	violi	violi	PROPN
admet-2772	1543	21	,	,	PUNCT
admet-2772	1543	22	a.o	a.o	PROPN
admet-2772	1543	23	.	.	PROPN
admet-2772	1543	24	hero	hero	PROPN
admet-2772	1543	25	.	.	PUNCT
admet-2772	1544	1	a	a	DET
admet-2772	1544	2	deep	deep	ADJ
admet-2772	1544	3	learning	learning	NOUN
admet-2772	1544	4	architecture	architecture	NOUN
admet-2772	1544	5	for	for	ADP
admet-2772	1544	6	metabolic	metabolic	NOUN
admet-2772	1544	7	pathway	pathway	NOUN
admet-2772	1544	8	prediction	prediction	NOUN
admet-2772	1544	9	.	.	PUNCT
admet-2772	1545	1	bioinformatics	bioinformatic	NOUN
admet-2772	1545	2	36	36	NUM
admet-2772	1545	3	(	(	PUNCT
admet-2772	1545	4	2020	2020	NUM
admet-2772	1545	5	)	)	PUNCT
admet-2772	1545	6	2547	2547	NUM
admet-2772	1545	7	-	-	SYM
admet-2772	1545	8	2553	2553	NUM
admet-2772	1545	9	.	.	PUNCT
admet-2772	1546	1	https://doi.org/10.1093/bioinformatics/btz954	https://doi.org/10.1093/bioinformatics/btz954	NOUN
admet-2772	1546	2	[	[	X
admet-2772	1546	3	245	245	NUM
admet-2772	1546	4	]	]	PUNCT
admet-2772	1546	5	k.	k.	PROPN
admet-2772	1546	6	sasahara	sasahara	PROPN
admet-2772	1546	7	,	,	PUNCT
admet-2772	1546	8	m.	m.	NOUN
admet-2772	1546	9	shibata	shibata	PROPN
admet-2772	1546	10	,	,	PUNCT
admet-2772	1546	11	h.	h.	PROPN
admet-2772	1546	12	sasabe	sasabe	PROPN
admet-2772	1546	13	,	,	PUNCT
admet-2772	1546	14	t.	t.	PROPN
admet-2772	1546	15	suzuki	suzuki	PROPN
admet-2772	1546	16	,	,	PUNCT
admet-2772	1546	17	k.	k.	PROPN
admet-2772	1546	18	takeuchi	takeuchi	PROPN
admet-2772	1546	19	,	,	PUNCT
admet-2772	1546	20	k.	k.	PROPN
admet-2772	1546	21	umehara	umehara	PROPN
admet-2772	1546	22	,	,	PUNCT
admet-2772	1546	23	e.	e.	PROPN
admet-2772	1546	24	kashiyama	kashiyama	PROPN
admet-2772	1546	25	.	.	PUNCT
admet-2772	1547	1	predicting	predict	VERB
admet-2772	1547	2	drug	drug	NOUN
admet-2772	1547	3	metabolism	metabolism	NOUN
admet-2772	1547	4	and	and	CCONJ
admet-2772	1547	5	pharmacokinetics	pharmacokinetic	NOUN
admet-2772	1547	6	features	feature	NOUN
admet-2772	1547	7	of	of	ADP
admet-2772	1547	8	in	in	ADP
admet-2772	1547	9	-	-	PUNCT
admet-2772	1547	10	house	house	NOUN
admet-2772	1547	11	compounds	compound	NOUN
admet-2772	1547	12	by	by	ADP
admet-2772	1547	13	a	a	DET
admet-2772	1547	14	hybrid	hybrid	ADJ
admet-2772	1547	15	machinelearning	machinelearning	NOUN
admet-2772	1547	16	model	model	NOUN
admet-2772	1547	17	.	.	PUNCT
admet-2772	1548	1	drug	drug	NOUN
admet-2772	1548	2	metabolism	metabolism	NOUN
admet-2772	1548	3	and	and	CCONJ
admet-2772	1548	4	pharmacokinetics	pharmacokinetic	NOUN
admet-2772	1548	5	39	39	NUM
admet-2772	1548	6	(	(	PUNCT
admet-2772	1548	7	2021	2021	NUM
admet-2772	1548	8	)	)	PUNCT
admet-2772	1548	9	100395	100395	NUM
admet-2772	1548	10	.	.	PUNCT
admet-2772	1549	1	https://doi.org/10.1016/j.dmpk.2021.100395	https://doi.org/10.1016/j.dmpk.2021.100395	PROPN
admet-2772	1549	2	©	©	PROPN
admet-2772	1549	3	2025	2025	NUM
admet-2772	1549	4	by	by	ADP
admet-2772	1549	5	the	the	DET
admet-2772	1549	6	authors	author	NOUN
admet-2772	1549	7	;	;	PUNCT
admet-2772	1549	8	licensee	licensee	PROPN
admet-2772	1549	9	iapc	iapc	PROPN
admet-2772	1549	10	,	,	PUNCT
admet-2772	1549	11	zagreb	zagreb	PROPN
admet-2772	1549	12	,	,	PUNCT
admet-2772	1549	13	croatia	croatia	PROPN
admet-2772	1549	14	.	.	PUNCT
admet-2772	1550	1	this	this	DET
admet-2772	1550	2	article	article	NOUN
admet-2772	1550	3	is	be	AUX
admet-2772	1550	4	an	an	DET
admet-2772	1550	5	open	open	ADJ
admet-2772	1550	6	-	-	PUNCT
admet-2772	1550	7	access	access	NOUN
admet-2772	1550	8	article	article	NOUN
admet-2772	1550	9	distributed	distribute	VERB
admet-2772	1550	10	under	under	ADP
admet-2772	1550	11	the	the	DET
admet-2772	1550	12	terms	term	NOUN
admet-2772	1550	13	and	and	CCONJ
admet-2772	1550	14	conditions	condition	NOUN
admet-2772	1550	15	of	of	ADP
admet-2772	1550	16	the	the	DET
admet-2772	1550	17	creative	creative	ADJ
admet-2772	1550	18	commons	common	NOUN
admet-2772	1550	19	attribution	attribution	NOUN
admet-2772	1550	20	license	license	NOUN
admet-2772	1550	21	(	(	PUNCT
admet-2772	1550	22	http://creativecommons.org/licenses/by/3.0/	http://creativecommons.org/licenses/by/3.0/	NOUN
admet-2772	1550	23	)	)	PUNCT
admet-2772	1550	24	https://doi.org/10.5599/admet.2772	https://doi.org/10.5599/admet.2772	NOUN
admet-2772	1550	25	https://doi.org/10.1016/j.sbi.2023.102575	https://doi.org/10.1016/j.sbi.2023.102575	PROPN
admet-2772	1550	26	https://doi.org/10.1111/imr.13236	https://doi.org/10.1111/imr.13236	PROPN
admet-2772	1550	27	https://doi.org/10.22224/gistbok/2019.3.4	https://doi.org/10.22224/gistbok/2019.3.4	NOUN
admet-2772	1550	28	https://doi.org/10.3758/s13423-020-01825-5	https://doi.org/10.3758/s13423-020-01825-5	NUM
admet-2772	1550	29	https://doi.org/10.1109/mitp.2021.3123495	https://doi.org/10.1109/mitp.2021.3123495	PROPN
admet-2772	1550	30	https://doi.org/10.48550/arxiv.2306.00635	https://doi.org/10.48550/arxiv.2306.00635	PROPN
admet-2772	1550	31	https://doi.org/10.1016/j.compeleceng.2024.109246	https://doi.org/10.1016/j.compeleceng.2024.109246	PROPN
admet-2772	1551	1	https://doi.org/10.1147/jrd.2018.2888987	https://doi.org/10.1147/jrd.2018.2888987	ADJ
admet-2772	1551	2	https://doi.org/10.3390/electronics12112402	https://doi.org/10.3390/electronics12112402	PROPN
admet-2772	1551	3	https://doi.org/10.1109/csci62032.2023.00240	https://doi.org/10.1109/csci62032.2023.00240	PROPN
admet-2772	1551	4	https://doi.org/10.1109/mnano.2023.3249499	https://doi.org/10.1109/mnano.2023.3249499	PROPN
admet-2772	1551	5	https://doi.org/10.1016/j.jval.2022.04.1215	https://doi.org/10.1016/j.jval.2022.04.1215	NOUN
admet-2772	1551	6	https://doi.org/10.2174/1389200219666180820112457	https://doi.org/10.2174/1389200219666180820112457	PROPN
admet-2772	1551	7	https://doi.org/10.1093/bioinformatics/btz954	https://doi.org/10.1093/bioinformatics/btz954	VERB
admet-2772	1551	8	https://doi.org/10.1016/j.dmpk.2021.100395	https://doi.org/10.1016/j.dmpk.2021.100395	PROPN
admet-2772	1551	9	http://creativecommons.org/licenses/by/3.0/	http://creativecommons.org/licenses/by/3.0/	PROPN