210 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) ISSN (Print) 2313-4410, ISSN (Online) 2313-4402 © Global Society of Scientific Research and Researchers http://asrjetsjournal.org/ Study of Influence of Formulation Variables on Drug Release: Optimization of Sustained Release Matrix Tablets of Metoclopramide HCl Using Central Composite Experimental Design Afifa Saghira, Ahmad Khanb*, Muhammad Farooq Umerc, Jallat Khand, Obaidullah Malike, Munira Joharf a,b,cDepartment of Pharmacy, Quaid-i-Azam University, Islamabad, Pakistan dDepartment of Chemistry, Khuwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Punjab, Pakistan eDrug Regulatory Authority of Pakistan, Islamabad, Pakistan fDr Saeed Akhtar College of Nursing, DAKSON Institute of Health Sciences, Islamabad, Pakistan aEmail: afifa.pharmd14@gmail.com bEmail: akhan@qau.edu.pk cEmail: farooqyarhussain@gmail.com dEmail: jallat.khan@kfueit.edu.pk eEmail: obaiddr@yahoo.com fEmail: munirajohar03@gmail.com Abstract Metoclopramide Hydrochloride (MCP), has a short half-life. In order to maintain therapeutic levels in blood, it administered in dose of 10-15 mg four times a day. Fluctuation in plasma concentration of drug is commonly observed for drugs that are rapidly absorbed and eliminated when used in long term therapy. This attribute makes metoclopramide a suitable candidate for controlled release delivery. In this work HPMC K4M was used as release rate controlling polymer for the development of controlled release tablet formulation. Experimental Design using CCRD was utilized to determine the influence of varying the concentration of different variables such as polymer and diluents on the release behavior of the drug from matrix tablets and optimization of formulation. Different SR formulation prepared were designed and optimized with the help of software Design Expert® version 10. ------------------------------------------------------------------------ * Corresponding author. http://asrjetsjournal.org/ American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2020) Volume 64, No 1, pp 210-221 211 Using Central Composite Rotatable Design (CCRD), fifteen formulations were selected and prepared using HPMC K4M, Avicel PH-102 and Lactose DC as variables. All the trial formulations were evaluated using different pharmacotechnical tests including hardness, friability, disintegration, dissolution. Online Dissolution apparatus type II and 900 ml different dissolution media in the pH range 1-6.8 and distilled water for dissolution. The drug release was studied by applying the dissolution models by DDSolver® software. Hixson- Crowell model was best fit to the F13 SR formulation. The CCRD experimental design was successfully used in optimization of sustained release Metoclopramide HCl formulation. Keywords: Metoclopramide HCl (MCP); Sustained Release; Optimization; CCRD; Model Dependent approaches; Swelling and Erosion; Stability Study. 1. Introduction Metoclopramide HCl (MCP), a freely water-soluble drug, acts as dopamine receptor antagonist. The relative shorter plasma half-life of about 5-6 hours requires small dose of 15-20mg peroral to be administered 3-4 times a day [23]. This frequent dosing to overcome plasma level fluctuation, results in extrapyramidal effects. The relatively small dose, rapid absorption from intestine, undesirable side effects and shorter half-life forms strong basis to develop sustained release formulation of Metoclopramide. Metoclopramide is affected by hepatic first pass metabolism which discourages its selection as candidate for sustained release formulation [18]. Modified release dosage forms offer an effective means to optimize the bioavailability and plasma drug levels, which other-wise results in various problems. Controlled release drug delivery System is one of such attempts being made to achieve; control over drug release, drug concentration at target site and optimization of therapeutic effects by controlling drug release, dosing frequency and improved patient compliance. Such sustained release behavior of the formulation would obviate the secondary effects of the metoclopramide on the central nervous system normally encountered with the administration of immediate release formulations. It along with decreasing the number of doses improves the patient compliance [32]. Hypromellose or hydroxyl propyl methyl cellulose (HPMC) is an odorless, colorless white, fibrous or powder material which is stable at large pH ranging from 3-11 [1]. HPMC is a multi-purpose material available in various grades and viscosities which are used in different concentrations in formulations for different purposes i.e. coating agent by (Sangalli and his colleagues 2004).Avecil is commercially available in different particle sizes and moisture grade. Due to variable properties Avicel applications ranges from disintegrant and lubricant depending on the case [1]. The aim of this study was to evaluate the effect of both the diluents and polymer on the drug release behavior and optimization of Metoclopramide HCl from matrix SR oral tablets using CCRD optimization technique. 2. Materials and Methods 2.1. Materials Metoclopramide HCl (standard obtained from Shaigan Parma (Pvt) limited Pakistan), Avicel PH-102 - (FMC Biopolymer, Philadelphia), Magnesium Stearate (Dow Chemical Co., USA), HPMC K4M cps (Dow chemical Co., US). All glass wares like Beakers, Funnels, Volumetric Flasks, Pipettes, Graduated Cylinders (Pyrex, England). American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2020) Volume 64, No 1, pp 210-221 212 2.2. Design of the formulations by CCRD To formulate the tablets RCCD (Rotatable Central Composite design) was used. The Design Expert® (Version 10, Stat-Ease Inc., Minneapolis, MN) was used for the performance of statistical analysis. Ranges of three independent factors used were (X1) HPMC K4M (15%-50%), (X2) Avicel PH-1O2 (15%-40%), (X3) Lactose DC (15%-45%). Disintegration time (R1) hardness (R2), friability (R3) and dissolution (R4) were taken as response variables. Formulations were selected on random basis and the results obtained were evaluated as shown in the table below[2, 3]. Table 1: Independent variables and levels Independent variables (Factors) Levels -α 0 +α A; Amount of HPMC K4M (%) 15 32.5 50 B; Amount of AvecilPH102 (%) 15 27.5 40 C; Amount of Lactose DC 15 30 45 2.3. Preparation of SR Metoclopramide HCl tablets Direct compression method was used after mixing the powder for about 10min in ERWEKA® motor drive type AR 403 which is a main drive for ERWEKA® world-wide known all-purpose equipment, to compress the target weight with punches having round shape. 2.4. Evaluation of SR Metoclopramide HCl tablets All the tablets formulations compressed were subjected to assess for different pharmacopoeial characteristics including hardness [4] , friability [4], disintegration time, disintegration [5]. The drug release of Metoclopramide HCl tablet formulations was evaluated by using USP [5] official method. All the measurements were made automatically by software Disso.net at  = 309 nm. 2.5. Model dependent approaches To compare different formulations model dependent approaches are frequently employed and also used in optimization process due to differences in release mechanism. The model dependent approaches applied are reported in literature [6, 7]. Hixson-Crowell cube root model [7-9]Korsmeyer-peppas model [7, 10]. 3. Results Among fifteen possible combinations the blended mixtures of each runs were selected randomly on the basis of American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2020) Volume 64, No 1, pp 210-221 213 target tablet weight i.e. 200mg given in the table below. Table 2: Trial Metoclopramide Formulations Derived from DE using Central Composite Model Run HPMC K4M (%) Avicel PH102 (%) Lactose DC (%) HPMC K4M (mg) Avicel PH102 (mg) Lactose DC (mg) Mg. Stearate (mg) MCP (mg/tablet) Total weight (mg/tablet) 10 50 15 45 100 30 90 5 30 255 13 15 27.5 30 30 55 60 5 30 180 14 15 15 45 30 30 90 5 30 185 Compressed formulations were subjected to physicochemical evaluations represented in table 3. Table 3: Physicochemical Tests of Metoclopramide Formulations Hardness (Kg±SD) Friability (%) Disinte g. Time Shelf Life Limits [5] 7-9 Kg <1% (min) (months) SR F10 7.62±0.215 0.57 236 60 F13 8.60±0.113 0.20 258 66 F14 7.95±0.223 0.33 225 57 Response surface methodology graphs are sown in figure. 1(a, b, c, d). Figure 1a: Response surface plot for disintegration time A: 3D surface plot, B: contour plot American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2020) Volume 64, No 1, pp 210-221 214 Figure 1b: Response surface plot for hardness A: 3D surface plot, B: contour plot Figure 1c: Response surface plot for friability A: 3D surface plot, B: contour plot Figure 1d: Response surface plot for Dissolution (%) at 12th hour A: 3D surface plot, B: contour plot The friability results are shown in table 4. American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2020) Volume 64, No 1, pp 210-221 215 Table 4: In Vitro Model Dependent Kinetic Studies of Metoclopramide HCl SR Tablets in Different Media Zero Order Model First Orders Model Higuchi Model Hixson- Crowell Model Korsmeyer –Peppas Model R2 K0 (h- 1) R2 K1 (h- 1) R2 KH (h- 1/2) R2 KHC (h1/3) R2 n KKP (h- n) Dissolution Medium 1: SR in 0.1NHCl (pH 1.2) F-10 0.866 2 4.484 0.856 5 0.485 0.9779 27.1123 0.9804 0.0752 0.9186 0.4223 20.5238 F-13 0.870 3 4.606 0.867 0 0.356 0.9855 18.2124 0.9901 0.0503 0.9208 0.5129 18.2347 F-14 0.864 7 3.451 0.861 2 0.338 0.9708 22.1358 0.9755 0.0555 0.9004 0.4557 15.7345 Dissolution Medium 2: SR in Phosphate Buffer pH 4.5 F-10 0.837 7 3.600 0.810 6 0.421 0.9622 12.3219 0.9752 0.0347 0.9766 0.5003 26.3210 F-13 0.845 0 4.652 0.846 9 0.451 0.9690 10.5620 0.9887 0.0571 0.9852 0.5195 32.9803 F-14 0.833 4 3.603 0.825 7 0.413 0.9440 7.8346 0.9788 0.0438 0.9829 0.5125 26.2206 Dissolution Medium 3: SR in Phosphate Buffer pH 6.8 F-10 0.867 1 3.571 0.845 6 0.510 0.9122 21.3210 0.9654 0.0605 0.9454 0.4863 40.5096 F-13 0.880 9 4.605 0.867 3 0.495 0.9156 19.8324 0.9848 0.0506 0.9667 0.5006 48.7022 F-14 0.872 5 3.542 0.860 5 0.424 0.9053 26.0872 0.9780 0.0414 0.9589 0.4903 43.4434 Dissolution Medium 4:SR in Distilled Water F-10 0.840 8 3.126 0.811 1 0.422 0.9457 15.5679 0.9783 0.0629 0.9403 0.4886 44.3456 F-13 0.865 4 4.147 08153 0.466 0.9558 13.6305 0.9925 0.0333 0.9452 0.4958 47.2212 F-14 0.855 6 2.128 0.806 7 0.453 0.9502 11.7322 0.9804 0.0401 0.9308 0.3787 38.3321 Disintegration time of SR was calculated (table 3). The fig. 1a-1d shows the Response Surface Plots and contour plots. Multiple point dissolution of all the SR formulations was performed in different dissolution medium as represented in figures. 2a-2d. American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2020) Volume 64, No 1, pp 210-221 216 Figure 2: (a-d): Percentage Release of Metoclopramide HCl from SR Tablets at pH 1.2, 4.5, 6.8 and Distilled Water (n=12) Table 5: Analysis of variance for disintegration Source Sum of Squares df Mean Square F Value p-value Prob> F Model 1.470E+005 9 16330.17 23.29 0.0015 significant A-HPMC K4M 1.014E+005 1 1.014E+005 144.55 < 0.0001 B-Avicel PH102 752.34 1 752.34 1.07 0.3477 C-Lactose DC 6273.72 1 6273.72 8.95 0.0304 AB 1754.47 1 1754.47 2.50 0.1745 AC 3439.11 1 3439.11 4.90 0.0776 BC 183.16 1 183.16 0.26 0.6310 A2 2507.90 1 2507.90 3.58 0.1172 B2 45.41 1 45.41 0.065 0.8093 C2 1355.52 1 1355.52 1.93 0.2231 Residual 3505.82 5 701.16 Cor Total 1.505E+005 14 Table 6: Analysis of variance for Hardness Source Sum of Squares df Mean Square F Value p-value Prob> F Model 70.37217 9 7.81913 7.221798 0.021171 significant A-HPMC K4M 11.59386 1 11.59386 10.70816 0.022141 B-Avicel PH102 34.31932 1 34.31932 31.69754 0.00245 C-Lactose DC 2.834052 1 2.834052 2.617548 0.166612 AB 0.234173 1 0.234173 0.216284 0.661437 AC 1.006224 1 1.006224 0.929355 0.379306 BC 2.076211 1 2.076211 1.917602 0.224729 A^2 1.078687 1 1.078687 0.996282 0.364036 B^2 0.154013 1 0.154013 0.142247 0.721535 C^2 8.778887 1 8.778887 8.108235 0.035929 Residual 5.413562 5 1.082712 Cor Total 75.78573 14 The results of kinetic studies are shown in (table 4). The tables 5-8 show the analysis of variance for American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2020) Volume 64, No 1, pp 210-221 217 disintegration, hardness, Friability and dissolution respectively. Table 7: Analysis of variance for Friability Source Sum of Squares df Mean Square F Value p-value Prob> F Model 0.89 9 0.099 9.83 0.0108 significant A-HPMC K4M 0.14 1 0.14 13.93 0.0135 B-Avicel PH102 0.19 1 0.19 18.45 0.0077 C-Lactose DC 0.097 1 0.097 9.64 0.0267 AB 6.553E-003 1 6.553E-003 0.65 0.4568 AC 0.089 1 0.089 8.81 0.0312 BC 0.100 1 0.100 9.89 0.0255 A2 6.810E-003 1 6.810E-003 0.68 0.4486 B2 0.073 1 0.073 7.26 0.0431 C2 5.022E-004 1 5.022E-004 0.050 0.8322 Residual 0.050 5 0.010 Cor Total 0.94 14 Table 8: Analysis of variance for Dissolution % at 12th hour Source Sum of Squares df Mean Square F Value p-value Prob> F Model 221.76 9 24.64 20.82 0.0019 significant A-HPMC K4M 172.88 1 172.88 146.11 < 0.0001 B-Avicel PH102 0.020 1 0.020 0.017 0.9019 C-Lactose DC 0.21 1 0.21 0.17 0.6932 AB 20.63 1 20.63 17.44 0.0087 AC 3.24 1 3.24 2.74 0.1590 BC 2.26 1 2.26 1.91 0.2254 A2 5.28 1 5.28 4.46 0.0884 B2 3.72 1 3.72 3.15 0.1363 C2 0.93 1 0.93 0.79 0.4152 Residual 5.92 5 1.18 Cor Total 227.68 14 4. Discussion Optimization technique was employed to prepare 15 formulations. Out of fifteen designed formulations one SR formulations (table 2) was selected having three variables. Central Composite Design was also effectively used for the optimization of formulations [11-13]. Rotthauser and his colleagues in 1998 used Central Composite Design for optimization of effervescent tablet formulation to evaluate the effect of lubricants and compressional force on physical characteristics of these tablets [2]. Magnesium Stearate (5%) was kept constant for all formulations. The description of the effect of formulation factors on the responses with the help of empirical models (linear and quadratic) is one of the major advantages of the response surface design [14]. The three- dimensional response surface plots and the contour plots are portrayed in figs. 1 (a, b, c). These plots show that American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2020) Volume 64, No 1, pp 210-221 218 effect of two factors on a response at the same time, showing increase in the disintegration time with the increase of HPMC and MCC with only a little effect on the overall hardness and friability of the tablets. Different quality attributes of all the compressed trial formulations such as, hardness, disintegration time and dissolution were evaluated according to the USP specifications [15]. The results are shown in table 3. Nyqvist and his colleagues in 1982 also evaluated the physicochemical properties of tablets prepared by using Avicel PH 102, HPMC K4M and magnesium Stearate as excipients showed excellent physicochemical properties [16]. All the SR formulations were compressed with good hardness having the values of 8-10 kg, and friability was also found less than 1% (table 3)[17]. Shah and his colleagues in 2011 prepared fast dissolving Metoclopramide tablets using crospovidone, croscarmellose sodium and sodium starch glycolate by direct compression method and performed pharmacopoeial quality assessment tests. The hardness and % drug contents were in the range of 8-10 Kg/cm² and 98.54% to 101.23% respectively while % friability for all the formulations was found to be within limits (<1) [18]. The disintegration time of trial formulations were also found to be within limits. SR formulation took more than four hours to disintegrate (table 3). In SR formulations, presence of polymer HPMC K4M in the concentration of 22-43.46% increased the disintegration time (table3). During the development of formulations, dissolution testing can help in the selection of excipients as well as optimization of the manufacturing process and enable formulation of the test product to match the release of the reference product [19]. In vitro dissolution test is performed to measure the amount of drug released into the dissolution medium within specified time. [20]. In the present study multiple point dissolution test of Metoclopramide HCl was conducted in four different dissolution media i.e. 0.1 N HCl, phosphate buffer pH 4.5, 6.8 and distilled water (fig. 2-5). SR formulations (F10, F13, F14) containing higher concentrations of HPMC K4M (40-48%) F13 showed further decrease in the overall drug release rate compared to the rest of the two (figs. 2a-2d). Tandya and his colleagues in 2007 reported list of polymers which can be used in controlled release formulations [21]. 4.1. Model dependent approaches In order to describe the drug release from Metoclopramide HCl to get optimized formulation (SR) various mathematical model like Zero Order, First Order, Higuchi’s equation, Hixson-Crowell and Korsmeyer&Peppas were applied to the in vitro release data obtained in various dissolution media (0.1N HCl, phosphate buffer pH 4.5, 6.8 and distilled water). Criterion of selecting the most appropriate model was based on the best goodness of fit. Correlations (R2) of individual batch with applied equations are given in table 5. The release rates were calculated from the slope of the appropriate plots and regression coefficient was determined (tables 4). When SR formulations were subjected to Zero Order model, the values of R2 in 0.1N HCl, pH 4.5 and 6.8 and distilled water came out to be very poor (see tables 4).SR formulations are showing higher values for all the test media i.e. 0.1N HCl, pH 4.5 and 6.8 and distilled water and showing better compliance than other formulations with Zero Order model. Reddy and his colleagues (2003) reported that once-daily sustained-release matrix tablets of HPMC K4M based Nicorandil did not follow zero order release pattern [22]. The First order describes that the rate of drug release from systems is concentration dependent. The SR formulations are not following First Order release pattern. Hassan and his colleagues in 2003 reported similar results (0.987) for the Metoclopramide HCl tablets [23]. Mandal and Pal (2008) reported that the formulations of metformin HCl formulated using different grades of HPMC (HPMC K4M, K15M, K100M) did not follow first order release pattern [24]. However, the coefficient of correlation values of F10 and F14 formulations were comparatively lower than that of F13 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2020) Volume 64, No 1, pp 210-221 219 formulations as presented in tables 5. Similar Higuchi kinetics were reported by Merchant and his colleagues in 2006 in the preparation of once daily tablet formulation of cefpodoxime from HPMC by direct compression [25]. Another study by Shoaib and his colleagues in 2010 reported R2 values of 0.988 for slow release formulation Famotidine HPMC K4M matrix [26]. Abdel-Rahman and his colleagues in 2009 prepared HPMC based matrix tablets of Metoclopramide HCl and reported the R2 values 0.998 [27]. Hassan and his colleagues in 2003 reported similar Higuchi findings (R2 = 0.9929) and found it best fit for the release data of Metoclopramide HCl controlled release tablets [28]. The SR Metoclopramide HCl formulation (F13) was observed to show best linearity and compliance with Hixson-Crowell model. The value of R2 were found out to be 0.999 (0.1NHCl), 0.995, (phosphate buffer pH 4.5), 0.990 (phosphate buffer pH 6.8) and 0.996 (distilled water). Whereas the value of R2 for intermediate and immediate formulations in the same media was comparatively lower than that of slow release formulations (tables 5). Similar findings were reported by Shoaib and his colleagues in 2006 prepared Ibuprofen HPMC matrix tablets and obtained R2 value of 0.996 [29]. In another study, Sankar and his colleagues in 2010 also obtained similar results i.e. R2 = 0.9999 for zidovudine HPMC matrix tablets [30, 31]. To find the drug release mechanism the in vitro release data were applied to Korsmeyer-Peppas model (KorsmeyerPeppas, 1983). The corresponding plot of log cumulative % drug release vs time for all the trial formulations indicated good linearity as mentioned in table 5. Similar R2 results (0.9959) were obtained by Radhika and his colleagues 2005 using HPMC as polymer in glipzide tablets formulation development [32]. The value of release exponent (n) for SR formulations was following non-Fickian diffusion or anomalous release pattern (table 4). Venkatesh and his colleagues in 2010 used HPMC as polymer in the preparation of Prochlorperazine Maleate Sustained Release Tablets and found n values less than 0.5 [33]. In another study Korsmeyer–Peppas Model was applied to HPMC polymer based Metoclopramide tablets by Shiyani and his colleagues in 2008, the value of n was 0.266 showing Quasi –Fickian diffusion [34, 35]. 5. Conclusion By applying optimization technique different formulations of Metoclopramide Hydrochloride with varying release rates were developed. Multiple point dissolution studies using different dissolution media such as 0.1 N HCl, phosphate buffer pH 4.5, 6.8, distilled water was performed using USP Dissolution apparatus II (Paddle Method). 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