Purpose: Bupropion hydrochloride (BPH) is an aminoketone-derivative is considered as a potential treatment for depression and attention deficit hyperactivity disorder. In order to reduce the adverse effect like seizures (approximately 0.4 % (4/1,000) of patients treated at doses up to 450 mg/day) sustained-release BPH was proposed well tolerated. Therefore, the objective of this study was to evaluate the effect of formulation ingredients on the drug release from optimize novel sustained release matrix tablet formulations of BPH based on response surface methodology (RSM).
Methods: A three-factor, three-level Box-Behnken design was used for the optimization procedure with PEO content (X1), citric acid content (X2) and Compritol 888 ATO content (X3) as the independent variables. The percentages of the drug released at 1(Y1), 4(Y2) and 8(Y3) hours were used as dependent variables for desirable drug release. The obtained data was analyzed by RSM. To prepare tablets, each formula contained a fixed dose (150 mg) of BPH as the active ingredient. Hydrophilic polymer PEO, citric acid, lipid-based Compritol888 ATO, microcrystalline cellulose, and magnesium stearate was added adequately. In dissolution studies, the release of the drug from the matrix tablet was performed according to the USP paddle method (apparatus 2). BPH release was determined by UV-spectrophotometer. The dissolution profiles of BPH were compared to the commercial product Wellbutrin® SR containing similar amount of BPH using similarity factor (f2). The optimization process was performed for X1, X2 and X3 using the following target ranges of dissolution; 30% ≤ Y1 ≤ 45%; 70% ≤Y2≤ 85%; 85% ≤ Y3≤ 100%.
Results: For the response surface methodology involving Box-Behnken design, a total of 15 experiments were performed for three factors at three levels each. This number is equal to the mid-point of each edge and the three replicated center points of the cube. The quadratic model was selected as a suitable statistical model for optimized formulations because it had the smallest value of predicted residual sum of square (PRESS). The adequacy of the model was also confirmed with residual plot tests of regression models. ANOVA was applied to estimate the significance of the model at the 5% significance level. In addition, the contour plots and three-dimensional response surface plots were presented to estimate the effects of the independent variables on each response. The optimization process was performed by graphical and numerical analysis using Design Expert. The optimized levels of PEO content (X1), citric acid content (X2) and Compritol 888 ATO (X3) were 12.5%, 2.5%, and 10%, respectively. The calculated value of f2 was 79.83, indicating that the dissolution profiles of the optimized formulation was comparable to those of the commercial Wellbutrin ® SR tablet. In addition, the dissolution tests were performed at pH 1.2, 4.0, and 6.8 buffers. When calculating the similarity factor f2, values were 87.89, 72.56, and 69.37, respectively and all f2 values were above 50; this suggested that dissolution profiles of the matrix tablet were similar to those of Wellbutrin® SR in all four-dissolution media.
Conclusion: The optimized formulation for bupropion hydrochloride was obtained with PEO, citric acid, and Compritol 888 ATO using response surface methodology based on a Box-Behnken design. Furthermore, calculation of the similarity factors indicated that the dissolution of optimized formulation was similar to those of the commercial product Wellbutrin® SR.