Optimization of wet granulation by surface response method in obtaining GSB-106 tablets

Background. A key component of pharmaceutical development is the optimization and justification of technological processes, since the influence of critical process parameters (KPP) on critical quality indicators (CPC) is one of the dimensions of the design field within which a medicinal product (LP) is created. This study shows the relationship between the conditions of wet granulation and the characteristics of GSB-106 tablets. Aim. To study the effect of wet granulation PPC on the main parameters of GSB-106 tablets in the development of an optimal technological regime using the Box–Behnken plan. Materials and methods. Equipment used: high-speed mixer granulator GSL-12 (Etorch, China), granulator with screening function WG-30 (Pharmag, Germany); manual hydraulic press PRG-50 (Russia); strength analyzer TBF 1000 (Copley Scientific, UK); disintegration analyzer SVM 221 (Erweka, Germany); PTF 3DR abrasion analyzer (Pharma Test, Germany). The mathematical planning of the experiment was carried out using the surface response method with a three-level Box–Behnken plan, regression and variance analysis were applied, and multi-criteria optimization using generalized desirability by Derringer–Suich. Results. To develop the technological process, 15 experiments were conducted in the entire range of varying factors, such as the duration of mixing, the speed of rotation of the blades, and the amount of granulating solution. The following pharmaceutical and technological characteristics were studied: crushing strength and disintegration of tablets at a pressing pressure of 5 kN / m 2 , 10 kN / m 2 , as well as abrasion resistance. Based on the data obtained, regression analysis equations were developed for each studied characteristic, the obtained models were compared by determination coefficients, the statistical significance of the equation terms was evaluated, and regression equations were optimized by getting rid of statistically insignificant equation terms. After constructing a mathematical model with adequate predictive ability, multi-criteria optimization was performed using generalized Derringer–Suich desirability. Conclusion. Multi-criteria optimization allowed us to determine the most optimal combination of control factors in accordance with the prioritization of the desirability of pharmaceutical and technological characteristics. The identified optimal technological regime consists in adding 68.69 ml of purified water and stirring the tablet mixture for 9.92 minutes at a speed of a paddle mixer for 200 rpm, which provide the most optimal pharmaceutical and technological characteristics of the tablets.