Application of Simplex Lattice Mixture design and desirability function in the development and Optimization of SEDDS for protein kinase inhibitor-Pazopanib Hydrochloride

Abstract

Pazopanib Hydrochloride is a tyrosine protein kinase inhibitor molecule approved by USFDA and European agencies for the treatment of renal cell carcinoma (RCC) patients and other renal malignancies, but it has very poor aqueous solubility. Therefore, it is essential need to improve the solubility and in vitro dispersion or release characteristics. The purpose of this study was to investigate the Pazopanib hydrochloride drug solubility in various vehicles and screening of suitable solubilizers for the preparation of self-emulsifying lipid-based drug delivery systems (SE-LBDDS) of a poorly water-soluble drug (BCS class II), Pazopanib HCl by using simplex lattice mixture design. Ternaryplots wereconstructed by using oil (Labrafac WL 1349l), surfactant (Labrasol), and co-surfactant (Transcutol-P), and the concentration ranges were determined by using a simplex lattice design. The composition of pazopanib HCl SEEDS was optimized through various dependent variables (responses)such as solubility (Y1), precipitation after 15 min (Y2), and, particle size (Y3).Solubility study of pazopanib HCl in different oils, surfactants, and co-surfactants was carried out by shake flask method at 37°C. Three formulation components were chosen based on the maximum solubility results inthe oil, surfactant, and co-surfactant category and included in the experimental design. The results were analyzed by model fitting using the standard least-squares method. Pazopanib HCl were shown maximum solubility i.e. 25.64±0.24mg/g, 57.84 ±2.91mg/g and, 44.61±1.51mg/g in Labrafac WL 1349 (oil), Labrasol (surfactant) and Transcutol-P (co-surfactant) respectively. Hence these chosen formulation component's concentrations were further optimized by using a simplex lattice design (SLD). Derived mathematical polynomial equations and models were exercised to evaluate the impact of formulation input variables on the output variables (responses) using JMP software. The model p-value for both the responses i.e. solubility and particle size were found less than 0.05 hence models were significant. The results of the mathematical analysis demonstrated that the formulation components have a significant impact on the studied responses. Hence simplex lattice mixture design can be used as a powerful quality design to predict the optimized SEDDS formulation.The applicability of simplex lattice design with desirability function helped optimize a SEEDS formulation of pazopanib HCl and the selected model has made it possible to identify the impact of the critical factors to optimize the required responses.