Implementation of factorial experimental design in chitosan - tripolyphosphate nanoparticles development by ionotropic gelation

Abstract

Glimepiride (GM) is third generation sulfonylurea group and preferably used for the treatment of type -II diabetes mellitus. It belongs to BCS class II drugs according to biopharmaceutical classification system which shows low aqueous solubility. The purpose of this work was to develop and optimize glimepiride loaded chitosan- tripolyphosphate nanoparticles by ionotropic gelation method using 32 full factorial experimental designs. The developed chitosan nanoparticles were evaluated for particle size, zeta potential, entrapment efficiency, %yield and in vitro drug release etc. Factorial experimental design was implemented to optimize the independent variables like drug: polymer ratio (X1) and concentration of cross linking agent (X2) on dependent variables like particle size (Y1) and entrapment efficiency (Y2). A statistical analysis was performed using minitab 16 software with respect to ANOVA, regression analysis. The surface plots and contour plots represent the relationship between the experimental responses and the set of independent variables. The factorial experimental design was validated by checkpoint analysis and desirability function approach was applied for optimization of chitosan nanoparticle formulation. Drug entrapment efficiency and mean particle size of optimized formulation was found to be 61.25% and 222 nm respectively. Nanoparticles revealed initial burst release followed by slow drug release.