Abstract

This study investigated the utility of a 3² factorial design and optimization process for nanoparticle suspension prepared by two different polymers Eudragit^® RS 100 and Eudragit^® RL 100 respectively. Total 18 formulations (9 formulations with each polymer) were prepared by solvent displacement technique. In these designs, two factors namely polymer weight (X1) and Aq. phase volume (X2) were evaluated each at three levels and experimental trials were performed at all nine possible combinations. Polymer weight (X1) and aqueous phase volume (X2) were selected as independent variables and particle size (Y1), % entrapment (Y2), drug release at 12^th hrs. (Y3) are chosen as depended variables. In case of 3² factorial design, a full-model polynomial equation was established by subjecting the transformed values of independent variables to multiple regression analysis, and contour plots were drawn using the equation. The derived polynomial equations for particle size and % drug entrapment were verified by check point formulation. The result showed a wide variation in the responses for both of the polymer. For RS 100 polymer, particle size was 112-350 nm, entrapment: 26-72%, drug release was 42- 89% at 12^th hrs. and for RL 100 polymer, particle size was 114-390 nm, entrapment: 30-72%, drug release was 50-90% at 12^th hrs. The application of factorial design yielded a statistically systematic approach for the formulation and optimization of nanoparticles with desired particle size and high entrapment efficiency and release profile. The results of the optimized formulations showed particle size 225 nm, 63% drug entrapment and 83% drug release for RS 100 polymer and particle size was 148 nm, drug entrapment was 57%, drug release was 80% for RL 100 polymer.

Keywords: Checkpoint, Contour plot, Eudragit^®, Factorial, Nanoparticle, Three level.