OPTIMIZATION OF FORMULATION PARAMETERS OF SIMVASTATIN LOADED PLGA NANOPARTICLES BY USING 33 FACTORIAL DESIGN

Abstract

Factorial design enables researchers to study and understand how multiple factors affect a dependent variable, both independently and jointly. In present report, 33 factorial design was used to study the combined influence of three independent variables in preparation of Simvastatin loaded Poly (D, L Lactide -co- Glycolide) (PLGA) nanoparticles. Nanoparticles were prepared by nanoprecipitation method. The process variables like rate of addition of organic phase to aqueous phase, temperature, speed of magnetic stirrer and time to evaporate organic phase were kept constant throughout the investigation. The formulation variables like concentration of stabilizer (Polyvinyl alcohol), drug (Simvastatin): polymer ratio (PLGA), and organic (acetone): aqueous phase ratio were selected as independent variables. Prepared nanoparticles were evaluated for particle size (PS) and entrapment efficiency (EE). PS and EE were selected as dependent variables. The coded values of independent variables were subjected to multiple regressions to derive a second order polynomial equation (full model). After neglecting the non-significant terms from full model, F-Statistics was applied to set up reduce polynomial equation. Among the three independent variables, value of coefficient of drug: polymer ratio was found to be maximum. This revealed that major contributing variable for PS and EE in nanoparticles is drug: polymer ratio. Two dimensional contour plots and three dimensional response surface plots were established by varying levels of two factors and keeping the third factor at fixed level at a time. Thus the derived equation, surface response plot and contour plot helps in predicting the value of independent variables for optimum PS and EE in preparation of Simvastatin loaded PLGA nanoparticles.