Screening of important factors using factorial design to predict simvastatin loaded solid lipid nanoparticles

Abstract

This study aims to optimize Simvastatin-loaded Solid Lipid Nanoparticles (SLNs) using a 2^k factorial design approach. Simvastatin, a widely used cholesterol-lowering drug, faces bioavailability challenges, prompting the use of nanotechnology for drug delivery. The study focuses on lipid concentration, surfactant concentration, and homogenization speed as critical factors influencing SLN characteristics. These factors were chosen based on their potential impact on SLN physicochemical properties like particle size, polydispersity index, and drug entrapment efficiency. Through systematic variation of factor levels, a matrix of experiments will be created, measuring responses (particle size, polydispersity index, and drug entrapment efficiency) for each run. Statistical analysis, including ANOVA, will assess factor significance and interactions. The study aims to reveal critical parameters affecting Simvastatin-loaded SLN formulation. The optimized formulation targets uniform and stable nanoparticles with enhanced drug entrapment, enhancing Simvastatin bioavailability. The factorial design method offers a systematic, resource-efficient approach for simultaneously screening and optimizing multiple factors, streamlining the experimental process.Top of Form