Development, Statistical Optimization and Characterization of Fluvastatin Loaded Solid Lipid Nanoparticles: A 32 Factorial Design Approach - Afzal Haq Asif; Prasanna Kumar Desu; Rajasekhar Reddy Alavala; Gudhanti Siva Naga Koteswara Rao; Nagaraja Sreeharsha; Girish Meravanige (Pharmaceutics, 2022)
The purpose of the present research work was to design, optimize, and evaluate fluvastatin-loaded solid lipid nanoparticles (FLV-SLNPs) using 32 factorial design for enhancing the bioavailability. Fluvastatin has several disadvantages, including the low solubility and substantial first-pass metabolism resulting in a low (30%) bioavailability and a short elimination half-life. FLV-SLNPs were prepared using the nano-emulsion technique. For the optimization of the FLV-SLNPs, a total of nine formulations were prepared by varying two independent factors at three levels, using full factorial design. In this design, lipid (A) and surfactant (B) concentrations were chosen as independent factors, whereas entrapment efficiency (Y1) and in-vitro drug release (Y2) were selected as the dependent variables. Additionally, the prepared SLNPs were characterized for X-ray diffraction, Fourier transform-infrared spectroscopy, and differential scanning calorimetry. These studies revealed that there were no interactions between the drug and the selected excipients and the selected formulation components are compatible with the drug. Pharmacokinetic studies in rats confirmed significant improvement in AUC and MRT of SLNPs in comparison with the pure drug indicating the enhanced bioavailability of SLNPs. This study provides a proof-of-concept for the fact that SLNPs can be effectively developed via experimental factorial design, which requires relatively minimal experimentation.