DEVELOPMENT OPTIMIZATION OF SORAFENIB-LOADED PLGA NANOPARTICLES GUIDED BY IN SILICO COMPUTATIONAL TOOLS

Abstract

Objective: The purpose of this study was to develop, characterize, and optimize sorafenib-loaded Poly (lactic-co-glycolic acid) PLGA polymeric nanoparticles for prolonged delivery of sorafenib for improved hepatic cancer treatment Methods: The drug-excipient interaction was explored by molecular docking studies within silico tools. The drug-loaded polymeric nanoparticles were prepared by single emulsion solvent evaporation method using box-bhenkan design and characterized for particle size, zeta potential, and entrapment efficiency. Shape and surface morphology was analysed by Transmission Electron Microscopy (TEM). In vitro drug release study was performed by using a diffusion membrane. Results: The docking analysis inferred that the drug has interacted well with PLGA and PF-68, which could prevent the drug crystal formation. The optimized polymeric nanoparticles had a particle size of 175 nm, Entrapment Efficiency (EE) of 85.1% and zeta potential of-23.8mV were found to be within 95% of CI of the predicted value, which is acceptable. TEM studies showed that the formed polymeric nanoparticles were smooth, spherical in shape and uniform in size. In vitro drug release study of optimized formulation showed extended release for sorafenib. Conclusion: Based on the computational studies and in vitro release studies, the developed Sorafenib loaded in PLGA nanoparticles could be a promising formulation in oral drug delivery for the treatment of liver cancer.