Design and optimization of nsaid loaded nanoparticles

ABSTRACT

The objective of the study was to design and evaluate NSAID loaded Nanoparticles drug delivery system, where Flurbiprofen [model drug] Nanoparticles with suitable size range are envisaged to concentrate at inflammation sites due to increase fragility of blood vessels at those sites and increased aggregation and prostaglandin synthesis. Materials used were surfactant [pluronic F 68] and polymer [poly lactic co glycolic acid; PLGA]. The flurbiprofen loaded nanoparticles were prepared by solvent diffusion nano-precipitation method. Experiment was carried out following 32 factorial designs, where drug-polymer ratio was varied to optimize the formulation. From I.R studies no drug-polymer interaction was found. Particles size analysis was done using Malvern Mastersizer. Two parameters, namely, drug-polymer ratio and solvent-nonsolvent ratio were chosen for optimization following the factorial design. Amount of drug loading and surfactant were kept constant, and only polymer load was varied. The in-vitro drug release profile from nanoparticles was found to follow Higuchi square root kinetics implying a diffusion dependent release as is expected of an insoluble, non-swellable nature of PLGA. It indicated that nanoparticles formed were matrix in nature, in which flurbiprofen dispersed uniformly. Suitable polynomial models were generated and statistically validated using ANOVA for the different responses, namely drug release [maximization] and particle size [minimization]. Those models were solved numerically and simultaneously to optimize the required formulation. Optimized formulation were found to have a polymer-drug ratio of 18.891 and manufactured at a nonsolvent-solvent ratio of 41 to maximized release after 8 hrs and minimized particle size. The methodology avoids the use of organic solvent and thus provides a safe, reproducible and fast method of production of nanoparticles. The study collaborates on the feasibility and suitability of aqueous polymeric drug delivery system, employing statistical design to develop a clinically useful Nanoparticle system with targeting potential