Preparation and Statistical Modeling of Solid Lipid Nanoparticles of Dimethyl Fumarate for Better Management of Multiple Sclerosis

The objective of this study was to synthesize and statistically optimize dimethyl fumarate (DMF) loaded solid lipid nanoparticles (SLNs) for better management of multiple sclerosis (MS).
SLNs were formulated by hot emulsion, ultrasonication method and optimized with response surface methodology (RSM). A three factor and three level box-behnken design was used to demonstrate the role of polynomial quadratic equation and contour plots in predicting the effect of independent variables on dependent responses that were particle size and % entrapment efficiency (%EE).
The results were analyzed by analysis of variance (ANOVA) to evaluate the significant differences between the independent variables. The optimized SLNs were characterized and found to have an average particle size of 300 nm, zeta potential value of -34.89 mv and polydispersity index value This study showed that the present formulation with improved characteristics can be a promising formulation with a longer half-life for the better management of MS.