Development and optimization of solid lipid nanoparticles of amikacin by central composite design.

TLDR: Fractional factorial design was applied to examine which variables affect the physicochemical properties of amikacin SLNs and showed that three quantitative factors, including the amount of lipid phase, ratio of drug to lipid, and volume of aqueous phase, were the most important variables on studied responses.

Abstract: Solid lipid nanoparticles (SLNs) have been studied as a drug-delivery system for the controlling of drug release. These colloidal systems have many important advantages, such as biocompatibility, good tolerability, and ease of scale-up. In the preparation of SLNs, many factors are involved in the characteristics of the particles, such as particle size, drug loading, and zeta potential. In this study, fractional factorial design was applied to examine which variables affect the physicochemical properties of amikacin SLNs. Study was continued by a statistical central composite design (CCD) to minimize particle size and maximize drug-loading efficiency of particles. The results showed that three quantitative factors, including the amount of lipid phase, ratio of drug to lipid, and volume of aqueous phase, were the most important variables on studied responses. The best predicted model for particle size was the quadratic model, and for drug-loading efficiency, was the linear model without any significant lack of fit. Optimum condition was achieved when the ratio of drug to lipid was set at 0.5, the amount of lipid phase at 314 mg, and the volume of aqueous phase at 229 mL. The optimized particle size was 149 +/- 4 nm and the drug-loading efficiency 88 +/- 5%. Polydispersity index was less than 0.3. The prepared particles had spherical shape, and the drug release from nanoparticles continued for 144 hours (6 days) without significant burst effect.