Application of Electrospray in Preparing Solid Lipid Nanoparticles and Optimization of Nanoparticles Using Artificial Neural Networks

BACKGROUND: Electrospray (Electrohydrodynamic atomization) has been introduced as a novel approach to prepare nanoparticles. This work aimed to prepare SLNs through electrospray and evaluate factors affecting particle size of prepared Solid Lipid Nanoparticles (SLNs). METHODS: SLNs were prepared by electrospray method. To study the factors affecting particle size of SLNs, Artificial Neural Networks (ANNs) were employed. Four input variables, namely, Tween 80 concentration, lipid concentration, flow rate, and polymer to lipid ratio were analyzed through ANNs and particle size was the output. RESULTS: The analyzed model presented concentration of Tween 80 (surfactant) and lipid as effective parameters on particle size. By increasing surfactant and decreasing lipid concentration, minimum size could be obtained, while flow rate and polymer to lipid ratio appeared not to be effective. CONCLUSION: Concentration of surfactant/lipid plays the most important role in determining the size.