Preparation of biodegradable nanoparticles of tri-block PLA–PEG–PLA copolymer and determination of factors controlling the particle size using artificial neural network

Abstract

The purpose of this study was to prepare nanoparticles made of tri-block poly(lactide)–poly(ethylene glycol)–poly (lactide) (PLA–PEG–PLA) with controlled size as drug carrier. Artificial neural networks (ANNs) were used to identify factors which influence particle size. In this way, PLA–PEG–PLA was synthesized and was made into nanoparticles by nanoprecipitation under different conditions. The copolymer and the resulting nanoparticles were characterized by various techniques such as proton nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy, gel permeation chromatography, photon correlation spectroscopy and scanning electron microscopy. The developed model was assessed and found to be of high quality. The model was then used to survey the effects of processing factors including polymer concentration, amount of drug, solvent ratio and mixing rate on particle size of polymeric nanoparticles. It was observed that polymer concentration is the most affecting parameter on nanoparticle size distribution. The results demonstrate the potential of ANNs in modelling and identification of critical parameters effective on final particle size.

• PLA–PEG–PLA
• nanoparticles
• particle size
• artificial neural network
• modelling