Superparamagnetic iron oxide nanoparticles (SPIONs) are the most commonly used negative MRI contrast agent which affect the transverse (T2) relaxation time

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.

This study is devoted to preparation of novel solid lipid nanoparticles (SLNs) for the encapsulation of curcumin which is produced by micro-emulsion and ultrasonication using stearic acid and tripalmitin as solid lipids, tween80 and span80 as surfactants. The relation between particle size and entrapment efficiency of the produced SLNs was operated by central composite design (CCD) under response likes surface method (RSM). The variables including the ratio of lipids (X₁), the ratio of surfactants (X₂), drug/lipid ratio (X₃), time of sonication (X₄) and time of homogenization (X₅). Particle size and entrapment efficiency of the loaded curcumin was justified according to the minimum particle size and maximum entrapment efficiency. The curcumin loaded SLNs presented fairly spherical shape with the mean diameter and entrapment efficiency of 112.0±2.6nm and 98.7±0.3%, respectively. The optimized SLNs were characterized by X-ray diffraction analysis (XRD), differential scanning calorimetry (DSC), photon correlation spectroscopy (PCS) and field emission scanning electron microscopy (FESEM). The drug release profile of the optimal formulated material was examined in aqueous media and almost 30% of the curcumin loaded in SLNs was gradually released during 48h, which reveals efficient prolonged release of the drug.