Spectral and spatial characterization of protein loaded PLGA nanoparticles

The objective of this study was to evaluate near infrared (NIR) spectroscopy and imaging as approaches to assess drug contents in poly(dl-lactide-co-glycolide) (PLGA) based nanoparticles of a model protein, cyclosporine A (CyA). A 6-factors 12-runs designed set of experiments with Plackett-Burman (PB) screening was applied in order to examine the effects of drug loading (X(1)), polymer loading (X(2)), emulsifier concentration (X(3)), stirring rate (X(4)), type of organic solvent (X(5)), and ratio of organic to aqueous phases' volumes (X(6)), on drug entrapment efficiency (EFF). After omitting the factors with nonsignificant influences on EFF, a reduced mathematical relationship, EFF = 48.34 + 7.3X(1) - 29.95X(3), was obtained to explain the effect of the significant factors on EFF. Using two different sets for calibration and validation, the developed NIR calibration model was able to assess CyA contents within the 12 PB formulations. NIR spectral imaging was capable of clearly distinguishing the 12 formulations, both qualitatively and quantitatively. A good correlation with a coefficient of 0.9727 was obtained for constructing a quantile-quantile plot for the actual drug loading percentage and the % standard deviation obtained for the drug loading prediction using the hyperspectral images.