[Show abstract][Hide abstract] ABSTRACT: This paper attempted the feasibility to determine the molecular weight of hyaluronic acid with near-infrared (NIR) diffuse reflectance spectroscopy. In this work, 46 experimental samples of hyaluronic acid powder were analyzed by partial least square (PLS) regression multivariate calibration method in the selected region of NIR spectra. The leave-one-out cross-validation method was used for the PLS model selection criterion. The accuracy of the final model was evaluated according to correlation coefficient of prediction set (Rp) and root mean square error of prediction set (RMSEP). The repeatability was verified through repeated measurement of spectra coupled with an appropriate chi-square test. Finally, the optimal calibration model was obtained with Rp=0.9814 and RMSEP=88.32 when using Savitzky-Golay first (SG-1st) derivative with 9 smoothing points spectral preprocessing method. The parameters above and repeatability of NIR spectroscopy obtained from chi-square test were both within the range of permissible error in factories. This study demonstrated that NIR spectroscopy was superior to conventional methods for the fast determination of molecular weight of hyaluronic acid.
Full-text · Article · Nov 2010 · Journal of pharmaceutical and biomedical analysis
[Show abstract][Hide abstract] ABSTRACT: Potency is an important parameter for evaluation of quality of heparin active pharmaceutical ingredient (API). In this paper the feasibility to determine potency of heparin API with near infrared reflectance spectroscopy (NIRS) coupled with partial least squares (PLS) algorithm is attempted. PLS factors, correlation coefficient of calibration set (R(c)), the root mean square of cross-validation (RMSECV), correlation coefficient of prediction set (R(p)) and the root mean square of prediction (RMSEP) were used to evaluate the performance of the models. The optimal calibration model was obtained with R(p)=0.9721 and RMSEP=0.55 in the 1700-1898nm spectral region when using SG-1st derivative spectral transform method and division of calibration/prediction samples was 1/1. Three other additional samples demonstrated good prediction capability of the final model and three validation samples gave good repeatability result. NIRS has the potential to be a final lot release test to be performed in a QC laboratory.
Full-text · Article · Apr 2010 · Journal of pharmaceutical and biomedical analysis