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Research Article Open Access
Heparin is a glycosaminoglycan (GAG) that plays an important role in the blood coagulation system. Its quality is of great importance, so it is necessary to develop a fast analytical method during the manufacture process to analyse the quality of heparin produced. In this study, the heparin contents of 80 samples collected from five batches during the precipitation process were analysed using nearinfrared (NIR) spectroscopy and a chemometrics approach. This was done in order to improve the efficiency, to understand the process directly and accurately, and to reduce the variation in product quality during manufacturing. First, the principal component analysis (PCA) method was applied to study the stability and the characteristic trajectory of all of the batches of heparin from ethanol precipitation qualitatively. Then, partial least square (PLS) regression, combined with several spectral pretreatment methods and variable selection methods, was performed to quantitatively predict the heparin contents during the ethanol precipitation process. The results showed that the values of the coefficient of determination (R2), the root mean square error of prediction (RMSEP) and the residual predictive deviation (RPD) were 0.974, 1.105 g/l and 6.37, respectively. This approach has a considerable potential for on-line monitoring of the heparin contents of each ethanol precipitation process. Additionally, it will cause a large transformation in the pattern of production of the pharmaceutical industry by application of NIR spectroscopy in the future.
Near infrared spectroscopy, Heparin,Ethanol precipitation, Principal component analysis,Partial least square, Near infrared spectroscopy, Heparin,Ethanol precipitation, Principal component analysis,Partial least square