Traditional Chinese medicine (TCM) products are usually manufactured through batch processes. To improve the batch-to-batch reproducibility, practical approaches for the real-time monitoring of batch evolution need to...
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Traditional Chinese medicine (TCM) products are usually manufactured through batch processes. To improve the batch-to-batch reproducibility, practical approaches for the real-time monitoring of batch evolution need to be developed. In-line near-infrared (NIR) spectroscopy combined with multivariate statistical process control (MSPC) method, as an efficient process analytical technology, is presented for the real-time batch process monitoring. Two representative TCM technical processes, the alkaline precipitation of the compound E-Jiao oral liquid and the liquid preparation process of Tanreqing injection, were taken as examples. The NIR spectra collected in-line was "variable-wise" unfolded into two-dimensional matrix, and multi-way principal component analysis (MPCA) model were developed based on the rearranged data of the normal operation condition (NOC) batches. Three kinds of multivariate control charts (PC scores, Hotelling T-2 and DModX) were used to monitor the evolution of test batches with artificial batch variations, including the change of starting material quality attributes and abnormal operation conditions. As illustrated with test batches, the established model can identify NOC or AOC (abnormal operation condition) batches accurately, and detect different kinds of deviations from NOC batches using these control charts. The results indicated that the NIR-based multivariate process trajectories can reflect the batch-to-batch reproducibility effectively, and can also help for the diagnosis of the failure batches in the TCM production. (C) 2016 Elsevier B.V. All rights reserved.
In this study, on-line NIRs (Near Infrared Spectroscopy) monitoring technology, as a useful tool, has been verified during the extraction process of Flos Lonicera Japonica. To gain representative samples and accurate ...
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In this study, on-line NIRs (Near Infrared Spectroscopy) monitoring technology, as a useful tool, has been verified during the extraction process of Flos Lonicera Japonica. To gain representative samples and accurate model result, the detrimental effects from NIR collecting circumstance were significantly reduced with meticulous designs. Based on what, different batches of Flos Lonicera Japonica material were real-time monitored in the extraction process. 10 design schemes were used to verify whether or not different batches could disturb predictive results of the quantitative model. According to a series of chemometric indicators, such as SEC, SECV, SEP, RPD, it is concluded that PLS models established by samples of different batches of raw herbs from the same source could be used to monitor the extraction process with acceptable accuracy. Our research has demonstrated that on-line NIRs monitoring technology as a fast, non-destructive and realtime monitoring tool could be utilized in traditional Chinese medicine preparation.
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