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采用在线近红外光谱结合多元分析监测液-液萃取过程的批间重现性。

Monitoring batch-to-batch reproducibility of liquid-liquid extraction process using in-line near-infrared spectroscopy combined with multivariate analysis.

机构信息

Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.

出版信息

J Pharm Biomed Anal. 2012 Nov;70:178-87. doi: 10.1016/j.jpba.2012.06.028. Epub 2012 Jun 28.

DOI:10.1016/j.jpba.2012.06.028
PMID:22776737
Abstract

Traditional Chinese medicine (TCM) products are usually manufactured through batch processes. To improve batch-to-batch reproducibility, the feasible approaches for real-time monitoring of batch evolution need to be developed. In-line near-infrared (NIR) spectroscopy combined with multivariate data analysis as an efficient process analytical technology (PAT) tool, is presented in this study for real-time batch process monitoring. Liquid-liquid extraction is a widely used purification technology in the TCM manufacture, and selected as the example to demonstrate the effectiveness of this PAT tool. Multi-way partial least squares (MPLS) model was developed based on in-line measured NIR spectral data of ten normal operation condition (NOC) batches. Three kinds of multivariate control charts (scores, Hotelling T(2) and DModX) were used to monitor the evolution of six test batches with artificial batch variations, including the change of starting material quality attributes and abnormal operation conditions. The approach was found very effective for real-time monitoring of process deviations from NOC batches. It is an alternative promising tool for monitoring batch reproducibility of the unit operations during the manufacture of TCM.

摘要

中药(TCM)产品通常通过批处理过程制造。为了提高批与批之间的重现性,需要开发可行的方法来实时监测批处理的演变。本研究提出了将在线近红外(NIR)光谱与多元数据分析相结合作为一种有效的过程分析技术(PAT)工具,用于实时批处理监测。液-液萃取是中药制造中广泛使用的一种纯化技术,被选为示例以证明该 PAT 工具的有效性。基于十个正常操作条件(NOC)批的在线测量的 NIR 光谱数据,建立了多向偏最小二乘(MPLS)模型。三种多元控制图(得分、Hotelling T(2)和 DModX)用于监测六个具有人为批变化的测试批的演变,包括起始物料质量属性和异常操作条件的变化。该方法对于实时监测 NOC 批处理的过程偏差非常有效。它是一种有前途的替代工具,可用于监测中药制造过程中单元操作的批重现性。

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