摘要
[目的]吸附过程是柱层析循环中的重要操作单元,对后续过程和终产品质量具有显著影响。因此,建立柱层析吸附终点的快速判断方法对中药实际大生产具有重要意义。[方法]皂苷的柱层析吸附过程是三七类注射液生产中的重要操作单元。本研究比较了三七柱层析吸附流出液紫外-可见光谱结合移动区块标准偏差(MBSD)、移动区块目标光谱差异分析(DMBA-TS)、软独立建模分类法(SIMCA)和偏最小二乘-判别分析(PLS-DA)算法对吸附终点的判断能力。[结果]MBSD不适合应用于吸附终点判断。DMBA-TS、SIMCA和PLS-DA对吸附终点判断的相对预测误差分别为13.2%、4.67%和5.71%。[结论]在线紫外-可见光谱结合SIMCA和PLS-DA较适合应用于三七柱层析吸附终点判断。本研究通过比较分析不同算法在三七柱层析吸附终点判断中的有效性,有助于为中药柱层析吸附终点的在线判断提供依据。
Objective: In a chromatographic cycle, the adsorption process is a critical unit operation that has a significant impact on downstream processes and, ultimately, the quality of the final products. The development of a rapid method to determine the endpoints of adsorption processes in a large-scale manufacturing is of substantial importance for herbal medicine(HM) manufacturers.Methods: In this study, the adsorption of saponins on a macroporous resin column chromatograph, a critical unit operation in Panax notoginseng(Burkill) F.H.Chen injection manufacturing, was considered as an example. The evaluation results of in-line ultraviolet and visible spectra combined with various multivariate analysis methods, including the moving block standard deviation(MBSD), difference between the moving block average and the target spectrum(DMBA-TS), soft-independent modeling of class analogy(SIMCA), and partial least-squares discriminant analysis(PLS-DA), were compared.Results: MBSD was unsuitable for adsorption processes. The relative standard errors of prediction between the predicted and experimental endpoints were 13.2%, 4.67%, and 5.71% using DMBA-TS, SIMCA, and PLS-DA, respectively.Conclusions: Among the considered analysis methods, SIMCA and PLS-DA were more effective for endpoint determination. The results of this study provide a more comprehensive overview of the effectiveness of various multivariate analysis methods to facilitate the selection of the most suitable method. This study was also conducive to address the issues of the in-line detection of adsorption endpoints to guide practical HM manufacturing.
作者
蒋程
瞿海斌
Cheng Jiang;Haibin Qu(College of Pharmaceutical Sciences,Zhejiang University,Hangzhou,China;Zhejiang Provincial Key Laboratory of Cancer Prevention and Treatment Technology of Integrated Traditional Chinese and Western Medicine,Zhejiang Academy of Traditional Chinese Medicine,Tongde Hospital of Zhejiang Province,Hangzhou,China;Innovation Center in Zhejiang University,State Key Laboratory of Component-Based Chinese Medicine,Hangzhou,China)
基金
supported by the National Natural Science Foundation of China(82104383)
National S&T Major Project of China(2012ZX09101201-003)
关键词
终点
多变量数据分析
紫外-可见
吸附
中药
Adsorption
Endpoint
Herbal medicine
Multivariate analysis
Ultraviolet and visible