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Authentication and distinction of Shenmai injection with HPLC fingerprint analysis assisted by pattern recognition techniques

In this paper, the feasibility and advantages of employing high performance liquid chromatographic (HPLC) fingerprints combined with pattern recognition techniques for quality control of Shenmai injection were investigated and demonstrated. The Similarity Evaluation System was employed to evaluate t...

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Published in:Journal of pharmaceutical analysis 2012-10, Vol.2 (5), p.327-333
Main Authors: Lu, Xue-Feng, Bi, Kai-Shun, Zhao, Xu, Chen, Xiao-Hui
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Language:English
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cited_by cdi_FETCH-LOGICAL-c6362-5ddcabcedb5be6bef3252161840663dac651428525294afddc421cf083a0aa023
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container_title Journal of pharmaceutical analysis
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creator Lu, Xue-Feng
Bi, Kai-Shun
Zhao, Xu
Chen, Xiao-Hui
description In this paper, the feasibility and advantages of employing high performance liquid chromatographic (HPLC) fingerprints combined with pattern recognition techniques for quality control of Shenmai injection were investigated and demonstrated. The Similarity Evaluation System was employed to evaluate the similarities of samples of Shenmai injection, and the HPLC generated chromatographic data were analyzed using hierarchical clustering analysis (HCA) and soft independent modeling of class analogy (SIMCA). Consistent results were obtained to show that the authentic samples and the blended samples were successfully classified by SIMCA, which could be applied to accurate discrimination and quality control of Shenmai injection. Furthermore, samples could also be grouped in accordance with manufacturers. Our results revealed that the developed method has potential perspective for the original discrimination and quality control of Shenmai injection.
doi_str_mv 10.1016/j.jpha.2012.07.009
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subjects Fingerprint
High performance liquid chromatography
HPLC
Pattern recognition
Shenmai injection
参麦注射液
指纹图谱分析
模式识别技术
认证
评价系统
质量控制
高效液相色谱
title Authentication and distinction of Shenmai injection with HPLC fingerprint analysis assisted by pattern recognition techniques
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