| Literature DB >> 29376242 |
Wen-Kang Yu1, Ling Dong1, Wen-Xuan Pei1, Zhi-Rong Sun1, Jun-Dong Dai1, Yun Wang1.
Abstract
The whole process quality control and management of traditional Chinese medicine (TCM) decoction pieces is a system engineering, involving the base environment, seeds and seedlings, harvesting, processing and other multiple steps, so the accurate identification of factors in TCM production process that may induce the quality risk, as well as reasonable quality control measures are very important. At present, the concept of quality risk is mainly concentrated in the aspects of management and regulations, etc. There is no comprehensive analysis on possible risks in the quality control process of TCM decoction pieces, or analysis summary of effective quality control schemes. A whole process quality control and management system for TCM decoction pieces based on TCM quality tree was proposed in this study. This system effectively combined the process analysis method of TCM quality tree with the quality risk management, and can help managers to make real-time decisions while realizing the whole process quality control of TCM. By providing personalized web interface, this system can realize user-oriented information feedback, and was convenient for users to predict, evaluate and control the quality of TCM. In the application process, the whole process quality control and management system of the TCM decoction pieces can identify the related quality factors such as base environment, cultivation and pieces processing, extend and modify the existing scientific workflow according to their own production conditions, and provide different enterprises with their own quality systems, to achieve the personalized service. As a new quality management model, this paper can provide reference for improving the quality of Chinese medicine production and quality standardization. Copyright© by the Chinese Pharmaceutical Association.Keywords: scientific workflow ; system development ; whole process quality control
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Year: 2017 PMID: 29376242 DOI: 10.19540/j.cnki.cjcmm.20171113.004
Source DB: PubMed Journal: Zhongguo Zhong Yao Za Zhi ISSN: 1001-5302