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[中药生产过程中智能质量控制技术的专利申请综述]

[Patent application of intelligent quality control technology in traditional Chinese medicine production process: a review].

作者信息

Tang Xue-Fang, Qi Fei-Yu, Wang Tuan-Jie, Liang Zi-Chen, Qiao Yan-Jiang, Xiao Wei, Xu Bing

机构信息

Department of Chinese Medicine Informatics, Beijing University of Chinese Medicine Beijing 102400, China Beijing Key Laboratory for Production Process Control and Quality Evaluation of Chinese Medicine, Beijing Municipal Science & Technology Commission Beijing 102400, China.

Jiangsu Kanion Pharmaceutical Co., Ltd. Lianyungang 222001, China State Key Laboratory of New-tech for Chinese Medicine Pharmaceutical Process Lianyungang 222001, China National and Regional Joint Engineering Research Center for Key Technologies of Chinese Patent Medicine Lianyungang 222001, China.

出版信息

Zhongguo Zhong Yao Za Zhi. 2023 Jun;48(12):3190-3198. doi: 10.19540/j.cnki.cjcmm.20230404.301.

Abstract

In the new stage for intelligent manufacturing of traditional Chinese medicine(TCM) from pilot demonstration to in-depth application and comprehensive promotion, how to raise the degree of intelligence for the process quality control system has become the bottleneck of the development of TCM production process control technology. This article has sorted out 226 TCM intelligent manufacturing projects that have been approved by the national and provincial governments since the implementation of the "Made in China 2025" plan and 145 related pharmaceutical enterprises. Then, the patents applied by these pharmaceutical enterprises were thoroughly retrieved, and 135 patents in terms of intelligent quality control technology in the production process were found. The technical details about intelligent quality control at both the unit levels such as cultivation, processing of crude herbs, preparation pretreatment, pharmaceutical preparations, and the production workshop level were reviewed from three aspects, i.e., intelligent quality sensing, intelligent process cognition, and intelligent process control. The results showed that intelligent quality control technologies have been preliminarily applied to the whole process of TCM production. The intelligence control of the extraction and concentration processes and the intelligent sensing of critical quality attributes are currently the focus of pharmaceutical enterprises. However, there is a lack of process cognitive patent technology for the TCM manufacturing process, which fails to meet the requirements of closed-loop integration of intelligent sensing and intelligent control technologies. It is suggested that in the future, with the help of artificial intelligence and machine learning methods, the process cognitive bottleneck of TCM production can be overcome, and the holistic quality formation mechanisms of TCM products can be elucidated. Moreover, key technologies for system integration and intelligent equipment are expected to be innovated and accelerated to enhance the quality uniformity and manufacturing reliability of TCM.

摘要

在中药智能制造从试点示范向深入应用和全面推广的新阶段,如何提高过程质量控制系统的智能化程度已成为中药生产过程控制技术发展的瓶颈。本文梳理了自“中国制造2025”计划实施以来经国家和省级政府批准的226个中药智能制造项目以及145家相关制药企业。随后,对这些制药企业申请的专利进行了全面检索,发现了135项生产过程智能质量控制技术方面的专利。从智能质量传感、智能过程认知和智能过程控制三个方面,对种植、中药材加工、制剂预处理、药物制剂等单元层面以及生产车间层面的智能质量控制技术细节进行了综述。结果表明,智能质量控制技术已初步应用于中药生产全过程。提取浓缩过程的智能控制和关键质量属性的智能传感是目前制药企业的重点。然而,中药制造过程缺乏过程认知专利技术,无法满足智能传感与智能控制技术闭环集成的要求。建议未来借助人工智能和机器学习方法,攻克中药生产的过程认知瓶颈,阐明中药产品的整体质量形成机制。此外,有望创新并加速系统集成和智能装备的关键技术,以提高中药的质量均匀性和制造可靠性。

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