Research on the application of artificial intelligence in the quality control of traditional Chinese medicine
10.19778/j.chp.2025.03.004
- VernacularTitle:人工智能在中药质量监管领域中的应用研究
- Author:
Haiyang XU
1
;
Yan GAO
1
Author Information
1. 山东中医药大学药物研究院国家中医药管理局高水平重点学科-中药药剂学黄河流域特色中药生态保护和高质量发展协同创新中心,山东省数字中药重点实验室,济南 250355
- Publication Type:Journal Article
- Keywords:
artificial intelligence;
quality control of traditional Chinese medicine;
cultivation and planting;
authenticity identification of decoction pieces;
risk assessment;
quality control paradigm
- From:
Drug Standards of China
2025;26(3):255-262
- CountryChina
- Language:Chinese
-
Abstract:
Artificial intelligence(AI)is reconstructing drug quality control systems with unprecedented depth.With the rapid development of the traditional Chinese medicine(TCM)industry,the quality regulation of TCM has garnered increasing attention.The efficacy and safety of TCM directly impact public health,making it imperative to enhance the scientific rigor and effectiveness of its quality control.In recent years,the application of AI technology has expanded across various fields,and its potential in TCM quality regulation has gradually been recognized.Cur-rently,AI has demonstrated advantages in multiple stages of TCM production,including cultivation and planting,authenticity identification of decoction pieces,compliance review of manufacturing processes,market circulation monitoring,and risk assessment.However,despite existing research achievements,challenges such as limited technological adoption,low standardization,and insufficient data sharing persist.This paper provides an in-depth review of innovative AI applications in TCM quality control,comprehensively analyzes their effectiveness and future prospects,and proposes a novel"AI-Digital Sensory-Blockchain"tri-synergistic quality control paradigm based on domestic and international research advancements.Furthermore,it explores potential future research directions to advance the modernization of TCM quality regulation,thereby achieving higher levels of safety assurance and scien-tifically robust supervision.
