Chinese Journal of Pharmacovigilance ›› 2026, Vol. 23 ›› Issue (5): 481-486.
DOI: 10.19803/j.1672-8629.20250880

Previous Articles     Next Articles

Applications of Artificial Intelligence in Research on Traditional Chinese Medicine Metabolomics

LI Yaolei1,2, CHENG Xianlong1,2, LIN Yongqiang1,2, LIU Jing1,2#, WEI Feng1,2,*   

  1. 1Institute for Control of Chinese Traditional Medicine and Ethnic Medicine, National Institutes for Food and Drug Control, Beijing 102629, China;
    2State Key Laboratory of Drug Regulatory Science, Beijing 102629, China
  • Received:2025-12-08 Published:2026-05-20

Abstract: Objective To explore the applications of artificial intelligence (AI) in research on traditional Chinese medicine (TCM) metabolomics in order to upgrade the intelligent analysis of complex systems of TCM. Methods Following the metabolomics research workflow, this review outlined AI applications in such spheres as data processing, metabolite identification, interpretation of mechanisms, and quality control of TCM. Specific examples were cited to demonstrate the strengths and weaknesses of AI. Results AI enables high-throughput, automated preprocessing of metabolomic data so that quality control and feature screening are improved. Integrated with databases and molecular networking, AI can shed light on mapping relationships from vast data on mass spectrometry for intelligent metabolite predictions. By automatically identifying complex patterns in high-dimensional data and assessing feature contributions, AI facilitates differential metabolite selection via feature selection, deep relationship mining, and interpretability analysis. Network analysis, machine learning, and knowledge graphs can combine to offer insights into the mechanisms of TCM. Furthermore, AI can assist in identification of geographical origins and quality control by analyzing secondary metabolites. While AI enhances data processing efficiency, accuracy of predictions, and multi-dimensional integration, such challenges persist as the lack of data standardization, limited model interpretability, and insufficient domain-specific adaptation. Conclusion AI can empower TCM metabolomics research and contribute to the informatization and intellectualization of the analysis of complex mechanisms of TCM.

Key words: Traditional Chinese Medicine(TCM), Metabolomics, Biomarker, Artificial Intelligence(AI), Machine Learning, Mechanism of Action

CLC Number: