Advancing network pharmacology with artificial intelligence: the next paradigm in traditional Chinese medicine.
10.1016/S1875-5364(25)60941-1
- Author:
Xin SHAO
1
;
Yu CHEN
2
;
Jinlu ZHANG
3
;
Xuting ZHANG
3
;
Yizheng DAI
3
;
Xin PENG
4
;
Xiaohui FAN
5
Author Information
1. Zhejiang Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314100, China; The Joint-laboratory of clinical multi-omics research between Zhejiang University and Ningbo Municipal Hospital of TCM, Ningbo Municipal Hospital of TCM, Ningbo 315010, China; Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China. Electronic address: xin_shao@zju.edu.cn.
2. School and Hospital of Stomatology, Wenzhou Medical University, Wenzhou 325035, China.
3. Zhejiang Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314100, China; The Joint-laboratory of clinical multi-omics research between Zhejiang University and Ningbo Municipal Hospital of TCM, Ningbo Municipal Hospital of TCM, Ningbo 315010, China.
4. The Joint-laboratory of clinical multi-omics research between Zhejiang University and Ningbo Municipal Hospital of TCM, Ningbo Municipal Hospital of TCM, Ningbo 315010, China. Electronic address: pengx@nit.zju.edu.cn.
5. Zhejiang Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314100, China; The Joint-laboratory of clinical multi-omics research between Zhejiang University and Ningbo Municipal Hospital of TCM, Ningbo Municipal Hospital of TCM, Ningbo 315010, China; Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China. Electronic address: fanxh@zju.edu.cn.
- Publication Type:Review
- Keywords:
Artificial intelligence;
Efficacy evaluation;
Mechanism elucidation;
Network analysis;
Network construction;
Network pharmacology;
Traditional Chinese medicine
- MeSH:
Medicine, Chinese Traditional/methods*;
Artificial Intelligence;
Network Pharmacology/methods*;
Humans;
Drugs, Chinese Herbal/chemistry*;
Drug Discovery
- From:
Chinese Journal of Natural Medicines (English Ed.)
2025;23(11):1358-1376
- CountryChina
- Language:English
-
Abstract:
Network pharmacology has gained widespread application in drug discovery, particularly in traditional Chinese medicine (TCM) research, which is characterized by its "multi-component, multi-target, and multi-pathway" nature. Through the integration of network biology, TCM network pharmacology enables systematic evaluation of therapeutic efficacy and detailed elucidation of action mechanisms, establishing a novel research paradigm for TCM modernization. The rapid advancement of machine learning, particularly revolutionary deep learning methods, has substantially enhanced artificial intelligence (AI) technology, offering significant potential to advance TCM network pharmacology research. This paper describes the methodology of TCM network pharmacology, encompassing ingredient identification, network construction, network analysis, and experimental validation. Furthermore, it summarizes key strategies for constructing various networks and analyzing constructed networks using AI methods. Finally, it addresses challenges and future directions regarding cell-cell communication (CCC)-based network construction, analysis, and validation, providing valuable insights for TCM network pharmacology.
