Artificial Intelligence in Traditional Chinese Medicine: Unraveling Herbal Medicine's Mechanisms - PubMed
5 hours ago
- #Artificial Intelligence
- #Network Pharmacology
- #Traditional Chinese Medicine
- Traditional Chinese Medicine (TCM) operates on a 'multicomponent, multitarget, multipathway' model, making scientific interpretation challenging.
- AI in TCM research often focuses on disease classification or prediction but struggles with reconstructing the biological logic of syndromes and formula compatibility.
- Network pharmacology provides a framework by building 'herb-compound-target-disease' networks that align with TCM's holistic approach.
- AI enhances network pharmacology through machine learning for component screening and ADME/T prediction, and deep learning for analyzing complex interactions.
- An integrated computational prediction and experimental validation workflow is now the gold standard for mechanistic studies in TCM.
- AI improves TCM quality control by linking chemical signatures to efficacy and integrates multiomics data to build regulatory networks.
- AI enables translational progress via precision patient stratification, real-world evidence, and knowledge graphs.
- Future AI advancements, like generative AI and large language models, promise deeper integration and modernization of TCM.