摘要Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease preven-tion and treatment.However,analyzing its biological mechanisms through the modern medic-al research paradigm of"single drug,single target"presents significant challenges due to its holistic approach.Network pharmacology and its core theory of network targets connect drugs and diseases from a holistic and systematic perspective based on biological networks,overcoming the limitations of reductionist research models and showing considerable value in TCM research.Recent integration of network target computational and experimental meth-ods with artificial intelligence(AI)and multi-modal multi-omics technologies has substan-tially enhanced network pharmacology methodology.The advancement in computational and experimental techniques provides complementary support for network target theory in de-coding TCM principles.This review,centered on network targets,examines the progress of network target methods combined with AI in predicting disease molecular mechanisms and drug-target relationships,alongside the application of multi-modal multi-omics technologies in analyzing TCM formulae,syndromes,and toxicity.Looking forward,network target theory is expected to incorporate emerging technologies while developing novel approaches aligned with its unique characteristics,potentially leading to significant breakthroughs in TCM re-search and advancing scientific understanding and innovation in TCM.