As the core carrier of the theoretical system of traditional Chinese medicine (TCM), classic famous prescriptions play a vital role in the prevention and treatment of chronic diseases and major diseases. However, their secondary development still faces numerous technical bottlenecks, such as limitations caused by insufficient data standardization and inadequate evidence chains in evidence-based medicine, which restrict the transformation process from clinical practice to industrialization. Artificial intelligence (AI) has promoted the shift of traditional empirical medicine to a new research paradigm of “algorithm-model-data-scenario-application”, providing a brand-new perspective for data mining, prescription optimization, and new drug research and development of classic famous prescriptions, and empowering the modernization of TCM. This article systematically investigates how AI is reshaping the research paradigm of classic famous prescriptions, proposing an integrated framework centered on intelligent data mining, in-depth mechanism analysis, and precise efficacy evaluation. Firstly, it elaborates on the foundational basis of key technologies such as machine learning and their applicable scenarios. Secondly, from application dimensions including intelligent screening of candidate prescriptions, analysis of the material basis for efficacy, and in-depth exploration of mechanisms of action, it summarizes the research progress and application prospects of the integration of AI and classic famous prescriptions. Finally, it analyzes challenges such as data heterogeneity, lack of standards, and poor adaptability between models and TCM theories, and proposes targeted solutions, aiming to provide references for AI empowering the secondary development of classic famous prescriptions.

artificial intelligence  /  classic famous prescriptions  /  secondary development  /  research and development paradigm  /  application prospects