人工知能（AI）を活用した人間の使用経験に基づく新規漢方薬開発の見通し

The development of traditional Chinese medicine(TCM) new drugs is undergoing profound transformation under the increasingly rigorous global standards of evidence-based medicine and drug regulatory science. A full-cycle R&D model based on human use experience(HUE) has emerged as a strategic bridge linking TCM theory, historical usage, clinical evaluation, and innovative drug development. On this foundation, artificial intelligence(AI) is empowering all stages of TCM new drug development with unprecedented depth. These include: semantic understanding, reconstruction, and dialogue of literature based on natural language processing(NLP) and large language models(LLMs); safety modeling and druggability assessment driven by statistical learning, including deep learning; syndrome objectification via multimodal learning that integrating heterogeneous data such as tongue images, pulse patterns, and electronic medical records; and intelligent optimization of clinical research through adaptive trial design, platform trials, and reinforcement learning. This paper systematically reviews the critical roles of AI throughout the TCM new drug lifecycle-from candidate selection, HUE-based evidence structuring, and safety prediction, to clinical trial design, regulatory submission, post-marketing risk identification, and secondary development-highlighting the paradigm shift enabled by the deep integration of AI and HUE. It further proposes the construction of an integrated intelligent TCM new drug development platform that forms a closed-loop system of "data-driven, model-supported, and intelligent decision-making", promoting the transformation of TCM R&D from empirical reasoning to one driven by high-dimensional knowledge graphs, expert-AI collaborative learning, and multi-source evidence integration. Looking forward, AI is expected to further facilitate individualized therapeutic modeling, intelligent optimization of herbal compatibility strategies, repositioning of indications for compound formulas, and intelligent alignment with international regulatory pathways. This will accelerate the establishment of an internationally adaptive and standardized intelligent TCM new drug development system. This study provides both a theoretical foundation and practical direction for building a future-oriented innovation ecosystem and enhancing the global competitiveness of China's TCM new drug industry.