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中国医药导刊 ›› 2026, Vol. 28 ›› Issue (1): 10-10-15.doi: 10.1009-0959.2026.020008

• 监管科学 • 上一篇    下一篇

生成式人工智能在药物研发中的应用、挑战与监管策略

侯健, 陈小明, 张原, 李海玲, 袁利佳, 许真玉*   

  1. 国家药品监督管理局药品审评中心,北京 100076
  • 收稿日期:2025-06-25 修回日期:2025-11-25 接受日期:2026-02-06 出版日期:2026-01-28 发布日期:2026-02-11
  • 基金资助:
    药品监管科学国家重点实验室项目(2023SKLDRS0151)

Applications Challenges and Regulatory Strategies of Generative Artificial Intelligence in Drug Development

HOU Jian, CHEN Xiaoming, ZHANG Yuan, LI Hailing, YUANG Lijia, XU Zhenyu*   

  1. Center for Drug Evaluation National Medical Products Administration Beijing 100076, China
  • Received:2025-06-25 Revised:2025-11-25 Accepted:2026-02-06 Online:2026-01-28 Published:2026-02-11

摘要:

生成式人工智能(Gen AI)正在重塑药物研发的各个环节,包括靶点发现、分子设计、临床研究优化及注册文档生成。Gen AI通过深度学习模型分析多源数据,优化药物靶点识别,加速候选分子的设计与筛选,优化临床试验设计和患者招募。尽管Gen AI在提高研发效率和成功率方面展现出巨大潜力,但其应用仍面临可解释性不足、数据隐私保护与合规性、模型偏见、专业人才和跨界知识缺口、全球法规标准和指导原则滞后、成功案例难以复制等挑战。为应对这些问题,药品监管机构探索先行先试推动开展监管科学实践,坚持社会共治协同发力攻克技术难题,抓住发展机遇引领医药产业高质量发展,推动AI技术的法规支持和合规管理。通过政策引导与产业协同,Gen AI有望进一步推动药物研发的创新和生物医药产业的高质量发展。


关键词: 生成式人工智能, 药物研发, 药品注册, 智慧审评

Abstract:

Generative artificial intelligence Gen AI is reshaping various stages of the pharmaceutical development process including target discovery molecular design clinical trial optimization and regulatory document generation. By utilizing deep learning models to analyze multi-source data Gen AI enhances drug target identification accelerates the design and screening of candidate molecules and optimizes clinical trial designs and patient recruitment. Although Gen AI shows tremendous potential in enhancing the efficiency and success rates of R&D its application still faces challenges such as insufficient interpretability data privacy protection and compliance issues model bias a shortage of specialized talent and interdisciplinary knowledge gaps lagging global regulatory standards and guidelines and difficulties in replicating successful cases.To address these issues drug regulatory agencies are exploring pilot initiatives to advance regulatory science practices promoting collaborative governance to tackle technical challenges and seizing development opportunities to lead the high-quality growth of the pharmaceutical industry thereby promoting regulatory support and compliance management for AI technologies. Through policy guidance and industrial collaboration Gen AI is poised to further drive innovation in drug development and contribute to the high-quality advancement of the biopharmaceutical industry.

 

Key words: Generative artificial intelligence , Gen AI); , Drug development , Drug registration , Intelligent drug review

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