CHINESE JOURNAL OF MEDICINAL GUIDE ›› 2025, Vol. 27 ›› Issue (11): 1121-1121-1126.doi: 10.1009-0959.2025.120014

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Exploring Ethical Governance of Artificial Intelligence in Drug Regulation

CHEN Feng， YOU Yuwei   

  1. Center for Information of NMPA， Beijing 100076， China
  • Received:2025-09-25 Revised:2025-12-22 Accepted:2025-12-24 Online:2025-11-28 Published:2025-12-24

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Abstract:

 In recent years， the rapid development of new technologies， particularly generative artificial intelligence， has profoundly reshaped the foundational paradigms across various industries. In the specific field of drug regulation， which is critical to public health and safety， the introduction of AI technologies enhances the efficiency of review and approval， routine oversight， public service， and decision-making support. However， it also introduces unique ethical challenges due to its inherent complexity and unpredictability. This paper systematically outlines typical application scenarios of AI in drug regulation and provides an in-depth analysis of potential risks， including inherent risks （such as algorithmic bias and hallucinations）， application risks （such as model security vulnerabilities and data privacy breaches）， and derivative risks （such as blurred accountability and undermined regulatory credibility）. By drawing on governance experiences of the World Health Organization， UNESCO， the European Union， and other regulatory agencies， and integrating with China's actual situation， this study constructs a comprehensive ethical governance framework spanning four levels： "concept-norm-governance-capability". This framework advocates for establishing a people-centered， development-safety-balanced value orientation at the conceptual level； promoting the integration of scientific and medical ethics requirements while developing specific technical standards at the normative level； implementing a risk-based full-lifecycle regulatory mechanism to ensure traceability and accountability at the governance level； and fostering a multidisciplinary talent pool and technical support platforms at the capability level. Through the establishment and refinement of this governance framework， it aims to provide theoretical support and a practical framework for promoting the robust and responsible application of AI in the field of drug regulation in China， thereby safeguarding public medication safety and health rights.

  

Key words: Drug regulation, AI ethics, Ethical governance, Risk classification, Full-lifecycle supervision

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