10 Asian Legal Business | February 2025 Regulators, lawyers keep pace with AI-driven drug development AI制药拓展想象空间，监管、法律服务 快速跟进 The impact of the 2024 Nobel Prize in Chemistry is still reverberating. Three scientists in protein structure prediction won the award, including two from Google’s AI company, DeepMind. Their AI model, AlphaFold, has made groundbreaking progress in predicting over 200 million protein structures, which are crucial for drug development. This has significantly expanded the possibilities of AI-driven pharmaceuticals. As the world’s second-largest market in terms of ongoing new drug projects, China has also seen rapid progress in AI-driven drug development. At last year’s China Pharmaceutical Industry Development Conference, a report on the digital transformation of the pharmaceutical industry noted that AI has already been widely integrated into innovative drug production. Li Junyi, a partner at Merits & Tree • During China’s 14th Five-Year Plan, 113 innovative drugs were approved, many incorporating AI at an advanced level. “十四五”期间获批上市创新药达113个，其中已“较高程度”运用到 人工智能技术 • China and the U.S. have released AI drug development guidelines, bringing regulatory oversight into focus. 中国、美国先后发布AI制药指导文件，相关领域监管提上日程 specializing in life sciences and healthcare, has observed the rise of AI-driven drug discovery through industry insights and discussions with clients. “The most prominent applications are in lead compound design, optimization, and synthesis, followed by compound screening and target discovery,” she says. However, Li also points out that AI-driven drug discovery is still in an early stage. “So far, no drug fully discovered and designed using AI has been approved for market release, either in China or globally,” she states. Beyond drug discovery, AI is playing a role in other key stages of pharmaceutical development, including preclinical research, clinical trials, manufacturing, and sales. The most mature applications of AI are in CMC (Chemistry, Manufacturing, and Controls) process management and GMP (Good Manufacturing The Briefs CHINA TECH COLUMN Practice) compliance. Another area seeking breakthroughs is clinical trials. “This is the most expensive stage of new drug development,” Li explains, “but AI applications in this field remain relatively limited.” Regulators keeping pace How are regulatory bodies responding in a field where scientific breakthroughs are still unfolding? Since pharmaceuticals directly impact human health and wellbeing, regulators are actively following the development of AI-driven drug discovery in various ways. In November 2024, China became the first country to release the Reference Guide for AI Application Scenarios in the Health Sector. Li explains that this document outlines several key “AI + drug development” scenarios, such as AI-assisted drug discovery, AI-supported clinical trials, and AI-driven comprehensive drug evaluations. “This demonstrates that regulators are generally showing a supportive attitude,” she says. Similarly, in early January this year, the U.S. Food and Drug Administration (FDA) released a draft guidance titled Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drugs and Biological Products, which also lists various AI applications across the drug lifecycle. However, Li points out that these guidelines from China and the U.S. only represent an initial regulatory stance. “Regulators have not yet reached a unified consensus or established clear and specific regulations on AI model usage throughout the entire drug lifecycle,” she explains. Beyond simply listing AI applications, the FDA’s draft also highlights challenges associated with AI and proposes regulatory considerations for the future. Li believes that as a leader in science regulation, the FDA’s stance and analysis could serve as a directional guide for future regulatory frameworks. For instance, the FDA identifies key challenges in AI-driven drug development, including the reliability of model outputs depending on training data By Hu Yangxiaoxiao 作者：胡阳潇潇
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