Reimagining drug regulation in the age of AI: a framework for the AI-enabled Ecosystem for Therapeutics - Singh, Rominder; Zhou, Karen; Auclair, Jared R. (Frontiers in Medicine, 2025)
Artificial intelligence (AI) is increasingly integrated into drug development and regulatory decision-making; however, the regulatory landscape governing these technologies remains fragmented. While agencies such as the US Food and Drug Administration (FDA) and European Medicines Agency (EMA) have begun issuing guidance on AI applications in human therapeutics, these frameworks differ substantially in scope, terminology, and application. This lack of alignment complicates regulatory interpretation, creates barriers to regulatory coordination, and impedes equitable access to AI-enabled therapies. In this article, we introduce the AI-enabled Ecosystem for Therapeutics (AI2ET) framework, a conceptual and policy-oriented model designed to support the federation of regulatory knowledge and promote regulatory alignment. The AI2ET shifts regulatory focus from individual AI-generated products to the broader AI-enabled systems, platforms, and processes that underpin drug development. This approach addresses current regulatory gaps in AI oversight by articulating clear definitions of the components that constitute the ecosystem, establishing risk-based decision-making pathways, and finally offering regulatory guidance to navigate the ecosystem. The article offers six key policy recommendations that include strengthening international cooperation, establishing shared regulatory definitions, and investing in regulatory capacity building. By laying down a conceptual foundation for regulatory science-based oversight of AI in therapeutic development, the AI2ET framework offers a path forward for inclusive, effective, and equitable oversight of AI in regulating human therapeutics.