Methodological and regulatory considerations for causal AI in drug development

Hana Lee(Center for Drug Evaluation and Research), Sky Qiu(University of California, Berkeley), Spencer R. Haupert(United States Food and Drug Administration), Gabriel K. Innes(United States Food and Drug Administration), Tristan Naumann(Microsoft (United States)), Demissie Alemayehu(Pfizer (United States)), Mark van der Laan(University of California, Berkeley)
npj Digital Medicine
February 27, 2026
Cited by 0Open Access
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Abstract

Advances in AI offer significant opportunities to enhance drug development. While several regulatory agencies have begun issuing guidance on AI adoption, its application to causal inference-a critical piece to understand treatment effects and inform regulatory decisions-remains limited. This paper reviews regulatory activities and examines statistical methodologies for AI-driven causal inference. We discuss key regulatory challenges and illustrate how AI adds value across diverse data sources and studies.


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