Generative AI in pharmaceutical R&D: From large language models to AI agents to regulation

Generative AI (GenAI) is reshaping pharmaceutical R&D, offering transformative potential across research and development. Applications of GenAI include scientific insight generation, mining large biological datasets to study diseases, molecule design, clinical document drafting, and many others. The DISRUPT-DS roundtable, a forum that brings together data science leaders from major pharmaceutical companies, has recently conducted an analysis of GenAI in R&D. Here, the roundtable participants report key findings from this effort. Specifically, we discuss areas that are regulatory-relevant, including GenAI-powered document drafting and statistical programming, and we explore emerging topics, such as AI agents and foundation models. The goal of this work is to provide an industry-wide perspective of where GenAI is today and how it might evolve in the future.

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Publication Details

Journal
Drug Discovery Today
Published
2026-01-01
DOI
https://doi.org/10.1016/j.drudis.2025.104593
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

Generative AI in pharmaceutical R&D: From large language models to AI agents to regulation

James Weatherall, Chris Meier
Drug Discovery Today
Artificial Intelligence in Healthcare and Education
article

Generative AI in pharmaceutical R&D: From large language models to AI agents to regulation

James Weatherall, Chris Meier
article en

Abstract

Generative AI (GenAI) is reshaping pharmaceutical R&D, offering transformative potential across research and development. Applications of GenAI include scientific insight generation, mining large biological datasets to study diseases, molecule design, clinical document drafting, and many others. The DISRUPT-DS roundtable, a forum that brings together data science leaders from major pharmaceutical companies, has recently conducted an analysis of GenAI in R&D. Here, the roundtable participants report key findings from this effort. Specifically, we discuss areas that are regulatory-relevant, including GenAI-powered document drafting and statistical programming, and we explore emerging topics, such as AI agents and foundation models. The goal of this work is to provide an industry-wide perspective of where GenAI is today and how it might evolve in the future.

Drug Discovery TodayVol. 31(1)
AstraZeneca (United Kingdom) (GB), Boston Consulting Group (United States)
Industry, innovation and infrastructure
Openalex Percentile: Top 94%
Artificial Intelligence in Healthcare and Education
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