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

Read full text
Authors: James Weatherall, Chris Meier
Cited by: 3
References: 24

Abstract

• Generative AI (GenAI) algorithms have started to make inroads into pharmaceutical R&D. • The DISRUPT-DS roundtable, a forum that brings together data science leaders from major pharmaceutical companies, has recently conducted an analysis of the impact of GenAI on R&D so far. • Here, the roundtable participants report key findings from this effort. • We discuss areas that are regulatory-relevant, including GenAI-powered document drafting and statistical programming, and we explore emerging topics such as the use of autonomous AI agents and foundation models. 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 artificial intelligence (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.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Computational Drug Discovery Methods Biomedical Text Mining and Ontologies

Publication details

Journal / source
Drug Discovery Today
Publisher
Elsevier BV
Volume
31
Issue
1
Pages
104593–104593
Publication date
1 January 2026
Language
EN