A policy framework for leveraging generative AI to address enduring challenges in clinical trials.

Can artificial intelligence improve clinical trial design? Despite their importance in medicine, over 40% of trials involve flawed protocols. We introduce and propose the development of application-specific language models (ASLMs) for clinical trial design across three phases: ASLM development by regulatory agencies, customization by Health Technology Assessment bodies, and deployment to stakeholders. This strategy could enhance trial efficiency, inclusivity, and safety, leading to more representative, cost-effective clinical trials.

Description

Acknowledgements: Any use of generative AI in this manuscript adheres to ethical guidelines for use and acknowledgement of generative AI in academic research19. Each author has made a substantial contribution to the work, which has been thoroughly vetted for accuracy, and assumes responsibility for the integrity of their contributions. The research was supported, in part, by a Novo Nordisk Foundation Grant for a scientifically independent International Collaborative Bioscience Innovation & Law Programme (Inter-CeBIL programme - grant no. NNF23SA0087056).

Keywords

4203 Health Services and Systems, 42 Health Sciences, Clinical Trials and Supportive Activities, Machine Learning and Artificial Intelligence, Bioengineering, Clinical Research, Networking and Information Technology R&D (NITRD), Generic health relevance, 3 Good Health and Well Being

Journal Title

NPJ Digit Med

Journal ISSN

2398-6352
2398-6352

Volume Title

8

Publisher

Springer Nature

Publisher DOI

https://doi.org/10.1038/s41746-025-01440-5

Rights and licensing

Except where otherwised noted, this item's license is described as http://creativecommons.org/licenses/by-nc-nd/4.0/

Sponsorship

Novo Nordisk Foundation (via University of Copenhagen) (NNF23SA0087056)

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