Chat-IRB? How application-specific language models can enhance research ethics review.

Journal: Journal of medical ethics
Published Date: Aug 5, 2025

Abstract

Institutional review boards (IRBs) play a crucial role in ensuring the ethical conduct of human subjects research, but face challenges including inconsistency, delays, and inefficiencies. We propose the development and implementation of application-specific large language models (LLMs) to facilitate IRB review processes. These IRB-specific LLMs would be fine-tuned on IRB-specific literature and institutional datasets, and equipped with retrieval capabilities to access up-to-date, context-relevant information. We outline potential applications, including pre-review screening, preliminary analysis, consistency checking, and decision support. While addressing concerns about accuracy, context sensitivity, and human oversight, we acknowledge remaining challenges such as over-reliance on artificial intelligence and the need for transparency. By enhancing the efficiency and quality of ethical review while maintaining human judgement in critical decisions, IRB-specific LLMs offer a promising tool to improve research oversight. We call for pilot studies to evaluate the feasibility and impact of this approach.

Authors

  • Sebastian Porsdam Mann
    Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Jiehao Joel Seah
    Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Stephen Latham
    Yale Interdisciplinary Center for Bioethics, Yale University, New Haven, Connecticut, USA.
  • Julian Savulescu
    2Uehiro Centre for Practical Ethics, University of Oxford, Oxford, UK.
  • Mateo Aboy
    Centre for Law, Medicine, and Life Sciences (LML), Faculty of Law, University of Cambridge, Cambridge, UK. ma608@cam.ac.uk.
  • Brian D Earp
    Philosophy, Psychology, Yale University, New Haven, Connecticut, USA brian.earp@yale.edu.

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