Innovating global regulatory frameworks for generative AI in medical devices is an urgent priority

Research output: Contribution to journalReview articleContributedpeer-review

Contributors

  • Jasmine Chiat Ling Ong - , Singapore General Hospital, Duke-NUS Medical School (Author)
  • Yilin Ning - , Duke-NUS Medical School (Author)
  • Mingxuan Liu - , Duke-NUS Medical School (Author)
  • Yian Ma - , Duke-NUS Medical School (Author)
  • Liang Zhao - , University of California at San Francisco (Author)
  • Kuldev Singh - , Stanford University (Author)
  • Robert T. Chang - , Stanford University (Author)
  • Silke Vogel - , Duke-NUS Medical School (Author)
  • John C.W. Lim - , Duke-NUS Medical School (Author)
  • Iris Siu Kwan Tan - , Singapore Health Services (Author)
  • Oscar Freyer - , Else Kröner Fresenius Center for Digital Health (Author)
  • Stephen Gilbert - , Else Kröner Fresenius Center for Digital Health (Author)
  • Danielle S. Bitterman - , Harvard Medical School (HMS), Brigham and Women's Hospital (Author)
  • Xiaoxuan Liu - , University of Birmingham, University Hospitals Birmingham NHS Foundation Trust (Author)
  • Alastair K. Denniston - , University of Birmingham, University Hospitals Birmingham NHS Foundation Trust (Author)
  • Nan Liu - , Duke-NUS Medical School, National University of Singapore, Duke University (Author)

Abstract

The integration of generative AI (GenAI) and large language models (LLMs) in healthcare presents both unprecedented opportunities and challenges, necessitating innovative regulatory approaches. In this perspective, we discuss the risks of GenAI and LLM-based medical devices, the limitations of current medical device regulation frameworks when applied to GenAI or LLMs, and advocate for global collaboration in regulatory science research through engaging multidisciplinary expertise and focusing on the needs of diverse populations.

Details

Original languageEnglish
Article number364
Journal npj digital medicine
Volume9
Issue number1
Publication statusPublished - 19 Mar 2026
Peer-reviewedYes

External IDs

PubMedCentral PMC13168469
Scopus 105039265298
ORCID /0000-0002-1997-1689/work/218584238
ORCID /0000-0003-3323-2492/work/218584358

Keywords