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Patients should be informed when AI systems are used in clinical trials

Nature Medicine volume 29, pages 1890–1891 (2023)Cite this article

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Artificial intelligence (AI) systems are increasingly being investigated in clinical trials. Trials that use AI must be held to the same ethical standards for risk assessment and disclosure as all human participant studies. All clinical AI systems, especially those under active investigation, have new risks, including human–machine interactions, interpretability and data limitations. The full magnitude and scope of these risks is not yet known because clinical AI integration is still in its infancy. We argue that in light of these risks and the uncertainty therein, disclosure is a minimal standard when patients’ data are being used in an AI clinical trial that may affect clinical decisions, even if written informed consent is not required.

The US Food and Drug Administration (FDA) classifies AI systems as ‘Software as a Medical Device’ (SaMD), with a lineage from simpler decision support tools such as risk calculators1,2. However, AI algorithms have unique risk considerations (Table 1), and the full effects of emergent risks remain incompletely understood.

Table 1 AI system clinical trials
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References

  1. US Food and Drug Administration. https://go.nature.com/41xD0em (2022).

  2. US Food and Drug Administration. https://go.nature.com/3zefINL (2019).

  3. Bitterman, D. S. et al. Lancet Digit. Health 2, e447–e449 (2020).

    Article  PubMed  Google Scholar 

  4. He, J. et al. Nat. Med. 25, 30–36 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Reyes, M. et al. Radiol. Artif. Intell. 2, e190043 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Kaushal, A. et al. JAMA 324, 1212–1213 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Panch, T. et al. J. Glob. Health 9, 010318 (2019).

    Article  PubMed  Google Scholar 

  8. Finlayson, S. G. et al. N. Engl. J. Med. 385, 283–286 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  9. US Department of Health and Human Services. 45 CFR 46 https://go.nature.com/3yl1Rq4 (2018).

  10. The Pew Charitable Trusts. https://go.nature.com/3I4ZuwJ (2021).

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Authors and Affiliations

  1. Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA

    Subha Perni & Danielle S. Bitterman

  2. Department of Radiation Oncology, Brigham and Women’s Hospital/Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA

    Subha Perni, Lisa Soleymani Lehmann & Danielle S. Bitterman

  3. MD Anderson Cancer Center, Houston, TX, USA

    Subha Perni

  4. Harvard T.H. Chan School of Public Health, Harvard Medical School, Boston, MA, USA

    Lisa Soleymani Lehmann

Authors
  1. Subha Perni
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  2. Lisa Soleymani Lehmann
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  3. Danielle S. Bitterman
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Corresponding author

Correspondence to Danielle S. Bitterman.

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Competing interests

D.S.B. is an associate editor of Radiation Oncology, HemOnc.org, unrelated to this work, for which she receives no financial compensation; and funding from American Association for Cancer Research, unrelated to this work.

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Perni, S., Lehmann, L.S. & Bitterman, D.S. Patients should be informed when AI systems are used in clinical trials. Nat Med 29, 1890–1891 (2023). https://doi.org/10.1038/s41591-023-02367-8

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