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Trustworthy AI for safe medicines

Nature Reviews Drug Discovery volume 22, pages 855–856 (2023)Cite this article

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The pharmaceutical industry is rapidly adopting new and evolving applications of artificial intelligence (AI), and so we concur with the point made by Hines et al. (Nat. Rev. Drug Discov. 22, 81–82; 2023)1 that there is a need for regulatory agencies and industry to collaborate towards establishing a safety framework for this transition. However, the specifics of such a framework are yet to be defined. Here, we present our view of critical features of a potential regulatory framework for pharmaceutical applications of AI that improve understanding of the benefit–risk ratio of a medicinal product.

We use pharmacovigilance as an example to illustrate our view, as it is a field that is both well established and well regulated, but also one with matured usage of routinely collected healthcare data2 but only emerging experience with AI applications. Our view overlaps with the view of Hines et al.1, particularly in our shared emphasis on a risk-based regulatory framework that implements proportionate precautionary measures to enable responsible innovation. We consider, however, that an industry-wide risk-based framework must grade requirements according to risk level and harmonize with existing pharmaceutical regulation, and should not require regulatory access to the underlying algorithms and datasets, particularly considering more effective alternatives.

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Author information

Authors and Affiliations

  1. Global Safety, GSK, Wavre, Belgium

    Jens-Ulrich Stegmann

  2. Global Safety, GSK, Stevenage, UK

    Rory Littlebury

  3. Artificial Intelligence and Machine Learning, GSK, London, UK

    Markus Trengove & Lea Goetz

  4. Global Safety, GSK, Brentford, UK

    Andrew Bate

  5. Artificial Intelligence and Machine Learning, GSK, San Francisco, USA

    Kim M. Branson

Authors
  1. Jens-Ulrich Stegmann
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  2. Rory Littlebury
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  3. Markus Trengove
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  4. Lea Goetz
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  5. Andrew Bate
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  6. Kim M. Branson
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Corresponding author

Correspondence to Andrew Bate.

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All authors are employees of GSK and hold GSK stock and stock options.

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Nature Reviews Drug Discovery thanks David Bates and Rajesh Ghosh for their contribution to the peer review of this work.

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Stegmann, JU., Littlebury, R., Trengove, M. et al. Trustworthy AI for safe medicines. Nat Rev Drug Discov 22, 855–856 (2023). https://doi.org/10.1038/s41573-023-00769-4

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