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AI/ML in Precision Medicine: A Look Beyond the Hype

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Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are making headlines in medical research, especially in drug discovery, digital imaging, disease diagnostics, genetic testing, and optimal care pathway (personalized care). However, the potential uses and benefits of AI/ML applications need to be distinguished from hype. In the 2022 American Statistical Association Biopharmaceutical Section Regulatory-Industry Statistical Workshop, we convened a panel of experts from FDA and industry to talk about the challenges of successfully applying AI/ML in precision medicine and how to overcome those challenges. This paper provides a summary and expansion on the topics discussed in the panel: the application of AI/ML, bias, and data quality.

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This article reflects the views of the authors and should not be construed to represent FDA’s views or policies.

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Authors and Affiliations

  1. U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD, 20993, USA

    Zhiheng Xu & Bipasa Biswas

  2. PharmaLex, Inc, 5280 Corporate Dr, Frederick, MD, 21703, USA

    Lin Li

  3. Quinten Health, Inc, 8, Rue Vernier, 75017, Paris, France

    Billy Amzal

Authors
  1. Zhiheng Xu
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  2. Bipasa Biswas
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  3. Lin Li
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  4. Billy Amzal
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Substantial contributions are equally distributed among all four authors.

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Correspondence to Zhiheng Xu.

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Xu, Z., Biswas, B., Li, L. et al. AI/ML in Precision Medicine: A Look Beyond the Hype. Ther Innov Regul Sci 57, 957–962 (2023). https://doi.org/10.1007/s43441-023-00541-1

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  • DOI: https://doi.org/10.1007/s43441-023-00541-1

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