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Artificial Intelligence, Real-World Automation and the Safety of Medicines

Author

Listed:
  • Andrew Bate

    (GSK
    London School of Hygiene and Tropical Medicine)

  • Steve F. Hobbiger

    (GSK)

Abstract

Despite huge technological advances in the capabilities to capture, store, link and analyse data electronically, there has been some but limited impact on routine pharmacovigilance. We discuss emerging research in the use of artificial intelligence, machine learning and automation across the pharmacovigilance lifecycle including pre-licensure. Reasons are provided on why adoption is challenging and we also provide a perspective on changes needed to accelerate adoption, and thereby improve patient safety. Last, we make clear that while technologies could be superimposed on existing pharmacovigilance processes for incremental improvements, these great societal advances in data and technology also provide us with a timely opportunity to reconsider everything we do in pharmacovigilance operations to maximise the benefit of these advances.

Suggested Citation

  • Andrew Bate & Steve F. Hobbiger, 2021. "Artificial Intelligence, Real-World Automation and the Safety of Medicines," Drug Safety, Springer, vol. 44(2), pages 125-132, February.
    • Handle: RePEc:spr:drugsa:v:44:y:2021:i:2:d:10.1007_s40264-020-01001-7
    DOI: 10.1007/s40264-020-01001-7
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    References listed on IDEAS

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