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European Medicines Agency, Amsterdam, The Netherlands; Faculty of Health Medicines and Life Sciences, Maastricht University, Maastricht, The Netherlands.
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European Medicines Agency, Amsterdam, The Netherlands.
You can also search for this author in PubMed Google Scholar
European Medicines Agency, Amsterdam, The Netherlands.
You can also search for this author in PubMed Google Scholar
European Medicines Agency, Amsterdam, The Netherlands.
You can also search for this author in PubMed Google Scholar
European Medicines Agency, Amsterdam, The Netherlands.
You can also search for this author in PubMed Google Scholar
The ability of artificial intelligence (AI) tools to generate new insights and improve processes could enhance the development and regulation of medicines in areas ranging from preclinical research to pharmacovigilance. Many applications of AI tools have the potential to impact the benefit–risk ratio of medicinal products, and so intersect with the mandate of regulatory agencies such as the European Medicines Agency (EMA) to assure the quality, safety and efficacy of medicines (Supplementary Table 1). For example, an AI tool could be used to predict the relationship between different patient characteristics and a medicine’s safety and efficacy, and thereby help optimize the patient populations in clinical trials accordingly. Other uses could include AI-based classification of individual case safety reports by seriousness, or supporting medicine administration; for example, a digital insulin pump that uses AI as part of its administration, monitoring or feedback control. AI applications, therefore, have great potential for public and animal health.
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doi: https://doi.org/10.1038/d41573-022-00190-3
Disclaimer
The views expressed in this article are the personal views of the authors and may not be understood or quoted as being made on behalf of or reflecting the position of the European Medicines Agency or one of its committees or working parties.
Correction 23 November 2022: The section about regulatory access to algorithms and datasets has been modified to remove the statement that the definition of commercially confidential information in the context of AI should mirror the one applicable to clinical trial data. One author, Peter Arlett, was not displaying owing to a platform error that has now been corrected.
The authors declare no competing interests.
The University of British Columbia (UBC)
Vancouver, Canada
German Aerospace Center (DLR)
Stuttgart, Germany
Jülich Research Centre (FZJ)
Jülich, Germany
Alfred Wegener Institute – Helmholtz Centre for Polar and Marine Research (AWI)
Bremerhaven, Germany
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