Developing an Artificial Intelligence-Guided Signal Detection in the Food and Drug Administration Adverse Event Reporting System (FAERS): A Proof-of-Concept Study Using Galcanezumab and Simulated Data.

Journal: Drug safety
PMID: 37300636

Abstract

INTRODUCTION: Time- and resource-demanding activities related to processing individual case safety reports (ICSRs) include manual procedures to evaluate individual causality with the final goal of dismissing false-positive safety signals. Eminent experts and a representative from pharmaceutical industries and regulatory agencies have highlighted the need to automatize time- and resource-demanding procedures in signal detection and validation. However, to date there is a sparse availability of automatized tools for such purposes.

Authors

  • Fahed Al-Azzawi
    Department of Drug Design and Pharmacology, University of Copenhagen, Jagtvej 160, 2100, Copenhagen, Denmark. kdz640@sund.ku.dk.
  • Israa Mahmoud
    Department of Drug Design and Pharmacology, University of Copenhagen, Jagtvej 160, 2100, Copenhagen, Denmark.
  • François Haguinet
    GSK, Wavre, Belgium.
  • Andrew Bate
    Pfizer, London, UK.
  • Maurizio Sessa
    Department of Drug Design and Pharmacology, Drug Safety Group, University of Copenhagen, Copenhagen, Denmark.

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