Innovation in Pharmacovigilance: Use of Artificial Intelligence in Adverse Event Case Processing.

Journal: Clinical pharmacology and therapeutics
Published Date:

Abstract

Automation of pharmaceutical safety case processing represents a significant opportunity to affect the strongest cost driver for a company's overall pharmacovigilance budget. A pilot was undertaken to test the feasibility of using artificial intelligence and robotic process automation to automate processing of adverse event reports. The pilot paradigm was used to simultaneously test proposed solutions of three commercial vendors. The result confirmed the feasibility of using artificial intelligence-based technology to support extraction from adverse event source documents and evaluation of case validity. In addition, the pilot demonstrated viability of the use of safety database data fields as a surrogate for otherwise time-consuming and costly direct annotation of source documents. Finally, the evaluation and scoring method used in the pilot was able to differentiate vendor capabilities and identify the best candidate to move into the discovery phase.

Authors

  • Juergen Schmider
    Pfizer R&D, Lake Forest, Illinois, USA.
  • Krishan Kumar
    Pfizer Business Technology, Artificial Intelligence Center of Excellence, La Jolla, California, USA.
  • Chantal LaForest
    Pfizer Global Product Development, Safety Solutions, Kirkland, Quebec, Ontario, Canada.
  • Brian Swankoski
    Pfizer Finance and Business Operations, Peapack, New Jersey, USA.
  • Karen Naim
    Pfizer R&D, Collegeville, Pennsylvania, USA.
  • Patrick M Caubel
    Pfizer R&D, New York, New York, USA.