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

Juergen Schmider, Krishan Kumar, Chantal LaForest, Brian Swankoski, Karen Naim, Patrick Caubel

Year
2018
Citations
86
Access
Open access

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.

Keywords

PharmacovigilanceAdverse effectEvent (particle physics)Complex event processingAdverse Event Reporting SystemArtificial intelligenceComputer scienceMedicinePharmacology

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