OpenPVSignal Knowledge Graph: Pharmacovigilance Signal Reports in a Computationally Exploitable FAIR Representation

Achilleas Chytas, George Gavriilides, Anargyros Kapetanakis, Alix Langlais, Marie-Christine Jaulent and Pantelis Natsiavas ()
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Achilleas Chytas: Institute of Applied Biosciences, Centre for Research and Technology Hellas
George Gavriilides: Institute of Applied Biosciences, Centre for Research and Technology Hellas
Anargyros Kapetanakis: Institute of Applied Biosciences, Centre for Research and Technology Hellas
Alix Langlais: ESIEE Paris
Marie-Christine Jaulent: Sorbonne Université, UMR_S 1142, LIMICS
Pantelis Natsiavas: Institute of Applied Biosciences, Centre for Research and Technology Hellas

Drug Safety, 2025, vol. 48, issue 4, No 9, 425-436

Abstract: Abstract Introduction Pharmacovigilance signal report (PVSR) documents contain valuable condensed information published by drug monitoring organizations, typically in a free-text format. They provide initial insights into potential links between drugs and harmful effects. Still, their unstructured format prevents this valuable information from being integrated into data-processing pipelines (e.g., to support either the investigation of drug safety signals or decision-making in the clinical context). Objective OpenPVSignal is a data model designed specifically to publish PVSRs via a computationally exploitable format, compliant with the FAIR (Findable, Accessible, Interoperable, Reusable) principles to promote ease of access and reusability of these valuable data. Methods This paper outlines the procedure for converting pharmacovigilance signals published by the World Health Organization Uppsala Monitoring Centre (WHO-UMC) into the OpenPVSignal data model, resulting in a Knowledge Graph (KG). It details each step of the process, including the technical validation by KG engineers and the qualitative verification by medical and pharmacovigilance experts, leading to the finalized KG. Results A total of 101 PVSRs from 2011 to 2019 were incorporated into the openly available KG. Conclusion The presented KG could be useful in various data-processing pipelines, including systems that support drug safety activities.

Date: 2025
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DOI: 10.1007/s40264-024-01503-8

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