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

IF 4 2区医学 Q1 PHARMACOLOGY & PHARMACY

Drug Safety Pub Date : 2025-02-08 DOI:10.1007/s40264-024-01503-8

Achilleas Chytas, George Gavriilides, Anargyros Kapetanakis, Alix de Langlais, Marie-Christine Jaulent, Pantelis Natsiavas

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引用次数: 0

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.

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来源期刊

Drug Safety 医学-毒理学

CiteScore

7.60

自引率

7.10%

发文量

112

审稿时长

6-12 weeks

期刊介绍： Drug Safety is the official journal of the International Society of Pharmacovigilance. The journal includes: Overviews of contentious or emerging issues. Comprehensive narrative reviews that provide an authoritative source of information on epidemiology, clinical features, prevention and management of adverse effects of individual drugs and drug classes. In-depth benefit-risk assessment of adverse effect and efficacy data for a drug in a defined therapeutic area. Systematic reviews (with or without meta-analyses) that collate empirical evidence to answer a specific research question, using explicit, systematic methods as outlined by the PRISMA statement. Original research articles reporting the results of well-designed studies in disciplines such as pharmacoepidemiology, pharmacovigilance, pharmacology and toxicology, and pharmacogenomics. Editorials and commentaries on topical issues. Additional digital features (including animated abstracts, video abstracts, slide decks, audio slides, instructional videos, infographics, podcasts and animations) can be published with articles; these are designed to increase the visibility, readership and educational value of the journal’s content. In addition, articles published in Drug Safety Drugs may be accompanied by plain language summaries to assist readers who have some knowledge of, but not in-depth expertise in, the area to understand important medical advances.