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OpenPVSignal: Advancing Information Search, Sharing and Reuse on Pharmacovigilance Signals via FAIR Principles and Semantic Web Technologies

Signal detection and management is a key activity in pharmacovigilance (PV). When a new PV signal is identified, the respective information is publicly communicated in the form of periodic newsletters or reports by organizations that monitor and investigate PV-related information (such as the World...

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Autores principales: Natsiavas, Pantelis, Boyce, Richard D., Jaulent, Marie-Christine, Koutkias, Vassilis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6028717/
https://www.ncbi.nlm.nih.gov/pubmed/29997499
http://dx.doi.org/10.3389/fphar.2018.00609
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author Natsiavas, Pantelis
Boyce, Richard D.
Jaulent, Marie-Christine
Koutkias, Vassilis
author_facet Natsiavas, Pantelis
Boyce, Richard D.
Jaulent, Marie-Christine
Koutkias, Vassilis
author_sort Natsiavas, Pantelis
collection PubMed
description Signal detection and management is a key activity in pharmacovigilance (PV). When a new PV signal is identified, the respective information is publicly communicated in the form of periodic newsletters or reports by organizations that monitor and investigate PV-related information (such as the World Health Organization and national PV centers). However, this type of communication does not allow for systematic access, discovery and explicit data interlinking and, therefore, does not facilitate automated data sharing and reuse. In this paper, we present OpenPVSignal, a novel ontology aiming to support the semantic enrichment and rigorous communication of PV signal information in a systematic way, focusing on two key aspects: (a) publishing signal information according to the FAIR (Findable, Accessible, Interoperable, and Re-usable) data principles, and (b) exploiting automatic reasoning capabilities upon the interlinked PV signal report data. OpenPVSignal is developed as a reusable, extendable and machine-understandable model based on Semantic Web standards/recommendations. In particular, it can be used to model PV signal report data focusing on: (a) heterogeneous data interlinking, (b) semantic and syntactic interoperability, (c) provenance tracking and (d) knowledge expressiveness. OpenPVSignal is built upon widely-accepted semantic models, namely, the provenance ontology (PROV-O), the Micropublications semantic model, the Web Annotation Data Model (WADM), the Ontology of Adverse Events (OAE) and the Time ontology. To this end, we describe the design of OpenPVSignal and demonstrate its applicability as well as the reasoning capabilities enabled by its use. We also provide an evaluation of the model against the FAIR data principles. The applicability of OpenPVSignal is demonstrated by using PV signal information published in: (a) the World Health Organization's Pharmaceuticals Newsletter, (b) the Netherlands Pharmacovigilance Centre Lareb Web site and (c) the U.S. Food and Drug Administration (FDA) Drug Safety Communications, also available on the FDA Web site.
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spelling pubmed-60287172018-07-11 OpenPVSignal: Advancing Information Search, Sharing and Reuse on Pharmacovigilance Signals via FAIR Principles and Semantic Web Technologies Natsiavas, Pantelis Boyce, Richard D. Jaulent, Marie-Christine Koutkias, Vassilis Front Pharmacol Pharmacology Signal detection and management is a key activity in pharmacovigilance (PV). When a new PV signal is identified, the respective information is publicly communicated in the form of periodic newsletters or reports by organizations that monitor and investigate PV-related information (such as the World Health Organization and national PV centers). However, this type of communication does not allow for systematic access, discovery and explicit data interlinking and, therefore, does not facilitate automated data sharing and reuse. In this paper, we present OpenPVSignal, a novel ontology aiming to support the semantic enrichment and rigorous communication of PV signal information in a systematic way, focusing on two key aspects: (a) publishing signal information according to the FAIR (Findable, Accessible, Interoperable, and Re-usable) data principles, and (b) exploiting automatic reasoning capabilities upon the interlinked PV signal report data. OpenPVSignal is developed as a reusable, extendable and machine-understandable model based on Semantic Web standards/recommendations. In particular, it can be used to model PV signal report data focusing on: (a) heterogeneous data interlinking, (b) semantic and syntactic interoperability, (c) provenance tracking and (d) knowledge expressiveness. OpenPVSignal is built upon widely-accepted semantic models, namely, the provenance ontology (PROV-O), the Micropublications semantic model, the Web Annotation Data Model (WADM), the Ontology of Adverse Events (OAE) and the Time ontology. To this end, we describe the design of OpenPVSignal and demonstrate its applicability as well as the reasoning capabilities enabled by its use. We also provide an evaluation of the model against the FAIR data principles. The applicability of OpenPVSignal is demonstrated by using PV signal information published in: (a) the World Health Organization's Pharmaceuticals Newsletter, (b) the Netherlands Pharmacovigilance Centre Lareb Web site and (c) the U.S. Food and Drug Administration (FDA) Drug Safety Communications, also available on the FDA Web site. Frontiers Media S.A. 2018-06-26 /pmc/articles/PMC6028717/ /pubmed/29997499 http://dx.doi.org/10.3389/fphar.2018.00609 Text en Copyright © 2018 Natsiavas, Boyce, Jaulent and Koutkias. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Natsiavas, Pantelis
Boyce, Richard D.
Jaulent, Marie-Christine
Koutkias, Vassilis
OpenPVSignal: Advancing Information Search, Sharing and Reuse on Pharmacovigilance Signals via FAIR Principles and Semantic Web Technologies
title OpenPVSignal: Advancing Information Search, Sharing and Reuse on Pharmacovigilance Signals via FAIR Principles and Semantic Web Technologies
title_full OpenPVSignal: Advancing Information Search, Sharing and Reuse on Pharmacovigilance Signals via FAIR Principles and Semantic Web Technologies
title_fullStr OpenPVSignal: Advancing Information Search, Sharing and Reuse on Pharmacovigilance Signals via FAIR Principles and Semantic Web Technologies
title_full_unstemmed OpenPVSignal: Advancing Information Search, Sharing and Reuse on Pharmacovigilance Signals via FAIR Principles and Semantic Web Technologies
title_short OpenPVSignal: Advancing Information Search, Sharing and Reuse on Pharmacovigilance Signals via FAIR Principles and Semantic Web Technologies
title_sort openpvsignal: advancing information search, sharing and reuse on pharmacovigilance signals via fair principles and semantic web technologies
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6028717/
https://www.ncbi.nlm.nih.gov/pubmed/29997499
http://dx.doi.org/10.3389/fphar.2018.00609
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