Abstract
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.
Highlights
Definitions and Problem StatementPharmacovigilance (PV) is “the science and activities related with the detection, assessment, understanding, and prevention of adverse effects or any other possible drug-related problems” (World Health Organization, 2002)
It should be noted that in the context of the analysis presented in Table 2, we consider that the term data refers to the original free-text Problem StatementPharmacovigilance (PV) signal reports and the term metadata refers to the respective OpenPVSignal instantiations
Beyond research on Adverse Drug Reactions (ADR) representation, which was extensively presented in section “Related Work: ADR Representation Formalisms and Frameworks”, of note is the Linked Open Drug Data (LODD) initiative (Samwald et al, 2011), a project conducted by the W3C Semantic Web for Health Care and Life Sciences Interest Group (HCLS IG), exploiting semantic discovery techniques to automatically interlink diverse datasets
Summary
Definitions and Problem StatementPharmacovigilance (PV) is “the science and activities related with the detection, assessment, understanding, and prevention of adverse effects or any other possible drug-related problems” (World Health Organization, 2002). The World Health Organization (WHO) releases its bi-monthly Pharmaceuticals Newsletter, containing a section devoted to PV signals identified and assessed by Uppsala Monitoring Centre, while other organizations (e.g., the European Medicines Agency (EMA), the Food and Drug Administration (FDA) in the United States, the Medicines and Healthcare products Regulatory Agency (MHRA) in the United Kingdom, the Netherlands Pharmacovigilance Centre (Lareb)5) publish information regarding new PV signals on their Web sites. A typical structure of a PV signal report contains a title referring to the ADR and the respective drug(s), the author(s) of the report, a summary of the report and/or an introductory section, evidence supporting the signal (e.g., individual case safety reports (ICSRs), a.k.a. individual case reports or spontaneous reports, coming from Spontaneous Reporting Systems (SRS), and the literature), a conclusion and, the respective bibliographic references
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