1. Exploiting heterogeneous publicly available data sources for drug safety surveillance: computational framework and case studies
- Author
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Vassilis Koutkias, Agnès Lillo-Le Louët, Marie-Christine Jaulent, Institute of Applied Biosciences, Centre for Research and Technology-Hellas, Thessaloniki, Greece, Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé (LIMICS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris 13 (UP13), Centre Régional de Pharmacovigilance (CRPV), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé ( LIMICS ), Université Paris 13 ( UP13 ) -Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Centre Régional de Pharmacovigilance ( CRPV ), Assistance publique - Hôpitaux de Paris (AP-HP)-Hôpital Européen Georges Pompidou [APHP] ( HEGP ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Université Paris 13 ( UP13 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), and Université Paris 13 (UP13)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)
- Subjects
Drug-Related Side Effects and Adverse Reactions ,Pyridones ,social media ,Information Storage and Retrieval ,joint exploitation ,Adverse drug events ,030226 pharmacology & pharmacy ,case studies ,computational framework ,Pharmacovigilance ,03 medical and health sciences ,Adverse Event Reporting System ,0302 clinical medicine ,Data acquisition ,emerging data sources for pharmacovigilance ,Robustness (computer science) ,Adverse Drug Reaction Reporting Systems ,Humans ,Medicine ,Pharmacology (medical) ,Social media ,030212 general & internal medicine ,spontaneous reporting systems ,Clozapine ,Cerebral Hemorrhage ,heterogeneous public data ,Safety surveillance ,business.industry ,[ SDV.SP.PHARMA ] Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology ,General Medicine ,Data science ,Cardiotoxicity ,3. Good health ,Visualization ,Identification (information) ,[SDV.SP.PHARMA]Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology ,Haloperidol ,Pyrazoles ,bibliographic databases ,business ,Antipsychotic Agents ,Factor Xa Inhibitors - Abstract
International audience; Objective: Driven by the need of pharmacovigilance centres and companies to routinely collect and review all available data about adverse drug reactions (ADRs) and adverse events of interest, we introduce and validate a computational framework exploiting dominant as well as emerging publicly available data sources for drug safety surveillance.Methods: Our approach relies on appropriate query formulation for data acquisition and subsequent filtering, transformation and joint visualization of the obtained data. We acquired data from the FDA Adverse Event Reporting System (FAERS), PubMed and Twitter. In order to assess the validity and the robustness of the approach, we elaborated on two important case studies, namely, clozapine-induced cardiomyopathy/myocarditis versus haloperidol-induced cardiomyopathy/myocarditis, and apixaban-induced cerebral hemorrhage.Results: The analysis of the obtained data provided interesting insights (identification of potential patient and health-care professional experiences regarding ADRs in Twitter, information/arguments against an ADR existence across all sources), while illustrating the benefits (complementing data from multiple sources to strengthen/confirm evidence) and the underlying challenges (selecting search terms, data presentation) of exploiting heterogeneous information sources, thereby advocating the need for the proposed framework.Conclusions: This work contributes in establishing a continuous learning system for drug safety surveillance by exploiting heterogeneous publicly available data sources via appropriate support tools.
- Published
- 2016
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