Will the future of pharmacovigilance be more automated?
dc.rights.license | open | en_US |
hal.structure.identifier | Bordeaux population health [BPH] | |
dc.contributor.author | SALVO, Francesco
IDREF: 221043470 | |
dc.contributor.author | MICALLEF, Joelle | |
dc.contributor.author | LAHOUEGUE, Amir | |
dc.contributor.author | CHOUCHANA, Laurent | |
hal.structure.identifier | Bordeaux population health [BPH] | |
dc.contributor.author | LETINIER, Louis | |
dc.contributor.author | FAILLIE, Jean-Luc | |
hal.structure.identifier | Bordeaux population health [BPH] | |
dc.contributor.author | PARIENTE, Antoine
IDREF: 13395711X | |
dc.date.accessioned | 2023-11-06T16:17:46Z | |
dc.date.available | 2023-11-06T16:17:46Z | |
dc.date.issued | 2023-07-01 | |
dc.identifier.issn | 1744-764X | en_US |
dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/184632 | |
dc.description.abstractEn | Artificial intelligence (AI) based tools offer new opportunities for pharmacovigilance (PV) activities. Nevertheless, their contribution to PV needs to be tailored to preserve and strengthen medical and pharmacological expertise in drug safety. This work aims to describe PV tasks in which the contribution of AI and intelligent automation (IA) tools is required, in the context of a continuous increase of spontaneous reporting cases and regulatory tasks. A narrative review with expert selection of pertinent references was performed through Medline. Two areas were covered, management of spontaneous reporting cases and signal detection. The use of AI and IA tools will assist a large spectrum of PV activities, both in public and private PV systems, in particular for tasks of low added value (e.g. initial quality check, verification of essential regulatory information, search for duplicates). Testing, validating, and integrating these tools in the PV routine are the actual challenges for modern PV systems, to guarantee high-quality standards in terms of case management and signal detection. | |
dc.language.iso | EN | en_US |
dc.subject.en | Artificial intelligence | |
dc.subject.en | Digital twins | |
dc.subject.en | Explainability | |
dc.subject.en | Human intelligence | |
dc.subject.en | Machine learning | |
dc.subject.en | Regulation | |
dc.subject.en | System interoperability | |
dc.title.en | Will the future of pharmacovigilance be more automated? | |
dc.title.alternative | Expert Opin Drug Saf | en_US |
dc.type | Article de revue | en_US |
dc.identifier.doi | 10.1080/14740338.2023.2227091 | en_US |
dc.subject.hal | Sciences du Vivant [q-bio]/Santé publique et épidémiologie | en_US |
dc.identifier.pubmed | 37435796 | en_US |
bordeaux.journal | Expert Opinion on Drug Safety | en_US |
bordeaux.page | 541-548 | en_US |
bordeaux.volume | 22 | en_US |
bordeaux.hal.laboratories | Bordeaux Population Health Research Center (BPH) - UMR 1219 | en_US |
bordeaux.issue | 7 | en_US |
bordeaux.institution | Université de Bordeaux | en_US |
bordeaux.institution | INSERM | en_US |
bordeaux.team | AHEAD | en_US |
bordeaux.peerReviewed | oui | en_US |
bordeaux.inpress | non | en_US |
bordeaux.import.source | pubmed | |
hal.identifier | hal-04272597 | |
hal.version | 1 | |
hal.date.transferred | 2023-11-06T16:17:48Z | |
hal.popular | non | en_US |
hal.audience | Internationale | en_US |
hal.export | true | |
workflow.import.source | pubmed | |
dc.rights.cc | Pas de Licence CC | en_US |
bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Expert%20Opinion%20on%20Drug%20Safety&rft.date=2023-07-01&rft.volume=22&rft.issue=7&rft.spage=541-548&rft.epage=541-548&rft.eissn=1744-764X&rft.issn=1744-764X&rft.au=SALVO,%20Francesco&MICALLEF,%20Joelle&LAHOUEGUE,%20Amir&CHOUCHANA,%20Laurent&LETINIER,%20Louis&rft.genre=article |
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