Synapse
⌘+K
Synapse
PulseExploreJournal ClubResearchersJournals
Instagram
HomeJournal ClubExplore
July 31, 2025International Journal of Clinical PharmacyOpen Access

Artificial intelligence in pharmacovigilance: a narrative review and practical experience with an expert-defined Bayesian network tool

View Full Paper
Ask AI
Bookmark
Share

Authors

RARogério Caixinha AlgarvioJCJaime ConceiçãoPRPedro Pereira Rodrigues

Discussion

Loading...

Member takes

Overview

Narrative review highlights artificial intelligence’s impact on drug safety and efficiency in pharmacovigilance, suggesting significant improvements in adverse drug reaction management.

Key Points

  • AI enhances pharmacovigilance by streamlining signal detection and automating adverse drug reactions reporting.
  • The use of a Bayesian network at a pharmacovigilance center reduced causality assessment processing times from days to hours.
  • Data mining techniques employed by AI expedite safety signal identification, improving drug safety evaluations.
  • Despite promising improvements, practical AI application in pharmacovigilance is limited by data quality and regulatory challenges.

Cite This Study

Algarvio et al. (2025) studied this question.

synapsesocial.com/papers/689a094be6551bb0af8cf416https://doi.org/10.1007/s11096-025-01975-3
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Unveiling the future: precision pharmacovigilance in the era of personalized medicine2024 · 29 citations
  2. 2Timing Matters: A Machine Learning Method for the Prioritization of Drug–Drug Interactions Through Signal Detection in the FDA Adverse Event Reporting System and Their Relationship with Time of Co-exposure2024 · 16 citations
  3. 3Application of data mining techniques in pharmacovigilance2003 · 228 citations
  4. 4Developing an Artificial Intelligence-Guided Signal Detection in the Food and Drug Administration Adverse Event Reporting System (FAERS): A Proof-of-Concept Study Using Galcanezumab and Simulated Data2023 · 15 citations
  5. 5Application of Machine Learning Techniques in Drug-target Interactions Prediction2020 · 6 citations