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Interplay of Spontaneous Reporting and Longitudinal Healthcare Databases for Signal Management: Position Statement from the Real-World Evidence and Big Data Special Interest Group of the International Society of Pharmacovigilance

  • Salvatore Crisafulli
  • , Andrew Bate
  • , Jeffrey Stuart Brown
  • , Int Soc Pharmacovigilance
  • , Gianmario Candore
  • , Rebecca E. Chandler
  • , Tarek A. Hammad
  • , Samantha Lane
  • , Judith Christina Maro
  • , G. Niklas Noren
  • , Antoine Pariente
  • , Mulugeta Russom
  • , Maribel Salas
  • , Andrej Segec
  • , Saad Shakir
  • , Andrea Spini
  • , Sengwee Toh
  • , Marco Tuccori
  • , Eugene van Puijenbroek
  • , Gianluca Trifiro
  • University of Verona
  • GlaxoSmithKline
  • University of London
  • Harvard University
  • Bayer AG
  • Takeda Pharmaceutical Company Limited
  • University of Portsmouth
  • Université de Bordeaux
  • Institut national de la santé et de la recherche médicale
  • University of Pennsylvania
  • Data Analyt & Methods Task Force
  • University of Groningen

Research output: Contribution to journalArticleAcademicpeer-review

23 Citations (Scopus)
65 Downloads (Pure)

Abstract

Signal management, defined as the set of activities from signal detection to recommendations for action, is conducted using different data sources and leveraging data from spontaneous reporting databases (SRDs), which represent the cornerstone of pharmacovigilance. However, the exponentially increasing generation and availability of real-world data collected in longitudinal healthcare databases (LHDs), along with the rapid evolution of artificial intelligence-based algorithms and other advanced analytical methods, offers a wide range of opportunities to complement SRDs throughout all stages of signal management, especially signal detection. Integrating information derived from SRDs and LHDs may reduce their respective limitations, thus potentially enhancing post-marketing surveillance. The aim of this position statement is to critically evaluate the complementary role of SRDs and LHDs in signal management, exploring the potential benefits and challenges in integrating information coming from these two data sources. Furthermore, we presented successful cases of the interplay between SRDs and LHDs for signal management, along with future opportunities and directions to improve such interplay.
Original languageEnglish
Pages (from-to)959-976
Number of pages18
JournalDrug Safety
Volume48
Issue number9
Early online date13 Apr 2025
DOIs
Publication statusPublished - Sept 2025

Bibliographical note

Publisher Copyright:
© The Author(s) 2025.

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