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, Gianmario Candore, Rebecca E. Chandler, Tarek A. Hammad, Samantha Lane, Judith Christina Maro, G. Niklas Norén, Antoine Pariente, Mulugeta Russom, Maribel Salas, Andrej Segec, Saad Shakir, Andrea Spini, Sengwee Toh, Marco Tuccori, Eugène Puijenbroek and Gianluca Trifirò ()
Additional contact information
Salvatore Crisafulli: University of Verona
Andrew Bate: Global Safety, GSK
Jeffrey Stuart Brown: TriNetX
Gianmario Candore: Bayer AG
Rebecca E. Chandler: Coalition for Epidemic Preparedness Innovations
Tarek A. Hammad: Takeda Development Center Americas, Inc.
Samantha Lane: Drug Safety Research Unit
Judith Christina Maro: Harvard Medical School
G. Niklas Norén: Uppsala Monitoring Centre
Antoine Pariente: Université de Bordeaux, INSERM, BPH, Team AHeaD, U1219
Mulugeta Russom: National Medicines and Food Administration, Ministry of Health
Maribel Salas: Bayer Pharmaceuticals Inc.
Andrej Segec: European Medicines Agency
Saad Shakir: Drug Safety Research Unit
Andrea Spini: University of Verona
Sengwee Toh: Harvard Medical School
Marco Tuccori: University of Verona
Eugène Puijenbroek: Netherlands Pharmacovigilance Centre Lareb
Gianluca Trifirò: University of Verona

Drug Safety, 2025, vol. 48, issue 9, No 1, 959-976

Abstract: 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.

Date: 2025
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DOI: 10.1007/s40264-025-01548-3

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