Global Data Exchange and Interoperability

Modern pharmacovigilance requires seamless data exchange between safety databases, regulatory submission systems, clinical trial systems, and real-world evidence platforms — enabled by continuously evolving international data standards. ICH E2B(R3) XML is globally mandated for ICSR transmission; ISO IDMP standardises product/substance identification (EMA SPOR implementation ongoing); MedDRA (currently v29.0, released March 2026, with v29.1 due September 2026) standardises adverse event coding on a biannual update cycle; and HL7 FHIR is seeing active adoption linking PV systems to EHRs in Sentinel and DARWIN EU.

Federated data models are the most significant structural innovation in global PV data sharing: rather than centralising raw patient-level data — which raises privacy, governance, and data sovereignty concerns — federated models run analytical algorithms at each participating data source and share only aggregate results. EMA’s DARWIN EU network applies this across European healthcare databases for multi-country RWE studies without data leaving national boundaries; FDA’s Sentinel uses a similar distributed architecture; and the WHO-UMC AI Hub is developing federated signal detection tools that would let algorithms learn from national databases globally without accessing individual ICSRs.

Blockchain is being piloted for PV audit trails — an unalterable, cryptographically secured log of every access, modification, and decision on a safety record — but full operational deployment in regulated PV systems remains limited as of 2026, pending regulatory guidance on acceptable architectures for GxP applications. Meanwhile, cloud migration of safety databases is now mainstream: Veeva Vault Safety, ArisGlobal LifeSphere NavaX, and Oracle Argus Cloud are all cloud-native or cloud-migrated, enabling real-time AI integration and global team accessibility, with data residency (GDPR, DPDP Act) as the main governance challenge.

Federated models deserve extra attention because they resolve what used to be a genuine dead end: regulators wanted broader real-world evidence, but privacy law increasingly restricted moving patient-level data across borders. Rather than choosing one goal over the other, DARWIN EU and Sentinel both prove the same architectural idea — send the analysis to the data, not the data to the analysis — which is why this pattern is likely to expand well beyond its current EU/US use cases as more countries build their own federated networks.