The world's largest repository of individual case safety reports. Primary tool for identifying extremely rare adverse events across global populations.
The centralized EU database for adverse reaction reports. Critical for signal detection within the European Economic Area (EEA).
The US repository for adverse event reports, medication errors, and product quality complaints. Publicly accessible for data mining.
Definitions and standards for expedited reporting of adverse drug reactions
Data elements and message specification for electronic safety reporting (HL7-based)
PBRER format and content requirements for periodic aggregate safety assessment
Standards for safety data reporting after marketing authorization is granted
Framework for proactive safety surveillance planning throughout the product lifecycle
DSUR format for annual safety reporting during clinical development
System requirements and master file
Detailed content requirements
Regulatory inspection framework
Internal audit standards
Risk Management Plans (RMPs)
Case management and reporting
Periodic safety update reports
PASS and safety studies
Detection, validation, evaluation
Enhanced surveillance activities
DHPCs and risk communication
Measures to reduce risk in practice
Of pharmaceutical firms reported using Real-World Data (RWD) in drug development by 2025
Of AI pharmacovigilance studies utilize Random Forest algorithms for signal detection
Systems that autonomously prioritize and triage incoming safety reports, reducing human workload on low-risk cases
AI and Machine Learning are being integrated into safety systems to autonomously prioritize incoming reports, detect patterns in large datasets, and augment traditional statistical methods. The combination of real-world data with spontaneous reporting is creating a more comprehensive safety surveillance ecosystem.