Insights for intelligent safety
Guides, frameworks and explainers for safety leaders adopting AI in pharmacovigilance.
Guides and explainers
The S.A.F.E.T.Y. framework for AI in pharmacovigilance
Six tests for any AI you bring into drug safety: Secure, Auditable, Fit-for-purpose, Expert-in-the-loop, Trusted data and Yield. A practical guide for safety leaders and executives.
Read the framework →What is neurosymbolic AI, and why does safety need it?
Language models can read a case like an expert, but they can also invent a fact. Neurosymbolic AI pairs them with rules and knowledge, so every answer can be checked and explained.
Read the explainer →A buyer’s checklist for AI in pharmacovigilance
The questions to ask any vendor about scope, validation, explainability, oversight, integration, security and proof, with a scoring model you can use in your selection.
Read the guide →Zero-touch case processing: what it is and what it isn’t
How eligible cases flow from intake to acknowledgement automatically, why judgement stays with your experts, and how to introduce it safely.
Read the guide →Configuring AI to your SOPs
Why a generic model isn’t enough, what gets configured, and how SOP-based configuration is mapped, validated and kept in step with your procedures.
Read the explainer →The PV landscape in numbers
EudraVigilance volumes, signal reviews, where pharmacovigilance effort goes, and the growth of AI in drug safety, with sources.
Read the brief →Pharmacovigilance glossary
60 key terms, from ADR and ICSR to PBRER, E2B (R3), MedDRA and SUSAR, explained in plain language.
The S.A.F.E.T.Y. framework
AI you can trust, because patient safety comes first.
Secure
Privacy-by-design patient data protection
Auditable
Explainable, traceable, inspection-ready decisions
Fit-for-purpose
GxP-validated models, monitored for drift and bias
Expert-in-the-loop
Risk-based human oversight at critical decisions
Trusted data
Clean, standardised, integrated safety data
Yield
Measurable value in speed, quality and compliance
The PV landscape in numbers
Sources: EMA, 2025 Annual Report on EudraVigilance · Mordor Intelligence, AI in Pharmacovigilance Market (2026). Daily figure = 2025 total ÷ 365.
Intelligent safety should be one connected operation
Automate the work. Keep the decisions with your experts. Keep the evidence traceable. See it on your own data in six weeks.
6-week pilot on literature monitoring
- Baselines agreed up front
- Configured to your SOPs
- Measured on your own data
- Validation evidence from day one