Pharmacovigilance

Evolving the System Validation Plan (SVP) for AI-Enabled Pharmacovigilance Systems For years the validation playbook in pharmacovigilance barely changed, and for good reason — it worked. You wrote a User Requirement Specification, the team built the code against it, you put together a validation plan, ran your IQ, OQ and PQ, signed off the Validation Summary Report, and issued the release notice. Clean, linear, defensible. An auditor could trace any output back through the system to a requirement, and you could prove, with evidence, that the system did exactly what it was specified to do....

Artificial intelligence is rapidly modernising pharmacovigilance (PV). It now offers powerful capabilities for processing Individual Case Safety Reports (ICSRs), detecting safety signals, and predicting adverse drug reactions. However, as AI systems become more sophisticated, many rely on complex “black-box” models. These models can produce highly accurate results, but their internal reasoning is often difficult for humans to interpret. This raises an important question: How can PV professionals and regulators trust decisions they cannot clearly understand?...

Pharmacovigilance has long sat at the heart of patient safety, traditionally relying on structured processes and conservative risk management to detect and prevent adverse drug reactions. Today, Artificial Intelligence is fundamentally transforming PV operations-from automated case intake and triage using Natural Language Processing to machine learning algorithms identifying patterns across massive safety datasets. However, introducing dynamic, learning AI systems into a highly regulated environment raises a critical challenge: How do we govern and validate these systems while maintaining compliance and patient protection?...

Whether you are in a big pharma company, an emerging biotech, or a CRO, the reality is the same: we all rely on vendors. But simply hiring a vendor and hoping for the best doesn’t cut it anymore. Today, having a rock-solid oversight process and governance model isn’t just “nice to have” - it is survival. You might be asking, “Why the sudden urgency?” The short answer is that the regulators have drawn a line in the sand....

In my previous post, I explored the European Commission guidelines and the EU AI Act, looking at how they influence AI applications and the validation strategies surrounding them. This time, I want to shift focus to the FDA’s draft guidance on AI, released in January 2025. Although still in draft form, the document is an important signal of how the FDA is approaching AI, and it helps us understand what kinds of validation methodologies are expected to align with global regulatory thinking....