Consistent Is Not Correct: AI in PV Causality Assessment & GxP Validation
When an AI model assesses a borderline DILI case 30 times, it gives the same answer 30 times. That’s consistency—not clinical accuracy. Join our live benchmark comparing 4 LLMs against human QPPVs and learn how to validate AI for EU GMP Annex 11 & 22.
Full details
One patient. Two suspect drugs. One liver signal.
Give a borderline causality case—such as an asymptomatic ALT elevation (4.2 × ULN) on Day 21 of atorvastatin following a 7-day course of amoxicillin-clavulanate—to five experienced drug safety physicians, and you will spark a rich scientific debate between WHO-UMC "Probable" and "Possible."
Ask a standard large language model the exact same question 30 times, and it will often give you the exact same answer 30 times.
In typical software engineering, 100% repeatability looks like a win. In Pharmacovigilance and GxP Quality, consistent is not the same as correct. A model that confidently converges on a single category by ignoring delayed-latency confounders does not eliminate human variance—it standardises a blind spot at scale. And during an EMA or FDA inspection, "the model said so" is not a defensible medical rationale.
In this 60-minute live technical seminar, we put four leading AI models through 30 runs each on complex, confounded PV cases and compare their outputs side by side against community QPPV votes and our GxP-validated PV architecture (VAIO-PV).
What you will learn in this session:
- Live 120-Run Benchmark Reveal: See exactly where generic LLMs hyper-converge on dechallenge bias and miss delayed-onset drug-induced liver injury (DILI) confounders.
- The "Smooth Narrative" Inspection Trap: Why polished AI-generated case narratives pass internal review but fail regulatory scrutiny on audit-trail reasoning.
- Validating Non-Deterministic AI: How to bridge EU GMP Annex 11, GAMP 5, and upcoming Draft Annex 22 expectations when deploying AI in safety and quality workflows.
- GxP-by-Design Architecture: How Molgenium’s VAIO-PV platform enforces structured clinical reasoning, outlier sensitivity, and full inspection traceability.
Who should attend:
- QPPVs, Deputy QPPVs, and Drug Safety Physicians
- Heads of Pharmacovigilance and Case Processing Leads
- GxP Quality Assurance, CSV Specialists, and Regulatory Affairs Leaders
Want to see how your current PV system stacks up before the session? Take our 5-minute PV Maturity Benchmark at https://www.molgenium.com