Unlock the transformative potential of AI in PV


As we approach the end of the year, we also near the deadline for providing feedback on the European Medicines Agency's (EMA) Draft Reflection Paper on Artificial Intelligence (AI) in the Medicinal Product Lifecycle.

This year marked significant strides in AI, with leading regulatory bodies inviting public commentary on their perspectives regarding AI and Machine Learning (AI/ML) in drug development. While the FDA's consultation period concluded earlier in August (find the paper here), the EMA's window remains open until year-end.

Both the @FDA and @europeanmedicinesagency papers offer intriguing insights with their own distinct focuses.

The FDA's discussion paper, particularly in its Post-market Surveillance section, delves into model development validation, performance monitoring, and the V&V 40 risk-informed credibility assessment framework. It underscores a risk-based approach for evidence and record-keeping requirements in AI/ML model verification and validation, advocating for early engagement with the FDA.

The EMA's paper highlights a human-centric approach in the development and deployment of AI/ML. It points out the necessity of close human supervision during marketing and post-authorization phases, acknowledging the potential for generative language models to produce plausible yet incorrect outputs. The paper calls for robust Quality Control (QC) mechanisms to ensure AI-generated text is both factually and syntactically accurate.

Both papers agree that Marketing Authorization Holders must validate, monitor, and document model performance, integrating AI/ML operations into their Pharmacovigilance (PV) system to mitigate the risks associated with all the algorithms and models employed.

At iVigee, we are fully committed to leveraging the latest AI advancements for our clients' benefit. We have thoroughly reviewed both papers and have submitted our comments, contributing to shaping the future of AI in pharmaceuticals.

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