Limitation or failure · Medicine

EMA publishes a reflection paper on AI across the medicinal product lifecycle

EMA publishes a reflection paper on AI across the medicinal product lifecycle: cautionary signal for reliability, quality, governance, or limits of AI in research.

Summary

EMA published a reflection paper on the use of AI in the medicinal product lifecycle. The agency says the paper covers principles relevant to applying AI and machine learning from drug discovery through post-authorization settings, following a 2023 draft and consultation period.

AI role

AI systems or AI-enabled research workflows are evaluated for reliability, rigor, trust, quality, or failure modes in medicine.

Narrative role

This qualifies the acceleration story by documenting reliability, rigor, governance, quality, or failure modes that can weaken simple progress narratives.

Caveat

This identifies a limitation or risk and should be connected to specific downstream effects before generalizing.