WHITE PAPER · 14 PAGES · PDF
FDA–EMA Good AI Practice for Pharma and Biologics
Explore FDA–EMA Good AI Practice principles for pharma and biologics, mapped to scientific models, explainable AI and human oversight.
Written for Biologics executives, MSAT, process development, Quality, regulatory and digital leaders.
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INSIDE THE WHITE PAPER
Move from interest to a reviewable decision.
Distinguish the joint ten principles from FDA draft credibility guidance and draft Annex 22.
Map scientific models, traceable information and human oversight to a defined context of use.
Follow a quality-prediction workflow from intended use and evidence to expert review.
Assess the complete human–AI workflow, failure scenarios and continued suitability.
What you’ll find inside
- What FDA–EMA Good AI Practice means for pharmaceutical leaders
- BioMedAna’s scientific approach to AI in biologics
- Mapping the ten FDA–EMA principles to BioMedAna
- Illustrative workflow for AI quality prediction in biologics
- Applying the approach to other pharmaceutical AI workflows
Includes an executive summary, practical decision tools, primary references and a next-step workflow review.
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