As organizations deploy artificial intelligence (AI) across current good manufacturing practices (cGMP) platforms, uncertainty and a lack of AI-specific regulations are slowing adoption. Yet regulatory silence is not a prohibition. Although existing regulations do not specifically address AI, the established U.S. and EU regulatory frameworks, including 21 CFR parts 210 and 211 and EudraLex Volume 4, are sufficiently flexible to accommodate AI-enabled approaches, when implemented thoughtfully. Within this structure, AI is not a regulatory exception, but a GMP control that must be justified, governed, and defended like any other.
In this webinar, experts from Arnold & Porter and Lachman Consultants examine the existing regulatory framework and FDA and EMA positions on AI in cGMP use-cases. Drawing on Annex 22 (EMA draft guidance on AI in GMP), FDA's draft guidance on AI to support regulatory decision-making, and the joint FDA-EMA Guiding Principles of Good AI Practice as reference points, we will analyze how regulators are framing expectations for AI across the product lifecycle, with a particular focus on manufacturing applications.
We will explore practical implementation considerations, using cGMP flexibility, ICH Q9 (Quality Risk Management) and ICH Q10 (Pharmaceutical Quality System) as the operational backbone. Key topics will include defining context of use, calibrating validation effort, managing model evolution, and preserving human authority and oversight, using mechanisms that regulators recognize. Throughout, the discussion will be guided by the questions that a manufacturing facility may face in a regulatory inspection or engagement with respect to AI, such as the decisions AI influences, how risk proportionality is demonstrated, who holds authority for model changes and decision making, and how quality is protected.
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