⚠️ Disclaimer: This video explains the draft FDA guidance (2025) on Artificial Intelligence. These are consultation-stage recommendations and not yet final regulations.
???? Artificial Intelligence (AI) is reshaping the pharmaceutical industry — from clinical development to manufacturing. But how can AI be used in a way that meets regulatory expectations?
In this video, we simplify the FDA’s draft guidance on the use of AI to support regulatory decision-making for drugs and biologics. This draft framework will help pharma professionals understand how to evaluate, document, and maintain AI systems to ensure safety, product quality, and compliance.
???? What you’ll learn in this video:
✔️ Scope: When AI models fall under FDA review — and when they don’t
✔️ FDA’s 7-step credibility framework for AI models
✔️ How model influence and decision consequence define risk levels
✔️ Clinical example: AI predicting patient monitoring needs (High Risk)
✔️ Manufacturing example: AI for vial fill inspection (Medium Risk)
✔️ FDA expectations for documentation, model training, and evaluation
✔️ Life cycle maintenance: dealing with data drift and retraining
✔️ Why early engagement with FDA is critical for AI solutions
⚠️ Why it matters:
FDA’s draft guidance gives us the clearest picture yet of how regulators view AI in pharma. If your team is considering AI solutions, understanding these rules early will help avoid compliance risks and inspection challenges.
???? Who should watch?
This video is for pharma manufacturers, QA leaders, regulatory affairs teams, IT & digital transformation specialists, and AI solution providers in life sciences.
???? More from ReveonAI
At ReveonAI, we specialize in AI-powered compliance solutions, consulting, and workforce training for the life sciences industry.
???? Learn more: www.reveon.ai
???? Contact: contact@reveonai.com
#FDAAI #PharmaCompliance #ArtificialIntelligence #PharmaManufacturing #DrugDevelopment #GMPCompliance #RegulatoryAffairs
???? If this breakdown was helpful, like, share, and subscribe for more insights on AI and compliance in life sciences.
???? Comment below: What’s the biggest challenge your team faces in adopting AI while staying compliant with FDA expectations?
???? Artificial Intelligence (AI) is reshaping the pharmaceutical industry — from clinical development to manufacturing. But how can AI be used in a way that meets regulatory expectations?
In this video, we simplify the FDA’s draft guidance on the use of AI to support regulatory decision-making for drugs and biologics. This draft framework will help pharma professionals understand how to evaluate, document, and maintain AI systems to ensure safety, product quality, and compliance.
???? What you’ll learn in this video:
✔️ Scope: When AI models fall under FDA review — and when they don’t
✔️ FDA’s 7-step credibility framework for AI models
✔️ How model influence and decision consequence define risk levels
✔️ Clinical example: AI predicting patient monitoring needs (High Risk)
✔️ Manufacturing example: AI for vial fill inspection (Medium Risk)
✔️ FDA expectations for documentation, model training, and evaluation
✔️ Life cycle maintenance: dealing with data drift and retraining
✔️ Why early engagement with FDA is critical for AI solutions
⚠️ Why it matters:
FDA’s draft guidance gives us the clearest picture yet of how regulators view AI in pharma. If your team is considering AI solutions, understanding these rules early will help avoid compliance risks and inspection challenges.
???? Who should watch?
This video is for pharma manufacturers, QA leaders, regulatory affairs teams, IT & digital transformation specialists, and AI solution providers in life sciences.
???? More from ReveonAI
At ReveonAI, we specialize in AI-powered compliance solutions, consulting, and workforce training for the life sciences industry.
???? Learn more: www.reveon.ai
???? Contact: contact@reveonai.com
#FDAAI #PharmaCompliance #ArtificialIntelligence #PharmaManufacturing #DrugDevelopment #GMPCompliance #RegulatoryAffairs
???? If this breakdown was helpful, like, share, and subscribe for more insights on AI and compliance in life sciences.
???? Comment below: What’s the biggest challenge your team faces in adopting AI while staying compliant with FDA expectations?
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- Artificial Intelligence
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