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Artificial Intelligence: US FDA Outlines 7 Steps To Establishing Model Credibility

 
• By Sue Sutter

The risk-based framework described in a new draft guidance starts with defining the question of interest and context of use and includes development and execution of a credibility assessment plan. The guidance is limited to AI models used to support regulatory decisions about drug safety, effectiveness or quality.

Artificial intelligence
The FDA outlined a seven-step framework for establishing credibility of artificial intelligence models. (Shutterstock)
Key Takeaways
  • A new FDA draft guidance describes a seven-step, risk-based framework for assessing and demonstrating the credibility of artificial intelligence models when outputs are used to make drug regulatory decisions.
  • The guidance also discusses model life cycle management and FDA engagement opportunities.
  • The agency seeks feedback on whether the proposed assessment framework aligns with industry’s experience, and whether the available agency engagement options for sponsors and other interested parties are sufficient.

The US Food and Drug Administration wants drug sponsors to follow a seven-step framework for assessing and establishing the credibility of artificial intelligence models when their outputs are used to...

The framework employs a risk-based approach that generally will be tailored to the specific context of use and the model’s risk, the FDA said in a new draft

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