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

The risk-based framework described in a new draft guidance starts with defining the question of interest and context of use and includes development and execution of a credibility assessment plan.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  • A new FDA draft guidance describes a seven-step, risk-based framework for assessing and demonstrating the credibility of artificial intelligence models when outputs are used to make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

Read the full article – start your free trial today!

Join thousands of industry professionals who rely on Pink Sheet for daily insights

  • Start your 7-day free trial
  • Explore trusted news, analysis, and insights
  • Access comprehensive global coverage
  • Enjoy instant access – no credit card required

More from AI

US HHS Deputy Nominee Talks AI, Not FDA, In Confirmation Hearing

 

Silicon Valley investor Jim O’Neill’s Senate confirmation hearings showcased the unique background of someone with government and tech experience and avoided discussions of his past statements about lowering the bar for regulatory approval.

Canada’s HTA Agency Reveals How To Submit AI-Driven Evidence

 

Recognizing that the evidence it receives in applications for health technology assessments will increasingly be informed by artificial intelligence, the CDA-AMC has clarified its expectations for companies that use AI methods in the generation and/or reporting of evidence.

AI Could Be Used ‘In The Deliberation’ Of HTA Reviews In England, Says NICE

 

England’s health technology assessment institute, NICE, is looking to “reimagine” its evaluation process with the help of AI, rather than just using this technology to speed up its existing processes.

EMA’s Newly Qualified AI Tool To Boost MASH Market Dynamics

 

The European Medicines Agency’s qualification of the AIM-NASH tool is said to signify a major advancement for clinical trials for metabolic dysfunction-associated steatohepatitis. The market size for MASH treatments is expected to grow substantially in the coming years.

More from Advanced Technologies

Keep Talking: US FDA’s Beleaguered Biologics Center Remains Vital To Regenerative Medicine

 

Advisory committee for Capricor’s deriamocel planned, regenerative medicine advanced therapy designations proliferate for osteoarthritis, and the ranks of dual RMAT/breakthrough therapy designation holders grow.

EU Health Data Space May Speed Up R&D Through Access To Multi-Omics & Clinical Record Data

 

The European Health Data Space framework will allow companies to accelerate R&D processes and identify new molecular targets faster by facilitating centralized access to certain types of high-quality data, Finland’s Orion Pharma says.

EU Wants Industry To Define ‘Trade Secrets’ Under Health Data Sharing Regulation

 

The European Health Data Space Regulation is deliberately “vague” when it comes to defining trade secrets because the EU wants the pharma industry to make recommendations on safeguarding intellectual property, a policy officer for the European Commission says.