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Small Change: FDA’s Final Predetermined Change Control Plan (PCCP) Guidance Ditches ML and Adds Some Details, But Otherwise Sticks Closely to the Draft

FDA Law Blog

The final guidance hasnt changed much from the draft guidance with respect to the type of modifications FDA considers applicable for a PCCP and the required components of a PCCP (see our prior blog post on the draft guidance here ). FDA recommends including only a limited number of modifications in the PCCP.

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Change is Inevitable – Plan Ahead: An Assessment of FDA’s Draft Guidance on Predetermined Change Control Plans for Artificial Intelligence/Machine Learning-Enabled Device Software Functions

FDA Law Blog

Javitt — FDA recently published a long-awaited draft guidance aimed at reducing the need for prior FDA authorization of modifications to artificial intelligence/machine learning (AI/ML)-enabled device software functions (ML-DSFs). The draft guidance follows the December 2022 enactment of the Food and Drug Omnibus Reform Act of 2022 (FDORA).

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Are Predetermined Change Control Plans on the road to Global Harmonization?

FDA Law Blog

Additionally, when models are periodically or continually trained after deployment, there are appropriate controls in place to manage risks of overfitting, unintended bias, or degradation of the model (for example, dataset drift) that may impact the safety and performance of the model as it is used by the Human-AI team.

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The Incredible Shrinking Exemption: FDA Final CDS Guidance Would Significantly Narrow the Scope of Exempt Clinical Decision Support Software Under the Cures Act

FDA Law Blog

Javitt — On September 28, 2022, the FDA issued the long anticipated final Clinical Decision Support Software Guidance (CDS Guidance), which replaces the revised draft guidance document from 2019. You can find our preliminary blog post on the release of this guidance here , and our blog posts on the draft CDS guidances here and here.

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FDA Would Like to Join You in the Sandbox When Developing AI Enabled Devices

FDA Law Blog

Both guidance documents recommend data management practices for collecting data for use in developing, tuning, and testing an artificial intelligence model and making changes to said model.