New U.S. FDA Draft Guidance Outlines Path To Faster Modification of AI/ML-Enabled Devices

The U.S. Food and Drug Administration (FDA or Agency) has issued new draft guidance on “Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence/Machine Learning (AI/ML)-Enabled Device Software Functions”¹ that discusses a “science-based approach to ensuring that AI/ML-enabled devices can be safely, effectively, and rapidly modified, updated, and improved in response to new data.”² This approach should offer more certainty to industry as FDA’s stated goal is to allow AI/ML-enabled devices to be modified faster in accordance with FDA requirements while being “built to adapt to the data and needs of individual health care facilities” and “adapt to deliver treatments according to individual users' particular characteristics and needs.”³ Those wishing to comment on the draft guidance should note that the comment period closes on July 3, 2023.

The draft guidance proposes recommended information to be included in a Predetermined Change Control Plan (PCCP) as part of a marketing submission for a device that is or includes an ML-enabled device software function (ML-DSF). The PCCP would need to be reviewed and agreed to by FDA “to ensure the continued safety and effectiveness of the device,” but importantly, once it is approved or cleared as part of the marketing application, companies would not need to submit “additional marketing submissions” for each change made consistent with the plan.⁴

The Draft Guidance and PCCP Components

The draft guidance comes on the heels of the Food and Drug Omnibus Reform Act of 2022(FDORA)⁵, passed by Congress as a part of the 2022 omnibus bill, amending the Federal Food, Drug, and Cosmetic Act (FDCA) to provide FDA “with express authority to approve or clear PCCPs for devices requiring premarket approval or premarket notification.”⁶ FDA explained that the draft guidance is “informed by the considerable experience the FDA has gained by regulating AI/ML-enabled devices”⁷ and that it builds on the proposed approach described in the 2019 discussion paper and 2021 action plan.⁸

The PCCP focuses on device changes that would otherwise require FDA review (e.g., a premarket approval (PMA) supplement, a 510(k) premarket notification, or a de novo submission), and therefore minor modifications are not meant to be covered.⁹ Sponsors can use the PCCP as part of a marketing submission to proactively plan for and specify future changes to FDA. FDA will then review the proposed future modifications and method of implementation. If FDA agrees with the plan as part of the marketing authorization, these modifications can be made (if consistent with PCCP) without any need to seek further premarket authorization or review from FDA.¹⁰

A PCCP “should consist of a detailed Description of Modifications, a Modification Protocol, and an Impact Assessment” (refer to Sections VI–VIII of the draft guidance). Below are some highlights of each component mentioned above.

Description of Modifications — should describe and provide rationale for the planned modifications and describe device characteristics and performance changes that would result from the implementation of such modifications.¹¹ FDA recommends including a limited number of specific changes that are able to be verified and validated, and each proposed modification should state whether it would be implemented automatically (i.e., by software) or manually (i.e., require human involvement).¹²

Modification Protocol — should describe “the verification and validation activities (including pre-defined acceptance criteria) that will support those modifications” and must be compliant with the quality system (QS) regulation under 21 CFR Part 820.¹³ This includes device design controls and production and process controls requirements (see 21 CFR 820.30 and 820.70) and the need for documentation of the changes and relevant approvals (see 21 CFR 820.181).¹⁴

Impact Assessment — using an existing manufacturer’s quality system as a framework, should document the benefits and risks that the modifications would introduce and any mitigations.¹⁵ Documentation should 1) include a comparison of the device version with each modification with the device version without any modifications; 2) discuss benefits and risk for each modification, including risk of social harm; 3) “discuss how the activities proposed within the Modification Protocol continue to reasonably ensure the safety and effectiveness of the device”; and also discuss “4) how the implementation of one modification impacts the implementation of another, and 5) the collective impact of implementing all modifications.”¹⁶

Additional Considerations

FDA encourages early engagement using the Q-submission process to obtain Agency feedback regarding a proposed PCCP, particularly when the ML-DSF is combination product or a “high-risk, life-sustaining, life-supporting, or implantable device.”¹⁷

Another consideration relates specifically to developers of products with a predicate device. The statute and guidance essentially state that when making a substantial equivalence determination using a predicate device authorized with a PCCP, the comparison must use the predicate device version cleared or approved prior to changes made under the PCCP.¹⁸

Unsurprisingly, the draft guidance states that the FDA review division will determine “what evidence and information are required to support proposed modifications in a marketing submission.”¹⁹

Appendix A to the Guidance²⁰ includes example elements of Modification Protocol Components for ML-DSFs, and Appendix B to the Guidance²¹ includes examples that “illustrate different ML-DSF scenarios where a PCCP could be employed.”

Key Takeaway

Overall, this approach has the potential to save companies time and reduce uncertainty around the need for FDA authorization and the support required before making changes to devices with AI/ML. Nevertheless, there are extensive requirements described in the current draft that developers would have to fulfill. This draft guidance will need to be finalized and may change based on comments received.

¹See FDA Draft Guidance, “Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence/Machine Learning (AI/ML)-Enabled Device Software Function” (Apr. 2023) (available at https://www.fda.gov/media/166704/download) (PCCP Guidance).

²FDA, “CDRH Issues Draft Guidance on Predetermined Change Control Plans for Artificial Intelligence/Machine Learning-Enabled Medical Devices” (Mar. 30, 2023) (available at https://www.fda.gov/medical-devices/medical-devices-news-and-events/cdrh-issues-draft-guidance-predetermined-change-control-plans-artificial-intelligencemachine (FDA Announcement).

³Id.

⁴See PCCP Guidance at 2.

⁵See Food and Drug Omnibus Reform Act of 2022, Title III of Division FF of the Consolidated Appropriations Act, 2023, Pub. L. No. 117-328 (Dec. 29, 2022).

⁶See PCCP Guidance at 5.

⁷See FDA Announcement.

⁸See FDA, “Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) — Discussion Paper and Request for Feedback” (April 2019) (available at https://www.fda.gov/media/122535/download); FDA, “Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) Action Plan” (Jan. 2021) (available at https://www.fda.gov/media/145022/download).

⁹See FDA PCCP Guidance at 6.

¹⁰Id.

¹¹See PCCP Guidance at 11, 16.

¹²Id.

¹³See id. at 11, 18.

¹⁴Id. at 18.

¹⁵See id. at 24-25.

¹⁶Id.

¹⁷See id. at 7.

¹⁸Id.

¹⁹Id. at 8.

²⁰See id. at 26-32.

²¹See id. at 33-39.

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