Importance Predetermined Change Control Plans (PCCPs) are a recent regulatory innovation by the U.S. Food and Drug Administration (FDA) introduced to enable dynamic oversight of artificial intelligence and machine learning (AI/ML)-enabled medical devices.

Objective To characterize FDA program of PCCPs among AI/ML-enabled medical devices, including device characteristics, preapproval testing, planned modifications, and post-clearance update mechanisms.

Design This cross-sectional study reviewed FDA-cleared or approved AI/ML-enabled medical devices with authorized PCCPs.

Setting AI/ML-enabled devices approved or cleared prior to May 30, 2025 were identified from an FDA-maintained public list and their characteristics extracted from FDA approval databases.

Main Outcome(s) and Measure(s) Primary outcomes included (1) prevalence and characteristics of devices with authorized PCCPs, (2) types of FDA-authorized modifications, (3) presence and nature of preapproval testing, such as study design and subgroup testing, and (4) postmarket device update mechanisms and transparency.

Results Among 26 identified AI/ML-enabled medical devices with authorized PCCPs, 92% were cleared via the 510(k) pathway, and all were classified as moderate risk. Devices were primarily intended for use in diagnosis or clinical assessment, and six had consumer-facing components. Authorized modifications spanned the product lifecycle, most commonly allowing model retraining (69% of devices), logic updates (42% of devices), and expansion of input sources (35% of devices). Preapproval testing was limited with seven devices prospectively evaluated and thirteen undergoing human factors testing. Subgroup analyses were reported for eleven devices and none included patient outcomes data. No postmarket studies or recalls were identified. User manuals could be identified online for 54% of devices, though many lacked performance details or mentioned PCCPs.

Conclusions and Relevance FDA authorization of PCCPs grants manufacturers substantial flexibility to modify AI/ML-enabled devices postmarket, while preapproval testing and postmarket transparency are limited. These findings highlight the need for strengthened oversight mechanisms to ensure ongoing safety and effectiveness of rapidly evolving AI/ML-enabled technologies in clinical care.

The authors have declared no competing interest.

National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (U01TR002623)

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

All data presented in the study are publicly available.