Currently submitted to: Journal of Medical Internet Research
Date Submitted: Oct 7, 2026
Open Peer Review Period: Oct 8, 2026 - Dec 3, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
FDA Review Timeliness, Regulatory Capacity, and Postmarket Reporting During the Rise of AI-Enabled Medical Devices: Cross-sectional Study
ABSTRACT
Background:
AI-enabled medical devices are increasing rapidly, but whether FDA review capacity, regulatory resources, and postmarket surveillance indicators have scaled in parallel is unclear.
Objective:
To analyze temporal trends in time to decision for AI-enabled versus non-AI devices, (Center for Devices and Radiological Health) CDRH resources and workload, review timeliness, and medical device reports.
Methods:
Cross-sectional analysis of publicly available FDA data from 2015 to 2025. Traditional 510(k) clearances, CDRH program activity metrics, MDUFA performance measures, statutory response metrics, and MAUDE reports information was extracted from FDA publically available databases and FDA Reports to Congress. Main outcomes included review time trends; funding composition, workload, full-time equivalents, and workload per full-time equivalent; MDUFA goal performance; statutory on-time response rates; and MAUDE report counts and rates.
Results:
From 2017 to 2025, AI-enabled Traditional 510(k) clearances increased from 20 of 2614 (0.77%) to 288 of 2655 total (10.85%; annual growth rate, 39.30%). Annual median review time increased by 3.94 days/year for AI-enabled devices, and 1.93 days/year for non-AI devices. AI-enabled median review time was higher in 12 of 15 shared clinical specialties. CDRH user-fee share increased from 26.42% to 46.90%, and pre-submissions increased from 2154 to 3910. MDUFA 510(k) monthly performance shortfalls were greatest in 2021 and 2022 (11.7% and 9.0%). Median statutory on-time response rates were 30% for 513(f)(2), 29% for 513(g), and 77% for postmarket surveillance plans. MAUDE included 17,707,433 all-device reports; AI-enabled devices accounted for 2097 reports, including 1847 malfunctions, 240 injuries, and 10 deaths.
Conclusions:
Rising AI-enabled device volume, steeper annual review-time increases, increasing user-fee dependence, selected MDUFA shortfalls, low information-request response performance, and expanding postmarket reporting signal volume suggest growing operational pressure on FDA device review and surveillance functions.
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