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FDA-Regulated AI-Enabled Medical Devices With Pediatric Indications
Grzegorz Zapotoczny1, Ansh Goyal2, Madison Christmas1
1Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois.
Insights
Pediatric artificial intelligence (AI) medical devices are rare and recently emerged, with longer review times and more clinical trials required. The FDA should standardize AI device labeling for children.
Area of Science:
- Medical Technology
- Artificial Intelligence in Healthcare
- Pediatric Device Innovation
Background:
- Artificial intelligence (AI) technologies offer potential for advanced healthcare devices.
- Limited data exists on the availability and characteristics of AI devices for pediatric patients.
- Analysis of regulatory submissions is crucial to understand pediatric AI device landscape.
Purpose of the Study:
- To characterize AI medical devices marketed in the U.S.
- To identify AI devices with specific pediatric indications.
- To explore barriers in pediatric AI device innovation.
Main Methods:
- Retrospective descriptive cross-sectional study.
- Analysis of FDA AI-Enabled Medical Device List data.
- Review of marketing submissions from November 1995 to June 2024.
Main Results:
- Only 4.4% of 952 AI devices had pediatric indications, emerging after 2015.
- Radiology and neurology were key areas, but 55.6% of clinical areas lacked pediatric AI devices.
- Pediatric AI devices showed longer FDA review times and higher clinical trial registration rates.
Conclusions:
- Pediatric AI devices are scarce, recent, and face longer regulatory reviews, indicating a need for more pediatric-specific evidence.
- Despite similar statutory standards, pediatric AI devices require more evidence generation.
- Standardizing age labeling and validation for AI-enabled technologies is recommended for the FDA.
Importance:
Artificial intelligence (AI)-based technologies hold promise for faster and more accurate devices in health care; however, little is known about their availability to pediatric patients. A comprehensive analysis of US Food and Drug Administration (FDA) regulatory submissions is necessary to identify technologies with pediatric labeling.
Objective:
To characterize AI devices marketed in the US, identify those with pediatric indications, and provide clues on AI-specific barriers to pediatric device innovation.
Design, Setting, And Participants:
This retrospective descriptive cross-sectional study was conducted using public data from the FDA's AI-Enabled Medical Device List. Marketing submissions reviewed by the FDA between November 1995 and June 2024 were analyzed.
Main Outcomes And Measures:
Prevalence of pediatric AI devices and their main characteristics (eg, clinical area, review time, and year of FDA marketing decision).
Results:
Among 952 submissions, 42 (4.4%) included pediatric age ranges (0-17 years). The first pediatric-inclusive device was cleared in 2015, and 5 exclusively pediatric technologies were introduced between 2020 and 2024. Of 18 clinical areas, radiology comprised 723 of all devices (75.9%) but only 18 of the devices specifically labeled for pediatrics (42.9%), whereas neurology comprised 34 devices overall (3.6%) vs 13 pediatric devices (31.0%); 10 clinical areas (55.6%) were missing among pediatric devices. The median (IQR) FDA review time was significantly longer for pediatric than for nonpediatric devices (162 [114-228] days; 95% CI, 151-212 days vs 134 [87-214] days; 95% CI, 149-162 days; 2-sided Mann-Whitney U test P = .049). Based on National Clinical Trial Identifiers in FDA summaries, clinical trial registration was noted in 6 pediatric (14.3%) vs 20 of 906 nonpediatric (2.2%) submissions.
Conclusions And Relevance:
In this study, pediatric devices were rare, emerged recently, and had longer review times and a higher proportion of registered clinical trials compared with nonpediatric devices, suggesting expectations for more pediatric-specific evidence despite unchanged statutory standards. To address gaps in pediatric device development, the FDA should standardize age labeling and validation requirements for AI-enabled technologies.
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