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Benefit-Risk Reporting for FDA-Cleared Artificial Intelligence-Enabled Medical Devices.

John C Lin1, Bhav Jain2, Jay M Iyer3

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The US Food and Drug Administration (FDA) clearance of artificial intelligence (AI) and machine learning (ML) devices lacks standardized reporting for efficacy and safety. Improved regulatory pathways and postmarket surveillance are needed for AI/ML medical devices.

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Area of Science:

  • Medical device regulation
  • Artificial intelligence in healthcare
  • Machine learning in medicine

Background:

  • Artificial intelligence (AI) and machine learning (ML) devices are increasingly adopted in clinical settings.
  • Concerns exist regarding the benefit-risk assessment and surveillance of these AI/ML devices by the US Food and Drug Administration (FDA).

Purpose of the Study:

  • To characterize pre- and postmarket efficacy, safety, and risk assessment reporting for FDA-cleared AI/ML devices.

Main Methods:

  • A cross-sectional study analyzed linked FDA data for AI/ML devices cleared from September 1995 to July 2023.
  • Data sources included FDA decision summaries, approvals databases, and adverse event and recall databases.

Main Results:

  • Of 691 AI/ML devices cleared by 2023, many lacked reporting on study design (46.7%), training data (53.3%), and demographics (95.5%).
  • Few devices reported data from randomized trials (1.6%) or prospective studies (7.7%).
  • Adverse events were reported for 5.2% of devices, with 5.8% recalled, primarily due to software issues.

Conclusions:

  • Standardized efficacy, safety, and risk assessment reporting for FDA-cleared AI/ML devices is currently lacking.
  • Dedicated regulatory pathways and enhanced postmarket surveillance are recommended to address challenges in AI/ML device safety.