AI-enabled combination devices (CDs) have the potential to transform healthcare by improving diagnostic accuracy, enhancing patient monitoring, and optimizing treatment efficacy. By integrating machine learning, natural language processing, and other AI-driven technologies, these devices can significantly enhance medical outcomes. However, their dynamic and evolving nature presents substantial regulatory challenges in maintaining safety, effectiveness, and compliance.

This paper, published in Frontiers in Medical Technology, explores the regulatory landscape for AI-enabled CDs, comparing the approaches of the U.S. Food and Drug Administration (FDA) and the European Union’s Medical Device Regulation (MDR). While the FDA is adopting more flexible, adaptive regulatory strategies, the EU enforces a stricter, more structured framework through the MDR, highlighting the need for global harmonization in AI medical device regulation.

To ensure the safe and effective integration of AI in medical technology, regulatory frameworks must evolve by incorporating risk-based, transparent, and adaptable approaches. This paper serves as a valuable resource for policymakers, regulators, and industry stakeholders navigating the complexities of AI-driven healthcare innovation.

The key differences in regulatory approaches can be summarized as follows:

• Flexibility vs rigidity
• Approval process
• Post-market surveillance
• Data privacy regulations