Navigating FDA Regulations for Development of Artificial Intelligence Technologies in Plastic Surgery.

Abstract

Artificial intelligence (AI) technologies are rapidly transforming the field of plastic surgery, offering new opportunities for improving patient outcomes through enhanced diagnostic capabilities, personalized treatment planning, and outcome prediction. However, the integration of these technologies into clinical practice requires navigation of complex regulatory frameworks established by the U.S. Food and Drug Administration (FDA). This review outlines the current FDA regulatory pathways relevant to AI applications in plastic surgery, including the 510(k), De Novo, and Premarket Approval processes. We discuss the FDA's Digital Health Center of Excellence, established in 2020, which serves as a central resource for developers of AI-based medical devices. The unique challenges of regulating adaptive AI technologies in plastic surgery are examined, with particular focus on the FDA's "total product lifecycle" approach and real-world performance monitoring requirements. We highlight the importance of Good Machine Learning Practices (GMLP) and the collaborative framework developed by FDA, NIST, and international regulatory bodies. For plastic surgeons and researchers developing AI tools, we provide practical recommendations including early FDA engagement, emphasis on algorithm transparency and explainability, and strategies for addressing bias in training datasets. By understanding and effectively navigating these regulatory requirements, plastic surgeons can successfully develop and implement safe, effective AI technologies that advance patient care while maintaining compliance with evolving FDA standards.