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MINI REVIEW article

Front. Med. Technol.
Sec. Regulatory Affairs
Volume 6 - 2024 | doi: 10.3389/fmedt.2024.1473350
This article is part of the Research Topic Regulatory Affairs for Combination Products View all 5 articles

Navigating Regulatory and Policy Challenges for AI enabled Combination Devices

Provisionally accepted
  • 1 Novartis (United States), East Hanover, United States
  • 2 Chugai Pharmaceutical Co., Ltd, Kamakura, Kanagawa, Japan
  • 3 St. John’s Episcopal Hospital, Fra Rockaway, New York, United States
  • 4 Takeda Oncology, Cambridge, Massachusetts, United States
  • 5 Johns Hopkins Medicine, Johns Hopkins University, Baltimore, Maryland, United States

The final, formatted version of the article will be published soon.

    In recent years, the Artificial Intelligence (AI) has enabled conventional Combination Devices (CDs) to innovate in healthcare merging with technology sectors. However, the challenges like reliance on predicate devices in US Food and Drug Administration (FDA)'s 510(k) pathway, especially for perpetually updating AI are stressed. Though the European Union (EU)'s new Medical Device Regulations address software and AI, fitting adaptive algorithms into conformity assessments remains difficult. The urgent need for frameworks cognizant of AI risks like model degradation and data biases is emphasized. Insights from recalled devices and case studies elucidate challenges in regulatory navigation for manufacturers. Adaptive policy frameworks balancing patient safeguards and rapid innovation are proposed.Recommendations target regulators and policy makers, advocating global standards to enable safe, effective and equitable AI adoption. This article aims to examine AI-enabled combination device regulation, inspecting US and EU strategies as well as obstacles for manufacturers and regulators.

    Keywords: AI-enabled combination devices, AI regulatory frameworks, FDA AI regulations, AI-enabled medical devices, AI policy frameworks, AI regulatory challenges

    Received: 30 Jul 2024; Accepted: 28 Oct 2024.

    Copyright: © 2024 Saxena, Santra, Kukreja, Gandhi and Singh. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Kinshuk Saxena, Novartis (United States), East Hanover, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.