How Does the FDA Address Cybersecurity in AI Devices?

Author: Rasit Dinc

Introduction

The integration of Artificial Intelligence (AI) and Machine Learning (ML) into medical devices is revolutionizing healthcare, offering unprecedented opportunities for diagnostics, treatment, and patient monitoring. From AI-powered imaging analysis to smart therapeutic devices, these technologies promise to enhance clinical decision-making and improve patient outcomes. However, the increasing connectivity of these devices to the internet and hospital networks also introduces significant cybersecurity vulnerabilities. The U.S. Food and Drug Administration (FDA) is actively addressing these challenges by developing a comprehensive regulatory framework to ensure the safety and effectiveness of AI-enabled medical devices. [1]

The FDA's Evolving Regulatory Landscape

The FDA acknowledges that its traditional approach to medical device regulation was not designed for the adaptive nature of AI/ML technologies. [2] These advanced algorithms can learn from real-world data and modify their performance over time, which presents a unique challenge for premarket review and postmarket surveillance. To address this, the FDA has been proactively developing a new regulatory paradigm that is both flexible and robust.

In 2019, the agency published a discussion paper, "Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD)," which outlined a potential approach for managing algorithm changes. [3] This was followed by the "Artificial Intelligence and Machine Learning Software as a Medical Device Action Plan" in 2021, which detailed the FDA's multi-pronged approach to overseeing AI/ML-based medical devices. [4]

Key Guidance and Frameworks

A cornerstone of the FDA's strategy is the development of specific guidance documents that provide recommendations for device manufacturers. The final guidance on "Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions," issued in 2023, is a critical resource for understanding the agency's expectations. [5] This guidance emphasizes the importance of a "secure by design" approach, where cybersecurity is integrated into the entire product lifecycle, from conception to postmarket surveillance.

One of the most innovative aspects of the FDA's approach is the concept of a "Predetermined Change Control Plan" (PCCP). A PCCP is a plan that a manufacturer submits to the FDA as part of a premarket submission. It describes the anticipated modifications to an AI/ML device, the methodology for implementing and validating those changes, and an assessment of the benefits and risks of the planned modifications. If the FDA agrees to the PCCP, the manufacturer can make the specified changes without needing to submit a new premarket submission for each modification. [6]

Cybersecurity as a Shared Responsibility

The FDA emphasizes that ensuring the cybersecurity of medical devices is a shared responsibility among all stakeholders, including medical device manufacturers, healthcare delivery organizations (HDOs), and the FDA itself. Manufacturers are expected to build security into their devices, while HDOs are responsible for securing their networks and implementing appropriate safeguards. The FDA plays a crucial role in setting regulatory expectations, providing guidance, and monitoring the postmarket performance of devices.

Recent Developments and Future Outlook

The FDA continues to refine its approach to AI and cybersecurity. In 2025, the agency issued a draft guidance on "Artificial Intelligence-Enabled Device Software Functions: Lifecycle Management and Marketing Submission Recommendations," which provides further clarity on the agency's expectations for AI-enabled devices. [2] The FDA is also actively collaborating with other regulatory bodies and stakeholders to harmonize regulatory approaches and promote best practices.

The agency's commitment to transparency is evident in its publication of a list of AI/ML-enabled medical devices that have been authorized for marketing in the United States. [7] This resource provides valuable insights into the types of AI-powered devices that are currently available and the regulatory pathways they have followed.

Conclusion

The FDA is taking a proactive and risk-based approach to addressing the cybersecurity challenges posed by AI-enabled medical devices. By developing a flexible regulatory framework, issuing clear guidance, and fostering collaboration among stakeholders, the agency is working to ensure that these innovative technologies are both safe and effective. As AI continues to transform the healthcare landscape, the FDA's ongoing efforts will be critical for protecting patient safety and promoting public health.