FDA Regulation of Artificial Intelligence/ Machine Learning Software following the 2025 draft Guidance

Overview:

AI/ML is rapidly transforming the landscape of medicine, driving unprecedented changes in how diagnoses are made and treatments are administered. Recent market analyses indicate that the global AI in healthcare market is experiencing significant growth, underscoring the urgent need for regulatory frameworks that can keep pace with innovation. While these advanced systems are already enhancing diagnostic accuracy and operational efficiency in areas like medical imaging and predictive analytics, their dynamic nature poses unique challenges for traditional FDA regulatory models.

Historically, the FDA has regulated medical device software by approving a fixed, validated version of the product. However, AI/ML programs are inherently different as they are designed to learn and evolve after deployment through the integration of real-world data. This evolving characteristic means that the version initially approved may soon become outdated, a scenario that under current regulations would necessitate a new 510(k) submission for each significant update. In today’s rapidly shifting technological environment, such a requirement is impractical and could impede innovation.

In response to these challenges, the FDA released a draft Guidance in January 2025 that sets forth the documentation and procedural requirements for obtaining clearance or approval of ML products. This session will offer a deep dive into the limitations of the existing framework and present a detailed exploration of the new Predetermined Change Control Program (PCCP). By providing insights into ML terminology, the ML development process, and the necessary submission documentation, the webinar will shed light on how the PCCP is poised to manage the continual evolution of AI/ML systems. The discussion reflects not only the regulatory shifts but also the broader momentum in the industry, where stakeholders are increasingly recognizing the need for adaptable oversight that can foster both innovation and patient safety.

Attendees will receive a comprehensive outline and checklist to help navigate the complex regulatory landscape.

Areas covered in the session:

• FDA Discussion Paper on device AI/ML and Action Plan
• Database management
• QC of datasets
• Preliminary Change Control Plan (PCCP)
• Reference standard development
• Standalone performance testing
• Clinical performance testing
• Emphasis on “explainability”
• Cybersecurity

Why should you attend?

Attending this webinar will provide you with a unique opportunity to understand the evolving regulatory landscape that governs AI/ML in healthcare. You'll gain clarity on the complexities of current FDA regulations versus the dynamic requirements of AI/ML systems, ensuring you’re prepared for the challenges and opportunities ahead.

The session offers insights into the new Predetermined Change Control Program (PCCP) and details on essential submission documentation, equipping you with a roadmap to navigate regulatory uncertainties. Moreover, by learning about the latest trends and real-world data shaping the industry, you'll be better positioned to drive innovation while maintaining compliance and patient safety.

Who will benefit?

This webinar is ideal for professionals involved in the development, regulation, and oversight of AI/ML technologies in healthcare. Those who will benefit include:

• Regulatory Affairs Managers
• Medical Device Engineers
• AI/ML Product Developers
• Compliance Officers
• Quality Assurance Specialists
• Clinical Affairs Managers
• Data Scientists
• Healthcare Executives
• Research & Development Teams