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Podcast

Artificial Intelligence and Machine Learning Based Software as a Medical Device

0 h 37 min

In our first episode, host Erika Porcelli is joined by Lisa Michels, General Counsel and Regulatory Affairs Expert at Regulatory Compliance Associates (RCA), to examine the FDA’s proposed regulatory framework for modifications to artificial intelligence and machine learning (AI/ML)-based software as a medical device. This episode dives into the FDA discussion paper, shedding light on what AI/ML software are, how they function within medical devices, and the unique regulatory challenges they present.

Erika and Lisa explore the intricacies of AI/ML software, explaining how these technologies operate and the benefits they bring to medical devices. However, the ability of AI/ML software to adapt and change over time introduces potential risk factors that have prompted the FDA to consider a new regulatory approach. The discussion delves into these risks and the rationale behind the FDA’s proposal for a total product lifecycle (TPLC) approach to regulate AI/ML-based devices more effectively.

The episode highlights the key elements of the FDA’s proposed framework, emphasizing the importance of continuous monitoring and evaluation throughout the product’s lifecycle. This approach aims to ensure that AI/ML software maintains its safety and effectiveness as it evolves. Lisa shares insights into the FDA’s call for industry feedback, encouraging stakeholders to contribute their perspectives on the proposed regulatory changes.

Listeners will gain a comprehensive understanding of the FDA’s vision for regulating AI/ML-based medical devices and the implications for manufacturers and developers. This episode is essential for those involved in the development, regulation, and deployment of AI/ML technologies in the medical device industry.

Join us to explore the future of AI/ML in medical devices and understand the regulatory landscape that will shape its development.

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