Course overview
Keeping up with the rapidly changing regulations applicable to AI-based medical devices takes time and effort. Many AI providers face regulatory, implementation, and investment uncertainties, particularly for advanced use cases like dynamic task specification, grounded reporting, and patient chatbots. Join this course to understand the legislative landscape and best practices, enabling you to shape your use cases and secure a prosperous future for your AI initiatives.
In the second part, participants will delve into the intricate world of the European AI Act and its impact on the medical device domain. They will gain insight into the geopolitical forces and better understand their relation with and impact on other AI legislations worldwide.
The AI Act qualifies many AI systems for medical devices as 'high-risk AI systems', mandating stringent criteria related to human oversight, safety, fundamental rights, robustness, and accessibility before entering the Union market. Our course leader will demystify the European AI Act, shedding light on its complex interplay with existing regulations governing medical devices. Participants will gain insights empowering them to implement the Act, secure their portfolios, and gain a significant competitive edge in the evolving landscape of AI-based medical devices. Cybersecurity is out of scope.
By the end of this course, participants will have gained a deeper understanding of the European AI Act's profound impact on the medical device industry, including its areas of consensus and ongoing debates. They will be equipped with practical insights to navigate the regulatory landscape.
CPD Hours: 12
Course Content
- Day 1
- Introduction to Artificial Intelligence
- Regulation as a Strategy: AI Legislation as a Global Power Play
- Regulatory requirements for AI-enabled medical devices
- Best Practices for Developing AI-enabled Medical Devices
- State-of-the-art data governance and data management
- Day 2
- EU Artificial Intelligence Act
- Implementing the EU Artificial Intelligence Act
- Publicly Funded Supporting Initiatives for the AI Ecosystem
- AI Standardization landscape
- Adaptive AI-based medical devices
Speakers
Koen Cobbaert
Koen Cobbaert works for Philips as a quality, regulatory, and standards expert. Through trade associations COCIR and DITTA, he represents the industry at the European Commission and the IMDRF on matters related to software and artificial intelligence. He also contributes to various standardisation organizations focusing on software and artificial intelligence.
In the legislative domain, Koen chairs COCIR’s and DITTA’s software focus groups, representing its members at respectively the European Commission MDCG workgroups on Borderline and Classification and New Technologies and at the international level at the International Medical Device Regulators Forum (IMDRF) workgroup on artificial intelligence. Koen is also an advisor in the SaMD workgroup at the Global Harmonization Working Party (GHWP). Currently, Koen is engaged in various proposed EU legislation relating to artificial intelligence and data (AI Act, Machinery Regulation, General Product Safety Directive, Data Act, European Health Data Space…). Aside from various publications through trade associations, Koen also edited the book Software as a Medical Device, published through the Regulatory Affairs Professionals Society (RAPS).
In the standardization domain, Koen is a member of CEN-CENELEC’s Industry Advisory Forum, and he is delegated as a Belgian expert to IEC JTC 1 SC 42 on artificial intelligence, CEN-CENELEC JTC21 on artificial intelligence, ISO TC215 JWG7 on health informatics, and to the IEC SC62A Advisory group on Software, Networks, and Artificial Intelligence (SNAIG).
Koen has a Master of Science in electrical engineering and safety risk management. He has over 15 years of hands-on experience establishing regulatory and market-access strategies for medical device software, performing worldwide regulatory submissions, and moderating risk management and clinical evaluation for software applications for general radiology, oncology, neurology, cardiology, orthopaedics, and clinical pathology. He has worked on software applications for pattern recognition, computer-aided detection, reasoning engines, clinical pathways, and other clinical decision support systems, including mobile apps, embedded software, and software operating in the cloud.
