Join this course to gain a solid understanding of the legislative landscape, enabling you to shape your use cases and secure a prosperous future for your AI initiatives.
It is challenging to keep up with the rapidly changing regulations applicable to AI-based medical devices. Many AI providers face regulatory, implementation, and investment uncertainties, particularly for advanced use cases like dynamic task specification, grounded reporting, and patient chatbots.
This course will also 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 medical device regulations. 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.
By the end of this course, participants will emerge: enlightened about the profound impact of the European AI Act on the medical device industry, including its areas of consensus and ongoing debates, and be equipped with practical insights to navigate the regulatory landscape.
Benefits of attending
- Get up to speed with current regulations and standards on AI-based medical devices and data
- Learn best practices for the development and regulatory submissions of AI-based medical devices
- Understand the interplay between medical devices and AI legislation
- Consider the impact on medical device use cases
- Learn how to convey in plain language how your company can comply with and safeguard its product roadmaps
- Identify the avenues available to mitigate the regulatory and investment uncertainties
Agenda
Regulatory requirements for AI-enabled medical devices
- Overview legislation and guidance specific to AI-based medical devices
- Regulatory initiatives (AU, CA, CN, EU, IMDRF, UK, US…)
- Notified body initiatives
- Future perspectives
- Lessons learned from regulatory submissions of AI-based medical devices
- Describing your application
- Clinical considerations
- Data governance considerations
- Post-market considerations
- Common pitfalls
EU Artificial Intelligence Act
- Introduction to the proposed European AI Act
- Timeline
- Scope
EU artificial intelligence act provider obligations
- Joint Conformity Assessment
- Standards
- Risk Management
- Fundamental Rights
- Data Governance
- Logging
- Transparency
- Human Oversight
- Accuracy and Robustness
- Cybersecurity
- Usability and Accessibility
- Environmental Sustainability
- Document Retention
EU artificial intelligence act
- Deployer obligations
- Notified body obligations
- Authorized representative obligations
- AIA governance
- AIA Timelines - detailed
- AIA implementing measures & standards
- AIA review
- AIA vs MDR/IVDR transition
- Penalties
- How to prepare for the AI Act as a medical device manufacturer?
Adaptive AI-enabled medical devices
- Role of machine-learning enabled medical devices (MLMD) in healthcare
- Learning during clinical use
- Change considerations
- Predetermined change control plan
- Significant changes to adaptive AI-based medical devices
General purpose artificial intelligence
- Compliant conversations: Large language models for medical devices
- Generalist medical AI systems
- GPAI model provider obligations following the EU AI Act
- GPAI models throughout the value chain
- Creating trust
- Finding answers to your challenges
- Regulatory sandboxes
- EU Testing and experimentation facilities
Standardisation landscape
- Overview of standards for AI-based medical devices
- Overview of horizontal standards with their impact on medical devices
- Overview of standards in support of the AI Act
- Trustworthiness framework
- Interplay between horizontal and vertical standardization landscape
Geopolitical considerations of AI landscape
Speakers
Koen Cobbaert,
Philips HealthcareKoen 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 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.
Who Should Attend
- Business strategists
- Product and service managers
- Project managers
- System analysts
- Regulatory Affairs Managers
- Compliance officers
- Legal professionals
- Software Engineers and Architects
- Data Governance Specialists
- Data Scientists
- Biomedical engineers
- Clinical research associates
- Clinical informatics managers of hospitals
- Safety Engineers
- AI Ethicists
