Program Overview
This program provides participants with a comprehensive understanding of the evolving regulatory landscape for AI/ML-based medical devices in the US and EU. Delivered by an industry veteran with over 25 years of expertise, the course explores the FDA’s AI/ML Action Plan, EU MDR/IVDR requirements, and the practical challenges of securing approvals for adaptive algorithms. Through real-world case studies, interactive classification exercises, and simulations, participants will learn how to address issues like algorithm transparency, bias, cybersecurity, and lifecycle compliance. The program equips teams with actionable strategies to design regulatory submissions that accelerate approvals while reducing compliance risks.
Features
- Interpret FDA and EU MDR/IVDR frameworks for AI/ML-enabled medical devices.
- Differentiate regulatory approaches for locked vs adaptive AI algorithms.
- Build compliant evidence packages covering clinical, risk, and cybersecurity requirements.
- Anticipate regulatory challenges and design strategies to overcome approval hurdles.
Target audiences
- Regulatory Affairs Professionals
- R&D Teams
- Clinical Affairs and IT/Software Teams
- Quality & Compliance Teams
Curriculum
- 5 Sections
- 20 Lessons
- 1 Day
Expand all sectionsCollapse all sections
- AI/ML in Medical Devices5
- 1.1Regulatory definitions: AI/ML-based SaMD vs traditional software
- 1.2Locked algorithms, adaptive algorithms, Clinical Evaluation, GMLP (Good Machine Learning Practice)
- 1.3US & EU focus: FDA’s AI/ML Action Plan vs EU MDR/IVDR interpretations
- 1.4Explainability, Bias & Transparency & Cybersecurity by Design
- 1.5Adaptive Learning Control Plans & Real-World Evidence (RWE)
- US & EU Regulatory Pathways4
- 2.1US FDA: 510(k), De Novo, PMA routes for AI/ML; Predetermined Change Control Plan (PCCP)
- 2.2EU MDR/IVDR: Device classification, conformity assessments, notified body oversight.
- 2.3Comparative lens: FDA flexibility vs EU rigidity
- 2.4Common challenges: AI bias, validation datasets, lack of harmonised guidance, notified body capacity issues
- Lessons from Market Approvals4
- Interactive Exercises & Simulation3
- 4.1Hands-On Activity: Draft a mini Predetermined Change Control Plan (PCCP) for an adaptive AI model
- 4.2Notified body reviewer challenges an AI algorithm’s bias risk → participants defend compliance strategy
- 4.3Classify hypothetical AI devices (locked vs adaptive) and propose regulatory submission routes (FDA vs EU MDR)
- Wrap-Up & Key Takeaways4
- 5.1AI/ML devices face unique regulatory scrutiny due to adaptive learning
- 5.2US FDA is leading with proactive PCCP frameworks, while EU MDR remains rigid but evolving
- 5.3Early regulatory engagement, robust clinical evaluation, and cybersecurity evidence
- 5.4Adaptive AI needs a lifecycle regulatory strategy, not a one-time approval mindset
Instructor
