Archives: Agenda

• Examining the “business behind clinical” and how operations leaders can demonstrate ROI, efficiency, and scalability
• Meeting regulatory expectations while supporting commercial growth
• Translating clinical results into business impact: internal KPIs that matter
• Creating adaptable infrastructure for long-term clinical evidence generation

• Exploring options when traditional clinical data requirements cannot be fully met at submission
• Establishing a robust clinical strategy using early dialogue, risk-based justification and post-market commitments
• Leveraging expert panels, NB consultations and scientific advice to de-risk approval pathways

Moderator: Dr. Fatima Bennai-Sanfourche, Senior Director of QA & RA Compliance for Medical Devices and eHealth, Bayer

• Sharing a practical case study on using retrospective clinical data to meet evidence requirements for CE marking
• Demonstrating how to align historical data with current MDR expectations for robust clinical evaluation
• Highlighting lessons learned, common pitfalls, and tips for ensuring Notified Body acceptance

• Future-proof your CERs against class shifts and MDR updates
• Address challenges when intended purpose evolves with technology
• Build defensible clinical arguments for AI-enabled systems

• Understand how notified body reviews differ by organization
• Learn what makes a CER or PMCF study “good enough” in practice
• Avoid overcommitting with evidence plans that are too ambitious

Moderator: Dominic Tong, Senior Analyst, Medical Devices, GlobalData

• Discussion of approaches to release retrained AI algorithms
• Case study for notified body pre-approval to retrain AI algorithms
• Overview of accompanying clinical evidence requirements
• Impact of AI Act implementation

• ISR Market Research results and insights into the State of AI in Clinical Trials
• Opportunities for companies that embrace AI across the Clinical Trial Lifecycle
• Adoption of AI in MedTech for Clinical Product Development