Archives: Agenda

• Understanding the increasing trend of combining medical devices and drugs
• Gaining insights from the European Medicines Agency (EMA) on the future of medical device and drug combinations
• Explaining the distinction between Medical Devices Regulation (MDR) and Medical Devices Directive (MR) for combination products
• Identifying compliance requirements and implications based on the device’s primary mode of action
• Presenting various regulatory pathways available for combination products
• Understanding how partnerships can drive innovation and development in this domain

This session will explore the pivotal role of clinical technology and AI in driving the success of Medtech trials, focusing on how a unified, AI-enabled platform can serve as the foundation for an expanded data health ecosystem. Attendees will learn the benefits of interconnected data flows, starting with purpose-built, simple electronic data capture (EDC) systems for Medtech trials, scaling by integrating Imaging capabilities, leveraging AI for enhanced data analysis, and enabling seamless one-click imports of Electronic Health Records (EHRs). This approach eliminates redundancies, enhances data integrity, reduces site burden, and can bridge clinical trial data with real-world evidence to improve device observation and long-term insights. By adopting an integrated, AI-driven platform, sponsors can meet current trial demands while building a robust data ecosystem to advance future patient care.

• Recognize the importance of choosing a scalable platform to future-proof clinical trials and enable seamless connections between trial data and real-world evidence for long-term impact
• Understand the role of a unified cloud-based platform in creating a connected data health ecosystem tailored to Medtech trials
• Explore how integrating Imaging and EHR data can enhance operational efficiency, data accuracy, and site engagement

• Navigating the evolving regulatory landscape for AI and software as medical devices
• Integrating AI into existing healthcare systems
• Managing the lifecycle of AI products
• Gaining clinical experience by users of AI based SaMDs

Navigating the journey from preclinical studies to market approval is a critical and complex process for medical devices. This presentation outlines a streamlined approach to ensure regulatory compliance, efficient development, and timely market access

• The importance of correct device classification and its impact on regulatory pathways.
• Strategies to define a comprehensive regulatory roadmap tailored to global requirements.
• Key preclinical tests to establish safety and performance baselines
• Insights into aligning preclinical findings with a robust clinical protocol
• Criteria for selecting the right Notified Body to streamline certification
• Best practices for creating a well-structured technical file to facilitate regulatory review

• Strategic insights for the incoming CTP Director
• Experience-based recommendations for improving internal processes
• Recommendations for industry stakeholders on building and sustaining trust through effective communication with CTP

Moderator: Willie McKinney, Ph.D. Founder & CEO, McKinney Regulatory Science Advisors, LLC

Panelists

Dr. Roxana Weil, Chief Regulatory Science Officer, McKinney Specialty Labs

Gabriel Muñiz, Owner & Principal Consultant, QualReg Solutions LLC

Angela Ho-Chen, Managing Counsel – Regulatory, Reynolds American

Melis Coraggio, Consultant, King & Spalding LLP

David Oliveira, Partner, Scrimshaw Strategies

As financial services firms look to integrate AI, questions of sovereignty, specialisation, and ethics have never been more important. Generic, off-the-shelf models struggle with the regulatory, compliance, and risk demands of this industry. This session will explore why sovereign AI, built on domain-specific data, and vertically tailored solutions are critical to ensuring safety, transparency, and trust. We’ll also discuss the role of ethically developed LLMs, like FinLLM, in helping financial institutions embed AI responsibly, avoiding common pitfalls while enabling business teams to capture genuine value.