Day Two

• Go through what teams must do to verify, validate, and keep traceability when AI tools help write software
• How to manage tool reliability, version changes, and documentation so AI-generated code remains testable and compliant
• Practical governance, human oversight, and documentation practices that allow safe use of AI while meeting regulatory expectations

• Practical walkthrough of a submission journey including pre-sub meetings, review questions, and lessons learned, followed by discussion
• What regulators expect in modern software and AI submissions
• Structuring documentation for clarity, traceability, and review efficiency
• Managing pre-submission interactions and mid-review information requests
• Lessons learned from successful and delayed software submissions

• Understand how FDA, EU MDR, and the EU AI Act expectations intersect
• Learn where global evidence can be reused versus duplicated
• Explore traceability and UDI expectations for software
• Leave with a more efficient global submission strategy

• Categorizing software as a medical device (SaMD) versus non-medical device functions
• Understanding new regulations in the digital health space, including EU MDR perspective
• Navigating the AI/ML space, including algorithm-only submissions and clearances

• Moderated expert panel with cross-industry perspectives, real-world examples, and audience Q&A focused on practical implementation challenges
• Where automated testing delivers the strongest compliance and risk-reduction value across the software lifecycle
• How leading teams validate automated test frameworks, scripts, and test environments to ensure they are audit-ready
• Practical validation expectations for automated test infrastructure Ideas for scaling test automation without creating regulatory blind spots

• Common root causes behind software-related field actions
• Using post-market signals to improve pre-market design and testing
• Strengthening feedback loops between complaints, risk files, and development
• Organizational practices that reduce repeat quality issues

Practical walkthrough of how a team built quality checkpoints into everyday development followed by peer discussion

• Moving from document-heavy compliance to integrated development checkpoints
• Building quality gates into design, development, and release workflows
• Reducing late-stage remediation through earlier risk and requirements control
• Cultural and tooling shifts required for “living” quality systems

• The gap between algorithm performance and deployable medical products
• Regulatory, usability, and reimbursement barriers that stall innovation
• Lessons from companies that successfully crossed the “last mile”
• What investors, regulators, and customers now expect from software-driven devices