Day One

• Establishing human-in-the-loop governance models that enable teams to leverage AI efficiently while maintaining accountability for decisions, documentation and product quality
• Defining validation and review processes to ensure AI-generated outputs are accurate, traceable and suitable for use in regulated software development environments
• Demonstrating how AI can improve engineering productivity without compromising compliance, audit readiness or patient safety

• Deploying internal AI agents to support product security and software development activities by streamlining security reviews, improving efficiency and helping teams keep pace with increasingly AI-enabled R&D workflows
• Establishing governance principles that enable AI adoption while maintaining security, compliance and regulatory confidence
• Aligning AI-driven development with evolving FDA expectations and product security requirements to accelerate innovation while maintaining audit readiness, quality standards and stakeholder trust

As the MedTech software development community reunites, this valuable session will ensure you get the chance to reconnect with peers and make brand new connections! This structured networking opportunity will pair you with fellow attendees for several 3-minute introductions, ensuring you have the opportunity to meet and network with your industry colleagues.

• Aligning MDR, AI Act and cybersecurity requirements into a single compliance framework to reduce duplicated effort, improve traceability and streamline software development and documentation activities
• Identifying what requirements genuinely apply to products and use cases to avoid over-compliance, focus resources on high-risk areas and reduce unnecessary regulatory burden
• Preparing products for evolving regulatory expectations across global markets by developing scalable compliance strategies that support market readiness, accelerate submissions and improve interactions with auditors and regulators`

• Understanding the critical differences and overlaps between MDR, AI Act, product cybersecurity and information security requirements to develop a more holistic compliance strategy for AI-enabled and connected medical devices
• Establishing cross-functional approaches to harmonise regulatory, cybersecurity and software development activities and reduce the risk of late-stage compliance issues that delay market access
• Preparing for the next generation of digital health technologies, including AI, synthetic data and digital twins, while ensuring products remain compliant with evolving European regulatory expectations

As AI capabilities rapidly transform software development, MedTech organisations face a critical question: should they accelerate adoption to capture productivity and innovation benefits, or wait for clearer regulatory expectations and governance frameworks to emerge? Join this interactive debate as industry leaders discuss whether moving fast creates a competitive advantage or introduces unacceptable quality, compliance and cybersecurity risks. Drawing on real-world experiences from software, regulatory, quality and cybersecurity teams, this session will explore how organisations can balance innovation with control in an increasingly AI-driven landscape.

Discussion points include:

• Should MedTech companies embrace AI today, or wait for greater regulatory clarity?
• Is moving too slowly on AI creating a bigger business risk than moving too quickly?
• How much validation and governance should be required before AI is deployed?
• Are human-in-the-loop requirements enabling trust or limiting innovation?

• Understanding common PMS and reporting challenges for SaMD by examining why organisations fail to recognise reportable events, struggle with adverse event identification and underutilise post-market data
• Exploring emerging challenges in AI-enabled products, including lessons learned from AI Airlock initiatives, dataset limitations and the implications of deploying AI systems in real-world healthcare environments
• Integrating cybersecurity into PMS frameworks by treating cyber incidents and security breaches as part of ongoing post-market surveillance activities to improve risk management and regulatory compliance

Continue the conversation beyond the presentations as attendees share practical examples, implementation experiences, validation frameworks and lessons learned from across the medical device software lifecycle. Designed to encourage open discussion and experience sharing, this session provides a unique opportunity to ask questions, exchange ideas and discover practical approaches that may not make it into formal presentations. For more information or to share your work, please email info@hansonwade.com

• Sharing real-world lessons learned from bringing innovative products to market including balancing limited resources, evolving regulations and technology adoption while maintaining progress toward commercialisation
• Applying practical cybersecurity and compliance strategies throughout product development to streamline CE marking activities, reduce regulatory hurdles and avoid costly rework for embedded software medical devices
• Leveraging AI to accelerate research and software development while maintaining control over data, security and regulatory obligations

This interactive benchmarking session will enable attendees to anonymously share their experiences, priorities and adoption strategies through a series of live polls and facilitated discussions. Participants will gain real-time insights into how their peers are approaching key software development, AI, regulatory and cybersecurity challenges, uncovering practical ideas, common obstacles and emerging industry trends that aren’t captured in guidance documents or conference presentations.

This session is designed to create a safe environment for honest discussion, allowing attendees to validate their own approaches, identify areas for improvement and learn directly from organisations facing similar challenges.

Some examples of questions (but not limited to) could be:

• How confident are you in your organisation’s ability to validate AI-generated outputs?
• What is one DevOps practice you’ve implemented that significantly improved development speed without creating additional compliance burden?
• How do you balance rapid software updates with customer expectations for stability and reliability?
• Which area – centralised control, security and secrets, logging and monitoring, or change traceability – will demand the greatest attention over the next three years?