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What to automate? What to keep human? And how to align regulatory, development and clinical in that world that is moving faster than ever.
AI has already revolutionized software development.
Beyond that, advanced teams are now integrating AI deeper across the MedTech product lifecycle including design controls, regulatory approval, qualify management, claims management, etc.
The question is, how far can you reliably push AI integration with current capabilities?
– When to use generic vs specialized AI tools for the MedTech lifecycle
– What can be reliably achieved today vs what should be aimed for in 3 years?
Speed has little value if outputs cannot be trusted or verified.
Effective AI integration requires reliable tools, secure data handling, traceable sources, defined review steps, and clear accountability. The speakers will discuss how they assess AI outputs, prevent unverified content from entering regulated documentation, and determine how to mitigate automation risks.
Regulatory, development, and clinical teams often work from different inputs, timelines and tools, even though their decisions shape the same submission. Effective AI adoption requires shared use cases, consistent inputs and clear responsibilities.
The panel will explore how to align these teams given the added capabilities and relentless speed unlocked by AI.