AI and genetic medicine

Custom genetic medicines hold the promise of bespoke treatments for rare disease. But scaling that approach has been a challenge. Could AI tools unlock a speedier, more effective approach to individualized gene therapies? Join experts working to discuss the opportunities and roadblocks.

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How does AI affect human skills?

AI tools are helping with — and in a few cases, taking over — some of the diagnostic and logistical work that used to fall entirely on human scientists and physicians. While they may boost efficiency, some early data hints that reliance on AI tools can make people worse at performing those tasks. How real is the risk, and how should health systems balance AI productivity with human expertise?

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In conversation with David Baker

Since winning a Nobel Prize in 2024, David Baker has kept pushing the frontier of protein design as the director of the University of Washington's Institute for Protein Design. He returns to AI Day to discuss the progress and challenges ahead in designing proteins from scratch, especially programs that look more and more like therapeutics. We'll explore how that could lead to dramatically different types of medicines.

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Best supporting actor: The role of AI agents in clinical monitoring

Before a CRA makes a decision, they must find the information that supports it—moving between their EDC, CTMS, eTMF, and other systems; reviewing data and outstanding tasks; preparing site communications; and aggregating everything to assess the next best action. But what if much of that work was already done?

This session will share how Clinical Monitoring Agents carry context across the monitoring workflow, connecting the technology and data ecosystem, surfacing targeted risks and recommendations, and accelerating visit preparation and report creation. Explore how CRAs can spend more time engaging with their sites and on the decisions that require their expertise.

Drawing on real implementations within top-10 pharma, you'll see where time is being saved, which parts of the workflow see the greatest impact, and what those efficiencies mean at portfolio scale. It’s a grounded look at where agents are creating value in clinical operations today—not another vision for what AI might deliver someday

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How biologics engineering moves from discovering molecules to building better medicines

Drug discovery funding and approvals are up, but timelines are stretching, cost per approval is rising and success rates remain stubbornly low. What will it take to bring more competitive molecules to the clinic and improve R&D productivity? How can scientists use AI to design for the properties that determine downstream success — not just binding, but developability, manufacturability and stability — before investing years and millions of dollars?

Drawing on Cradle's work with 10 of the top 25 global pharma companies, the conversation covers what successful AI adoption looks like in practice, how to tell whether it is improving R&D outcomes, and the incentives that shape adoption.

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