Speaker Profile
Lilly
Biography
Dr.sc. is a pioneer in AI for human health and coined the term Computational Pathology. His deep-learning systems for whole-slide images helped establish clinical-grade AI in oncology and built petabyte-scale AI infrastructure, enabling faster, more accurate diagnosis and accelerating precision treatment decisions across the globe. His research has advanced the field by linking tissue morphology to molecular drivers and outcomes across massive datasets.
Dr. Fuchs founded Paige AI, a leader in AI-based digital pathology, who received the first breakthrough designation for any AI in oncology and the first FDA approval for an AI in pathology. He previously held influential academic roles, including Dean and endowed Barbara T. Murphy professor for AI & Human Health and Director of the Hasso Plattner Institute for Digital Health at Mount Sinai. As inaugural chair, he founded the first department for AI at a medical school in the US and previously was Director of Computational Pathology at Memorial Sloan Kettering Cancer Center. Trained in machine learning at ETH Zurich, with earlier research at the California Institute of Technology and NASA’s Jet Propulsion Laboratory, he now serves as Eli Lilly’s first Chief Artificial Intelligence Officer, guiding AI across drug discovery, clinical development, manufacturing, finance and commercialization
Session Abstract – PMWC 2026 Silicon Valley
Track Chairs:
William Oh, Yale & David Reese, Amgen
PMWC Award Ceremony
• Nigam Shah, Stanford
Keynote
• David Reese, Amgen
Real-World Evidence & Clinical AI: Closing the Loop Between Data and Care
• Chair: Roxana Daneshjou, Stanford
• Aashima Gupta, Google
• David Sontag, Layer Health
• Brigham Hyde, Atropos Health
• Michael Pfeffer, Stanford
• Thomas Fuchs, Lilly
From Data to Decisions: Building Regulatory-Grade RWE from EHR Systems in Oncology
• Chair: Kate Estep, Flatiron Health
AI and Real-World Evidence: Building a Learning Health System for Precision Care
• Rich Gliklich, OM1
AI for Clinical Decision Support: From Models to Bedside
• Chair: Amrita Basu, UCSF
• Anurang Revri, Stanford
• Emily Alsentzer, Stanford
• Okan Ekinci, Roche
AI for CDS: From Models to Bedside
• Zachary Ziegler, OpenEvidence
Operationalizing AI in Health Systems: Trust, Adoption & Outcomes
• Chair: Danton Samuel Char, Stanford
• Matthew Solomon, Sutter Health
• Karan Singhal, Head of Health, OpenAI
• Sina Bari, iMerit Technology
• Hal Paz, Khosla Ventures
Safe, Scalable AI in Clinical Practice: What’s Working and What’s Not
• Chair: Nigam Shah, Stanford
• David Entwistle, CEO, Stanford Health Care
• Vincent Liu, Kaiser Permanente
AI for Precision Psychiatry: Integrating Multimodal Data Into Clinical Decision Support
• Erwin Estigarribia, HEADLAMP Health
Workflow-First Clinical AI: Integration Patterns, Guardrails & Change Management
• Jorge Duran, Klick Health
From Patient-Generated Data to Regulatory-Grade RWE: Design, Bias & Outcome Linkage
• Greg Bowyer, Evidation
