Speaker Profile
PMWC PIONEER AWARD
M.D., SVP and Chief AI Officer, 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 Chair:
William Oh, Yale
PMWC Award Ceremony
• Nigam Shah, Stanford
• Thomas Fuchs, Lilly
Keynote: Responsible AI in Healthcare: From RWE to Agentic Systems
• Nigam Shah, Stanford
Keynote: Scaling Trusted AI: From Computational Pathology to Next-Gen Medicines
• Thomas Fuchs, Lilly
Real-World Evidence & Clinical AI: Closing the Loop Between Data and Care
• Chair: Roxana Daneshjou, Stanford
• Aashima Gupta, Google
• Brigham Hyde, Atropos Health
• Michael Pfeffer, Stanford
• Thomas Fuchs, Lilly
From Data to Decisions: Building Regulatory-Grade RWE from EHR Systems in Oncology
• Chair: Nadia Poluhina, Mayo Clinic
• Kate Estep, Flatiron Health
• Alyssa Pybus, Moffitt Cancer Center
• Julie Stein Deutsch, Johns Hopkins
• Jeremy Jones, Mayo Clinic
Predicting Outcomes: An AI Model Trained on RWE 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
Keynote: AI for CDS-From Models to Bedside
• Zachary Ziegler, OpenEvidence
Operationalizing AI in Health Systems: Trust, Adoption & Outcomes
• Chair: Danton Samuel Char, Stanford
• Karan Singhal, OpenAI
• Sina Bari, iMerit Technology
• Shashi Shankar, Novellia
• Hal Paz, Khosla Ventures
• Syed Mohiuddin, Anthropic
Safe, Scalable AI in Clinical Practice: What’s Working and What’s Not
• Chair: Vincent Liu, Kaiser
• Richard Milani, Sutter Health
Transforming Transplant Care Through AI: From Predictive Insights to Precision Decisions
• Jing Huang, CareDx
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 Durand, Klick Health
From Patient-Generated Data to Regulatory-Grade RWE: Design, Bias & Outcome Linkage
• Phil Johnson, Evidation
