Speaker Profile
PMWC LUMINARY AWARD
Operationalized real-world data + AI to inform bedside decisions
Ph.D., Professor of Medicine and Chief Data Scientist, Stanford
Biography
Dr. Nigam Shah's research is focused on bringing AI into clinical use, safely, ethically and cost-effectively. He holds an MBBS from Baroda Medical College, India, a PhD from Penn State University and completedpostdoctoral training at Stanford University. Dr. Shah is an inventor oneight patents, has authored over 300 scientific publications, and hasco-founded three companies. Dr. Shah was inducted into the American College of Medical Informatics (A CMI) in 2015 and the American Society for Clinical Investigation (A SCI) in 2016.
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
