Speaker Profile
PMWC LUMINARY AWARD
Operationalized real-world data + AI to inform bedside decisions
Ph.D., MBBS, Professor of Medicine and Chief Data Scientist, Stanford U.
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 completed postdoctoral training at Stanford University. Dr. Shah is an inventor on eight patents, has authored over 300 scientific publications, and has co-founded three companies. Dr. Shah was inducted into the American College of Medical Informatics (ACMI) in 2015 and the American Society for Clinical Investigation (ASCI) in 2016.
Session Abstract – PMWC 2026 Silicon Valley
Track Co-Chairs:
- William Oh, Yale Cancer Center
- David Reese, Amgen
Patient-centric data, such as Real-World Evidence (RWE) and Real-World Data (RWD), has become critical in reshaping drug development and healthcare decision-making. Over the last few years, regulatory agencies like the FDA and EMA have increasingly embraced RWE/RWD for decision-making processes, influencing everything from new drug indications to post-marketing surveillance. The integration of RWE and RWD is not only supporting clinical trial design and regulatory approvals, but also enabling precision medicine by providing deeper insights into patient subpopulations and their outcomes
PMWC Award Ceremony Honorees
• Nigam Shah, Stanford
Keynote
• David Reese, Amgen
Keynote
• Zachary Ziegler, OpenEvidence
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
• Brian Bradbury, Amgen
From Data to Decisions: Building Regulatory-Grade RWE from EHR Systems in Oncology
• Chair: Kate Estep, Flatiron Health
AI for Clinical Decision Support: From Models to Bedside
• Chair: Amrita Basu, UCSF
• Anurang Revri, Stanford
• Emily Alsentzer, Stanford
• Okan Ekinci, Roche
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
• David Entwistle, CEO, Stanford Health Care
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
