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 Speaker Profile

M.D., Ph.D., CMO, OpenEvidence

Biography
Dr. Travis Zack is Chief Physician at Open Evidence and an adjunct professor at UCSF with a lab in predictive model development in real-world health data. His research lies at the intersection of computational biology, clinical medicine, and artificial intelligence. Travis received his PhD in Biophysics from Harvard and an MD in the Health Sciences and Technology track at MIT and Harvard Medical School. Dr. Zack has dedicated his career to using data-driven approaches to address pressing challenges in oncology. His lab focuses on developing AI models to support clinical decision-making and enhance patient outcomes, including machine learningbased tools for real-world evidence studies and natural language processing methods to extract valuable insights from electronic health records.


 Session Abstract – PMWC 2026 Silicon Valley

Track 2: AI - March 5 9.00 A.M.-5.00 P.M.


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

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