Speaker Profile
Ph.D., Associate Professor, UCSF
Biography
Dr. Basu has over15 years of experience in clinical informatics and bioinformatics, leading initiatives that improve clinical outcomes and support biomarker discovery. Her group develops computational models using machine learning to derive adverse event signatures linked to genotype and phenotype in earlystage high-risk breast cancer. She currently co-leads the electronic Patient-Reported Outcomes Initiative (ePRO) within I-SPY, a neoadjuvant breast cancer clinical trial and is working with other teams to seamlessly integrate PROs into the clinical workflow. She is also a recipient of the White House Presidential Innovation Fellowship (PIF) (2016-2017). Dr. Basu received her Bachelors degree in Electrical Engineering from Cornell University and her PhD from Rockefeller University.
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
