Speaker Profile
M.D., Associate Professor and Medical Director of Radiation Oncology Informatics, UCSF
Biography
Julian Hong is a radiation oncologist and informaticist. He specializes in the treatment of genitourinary malignancies such as prostate cancer. His research program focuses on the development and implementation of computational tools to provide personalized, precision cancer care for patients. His group combines clinical domain knowledge with computational expertise to generate insights from real world data, develop actionable artificial intelligence-based tools, and evaluate the benefit of these advances in patient care. He led one of the first randomized controlled studies of machine learning, successfully implementing machine learning-directed clinical evaluations to reduce emergency visits and hospitalizations during cancer radiotherapy.Dr. Hongs research has been published in high-impact, peer-reviewed journals such as the Journal of Clinical Oncology and JAMA Oncology. He has received awards including the Radiation Oncology Institute Publication Award, Bio-IT World Innovative Practices Award, and Symposium on Artificial Intelligence for Learning Health Systems New England Journal of Medicine Travel Award.
Session Abstract – PMWC 2025 Silicon Valley
Track Chair:
- William Oh, Yale Cancer Center
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
Sessions:
- PMWC 2025 Award Ceremony
Pioneer Honoree: Isaac Kohane, Harvard
- Keynote: Can AI succeed where humans have failed to personalize medicine?
- Isaac Kohane, Harvard
- From Data to Decisions: Real-Time Patient Insights for Improved Care (PANEL)
Chair: Michael Pfeffer, Stanford Medicine
- Chris Longhurst, UC San Diego Health
- Tanya Townsend, Stanford Children’s
- Kiran Mysore, Sutter Health
- Cherodeep Goswami, UW Health - AI-Powered RWE: Driving Trustworthy Insights and Innovation through Interoperability (PANEL)
Chair: Charles Jaffe, HL7 International
- Chris Longhurst, UC San Diego Health
- Donald Rucker, 1upHealth
- Stan Huff, Graphite Health
- John Ioannidis, Stanford
- Chris Boone, Oracle
- Accelerating Drug Development with Real World Evidence and AI: Amgen's Journey
- Brian Bradbury, Amgen
- AI-Powered RWE: Accelerating Drug Development and Post-Market Applications (PANEL)
Chair: Erik Reinertsen, Demand Discovery Group
- Michelle Chen, Insilico Medicine
- Jun Jeon, Khosla Ventures
- Dan Riskin, Verantos
- Andrew Trister, Verily - Advancing Patient-Centered Outcomes with AI and Real-World Data Integration
- Phil Johnson, Evidation Health
- Leveraging AI and Real-World Evidence to Transform Patient Care in Oncology
- Amrita Basu, UCSF
- How to Implement AI for Faster Readout of Clinical Trails
Chair:William Oh, Yale
- Jennifer Webster, Pfizer
- Brandon Allgood, Parabilis Medicines
- Julian Hong, UCSF
- Michiel Niesen, nference
