Speaker Profile
Ph.D., Assistant Professor, City of Hope
Biography
Dr. Nath is a cancer biologist with expertise in both experimental andcomputational biology. At City of Hope, Dr. Nath leads a collaborative research team that investigates the potential of A IML in enhancing cancer patient outcomes. Through the integration of bioinformatics and A IML tools, his research aims tounravel the underlying mechanisms of tumor progression and establishcutting-edge biomarkers for improving the clinical outcomes of patientswith cancer. His research employs multi-omics approaches to identify the drivers of tumor evolutionand the subsequent development of drug resistance. Dr. Nath aspires totranslate research findings into clinical impact, notably contributing to upcoming clinical trials in lung and breast cancer that will implement novel AI-guided biomarkers. Dr. Nath currently is aprincipal investigator (PI) of an A RPA-H grant, an NIH U01 grant, a PHASE ONE foundation grant, a JKTG foundation grant, andco-investigator of an A RPA-H and California Institute for Regenerative Medicine (CIRM) grant.
Session Abstract – PMWC 2026 Silicon Valley
Track Chair:
Alex Morgan, Khosla Ventures and Gad Getz, Broad Institute
PMWC Award Ceremony
• Steve Wozniak, Apple
• Greg Brockman, OpenAI
Fireside Chat
• Vinod Khosla, Khosla Ventures
• Greg Brockman, OpenAI
Target Discovery: Beyond Genomics – Revealing Hidden Layers of Biology with AI
• Chair: Cindy Lawley, Olink
• Aritro Nath, City of Hope
• John Quackenbush, Harvard
• Massa Shoura, Phinomics
• Omar Serang, DNAnexus
Foundation Models of Human Cancer Biology to Predict Clinical Outcomes
• Ron Alfa, Noetik
Mechanistic Modeling of the Human Immune System: A Data-Integrated Approach to Target and Biomarker Discovery
• Liat Dassa, CytoReason
Biological Foundation Models: Harmonizing Data to Accelerate Drug Discovery
• Vitalay Fomin, Numenos
From Prediction to Translation: AI and In Vivo Validation to Improve Drug Development Success
• Gabriel Musso, BioSymetrics
Interpretable AI for Biomarker Discovery: Accelerating Drug Development and Advancing Precision Medicine
• Chair: Shivanni Kummar, PATHOMIQ
• Dale Muzzey, Myriad Genetics
• Sanoj Punnen, University of Miami
• Mark Burkard, UI
Can AI Really Create the Next Blockbuster Drug? Closing the Loop from Drug Discovery to Development
• Chair: Amar Das, Guardant Health
• Ari Caroline, Weave Bio
• Dina Katabi, Emerald/MIT
• Andrei Georgescu, Vivodyne
• James Zou, Stanford
Gemini Digital Twins Accelerate Precision Medicine
• Collin Hill, Aitia
Scaling Rare Disease Discovery with AI: From Genomic Data to Therapeutic Insights
• Lisa Gurry, GeneDx
Limited Sample Models for Faster Lead Discovery, High Accuracy, and Regulatory Grade AI
• Lalin Theverapperuma, Expert Intelligence
Enabling Targeted Precision Drug & Gene Delivery with Predictive AI
• Andre Watson, Ligandal
Is AI the New Drug or the New Therapeutic Modality
• Chair: Alex Morgan, Khosla Ventures
• Michael J. Kahana, Nia Therapeutics
• Marc Tessier-Lavigne, Xaira
