Speaker Profile
Ph.D., Director, Cancer Genome Analysis & Professor of Pathology, MGH & Broad Inst.
Biography
Dr. Getz is an internationally acclaimed leader in cancer genomics and is pioneering widely used tools for analyzing cancer genomes. Dr. Getz is a Professor of Pathology at Harvard Medical School. He is the Director of Bioinformatics at the Massachusetts General Hospital (MGH) Cancer Center and Department of Pathology, and is an Institute Member of the Broad Institute of MIT and Harvard, where he directs the Cancer Genome Computational Analysis Group. He has published over 400 papers in prominent journals describing new methodologies to study cancer genomes that have identified new genes and pathways involved in different tumor types, mutational signatures, and tumor evolution.
Session Abstract – PMWC 2027 Silicon Valley
Track Chair:
Victor Velculescu, Johns Hopkins University
PMWC Award Ceremony
• Daniel De Carvalho, University of Toronto
From Mutation to Methylation: The Next Wave of Liquid Biopsy Biomarkers
• Chair: Victor Velculescu, Johns Hopkins University
• Daniel De Carvalho, University of Toronto
• Stephen Master, CHOP/U Penn
• Gordon Sanghera, Oxford Nanopore Technologies
Advancing Minimal Residual Disease Detection Through cfDNA & cfRNA Profiling
• Chair: Luis Diaz, Memorial Sloan Kettering Cancer Center
• Anne-Renee Hartman, Adela
• Minetta Liu, Natera
• Rita Shaknovich, Agilent
• Ajay Gannerkote, Integrated DNA Tech
AI-Informed Biomarker Trials: Turning Early Signals into Actionable Designs
• Chair: Manish Kohli, University of Utah
• Eric Klein, GRAIL
• Sarah Moseley, DELFI Diagnostics
• Samuel Levy, ClearNote Health
Role of AI in Liquid Biopsies & Cancer Detection
• Chair: Amoolya Singh, DELFI Diagnostics
• Ron Andrews, Dxcover
• Pankaj Vats, NVIDIA
• Paul Shi, Amgen
• Christopher Troll, Claret Bioscience
Integrating Genetic Risk with Early Detection: A Precision Prevention Framework for Cardiovascular Disease
• Paolo Di Domenico, Allelica
AI-Driven Metagenomic and Host RNA Profiling for Precision Diagnosis of Infections
• Charles Chiu, UCSF
AI-Driven Host–Pathogen Signatures from Plasma cfDNA: Bridging Infection Biology and Early Diagnostics
• Sivan Bercovici, Karius
Ultra-Sensitive Multimodal Liquid Biopsy for Early Cancer Detection: AI-Driven Signal Profiling
• John Sninsky, CellMax Life
Overcoming Limits of Traditional cfDNA Assays Using Active Chromatin
• Diana Abdueva, Aqtual
Whole-genome methylome-based early cancer signal detection
• Sally Mackenzie, EpiMethyl Analytics
BrainSee Sees the Brain: FDA-Approved AI for Predicting Modifiable Risk of Developing Alzheimer’s Within Five Year
• Padideh Kamali-Zare, Darmiyan
