Speaker Profile
Ph.D., Professor of Medicine, Stanford
Biography
Christina Curtis, PhD, MSc is the RZ Cao Professor of Medicine, Genetics, and Biomedical Data Science, Senior Vice Chair of Research in the Department of Medicine and Director of AI and Cancer Genomics at Stanford School of Medicine. Dr. Curtis's laboratory leverages computational modeling, high-throughput molecular profiling and experimentation to develop new ways to diagnose, treat and prevent cancer. Her research has redefined the molecular map of breast cancer and led to new paradigms in understanding the origins of human cancers, as well as how they evolve and metastasize.
Dr. Curtis's accomplishments have been recognized by numerous awards, including the 2018 National Institutes of Health (NIH) Director's Pioneer Award, the 2022 American Association for Cancer Research (AACR) Award for Outstanding Achievement in Basic Science, the 2024 Brinker Award for Scientific Distinction in breast cancer research and 2024 AACR - Breast Cancer Research Foundation (BCRF) Award for Outstanding Achievement in Breast Cancer Research, as well as the 2025 European Society for Molecular Oncology (ESMO) Translational Award and the Paul Marks Prize for Cancer Research. She is a Susan G. Komen Scholar, a Chan Zuckerberg Biohub Investigator, and a Fellow of the American Association for Cancer Research (FAACR).
In addition to her research, Dr. Curtis is an influential voice in the scientific, clinical and biopharma communities. She is an advisor to multiple academic institutes, as well as to biopharma and biotech. She has served on the editorial boards of journals, spanning computational biology to precision oncology, including Science, Cancer Discovery and Molecular Cancer Research. Dr. Curtis was a member of the AACR Board of Directors and is the chair of the AACR Data Science Task Force. She is also active within several clinical trial and cooperative groups, including the Alliance for Clinical Trials in Oncology, and American College of Radiology Imaging Network (ECOG/ACRIN), where she leads translational bioinformatics.
Session Abstract – PMWC 2026 Silicon Valley
Track Chair:
Victor Velculescu, Johns Hopkins University
PMWC Award Ceremony
• Klaus Pantel, University Medical Center Hamburg-Eppendorf / ELBS
• Daniel De Carvalho, University of Toronto
Keynote: Early Detection of Cancer by Multimodal Liquid Biopsy Analysis
• Klaus Pantel, UKE / ELBS
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
• Manel Esteller, Sant Pau Research Institute
• 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
• Klaus Pantel, UKE / ELBS
• Rita Shaknovich, Agilent
• Ajay Gannerkote, Integrated DNA Tech
AI-Informed Biomarker Trials: Turning Early Signals into Actionable Designs
• Chair: Manish Kohli, University of Utah
• Luis Diaz, MSKCC
• Eric Klein, GRAIL
• Peter Bach, DELFI Diagnostics
• Anne Docimo, UnitedHealthcare
• Samuel Levy, ClearNote Health
Role of AI in Liquid Biopsies & Cancer Detection
• Chair: Amoolya Singh, DELFI Diagnostics
• Ron Andrews, Dxcover
• Pankaj Vats, NVIDIA
Fragmentomics for Early Detection: End Motifs and Library Prep
• Christopher Troll, Claret Bioscience
Integrating Genetic Risk with Early Detection: A Precision Prevention Framework for Cardiovascular Disease
• Giordano Botta, Allelica
Metagenomic Diagnostics & Global Pathogen Surveillance
• 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
AI-Enhanced Proteomic Signatures for Early Cancer Detection
• Diana Abdueva, Aqtual
• Sally Mackenzie, EpiMethyl Analytics
