Speaker Profile
M.D., Professor and Division Head, OHSU
Biography
Dr. Shivaani Kummar is Margaret and Lester DeArmond Chair of Molecular Oncology, Division Chief of Hematology and Medical Oncology, co-Director of the Center of Experimental Therapeutics, and Deputy Director for Clinical and Translational Research, Knight Cancer Institute, Oregon Health Science University, Portland, Oregon, USA. She specializes in conducting pharmacokinetic and pharmacodynamic driven first-in-human trials tailored to make early, informed decisions regarding the suitability of novel molecular agents for further clinical investigation. She is a member of scientific planning committees of national and international professional organizations and has authored over 160 peer reviewed publications, 9 book chapters, and co-edited a book on Novel Designs of Early Phase Trials for Cancer Therapies. She is currently a member of the American Association for Cancer Research Exploratory INDPhase 0 Clinical Trials Task Force, and co-Chair of the Clinical Trials Committee, AACR Annual Meeting 2023-2024.
Talk
AI-powered Multi-omics Platform to Advance Precision Medicine
PATHOMIQ's AI-powered tests analyze cancer diagnostic tissue images to predict treatment response to various cancer treatments. It also identifies specific tissue regions that harbor cancer driver(s). These regions yield known or new targets in each patient for development of personalized therapies and efficacious medicine.
AI and Data Sciences Showcase:
OHSU
PATHOMIQ, a technology company, has developed an AI powered multi-omics platform that can accurately predict cancer treatment response from tissue images. These AI enabled tests can inform treatment decisions for a given patient as well as identify novel targets for drug development.
Session Abstract – PMWC 2025 Silicon Valley
The PMWC 2025 AI Company Showcase will provide a 15-30 minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.
