Impacting Cancer with HPC: Big Data, Bias and Digital Twins

Tuesday, 16 November 2021, 12:15pm - 1:15pm CST

High-performance computing has long been employed in cancer research and clinical applications. Yet recently, with the convergence of AI, large-scale computing and tremendous data assets, the role of HPC in cancer is undergoing a revolution. Borrowing from proven approaches in other HPC fields, the prospects for a personalized cancer patient digital twin, such as those comprising multi-scale integrated biological models are taking off. With implications for future clinical applications and research across the broader medical field, patient digital twins hold huge potential to be globally transformative to HPC and to medicine, as data and bias challenges are overcome.

Session Leaders:

Eric Stahlberg, Frederick National Laboratory for Cancer Research

Jeff Buchsbaum, National Cancer Institute

Patricia Kovatch, Icahn School of Medicine at Mount Sinai

Thomas Steinke, Zuse Institute Berlin