Dec. 16, 2021
Digital twins for cancer patients could be ‘paradigm shift’ for predictive oncology
Jeremy Thomas/LLNL
A multi-institutional team, including an LLNL contributor, has proposed a framework for digital twin models of cancer patients that researchers say would create a “paradigm shift” for predictive oncology. Published online Nature Medicine on November 25, the proposed framework for Cancer Patient Digital Twins (CPDTs) — virtual representations of cancer patients using real-time data — would combine high performance computing modeling and simulation, model inference and clinical data to make treatment predictions and individualized health care decisions for cancer patients. Read more at LLNL News.