The vision for the Center for Computational Oncology (CCO) is to develop biophysical models of tumor initiation, growth, invasion, and metastasis to establish a sound theoretical framework describing the hallmarks of cancer, and to use this knowledge to discover fundamental cancer biology, and develop tumor forecasting methods to optimize treatment and outcomes for the individual patient.
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Directors
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Amy Brock, Caroline De Santiago, David Fuentes, Andrea Gardner, Tyler Jost, Shelli Kesler, Hugo Miniere
The center takes a unique approach to tumor model construction through its application of model inputs constrained by experiments and/or metrics tailored to each individual patient. Constructing individualized, patient-centric models offers several key advantages over conventional, population-derived metrics. Models naturally incorporate patient-to-patient heterogeneity – an approach that enables quantitative, testable predictions of tumor progression on each individual tumor and patient, allowing the model to be refined and/or verified.
News
Feb. 27, 2026
After more than a decade of advances in AI, mathematics and supercomputing, UT is shaping the future of digital twins — bringing together researchers across campus to deploy physics‑informed, AI‑powered models for energy, healthcare, national security and natural hazard mitigation.
News
Dec. 4, 2025
The selected projects apply imaging, computational modeling, and digital twin technologies to improve prediction, treatment planning, and early detection across prostate, head and neck, and liver cancers.
Feature
Oct. 16, 2025
UT Austin researchers, in partnership with MD Anderson and Dell Medical School, are advancing breast cancer care through predictive modeling, protein-based therapies, 3D reconstruction tools, and large-scale data resources. These innovations aim to make treatments more precise, accessible, and patient-centered.