Three New Cancer Projects Receive Funding in Joint Collaboration Between Oden Institute, MD Anderson’s IDSO and TACC

The University of Texas MD Anderson Cancer Center, the Oden Institute for Computational Engineering and Sciences, and the Texas Advanced Computing Center (TACC) at The University of Texas at Austin have announced funding for three cancer research projects under the Joint Center for Computational Oncology (JCCO).

This collaboration advances oncology breakthroughs by combining the Oden Institute’s computational science expertise, MD Anderson’s leadership in clinical oncology and data science, and TACC’s high-performance computing resources.

Since its launch in 2020, JCCO has funded 25 projects. Each new project receives $60,000 in seed funding, split evenly between UT Austin and MD Anderson researchers, along with 12,500 core hours on TACC systems to support large-scale computation.

Tom Yankeelov, director of the Oden Institute’s Center for Computational Oncology, and John Hazle, Ph.D., chair of Imaging Physics at MD Anderson, co-lead the initiative.

“Our pilot project program has two main goals: connecting clinicians with computational scientists to address critical cancer challenges and translating those efforts into clinical applications,” Yankeelov said. “This year’s three selected projects reflect both aims, focusing on new disease settings with practical solutions suitable for clinical use.”

Hazle added, “Collaborations between UT Austin, MD Anderson, and TACC are essential for advancing cancer research. Each project demonstrates the interdisciplinary approach needed to convert computational innovations into tangible patient benefits. These seed funds enable teams to develop and secure further funding to bring innovations to the clinic.”

The 2025–2026 funded research projects are:

Computational Imaging-Based Forecasting of Growth, Dissemination, and Treatment Response in High-Risk Metastatic Prostate Cancer

Led by Thomas J.R. Hughes, Ph.D., professor of aerospace engineering & engineering mechanics and lead of the Computational Mechanics Group at the Oden Institute, and Aradhana Venkatesan, M.D., professor of Abdominal Imaging at MD Anderson, this project aims to develop a computational pipeline to forecast the progression of high-risk metastatic prostate cancer. By integrating imaging with advanced modeling, the project seeks to predict tumor growth and treatment response to guide clinical decision-making.

Biophysical Modeling of Head & Neck Cancer for Dose Adaptive Radiotherapy

Principal investigators Clifton Fuller, M.D., Ph.D., professor of Radiation Oncology at MD Anderson, and David Hormuth, Ph.D., research scientist in the Center for Computational Oncology at the Oden Institute, will generate a validated, perfusion and cellularity-informed dynamic digital twin of radiation response. This approach aims to accelerate the translation of quantitative imaging and digital twin modeling into patient-specific radiation planning, potentially impacting standard care for head and neck cancer treatment.

Lesion Image Forecasting for Early Detection in Liver Cancer

Building on prior JCCO-funded work, George Biros, Ph.D., professor of mechanical engineering and lead of the Parallel Algorithms for Data Analysis and Simulation Group at the Oden Institute, and Suprateek Kundu, Ph.D., associate professor of Biostatistics at MD Anderson, are developing computational models to predict liver tumor growth and spread. This project will generate essential preliminary results to inform physics-based modeling that incorporates mechanistic biological insights. The flexible, interpretable framework applies broadly across cancers, including liver, prostate, and brain, and can be adapted to predict treatment response and clinical outcomes for future studies involving digital twins.