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MD Anderson and UT Austin Create Unique Data-Driven Collaboration to Eliminate Cancer Using Novel Mathematical and Computational Approaches

Newswise — The University of Texas MD Anderson Cancer Center and two institutions at The University of Texas at Austin – the Oden Institute for Computational Engineering and Sciences and the Texas Advanced Computing Center (TACC) –  today announced a new initiative to build a strong collaboration in Oncological Data and Computational Science.

The collaboration between the three UT System institutions, based in Houston and Austin, will support the development of teams that bring together MD Anderson’s oncology expertise and data with novel mechanism-based computational modeling techniques led by researchers at Oden Institute and TACC.

“Integrating and learning from the massive amount of largely unstructured data in cancer care and research is a formidable challenge,” said David Jaffray, Ph.D., chief technology and digital officer at MD Anderson. “We need to bring together teams that can place quantitative data in context and inform state-of-the-art computational models of the disease to accelerate progress in our mission to end cancer.”

This collaboration in Oncological Data and Computational Sciences will create an environment for team science through funding of trans-institutional projects in computation and oncology. Overseen by an executive committee of experts from each institution, the collaboration will have shared infrastructure and will co-recruit faculty. Its ongoing success will be contingent on the development of educational programs designed to train a new generation of scientists in data and computational science and oncology.

“We have set out a vision to create a world-leading partnership to accelerate progress against cancer by combining MD Anderson’s substantial effort to digitally-enable its mission with the deep computational modeling capabilities of the teams at the Oden Institute and TACC,” said Karen Willcox, Ph.D., director of the Oden Institute. “Together, the teams will represent one of the largest ecosystems of cancer care and research, expertise in computational modeling, and high-performance computing in the world.” 

The initiative builds upon ongoing collaborations between the Oden Institute’s Center for Computational Oncology, led by Tom Yankeelov, Ph.D., and MD Anderson’s Department of Imaging Physics, led by John Hazle, Ph.D.

“Integrating oncological data with mechanism-based modeling is still a rare approach to cancer research, but these are really hard problems we’re attempting to address so new approaches are essential,” said Dan Stanzione, Ph.D., executive director at TACC. “Since this initiative brings together the best minds, the best tech, and a wealth of high-quality data, we are uniquely positioned to lead in the use of computational models to understand and defeat cancer.”

A request for applications from joint MD Anderson and Oden Institute/TACC teams interested in pursuing research in data-driven computational modelling in oncology was released today with projects and teams to be selected and funded by Sept. 1, 2020.

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Newswise — The University of Texas MD Anderson Cancer Center and two institutions at The University of Texas at Austin – the Oden Institute for Computational Engineering and Sciences and the Texas Advanced Computing Center (TACC) –  today announced a new initiative to build a strong collaboration in Oncological Data and Computational Science.

The collaboration between the three UT System institutions, based in Houston and Austin, will support the development of teams that bring together MD Anderson’s oncology expertise and data with novel mechanism-based computational modeling techniques led by researchers at Oden Institute and TACC.

“Integrating and learning from the massive amount of largely unstructured data in cancer care and research is a formidable challenge,” said David Jaffray, Ph.D., chief technology and digital officer at MD Anderson. “We need to bring together teams that can place quantitative data in context and inform state-of-the-art computational models of the disease to accelerate progress in our mission to end cancer.”

This collaboration in Oncological Data and Computational Sciences will create an environment for team science through funding of trans-institutional projects in computation and oncology. Overseen by an executive committee of experts from each institution, the collaboration will have shared infrastructure and will co-recruit faculty. Its ongoing success will be contingent on the development of educational programs designed to train a new generation of scientists in data and computational science and oncology.

“We have set out a vision to create a world-leading partnership to accelerate progress against cancer by combining MD Anderson’s substantial effort to digitally-enable its mission with the deep computational modeling capabilities of the teams at the Oden Institute and TACC,” said Karen Willcox, Ph.D., director of the Oden Institute. “Together, the teams will represent one of the largest ecosystems of cancer care and research, expertise in computational modeling, and high-performance computing in the world.” 

The initiative builds upon ongoing collaborations between the Oden Institute’s Center for Computational Oncology, led by Tom Yankeelov, Ph.D., and MD Anderson’s Department of Imaging Physics, led by John Hazle, Ph.D.

“Integrating oncological data with mechanism-based modeling is still a rare approach to cancer research, but these are really hard problems we’re attempting to address so new approaches are essential,” said Dan Stanzione, Ph.D., executive director at TACC. “Since this initiative brings together the best minds, the best tech, and a wealth of high-quality data, we are uniquely positioned to lead in the use of computational models to understand and defeat cancer.”

A request for applications from joint MD Anderson and Oden Institute/TACC teams interested in pursuing research in data-driven computational modelling in oncology was released today with projects and teams to be selected and funded by Sept. 1, 2020.

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