UT researchers will integrate two emerging disciplines — computational oncology and machine learning — to transform the future of cancer care. Machine learning applies algorithms to large data sets to build classifiers that can make accurate predictions, even in complex biological and chemical domains. Computational oncology uses physics-based and data-driven advanced mathematical and computational approaches to model tumors, calibrate patient-specific models, and simulate patient responses to potential treatment options.
Modeling and simulation occur across a spectrum of scales, from the cellular level to the organ level of the human body. The models can be theory-driven, knowledge-driven, or data-driven. Or, increasingly, a combination of all three. Substantial computational skills and capabilities, as well as medical knowledge, are required to capture the individuality of each cancer patient’s situation for accurate decision making at all levels.
“UT Austin has a unique environment that enables the interdisciplinary research critical to tackling societal grand challenges such as personalized care for cancer patients,” said Karen Willcox, Director of the Oden Institute. “We are thrilled to build a new partnership with the Machine Learning Lab, building on the Oden Institute’s strength in computational oncology and our existing partnerships with Dell Med, MD Anderson Cancer Center and the Texas Advanced Computing Center. Computational medicine is a top priority for the Oden Institute and the generosity of the Pandey family is a gamechanger in taking our efforts to a new level.”
The Oden Institute and its Center for Computational Oncology sit at the forefront of developing mechanism-based modeling techniques that optimize treatment and outcomes for an individual patient. The Machine Learning Laboratory is the university’s headquarters for machine learning and artificial intelligence.
“A new wave of machine learning is creating predictive models that are transforming science,” said Adam Klivans, director of the Machine Learning Lab and NSF-funded Institute for Foundations of Machine Learning. “Our technologies can anticipate new biological and chemical interactions to advance the automated discovery of new treatments.”
Currently, cancer biologists and chemists rely on trial and error to determine what treatments will be most effective. Connecting university research with community providers is central to the mission of Dell Med. Through initiatives such as the Livestrong Cancer Institutes, Dell Med translates leading-edge research into high-quality clinical trials and patient-focused precision medicine.
"Time is critical when treating cancer,” said Gail Eckhardt, director of the Livestrong Cancer Institutes at Dell Med. “The Pandeys’ gift brings us that much closer to the day when clinicians and researchers can integrate patient data and computational methods to individualize therapy, thereby improving the lives of patients with cancer.”
“Computational approaches are the key to accelerating progress against cancer,” said David Jaffray, Chief Technology and Digital Officer at The University of Texas MD Anderson Cancer Center. “This investment will further the collaborative, team science approach we have developed with the leadership at UT Austin. Together, we are building a critical mass of talent to use the power of data and computing to make real progress against this terrible disease.”
Read the feature story from Machine Learning Labs to learn more about this partnership.