UT biomedical engineer establishes computational oncology center

Amanda Kaeni

Meteorologists use computers to predict the weather. Computational oncology, a new approach to cancer research, uses similar methods to predict how someone’s cancer may grow.

Biomedical engineering professor Thomas Yankeelov is establishing a UT center for computational oncology, a collaboration between biomedical engineering researchers, UT’s Institute for Computational Engineering and Sciences and the Livestrong Institute.

Yankeelov said solving numerical weather predications was a major reason for developing computers decades ago. He said this lends itself to predicting cancer growth, although computers have only been used for this purpose for the past ten years.

“(Both of) these problems are very complex,” Yankeelov said.  “(Weather and cancer) are similar in the sense that they have a lot of free parameters. Errors in those parameters lead to large errors in long-term predictions. It’s why weather can’t be predicted more than a week in advance.”

Yankeelov added that it is hard to know exactly how many parameters need to be taken into account when trying to predict cancer growth. He said the lab is currently studying biological parameters at three levels: tissue, cellular and subcellular.

Curing cancer is different than accomplishing other scientific feats because of the lack of understanding of the disease, Yankeelov said.

“We don’t have a sound theory of cancer, and without a sound theory, we’re left with trial and error. … It’s all we have to work with,” Yankeelov said. “This is why we run clinical trials to see what drugs work and what drugs don’t.”

Currently, treating cancer involves looking at a patient’s symptoms and basing a treatment regimen on what worked in clinical trials. However, Yankeelov said that no two patients are the same, so their tumors and cancer are not the same.

“If we had a model that could characterize the important parts of a tumor and was good at predicting how a tumor was going to evolve,” he said. “Then we could go to the computer and try many therapeutic options and see which one prevents progression of the tumor for the longest time.”

Yankeelov’s lab is divided into three groups: one for developing models of tumor growth, one for developing new and improved imaging techniques and one that combines the two for use in clinical trials.

Undeclared sophomore Vic Frederick, who is not part of the research group but previously battled cancer, said that while he doesn’t doubt the effectiveness of his cancer treatment, additional analysis can help save lives.

“Even though there wasn’t any computation involved in my individual case, I can see how it would be extremely beneficial in a broader sense,” Frederick said.

Yankeelov said that this approach will allow doctors to optimally treat cancer. Yankeelov added that while many wouldn’t envision the cure to cancer coming from computers and equations, every branch of science has become more and more mathematized over time. 

“Although biological problems are very complex and have thousands of variables, at the end of the day, cancer has to succumb to the laws of the universe,” Yankeelov said. “There’s a reasonable hope that we could distill this down to a set of equations … on an individual patient basis to make predictions. Without that framework, we are left with trial and error.”