Precision medicine gives cancer run for its money

Samah Khan

Thanks to precision medicine, scientists are advancing in the battle against cancer.

UT computer science professor Chandrajit Bajaj is developing computational techniques, called precision medicine, to more accurately diagnose and treat cancer. Currently, doctors may assign many different drugs over a period of several years before they settle on the correct treatment for each patient. Bajaj predicts precision medicine could perform the same task in a matter of hours at a much lower cost. 

Bajaj could apply his techniques to other diseases as well. Nathan Clement, a computer science graduate student who helps Bajaj, said he hopes that precision medicine will help patients such as his friend Kent, who suffers from epilepsy. 

“There are hundreds of different epilepsy drugs, and each one takes about a year and a half to try out,” Clement said. 

Bajaj and his team are quantifying the body’s molecular interactions to treat cancer and other diseases, such as epilepsy. Using this data, Bajaj can predict the expected binding behaviors of molecules in the body. These behaviors are useful in distinguishing which drug will bind and treat the diseased cells most effectively.

Philips said that because cancer is transmitted through faulty protein structures, modeling each structure could help determine the best therapies for every cancer protein conformation in patients.

“If you can predict every way a protein changes based on any mutation in your genome, that’ll be really helpful to everybody,” Philips said. “Because each cancer is different.”

Precision medicine can also prevent the devastating effects of faulty drug administration, such as the recent case in France that led to six hospitalizations and one death, according to BBC News. By comparing each patient’s genetic sequences to expected models, Bajaj’s programs can find how each patient will respond differently to a single drug before the damage is done.

According to Clement, precision medicine techniques could solve seemingly incurable cases, such his friend Kent’s, in just a week.

“That’s the beautiful thing,” Clement said. “We try to find something that works for you, personally.”

Currently, Bajaj does not have access to real patient data to develop his precision medicine techniques. However, by collaborating with UT’s Dell Medical School in the future, Bajaj will be able to put his precision techniques to the test.

“I liken the battle between precision medicine and cancer to a football game,” Bajaj said. “Before precision medicine, cancer was winning 17 to three. Now, the score is 24 to 17. We are still working, but hope is there.”