Florida State University Associate Professor Jinfeng Zhang and his graduate student Kaixian Yu aren't your typical cancer researchers.
For one, they're not doctors. They are statisticians. And rather than looking at cancer cells in a lab, they are analyzing numbers representing more than 1,000 breast cancer patients, their genetic markers and their response rates to different cancer treatments.
Zhang and Yu's unique approach has led to the creation of a statistical program that personalizes chemotherapy treatments based on genetics, resulting in more favorable outcomes for each patient.
The program's initial results were so promising that Florida State University's Office of Commercialization awarded Zhang $50,000 through its annual GAP competition, a grant program that is designed to help bridge the gap between a faculty member's research and the commercial sphere for product development.
"I always wanted to do research that had a higher impact," said Zhang, an associate professor in the Department of Statistics. "All the time we hear of relatives or friends dying from cancer."
The initial statistical analysis showed that if the cancer treatments had been tailored to the patient, the response rate would have risen from 21 percent to 39 percent.
And it all came from crunching data.
"Every digit, every single one is a patient," Yu said. "It makes me feel really excited to be working on this. Science can be really exciting. It can help a human life."
According to the American Cancer Society, more than 1.6 million new cancer cases were projected for 2012—final numbers for the year are not yet available—and of those, 22 percent would receive chemotherapy.
But, the response rate of chemotherapy is less than 30 percent.
Cancer treatment is tricky. Chemotherapy, while having many benefits, is extremely toxic and comes with painful side effects. Sometimes, patients are given too much chemotherapy and cannot handle the toxicity.
Zhang said he had spoken with doctors in the area and other researchers at Florida State who acknowledged there was a need to take the large volumes of available data—so called big data—on cancer patients and analyze them to see if there was a way to improve the response rate.
But doctors, though trained to diagnose and treat, are not statisticians. That's where Zhang came in with his plan.
Admittedly, it was not smooth sailing at first.
Originally, Zhang, with the help of Yu, designed a program in May 2013 to examine whether the patients should have received chemotherapy at all. But the results were inconclusive and in August they went back to the drawing board and changed the approach to see if they could improve response rates by matching specific chemotherapy treatments to individual patients.
"You have to have faith that you will discover something," Zhang said.
After they had designed the statistical model, Yu set to work crunching the numbers.
This time, the numbers went their way.
"I pretty much did a dance every time we got a good result," Yu said.
The GAP award will help Zhang collect more data and do additional studies on the potential efficacy of his new system. The money will also help him get the system out into the marketplace so that patients can start benefiting from it.
Zhang said he hopes to do more studies and also look at different types of cancer. This first study focused solely on breast cancer.
For now, Zhang and Yu are logging their results in a paper to be submitted for publication this spring and developing the statistical program so it could be used for other researchers in the future.
Zhang has filed a patent application for his design and also formed a company, Innomedicine LLC, with hopes of marketing the new method, called PERS (Personalized Regimen Selection), to cancer patients around the country.
The research must undergo regulatory requirements before it can be sold to hospitals, so when it will be ready for commercial use is uncertain.