Predicting Effective Individualized Treatment
At Convergence Science Initiative (CSI) – Cancer, founded by Dr. Peter Kuhn, each project is led by a team of patients, medical doctors, scientists and students focused on improving the lives of cancer patients through scientific insights relevant to individual patients.
“Over the next five to 10 years, there’s going to be a big change in the way medical schools and oncologists think about disease.” – Peter Kuhn, Dean’s professor of biological sciences, professor of medicine, biomedical engineering and aerospace and mechanical engineering
For example, by studying cancer progression in many patients over a long period of time, CSI-Cancer researchers have developed a mathematical model to forecast cancer survival rates. The approach uses techniques usually reserved for weather prediction, financial forecasting and surfing the Web to answer questions like:
- Is cancer progression predictable? Is it random? Can we quantify the predictability/randomness?
- How does treatment affect the pathways of progression? How does it affect the speed of progression?
“I could easily see a situation 10 years down the road where a patient comes in with a particularly difficult disease. The oncologists in charge will put together a team of researchers to develop a model to forecast disease progression and determine best treatment options that they would then implement,” Kuhn said.
The center is also looking to better understand how fit individual patients’ fitness for their next course of cancer treatment. Currently patients’ fitness is evaluated in a subjective manner, which can have grave implications – patient-physician disagreement about fitness for treatment is associated with a 16 percent increase in the risk of death. A CSI-Cancer pilot project aims use body sensors and cameras, as well as a cell phone app for patients to report symptoms, to quantify patient fitness and help predict the need for hospitalization or other urgent interventions.
This approach can also make cancer treatment more than just episodic encounters between patients and doctors. “The more than 30,000 minutes between visits are a missed opportunity. Technology can be leveraged to fill this gap and provide a comprehensive picture. The collected data can lead to better treatment decisions, better survival rates, and better understanding between physician and patient,” Kuhn said.