The team is developing and testing new mathematically optimal approaches to controlling multiple simultaneous cancer treatment strategies, which include chemotherapy, immunotherapy and vaccine therapy.
“We have developed a series of specific mathematical models to address cancer cell division rates and other components,” says Lisette de Pillis, a cancer researcher and mathematics professor at Harvey Mudd College in California. “What is exciting about this work is that we are actually able to go beyond this, as we seek to capture in our mathematical models the complex dynamics of the interactions among cancer cells, our immune system, and medical treatments.”
She says the mathematical tools she and her team are developing will help determine best treatment practices through simulated experiments at no risk to patients. “They can also allow us to customize treatments for individuals,” she says. “The simulations, geometric visualization and treatment optimization tools we have created allow for virtual experiments to be run in a variety of cases.”
For example, de Pillis notes, an important but open question is how best to combine multiple cancer treatments in one patient. “Should we first boost the immune system, and then give toxic chemotherapy, should we give big doses of one treatment and small doses of another and how should we combine such treatments, how long should we wait before re-administering a toxic treatment?”
Through her team’s use of mathematics, she says: “We can gain insight into how to answer some of these questions, since computational experiments testing various cases can be performed quickly, and with no risk to living persons. Additionally, these mathematical and computational tools should even allow us to tailor treatments to individual patients, something that is not commonly done in medicine today.”
MEDICA.de; Source: Academy Communications