What is mathematical oncology?
Mathematical oncology involves using mathematical theories and models to answer questions about cancer. For example, mathematical models can be constructed and applied to predict a patient’s risk of developing cancer, to develop new cancer screening procedures, or to evaluate how a patient may respond to different cancer treatments, enabling clinicians to design more efficient treatment strategies. In addition to improving patient treatment strategies and diagnostic procedures, research into mathematical oncology gives insights into the biological processes and networks in living systems, contributing to our fundamental understanding of biology.
What does a mathematical oncologist do? What does it take to be a mathematical oncologist?
Many mathematical oncologists have PhDs in applied math or computational biology. Sometimes, these scientists will also have a background in biology or the physical sciences (but those aren’t requirements to be a successful mathematical oncologist)! Mathematical oncologists might expect to find jobs in universities, hospitals, or industry (such as biotechnology or pharmaceutical companies).
Where is the field of mathematical oncology heading?
Mathematical oncology as a field has only started to grow within the past decade — and will continue to grow in the future with advancements in technology and computing power. Progress in this field will be accelerated by collaborations between mathematicians, biologists, and doctors, who are working together to build and implement predictive mathematical models into real-life situations with current patients.