Computer scientist Danny Hillis and associates at the new National Cancer Institute-funded Physical Sciences Oncology Center at USC are testing a set of interlocking computational models they have developed to describe and predict different aspects of lymphoma: from protein interactions and modifications within cells, through a tumor’s growth and genetic evolution, to the host’s response to the disease and various therapies.

Within five years, the team hopes to have a single, all-embracing model of mouse lymphoma that, by plugging in key parameters — sex, blood pressure, genetic sequences and the like — could predict an individual’s response to various combinations of cancer therapies.

Other physical scientists developing new models include cosmologist Paul Davies of Arizona State University and Paul Newton, a project leader at the new physical sciences oncology center at the Scripps Research Institute, who aims to tackle metastasis as a physicist or engineer would: by breaking it down into simple steps that can each be modelled using equations.