Cancer can affect different people in markedly different ways
Mathematicians are to develop a virtual model of cancer growth in an effort to predict how it spreads.
Researchers at Dundee University have been given more than £1.5m to come up with a model that can measure the shape and speed of the disease.
The university has long pioneered the use of mathematics as a way of predicting tumour development.
The aim of the project, funded by the European Research Council, will be to aid clinicians with patient diagnosis.
Professor Mark Chaplain, head of mathematics at Dundee, said his team would use cutting edge computational mathematical techniques to develop the model.
He said: "One of the big challenges in addressing cancer treatment is that you can have two patients with the same kind of tumour in the same area of the body, but they will react to it completely differently.
"The factors which contribute to the creation and growth of cancerous cells can all be measured - most biological processes in the human body involve many different but inter-connected phenomena to which mathematical values can be applied."
The modelling approach of the project will be unique in its development of an individual-based model, focussed at the cell level and treating the biomechanical properties of each cell.
Prof Chaplain and his team will collaborate with researchers in life sciences, medicine and physics at Dundee to develop the new models.
He added: "We are uniquely placed in Dundee in having all the relevant expertise needed across the different disciplines to work on this project."
The grant covers five years and will provide seven new posts at the university - three post-doctoral research assistants, three PhD students and one research lecturer.
Cancer is one of the major causes of death in the developed world, with about 11 million people diagnosed and about seven million people dying each year.
The World Health Organisation predicts that current trends show about nine million people will die in 2015, with the number rising to 11.5 million by 2030.