Cancer patients of the future could benefit from personalised treatment plans based on mathematical and computer models.
The £1.2m project, led by the University of Stirling, will explore a tailored approach to cancer care that takes into consideration how cancer affects individuals differently.
L-R Matthew Hubbard, Carron Shankland, Ronald Lambert, Karen Polizzi and Fred Currell.
Dr Carron Shankland, Deputy Head of the School of Natural Sciences, said: 'Cancer is one of the top two healthcare challenges: current trends suggest 1 in 3 people will have cancer in their lifetime. While many advances have been made in cancer treatment, there are still ways in which therapy can be improved. For example, cancer is usually treated by combinations of surgery, radiotherapy, and/or chemotherapy, but the precise interaction of these treatments and the ways in which different people react to them is poorly understood. This makes it incredibly challenging to prescribe the best therapeutic strategy for an individual patient.'
The three and a half year project brings together expertise in biology, computer science, mathematics and physics to tackle this important problem.
Dr Shankland, explained: 'Our project will explore a more personalised approach to treatment. For example, in each person the progress of the disease is different: the tumour grows in different ways, in different shapes, at different speeds. In addition, each person responds in a different way to treatments of radiotherapy, and/or chemotherapy. How do these features interact to influence the progress of the disease? Over the next few years we aim to develop a set of fast, accurate and reliable mathematical and computer models which can be used to predict these interactions and thus help doctors recommend treatment plans.'
The project is funded by the Engineering and Physical Sciences Research Council and will see Stirling partner with academics at Cranfield University (Dr Ronald Lambert, Cranfield Health), Imperial College London (Dr Karen Polizzi, Centre for Synthetic Biology), Queen’s University Belfast (Dr Fred Currell, School of Mathematics and Physics) and the University of Leeds (Dr Matthew Hubbard, School of Computing).