Multi scale mathematical modelling of cancer growth, spread and treatment

Mark Chaplain (University of St Andrews, UK)

Abstract:
Cancer is one of the major causes of death in the world, particularly the developed world, with around 11 million people diagnosed and around 7 million people dying each year. The World Health Organisation predicts that current trends show around 9 million will die in 2015, with the number rising to 11.5 million in 2030. There are few individuals who have not been touched either directly or indirectly by cancer. While treatment for cancer is continually improving, "alternative approaches" can offer even greater insight into the complexity of the disease and its treatment. Biomedical scientists and clinicians are recognising the need to integrate data across a range of spatial and temporal scales (from genes to tissues) in order to fully understand cancer. In this respect, there are three natural, key scales linked to each other which, when considered together, go to make up understanding the complex phenomenom that is cancer: the sub-cellular scale, the cellular scale and the tissue scale itself.

Using techniques from modern applied mathematics and computational science, in the last few years novel multi-scale mathematical models have been developed which are now beginning to describe in more detail complex biomedical systems such as wound healing, cancer growth and spread, embryonic development, heart physiology, drug delivery and tissue engineering. This talk will give an overview of some multiscale mathematical models that have been developed to predict the growth and spread of cancer and to optimise patient therapy such as chemotherapy and radiotherapy.


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