Radiotherapy treats cancer through the precise delivery of high doses of radiation to tumours, killing cancerous cells by damaging their DNA. Radiotherapy is highly effective because radiation can be accurately targeted to tumours and avoid normal tissue, preventing the unwanted side effects which would result from killing healthy cells. The introduction of new advanced treatment techniques and better imaging to improve tumour targeting has significantly improved patient outcomes following radiotherapy in recent years. However, while radiotherapy benefits from a high degree of physical personalisation, more can be done to improve treatment outcomes. Cancer is a highly complex disease, and is associated with a large number of different types of mutation. These mutations can significantly affect the radiation sensitivity of a given patient's cancer. Despite this, all patients with cancer in a particular organ are typically treated with the same dose and treatment schedule. While these doses have been tailored to cancer at a population level, this almost certainly under- and over-treats some patients. If individual radiosensitivity can be precisely defined before treatment, significant improvements in outcome could be achieved, in terms of improved tumour control or reduced side effects, depending on the patient's particular genetics. This project seeks to address this challenge by developing models of how cells respond to radiation, which can accurately predict the sensitivity of an individual's disease based on the mutations present in their particular cancer. This work seeks to answer a number of questions, including: 1. How the initial radiation interacts with the cell to cause DNA damage. This will use mathematical modelling techniques from the physical sciences to calculate how energy is deposited in individual cells, and how this causes damage to individual DNA strands. 2. How cells respond to this initial damage. Here, we will model how cells respond to different distributions of DNA damage, including how likely they are to repair this damage, and how likely the cell is to survive following a given radiation exposure. 3. How patient genetics impacts on these responses. While we know the processes which determine how sensitive a cell is to radiation (for example, its ability to repair DNA damage), it is difficult to measure these for each patient. Instead, we will develop methods to predict how effective these processes are based on the genetics of the individual's disease, which can be directly measured before treatment. 4. How clinical treatments can be optimised to incorporate this knowledge. Based on these models, we will then develop a tool which will allow for the best radiotherapy treatment to be designed taking into account both physical and biological personalisation, to maximize the chance that each patient's disease will be successfully treated with minimal side-effects. If successful, this research programme will deliver a unique tool to enable the targeting of radiotherapy using both physical and biological factors, offering more personalised therapy and better treatment outcomes for patients suffering from cancer in the future.