Many medical procedures, including diagnostic (X-ray) imaging used to aid in the diagnosis of disease and radiotherapy for cancer treatment, involve the use of high energy ionising radiation. There is much to be gained from the knowledge of how that radiation is formed, interacts with devices and tissues, and deposits energy along its path. These are very complex processes that can only be accurately modelled using Monte Carlo (MC) procedures. MC uses random sampling to mimic the actual physical process of radiation transport. It is computationally intensive though yields enormous quantities of information. The use of a supercomputing facility will be used to speed up MC simulations being undertaken to understand why radiation detectors used in radiotherapy respond in the way they do, and to help in the design and testing of new detectors. These will be used to ensure the quality and safety of patients radiotherapy treatments.