Background


Current research interests


DTC short research projects


Extracurricular interests

Thomas Lewin


Personal photo - Thomas Lewin

Thomas Lewin

Doctoral Student at the

Rex Richards Building, South Parks Road, Oxford OX1 3QU

Background

MMath Mathematics, University of Oxford (2010-2014)

Areas of mathematics that I have studied include:


Current research interests

My DPhil research is focussed on the mathematical modelling of tumour growth and, in particular, the subsequent response to radiotherapy. More specifically, we aim to use modelling in order to better understand how to select radiotherapy treatment protocols down to a patient-specific level through which greater efficacy may be achieved in the clinic. We employ a variety of modelling approaches including the use of ordinary and partial differential equations. The models developed are linked back to clinical and/or experimental data through the use of parameter inference and model selection techniques.


DTC short research projects

Over the Summer of 2015, I completed two 11 week research projects. The first project was entitled 'Characterisation of pathological tumour tissue data by phenomic signatures to enable simulation of the tumour micro-environment' and was undertaken in collaboration with Roche (Penzberg, Germany). My second project involved 'Modelling the response of heterogeneous tumours to fractionated radiotherapy', working in collaboration with Moffitt Cancer Center (Tampa, Florida).

'Characterisation of pathological tumour tissue data by phenomic signatures to enable simulation of the tumour micro-environment', supervised by Anthony Connor1, Prof. Vicente Grau2, Dr Franziska Mech3 and Dr Tom Quaiser3
The interactions between a tumour and its micro-environment have a significant impact on disease progression with the immune cell infiltrate composition in particular significantly imfluencing patient survival. Images of stained histological sections of tumour tissue contain large amounts of data that are not fully utilised. In this project, we worked towards developing an automated image analysis pipeline to extract immune cell infiltration data from such images. Techniques used include a modification of the SLIC superpixel algorithm, alpha shapes, machine learning techniques and rigid image registration methods.

'Modelling the response of heterogeneous tumours to fractionated radiotherapy', supervised by Prof. Helen Byrne1, Dr Heiko Enderling4
Beyond tumour location and stage, very little patient-specific information is used to determine radiotherapy treatment schedules. We considered the use of mathematical models to inform the planning of personalised fractionation protocols in the clinic. We investigated the effect of model choice in using the metric proposed by Prokopiou et al. as a prognostic indicator for radiotherapy response. Preliminary work was also done in developing a simple, spatially-resolved ODE model incorporating radiotherapy.

1 Wolfson Centre for Mathematical Biology (WCMB), Mathematical Institute, Oxford; 2 Institute of Biomedical Engineering (IBME), Oxford; 3 Roche; 4 Moffitt Cancer Center


Extracurricular interests

Triathlon: I am a keen member of the Oxford University Triathlon Club and have competed in both BUCS and Varsity races for the last 3 years, earning a Half Blue in 2015
Other sports: Less competitively, I also like to play golf during the Summer and ski during the Winter
Guitar: In my spare time, I also like to play acoustic guitar