Thesis Title: Patient-specific tumour growth models to predict the outcome of neoadjuvant chemotherapy in breast cancer patients.
Supervisors: Dr Zeike Taylor, Prof. David Buckley
Tell us a bit about yourself
I’m a final year PhD student in the Fluid Dynamics CDT and the Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB). Before moving to Leeds for my PhD, I studied maths at the University of Glasgow, and grew up between France (hence the name) and Scotland (hence the accent).
What is your research about?
I work on developing mathematical models of tumour growth informed by MRI scans taken throughout the course of the patient’s treatment. We’re trying to predict the outcome of chemotherapy in individual breast cancer patients after only two cycles of chemotherapy, so as to leave time for a change of treatment if the first is expected to be ineffective. Chemotherapy is delivered through the bloodstream and we’re using a model based on the reaction diffusion equation, so although it may not sound like it, it is a fluid dynamics problem.
What did you wish you knew before starting a PhD?
Probably just that things take time, that it’s normal for a piece of code you thought would take an hour to write to actually take four days, and that letting that affect your self-worth is not going to do you any favours.
Also that a PhD is more about learning how to learn things than actually becoming an expert, so you never really get to the point where you feel like you’ve got it all figured out. There’s always some new approach that you should probably consider, which can get frustrating.
What are your plans for the future?
Right now I’m most interested in carrying on my research with a postdoc in the same area. It’s becoming apparent that my PhD will only really scratch the surface, and ultimately I’d like to feel like I’ve made a solid contribution to the field of tumour modelling.