Mathematical models for preclinical drug trials: small molecule drugs and antibody drug conjugates

Preclinical evaluation of drug efficacy plays a fundamental role in the development of cancer treatments. Mathematical modelling is fundamental to these preclinical studies, specifically to describe the tumour dynamics and evaluate the anti-tumour effect. This project is co-funded by GSK and will develop advanced models of tumour growth based on mechanistic principles for pre-clinical drug trials. The models will incorporate spatial resolution integrated with PKPD dynamics focusing on developing models that are fit-for-purpose in an industrial context. Challenges will include designing optimal dosing protocols and incorporating new treatments, including antibody drug conjugates, for which spatially resolved modelling is particularly important. Ultimately the aim is to improve drug translation from pre-clinical to clinical studies.

The proposed project is part of an ongoing research collaboration between Dr Carina Dunlop (University of Surrey) and Prof. Gianne Derks (University of Leiden, Netherlands) with Dr James Yates and Dr Adam Nasim (GSK) and the student will need to work collaboratively and across discipline boundaries. The project will include working with diffusion models (partial differential equations) and dynamical systems and their numerical solutions. There will also be a need to engage in mathematical modelling and with biological detail. Importantly models will be tested and validated against current best practice and pre-clinical data.

Open to any UK or international candidates. You will need to meet the minimum entry requirements for our PhD programme.

We are looking for students with a degree in a quantitative discipline e.g. Mathematics, Physics, or a related Engineering degree. Preferably applicants will hold a MMath, MPhys, MEng or MSc degree. For further details or to discuss the project further please contact Dr Carina Dunlop (c.dunlop@surrey.ac.uk).