Student
Caroline Purvis

Caroline originally graduated from the University of Cambridge in 2016 with a BA in Physical Natural Sciences (and a strong sense that she really should have just studied maths!)

Caroline originally graduated from the University of Cambridge in 2016 with a BA in Physical Natural Sciences (and a strong sense that she really should have just studied maths!). She completed a Postgraduate Certificate in Mathematics with the Open University whilst working as an editor for an educational publishing company, before returning to full time study, graduating from the University of Birmingham with an MSc in Applied Mathematics in 2021. At Birmingham she particularly enjoyed courses in mathematical biology, and also developed an interest in fluid mechanics, modelling the non-Newtonian dynamics of molten chocolate in the curtain-coating process for her dissertation project.

In general, she enjoys combining techniques from differential equations, applied analysis and numerical simulation to gain insight into real-world systems through mathematical modelling. Most recently, Caroline worked as an analyst in the Civil Service, but missed the challenge and stimulation of academia, and so is excited to be returning to complete her PhD with SAMBa. In her spare time, Caroline enjoys baking, running and playing board games, and is trying to learn to sew her own clothes.

Project title:
Modelling tuberculosis treatment within-host

Supervisor(s):
Ruth Bowness

Project description: 
Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium tuberculosis, which most often affects the lungs. Worldwide, TB is the second leading infectious killer after COVID-19 (above HIV and AIDS). It is a curable disease but treatment, even for drug-susceptible TB, currently lasts at least six months and consists of four or more antibiotics. New treatment protocols are necessary to shorten treatment, reduce the emergence of antibiotic-resistant TB, and improve outcomes.

Mathematical models that describe the within-host dynamics of infection and the effects of treatment can be used to help guide future clinical trial protocols. However, current pharmacokinetic/pharmacokinetic (PK/PD) treatment models are typically deterministic in nature, focused on the short-term effects of individual antibiotics. New and improved ways of modelling TB treatment must be developed in order to more accurately mimic current therapies and guide novel approaches.

During her PhD, Caroline will extend and combine two existing mathematical frameworks that describe TB host-pathogen interactions, namely an agent-based simulation and a continuum PDE model, integrating a novel treatment sub-model into these systems.