By Dr. Navideh Noori
Interview with Dr Ruth Bowness from the University of St Andrews and editor of SMB newsletter.
Could you tell us about your research background, and how you arrived in your current position?
I completed my PhD in 2011, in the Solar Magnetohydrodynamics group at the University of St Andrews, where I modelled the Solar Corona (the outer atmosphere layer of the Sun) trying to understand the ‘Coronal Heating’ Problem. After this I left St Andrews for a year to teach mathematics at a secondary school in England. However, I missed the stimulation of mathematics research, so re-entered academia in 2012 when I saw a PDRA position advertised in the Medical School at St Andrews on using mathematical modelling to understand tuberculosis (TB) disease. Through this job I finally found the right application for my passion of maths: Mathematical Biology. Using the mathematical modelling techniques that I learnt during my graduate degrees, I have begun to model important biological processes and help to address clinically relevant problems. During my PDRA I learnt a lot about the pathophysiology and immunology of TB and developed a rich inter-disciplinary network of collaborators. This work led to me gaining an independent fellowship from the Medical Research Council in 2017. My fellowship project involves developing an individual-based model (IBM) to simulate pulmonary TB infection within a human host, modelling the bacteria and host immune response as well as modelling treatment regimens through integrated Pharmacokinetic/Pharmacodynamic (PK/PD) models.
What do you like best about your role?
I love the flexibility and freedom of academia. To be able to work on problems that I find important and pique my interest is a privilege. I also enjoy the ability to work part-time, often remotely, and at times that fit around my family life.
Why did you choose your current career path?
The multidisciplinary nature of mathematical biology is one of the reasons why I re-entered academia and chose my current career path. The collaboration with clinicians and biologists inspires new ideas and, when teamed with the use of mathematical techniques, can provide unique and valuable insight into important problems.
What is something exciting that you are currently working on?
Having built PK/PD models into my IBM for standard TB antibiotics, I am currently running computational simulations on treatment adherence, trying to model the effect of missed doses. Treatment adherence is a huge factor in treatment of any disease but can be particularly challenging in TB due to the length of therapy (usually 6 months of combination therapy) and unpleasant side effects. I hope to be able to show the impact of missed doses on ultimate patient outcome.
Where is the best place you have travelled for work? And why?
I visited a PK/PD modelling group headed by Rada Savic in San Fransicso (UCSF) in 2017, which was a great research trip and a beautiful city to visit! I learnt about their pharmacological modelling and began a collaboration to integrate PK/PD models into my IBM.
What is your favorite research paper that you have written?
I’m still very proud of the first research paper that I wrote during my PhD (even if it is in another research field!)
Coronal heating and nanoflares: current sheet formation and heating
Bowness, R., Hood, A. W. & Parnell, C. E. Dec 2013 In : Astronomy & Astrophysics. 560, 14 p., A89
What is your favorite research paper (by another mathematical biologist)?
One of my favourite, fairly recent papers is by Amber Smith:
Quantifying the therapeutic requirements and potential for combination therapy to prevent bacterial coinfection during influenza
Amber M. Smith. April 2017. In: Journal of Pharmacokinetics and Pharmacodynamics. Volume 44, Issue 2, pp 81-93
What is the best piece of advice you have received?
Learn to say “no”!
Finally, what do you do in your spare time?
Spend time with my family: I have three children (ages 5, 3 and 1) so they keep me pretty busy when I’m not working! I also love to run, do yoga and bake when I get the chance.