Bindi Brook

Developing multiscale mathematical models to understand asthma and Long Covid.

Multiple biological processes, at different scales in the lung, interact to cause problems in asthmatic patients, e.g., smooth muscle cells that line the airways respond to inhaled allergens by contracting and causing rapid narrowing of the airways, -which makes breathing difficult. Experiments to understand what causes asthma, and how to find a potential cure, require the study of individual processes. I develop mathematical models, based on the underlying biology and physics to combine processes at both cell- and airway-level to simulate and predict what might happen to multiple airways in the lung. Such simulations allow us to explore new therapies.

I was inspired to apply mathematics to biological problems when I was choosing my PhD topic, as it seemed a worthwhile (and potentially useful) research area. Once I started seeing the possibility that applying mathematics to medicine (through my postdoc work on inhaled aerosols in the lung) could make a difference, I just wanted to continue in this field. That very few research groups were specifically modelling asthma using mathematical/computational models meant that I found something of a niche. The same is now true of Long Covid.

In my research, I work closely with clinicians and experimental biologists. Less frequently, I have organised sandpits and study groups as part of the EU VPH-network and more recently my ESPRC-funded NetworkPlus BIOREME. The latter brings together academics with clinicians, industry and charity representatives, and patient groups who are interested in integrating data-driven biophysical models into respiratory medicine. Additionally, I participate in public engagement events such as science festivals (Wonder, Science in the Park, British Science Festival) and schools visits, as well as working with Asthma+Lung UK to organise patient-focus groups, the outcomes of which will inform future grant applications.

Communicating our work to very different groups of people of all ages and from multidisciplinary backgrounds. I also learn a huge amount from them. For instance, for the Long Covid sandpit, we invited a number of different experts (a virologist, cardiologist, respiratory physician, imaging expert, patient advocates) to present their findings. We then split up into groups to discuss how our modelling expertise could be brought together with all their expertise to understand Long Covid. It was both extremely interesting as well as providing a forum for a genuine exchange of ideas from which a new collaborative team has been formed.

While I enjoy communicating our research to different groups of people, it can be challenging to ‘speak the same language’ as the people whomake up those different groups. Even though we may all be scientists, we approach our science quite differently. Therefore, the best approach I've found, is to find or develop creative ways of helping each other understand. Communicating our research to the public has similar challenges, and again the key here has been to make/build demonstrators or develop animation that provide a visual way of understanding underlying concepts.

Simulations of applying breathing like motions to my airway-level models have revealed that it is possible to improve the dilatability of individual virtual airways by selecting an appropriate baseline to apply breathing or deep inspirations. This baseline is associated with how constricted the airway is (due to inhaled allergens) and what inflation pressure is applied. Both these factors affect the non-linear mechanical properties of the airway. The question I would really like to address following on from this is: can one design breathing or singing exercises that improve the dilatability of the whole lung?

If we can use mechanical breathing exercises to improve the dilatability of the whole lung (not just individual airways) then it might be possible to optimise the delivery of inhaled bronchodilators to reach areas of the lung where it is most needed (i.e. in the most constricted parts). This area of research is termed "mechanopharmacology”. In the Long Covid research that I have just started, I would hope that the combination of mathematical modelling together with data will help us understand what causes it, bringing us closer to a therapy (potentially also for post-viral illnesses such as ME/CFS.

An area of research that I haven't yet mentioned is modelling the migration of dendritic cells (immune cells) to sites of the body where they are needed (such as areas of inflammation or injury) in response to inflammatory proteins called chemokines. The processes that underlie the migration of these cells include the diffusion of chemokines, the binding of chemokines to both extra-cellular matrix and dendritic cells, and the consequent cell migration. In my fourth-year teaching module I describe these processes and explain how we can model them mathematically. Many of the problems/exam questions are motivated by such research questions

To have more confidence in my own ideas. To have enough confidence to voice them. You just don't know where they will lead!