Research themes

The Centre's research can be divided into three overlapping themes:

Theme 1 - mathematical underpinning

Traditional approaches for studying dynamical systems focus on the long-term (asymptotic)
behaviour of closed systems with nonlinear feedbacks. By contrast, most clinically collected data
are imperfect observations of transient dynamics in noisy open systems. Moreover, many
physiologically important processes exhibit excitability in that there are large transient responses
to inputs. Thus, to develop mathematical models that are suitable for personalised prediction (in
contrast to merely explaining group population level differences), we must develop new techniques
to address the above challenges. To commence this process, we will focus on analysis of transient
dynamics in spatio-temporal excitable systems; the interaction between network structure and
emergent transients; and techniques for quantifying uncertainty to determine both the validity of the
data for constructing a generative model and the subsequent predictive capacity of that model.

Theme 2 - constructing clinically relevant models

Here we will develop clinically relevant models that build and inform the mathematical knowledge
developed in Theme 1. This forms a critical part of our reiterative cycle: they will provide new
challenges to extend the boundary of our understanding, whilst forming the basis of prototypes
developed in Theme 3. A critical strength of our approach is that we build predictive models of
clinical recordings that are routinely collected. Research will be informed by clinical and
experimental data, provided from our local clinical partners and our clinical co-investigators and
their associated research teams. At present, these clinical data total in excess of 2500 subjects
with diabetes, 500 with epilepsy, 150 with cardiac arrhythmias, 50 with dementia and 20 with
congenital adrenal hyperplasia. These numbers will increase through data collection as part of
other already funded projects.

Theme 3 - prototyping and preclinical discovery

This translational theme and workpackage will deliver:

- prioritisation of areas to be translated from Theme 2 to preclinical discovery and trials.
- data-driven prototyping with project partners in these areas
- development of decision support tools in these areas

Alongside our development of clinically relevant mathematical models in Theme 2, we will also
develop prototype devices and tools using previously collected data. Providing expertise in
scientific computation and data visualisation will provide a natural bridge between Themes 2 and 3;
helping build computationally efficient representations of mathematical models, as well as
designing the software and visualisation capabilities necessary for creation of prototypes. This
process of translation will be further enhanced through our pump-priming fund that will enable
researchers to work directly with clinical scientists and industry. There are some obvious
candidates that emerge from our preliminary work to date.