Data-Driven Multiscale Modelling of Asthmatic Airways

Inflammation, airway hyperresponsiveness and airway remodelling are key characteristics of asthma, but it is unclear how they are interconnected. A recent comprehensive experimental in vivo asthma mouse study quantifying structural changes and how they relate to the inflammatory state in the airway, has generated an unprecedented amount of data to inform a mechanistic model airway remodelling in asthma [1]. Some parameter sets are well-defined from experimental data but others provide high levels of uncertainty in parameter value and model selection. In this project we will use extensive data from a mouse model of asthma to develop and inform computational biomechanical models of airway tissue combined with regulatory biochemical signalling to establish a mathematical description for the homoeostatic state (ie for healthy airways). This will then allow us to understand how perturbations to this homoeostatic state could drive airways into an asthmatic state, and ultimately to understand which processes are the cause of the disease. This will then be extended to a network model of the branching airways.