Non-invasive real-time modelling of biophysical and metabolic changes in airways disease

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Sampling breath can uncover vast quantities of information about the underlying metabolic state of the body occurring in an individual in real-time. Tools to measure breath metabolites therefore have the potential for monitoring of a wide range of airways diseases. Despite increasingly large-scale studies being conducted in the last ten years, a clinically relevant breath test based on exhaled volatile organic compounds VOCs) test has yet to be validated. One reason for this is the number of confounding factors that must be accounted for during breath collection which makes reproducing published results difficult. Recent work on breath holding, oral versus nasal breathing (Sukul et al. 2014, 2017) and time of day (Wilkinson et al. 2019) has highlighted the need for standardised sampling protocols. Fractional exhaled nitric oxide (FeNO) levels, which are routinely used in asthma diagnosis and monitoring, are highly affected by these physiological parameters and it is therefore likely that the level of breath VOCs is similarly impacted. This combination of complex biological and physiological factors makes it difficult to interpret measurements or to develop analysis techniques that account for these factors. Therefore, this project will use a combination of controlled experiments with human volunteers and patients with airway disease (e.g. asthma) at the North West Lung Centre (Manchester University Hospitals) as well computational modelling of the lung to create new sampling protocols and analysis tools. This will build upon similar approaches that have been used previously to account for flow-rate and diffusion on FeNO measurement in the breath (Conderelli et al. 2007) or multiple breath washout measurements (Whitfield et al. 2022).The student will collaborate with our industry partner Imspex Diagnostic Ltd. to measure exhaled breath online using ion mobility spectrometry and mass spectrometry. The student will then build on sampling expertise within the group to assess the impact of changes in lung physiology on exhaled metabolites and investigate the short- and long-term variation observed in an individual's breath profile. These results will contribute to the optimisation of an existing lung function model that uniquely incorporates realistic rendering of lung physiology and gas washout in order to determine the factors governing exhaled VOC concentrations in health and disease.Although not essential, it would be advantageous for the prospective