Research Themes
Our network activities are distributed across 4 main themes. These are focused on areas where there is great potential for collaborative and translational research to be transformative to patient health in respiratory medicine. As a network we continue to review our priority areas and welcome engagement from those with interest in our wider network remit, as well as the 4 areas described below.
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Theme 1: Improving treatment delivery and clinical trial design.
Promoting integration of multi-scale models of lung structure function into clincial research and trials. The aim is to further our understanding of lung conditions and ability to predict patient responses to treatment in order to make clinical trials more effective and efficient. Find out more →
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Theme 2: Developing the next generation of clinical lung function measurement.
Supporting research to integrate mechanistic models into clinical lung function measurements and lung imaging. Leading to more sensitive and precise measurement of early-stage lung disease to improve patient outcomes. Find out more →
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Theme 3: Modelling pulmonary mechanics in critical and chronic care.
Connecting research into mathematical modelling of the lung airways, vasculature and mechanics to critical care medicine and mechanical ventilation. This theme also incorporates research around understanding the acute and long term effects of COVID-19 on the lungs. Find out more →
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Theme 4: Modelling environmental determinants of lung health from micro to macro-scale.
Focussing on the development of biophysical models to understand the respiratory health impacts of environmental exposures. Also encouraging the translation of this research into related disciplines, such as epidemiology, toxicology, and public health. Find out more →
Theme 1 - Improving treatment delivery and clinical trial design
Example topics:
The development of multi-scale models that synthesise knowledge of biophysical processes and the sub-cellular, tissue, airway and organ scales.
Coupling pharmacokinetic and biophysical modelling to predict the effects of inhaled drug delivery in obstructed or diseased lungs.
Modelling the link between inflammatory responses, biomechanical properties, and ventilation.
Using multi-scale modelling to predict or interpret patient responses from clinical trials of targeted therapies in respiratory medicine.
Incorporation of multi-scale modelling into the clinical trial design process.
Theme Leads: Prof Salman Siddiqui and Dr Carl Whitfield
Theme 2 - Developing the next generation of clinical lung function measurement.
Example topics:
Integration of modelling and statistical/ML methods with lung measurement technologies.
Using mechanistic models in combination with imaging to further our understanding of lung diseases.
Development of model-based diagnostic outcomes that quantify differences in underlying (patho)physiology.
Integration of patient data streams (such as MBW, Xe-MRI, CT and exhaled breath-sensing) into a 'digital lung twin'.
Mathematical methods to standardise of datasets collected using different devices or protocols via a common modelling framework to enable direct quantitative comparison between studies.
Theme Leads: Prof Peter Robbins and Prof Jim Wild
Theme 3 - Modelling pulmonary mechanics in critical and chronic care.
Example topics:
Mechanistic modelling of coupled ventilation and perfusion in the lung.
Incorporation of COVID-19 lung disease (COVID Acute Respiratory Distress Syndrome — CARDS) datasets in mechanistic models.
Development of methods to improve computational efficiency, uncertainty quantification, and heterogeneity of response.
Modelling the effectiveness and risks of acute CARDS and general ARDS interventions, such as mechanical ventilation.
Data-based modelling of persistent COVID sequelae in the lung (i.e. Long COVID effects).
Developing a mechanistic understanding of respiratory features of Long COVID and other post-viral sequelae.
Theme Leads: Prof Declan Bates and Prof Nick Hill
Theme 4 - Modelling environmental determinants of lung health from micro to macro-scale.
In addition to gas exchange, the lungs play an important role in providing a protective barrier against harmful particles, such as pollutants and pathogens, in the air. The impacts of long-term exposure to air pollution, particularly during childhood, are only now beginning to be estimated with any certainty. Furthermore, the intrinsic link between these exposures and wider societal factors, such as socio-economic deprivation or the environmental changes associated with the Anthropocene, is becoming increasingly clear.
This theme centres on the development of spatio-temporal multiscale mathematical/biophysical models to understand the respiratory health impacts associated with environmental exposure and the translation of this research into related disciplines, such as epidemiology, toxicology, environmental engineering and public health.
Below we have provided examples of research areas that fall within this theme, however this is not an exhaustive list and we would love to hear your suggestions and ideas.
Example topics:
Simulating inhaled particle deposition and fate to e.g. improve quantification of toxicology and/or dose-response for pollutants/pathogens/agonists;
Modelling of immunological pathways to gain new insights into disease mechanisms;
Changes in cell/airway/lung mechanics due to repeated agonist exposure to e.g. understand the link between exposure and lung function changes;
Modelling of reversible and irreversible changes to lung structure and function due to environmental factors;
Models of airway surface liquid and clearance mechanisms that protect the lung from inhaled pollutants and e.g. its implications for exposure risk and toxicology.