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Modelling lung deposition of inhaled particles in cystic fibrosis

Project Description

Cystic fibrosis (CF) is a genetic disorder that affects the production and clearance of mucus from various organs in the body. In the lungs this causes blockage and thickening of airways, leading to lung damage and early death from respiratory failure. A common method for administering therapies to treat the effects of infection and mucus blockage in CF lung disease involves using aerosols or inhalers. Building on an ongoing lung-modelling program, this project will use mathematical modelling to study the process of particle or droplet deposition at the single airway scale. The primary goal will be to model how changes in the mucus properties associated with CF alter deposition patterns and rates. This will involve working with experts in CF, airway modelling, lung modelling, fluid mechanics and the biophysical and rheological properties of mucus. Results will be incorporated into large scale simulations of flow and transport in the lungs that have been previously developed at Manchester. The aim of the project is to improve treatment protocols by testing dependence on particle size, breathing manoeuvres and aerosol properties. There is also the potential for this work to extend to applications involving the deposition of pathogens to predict infection probabilities in CF lungs. While being based primarily in the Department of Mathematics, the successful student will be able to attend CF clinics to understand the clinical nature of the condition and current therapies and will be expected to work closely with clinical academics. The student will have the opportunity to present their work at clinical, bioengineering and mathematical conferences.

Funding Notes

Please note that this project is competition funded and also open to Self-funding students. If you have the correct qualifications and access to your own funding, either from your home country or your own finances, your application to work with this supervisor will be considered.

How good is research at The University of Manchester in Mathematical Sciences?

FTE Category A staff submitted: 54.40

Research output data provided by the Research Excellence Framework (REF)

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