Inhalers: Personalised treatments for children to elderly

Background: Respiratory conditions such as asthma or allergies constitute significant personal, social and economic burden affecting millions of patients world-wide, especially in urbanised areas such as London. Pharmacological treatments are readily available and easily applicable to provide instant relief. However, external factors such as growing air pollution lead to more extreme cases where optimal medication delivery would be needed to provide instant pain relief while avoiding over medication and, eventually lower the socio-economic burden.

Project: The project aims at investigating the use of image based and patient-specific computational particle-fluid dynamic (CPFD) models to optimise drug deposition. We have developed statistical shape models and machine learning based tools to rapidly set up patient-specific CPFD models of the lung and the objectives of the project are

  1. implement a suitable set of boundary conditions that mimics breathing,
  2. investigate variation of such boundary conditions with disease
  3. simulate drug deposition for various agents and different boundary conditions.

Impact: If successful, the project will have direct, positive impact on developing personalised treatments, e.g. optimal particle deliver systems for asthma treatments or optimal amounts of active agent.

Other Comments: 

Some programming skills are beneficial.
Multiple projects are possible.

Supervisor name: 
Uwe Wolfram and Ali Ozel
Supervisor and Deputy email addresses:,
Project location: 
Project is computational so that remote supervision is possible
Deputy name: 
Josh Williams