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 developing image based and patient specific computational fluid dynamic (CFD) models to optimise particle dispersion. A key to that is the rapid availability of patient specific computation domains. Therefore, the objectives are

  1. review the state-of-the-art in statistical shape modelling (a form of machine learning),
  2. develop a statistical shape model for the lung
  3. use the model to provide personalised 3D computational domains based on clinically available X-ray images.
  4. perform personalised particle delivery simulations (if time allows)

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.

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