CLS Eupnoos studentship

The studentship is available to UK applicants only.

Supervisors: 

• Dr Thomas Ward tom.ward@leicester.ac.uk 
• Dr Neil Greening Neil.greening@leicester.ac.uk 

Additional Supervisors

• Dr Linzy Houchen-Wolloff linzy.houchen@nhs.net
• Dr Jennifer Creese jlc60@leicester.ac.uk

PhD in Infection, Immunity and Inflammation Research

>Project: Digital audio-phenotyping system for preventive screening and early diagnostics of chronic pulmonary disease using a smartphone and recorded breath sound

Project outline: Asthma and COPD are common, yet over 50% of individuals remain undiagnosed, partly due to reliance on spirometry which is challenging to perform correctly in primary care. There is therefore an unmet need for a simple, reliable and easy to perform test to detect asthma and COPD. This project will partner with Eupnoos, a small to medium-sized enterprise (SME) that have developed a smartphone application aimed at detecting obstructive airways disease (asthma and COPD). 

The aim of this studentship would be to collect clinical data from individuals suspected of having airways disease to further refine the Eupnoos diagnostic algorithms and to better understand how the app would be used by patients within the NHS. The project will take a mixed methods approach with appropriate training and support from supervisors.

The PhD would be split into three projects: 

1) Recruit individuals attending for spirometry for suspected airways disease to perform the Eupnoos platform alongside their clinical care. Data from the Eupnoos platform would be compared against spirometry variables and clinical diagnosis. This data would be used in machine learning algorithms to further develop and refine the Eupnoos algorithm, 

2) To perform a qualitative assessment of patient experience using the app and their opinions on clinical usefulness. This would use a mixture of remote measures of app interaction, remote surveys and face to face interviews. Interviews would encompass experience with current diagnostic pathways, the ideal diagnostic test for asthma and/or COPD, acceptability of the app and how an app based diagnostic test would be perceived.

3) To conduct semi structured interviews with healthcare professionals (HCPs) to better understand where the app would fit within the current diagnostic pathways to inform future implementation plans. This would include exploring HCP’s opinion on the diagnostic utility of a smartphone-based app for a range of positive and negative predicted values.