Precision medicine in the home for real-time zero-effort monitoring of health

Digital health technologies using measurements of urinary biomarkers of disease are available for self-administered home testing. Here they can help spot early signs of conditions like cancer, diabetes and heart disease. But they can be daunting to use, especially for older adults. This project develops a zero-effort home platform for testing and explores both technical and non-technical barriers to adoption.


Catalyst R2

Lead Organisation

Imperial College London




Managing Complaints of Ageing

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About the project

Our existing approach to healthcare is reactive and based on limited physiological information, collected months, years or even decades apart. Digital health technologies propose to solve this but often requires individuals to actively administer self-testing. This is a daunting prospect for any individual, particularly for the elderly. We propose to overcome this with the development of a toilet-based precision healthcare platform deployed in the home to measure urinary biomarkers of disease.

It is zero-effort taking samples autonomously without user intervention and can measure biomolecular signatures of health from urine over time. The aim is to take a personalised medicine approach to detecting disease early at the population scale. I lead the Analytical Systems Research group at Imperial College London, miniaturising the technology that is used conventionally to test patient samples in centralised facilities today. We are developing methods to detect urinary biomarkers for cancer, diabetes and heart disease and there is a growing body of literature reporting biomarkers for the early detection of Alzheimer’s disease and dementia.

While the core technology is well-developed, there are significant, largely non-technical, barriers to the adoption of ‘big-tech’ precision health solutions by the general population, which we will explore and investigate strategies to solve as part of this project: we will research the barriers to adoption by users and stakeholders, how the molecular data generated can and should be used, as well as conducting pilot projects focussed on the user interaction and engagement elements of the system.


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