Healthcare technologies projects

EPSRC has announced 20 healthcare technologies projects, funded with an investment of £30.8 million. Four projects were co-funded with the Medical Research Council (MRC).

The projects include:

  • Two EPSRC programme grants – Terabotics and Beyond Antibiotics – funded with a £14.5 million investment
  • Four projects funded by EPSRC and MRC through sandpit grants for novel digital technologies for improved self-monitoring and health management, with an investment of £1.6 million
  • Seven Healthcare Impact Partnerships funded with a £7 million EPSRC investment. This call supports novel mathematical, engineering, ICT and physical sciences research that is aligned to the Healthcare Technologies theme strategy and contributes to at least one of the Healthcare Technologies Grand Challenges
  • Seven NetworkPlus grants funded with a £5.7 million investment. The grants aim to support research communities that address our priorities for transforming healthcare including:
    • technologies to improve healthcare treatment;
    • affordable and inclusive healthcare solutions
    • healthier environments
    • new digital healthcare systems.

Programme grants

Beyond Antibiotics

Led by: Professor Eleanor Stride, University of Oxford

EPSRC support: £6.5 million

Antibiotic resistance has been identified by the World Health Organization as one of the greatest global threats, with the evolution of drug-resistant bacteria and lack of alternatives meaning we may not have viable treatments for even trivial infections within the next three decades.

The £6.5 million Beyond Antibiotics project led by Professor Eleanor Stride at the University of Oxford aims to develop alternatives to prevent this scenario from occurring.

They include developing ‘drug-free’ methods for treating infections and improving our immune function, as well as using antimicrobial therapeutics and targeted delivery techniques to improve the use of existing antibiotics and provide viable alternatives.


Led by: Professor Emma MacPherson, University of Warwick
EPSRC support: £8 million

The project aims to develop robotic sensors which can be used to detect cancerous bowel tumours in situ.

Bowel cancer is the fourth most common cancer and second most common cause of cancer death, and the project aims to significantly speed up the process of diagnosing and removing tumours.

The probes will use low-energy, harmless TeraHertz imaging and could be used for colonoscopies or on top of the skin, allowing for diagnosis in situ without having to wait for biopsy results.

Sandpit grants

Co-funded by the Medical Research Council (MRC). All £400,000.

Digital Health: On-organ Sensing For Bowel Monitoring - A Bottom Up Approach

Led by: Dr Michael Crichton, Heriot-Watt University

Researchers aim to develop a bowel sensor that could alert people when they need to go to the toilet through a smart phone app.

This could be used to help the estimated 1.5% of the UK population who suffer from faecal incontinence, allowing them to manage the condition and lead more active, confident lives.

These discreet digital sensors would sit in the large intestine and track the movement of stools, acting as an early warning system.

The project also involves researchers at The University of Manchester, University of Stirling, Sheffield Hallam University and The Glasgow School of Art.

HappierFeet - Disrupting the vicious cycle of healthcare decline in Diabetic Foot Ulceration through active prevention: The future of self-managed care

Led by: Dr Andrew Weightman, The University of Manchester

Diabetic foot ulcers affect a quarter of people with diabetes, costing the NHS £1 billion annually. A team led by Dr Andrew Weightman at The University of Manchester aims to address the issue by co-designing, with patients, the self-managed use of smart shoe insoles. These are intended to identify early signs of ulceration through the use of pressure, temperature, inertial measurement units and acoustic sensors. Using actuators that convert energy into movement, they will adjust the way people walk to support safe and comfortable movement. This will encourage people prone to diabetic foot ulcers to be more active while managing their conditions securely. Dr Weightman will collaborate with Andrew Eccles (The University of Strathclyde), Dr Katherine Bradbury (The University of Southampton), Prof Helen Dawes (Oxford Brookes University) and Dr Safak Dogan (Loughborough University) on the project. This multidisciplinary approach to developing a digital healthcare solution is supported by a £400,000 grant through the research sandpits call funded by EPSRC and MRC.

Digital Health: OptiMuscle - Improving health outcomes through the optimization of muscle function

Led by: Dr S Preece, University of Salford

Approximately 10% of people in the UK have a condition that impairs the muscles they use to breathe – otherwise known as dysfunctional breathing.

This project will use both visual and auditory biofeedback in the form of digital avatars that visualise the actions of the breathing muscle in real-time to guide patients through a process in which they gradually learn to correct their muscular breathing control.

Researchers will develop these new therapies by working closely with patients to understand their views on how the final system should operate.

Once created, they will carry out a small trial on people with dysfunctional breathing to understand the future potential with the aim of holding a larger NHS trial if results are encouraging.

Digital Health: Innovative engineering technologies to improve the understanding and management of fatigue

Led by: Dr R Adam, University of Aberdeen

This project will investigate sensory technologies to objectively, accurately and unobtrusively measure fatiguability, as an indicator of fatigue.

They will then correlate this with other data, including activity levels and heart rate, to obtain granular details about fatigue patterns in humans and reveal whether there could be distinct, clinically relevant fatigue phenotypes.

The researchers will use artificial intelligence algorithms to analyse the correlations, overcoming previous issues longitudinal studies in this area have faced.

Healthcare Impact Partnerships

Led by: Professor Ryan Donnelly, Queen’s University Belfast

EPSRC support: £1.2m

The researchers aim to develop a new type of transdermal patch that bypasses the skin's barrier layer using many tiny needles that cause no pain.

These needles then either dissolve quickly, leaving tiny holes through which medicines can enter the body, or swell, turning into a jelly-like material that keeps the holes open and allows continuous drug delivery.

This could potentially revolutionise the delivery of peptides, proteins, and long-acting small molecules that cannot currently be delivered across the skin. 

The swellable microneedles can extract fluid from the skin, allowing researchers to monitor the levels of medicines and markers of disease without taking blood samples.

Led by: Professor Rainer Cramer, University of Reading

EPSRC support: £890,000

This project aims to substantially advance Matrix-Assisted Laser Desorption/Ionisation (MALDI) mass spectrometry (MS) profiling of organisms.

The researchers aim to achieve this by exploiting multiply-charged ions and their co-analysis with lipids and other biomolecules on an MS/MS instrument specifically optimised for large-scale, inexpensive clinical analyses.

This will lead to the next generation of superior MALDI MS biotyping for clinical use and mass testing.

The proposed new instrument and the associated technology will be high speed, cost-effective, and allow high specificity by MS/MS sequencing.

It would allow multiple diseases to be tested in one test run and will be highly adaptable to new diseases.

This will negate the need to develop test reagents that are disease or microbe-specific, difficult to source and therefore expensive - in particular for newly discovered diseases like COVID-19.

The aim is to reach a throughput level of 100,000 samples per day at high detection accuracy and low cost per sample.

Led by: Dr Yuhang Chen, Heriot-Watt University

EPSRC support: £1.2million

When carrying out keyhole cancer surgery, the current resection margin to ensure tumour excision without unnecessary tissue removal is identified using a combination of the surgeon's experience, images taken prior to the operation coupled with any visual observations, and the tactile 'feel' during the operation.

It is only post-surgery histopathological tissue analysis that confirms whether the resection margin was correct.

The development of minimally invasive techniques has removed surgical 'feel' for tissue characteristics, including assessment of surgical margin.

This highlights an unmet clinical need for a quantitative, robust, reliable and evidence-based method of determining the optimal surgical margin and providing feedback to the surgeon in a way that it can be used to make decisions during the operation.

Led by: Professor Goran Nenadic, The University of Manchester

EPSRC support: £750,000

This project will use Natural Language Processing (NLP) and text mining to unlock information stored in outpatient letters and link it with other health data.

Researchers aim to develop new methods to extract key clinical events from letters and represent their details in a computerised form so they can be easily accessed. In doing so, they will ensure the information in the outpatient letters can be linked to other hospital databases while ensuring data protection.

Researchers will demonstrate the potential impact of the new system through two case studies with clinical and business partners.

The first case study will demonstrate how the proposed models can assist in timely, efficient, dynamic and transparent identification of patients for shielding in a pandemic, or for vaccination prioritisation.

The second case study will illustrate how the same information can be used address important gaps in our knowledge about health and care, including disease prevalence and drug utilisation patterns.

All outputs will be developed in a way that can be scaled beyond the single clinical site and single speciality.

Led by: Professor Steven Freear, University of Leeds

EPSRC support: £1.1 million

This project aims to improve on Computed Tomography Coronary Angiography (CTCA), the method used to image the detailed anatomy of the left main coronary artery, with new technology that is non-ionising and available at point of care.

The proposed technology would provide important prognostic information for heart disease patients, offering instant feedback without the downsides of purpose-built CTCA suites.

In addition, this project will address the imaging challenges present in conventional ultrasound using a state-of-the-art, high channel count system incorporating motion locked, automatic transmit adaptation enabled through deep learning.

The techniques developed will enable clinically relevant images to be obtained at the bedside, whilst reducing the level of expertise required, inter-observer variability, and additional testing.

Led by: Professor Matthew Brookes, University of Nottingham

EPSRC support: £900,000

The project aims to develop a helmet-like device which can be worn by children to measure electrical brain activity non-invasively. Partnering with UCL, the team will then use this device to study brain activity in infants with epilepsy. This new type of brain scanner, which employs quantum enabled sensors to measure magnetic fields above the scalp (a process termed magnetoencepaholography (MEG) could help to pinpoint the source of epileptic seizures in the brain, offering new information which will be extremely useful to neurosurgeons.

Led by: Professor Thomas Krauss, University of York

EPSRC support: £950,000

Researchers will work in partnership with clinicians at York and Leeds, industry partners and patient groups to create a new way to monitor the treatment of immunosuppressed patients. These include people with rheumatoid arthritis, which afflicts about 400,000 people in the UK.

The technology uses a photonic sensor chip which patients can use at home to examine their immune system and to monitor the progress with their treatment, all from a single drop of blood, removing the need for them to go to the hospital for a monthly blood test.

Network Plus

Integrating data-driven biophysical models into respiratory medicine – BIOREME

Led by: Dr Bindi Brook, University of Nottingham

EPSRC support: £760,000

The network’s first step will be to bring medics, imaging experts and mathematicians together with industry and patient group representatives to decide on which specific research areas will benefit most from data-driven biophysical modelling.

The NetworkPlus award will then allow researchers to organise multiple events to help researchers to collaborate and plan the best initial projects to help achieve their goals.

They will then develop these into larger projects to attract funding from other sources and continue the research into the future.

BIOREME will also continue to provide a lively forum for lung researchers to continue solving problems using these advanced computational tools.

The network will also support outreach activities to engage and educate communities and young people in the role that mathematics can play in medicine and healthcare and to inspire a new generation of respiratory scientists from diverse backgrounds.

Integrating Clinical Infrared and Raman Spectroscopy with digital pathology and AI: CLIRPath-AI

Led by: Professor Peter Gardner, The University of Manchester

EPSRC support: £800,000

Biopsy information is a key feature of disease diagnosis. This involves the removal and examination of a small sample of tissue from a patient.

Inspection of the sample, coupled with other relevant information, is the basis on which a diagnosis is generally made. This process is not ideal, however, as is not exact and depends upon the opinion of the clinicians, which may differ.

Recently, AI has been used to examine high-resolution photographs of biopsy slides to help the pathologists make diagnoses.

However, analysing the data from just the visible region of the spectrum severely restricts information content of the images obtained. Using other techniques outside the visible spectrum, such as infrared and Raman, can help distinguish diseased from non-diseased cells.

This funding will support a network of partners across digital pathology and AI that will develop dynamic and synergistic interaction between these separate communities.

Bionics+: User Centred Design and Usability of Bionic Devices

Led by: Professor C James, University of Warwick

EPSRC support: £900,000

The Bionics+ NetworkPlus will:

  • represent the spectrum of research, clinical and industrial communities across bionic technologies within the EPSRC Grand Challenge theme of Frontiers of Physical Intervention
  • invigorate and support a cohesive, open and active network with the mission of creating a mutually supportive environment
  • lead to the co-creation of user-centred bionic solutions that are fit for purpose

These advances will have a global impact, consolidating the world-leading position of the UK.

The founding tranche will focus on:

  • ambitious and transformative research
  • new collaborative and translational activities
  • the formulation of a longer-term strategy

As a community, the network will explore and identify areas of opportunity and value, driven by Bionics users' needs, complementary to existing activity and strengths.

The network will instigate and support early-stage research in these priority areas, alongside providing an outward-facing representation and engagement of the UK bionics community.

Further, it aims to contribute in an advisory capacity to public bodies, UK industry and government policy.

Future blood testing for inclusive monitoring and personalised analytics Network+

Led by: Dr Weizi Li, University of Reading

EPSRC support: £800,000

There is an extremely high demand for laboratory-based blood tests from community settings in the UK.

Analysis suggests an important role in the future for remote blood monitoring that would enable patients and health professionals to carry out their own tests remotely, greatly benefiting patients and speeding up decision making.

Current challenges include being able to obtain and process blood samples outside of clinical settings without training and laboratory facilities, and the added burden and risk associated with COVID-19 of patients needing to attend GP surgeries or hospitals.

Many blood analyses are done in batches that can take a long time to build up and process, with many tools labour-intensive or not suitable for use in monitoring at home.

The volume of tests carried out also means that inefficient and infrequent blood testing may lead to late diagnosis, incomplete knowledge of disease progression and potential complications.

The network will build an interdisciplinary community that will explore future blood testing solutions to achieve remote, inclusive, rapid, affordable and personalised blood monitoring, and address the above challenges in community health and care.

Next Generation Rehabilitation Technologies

Led by: Professor Ruth Goodridge, University of Nottingham

EPSRC support: £830,000

This network will focus on developing the next generation of advanced technologies for rehabilitation, targeting musculoskeletal, cardiorespiratory, neurological and mental health conditions.

It will be connected to the new £70 million National Rehabilitation Centre (NRC), a major national investment in patient care, innovation and technology, due to open to patients in 2024.

The NRC is being co-located with the specialist Defence Medical Rehabilitation Centre on the Stamford Hall Rehabilitation Estate so that the two centres can benefit from the sharing of a wealth of knowledge, expertise and facilities.

The network aims to capitalise on this significant investment, actively involving the UK engineering and physical science community in this initiative and embedding technology innovation at the earliest stage.

Transformative Innovation in the Delivery of Assisted Living products and services (TIDAL)

Led by: Professor C Holloway, UCL

EPSRC support: £950,000

The network will carry out a series of five short, focused projects, including two that will focus on the regulatory landscape for AI post-Brexit and review successful translation of EPSRC-funded research into AI products and services.

One project will establish the network and maintain inclusive engagement. A major activity will be running the annual symposia and doctoral colloquium, with the first focused on responsible engineering.

Through the second, up to eight subsidiary research projects will be funded to support interdisciplinary teams who have an excellent research hypothesis for solving a clear unmet need.

EMERGENCE: Tackling Frailty - Facilitating the Emergence of Healthcare Robots from Labs

Led by: Professor Praminda Caleb-Solly, The University of the West of England Bristol

EPSRC support: £700,000

Professor Caleb-Solly at UWE Bristol will lead a team of four other UK universities, Sheffield, Heriot Watt, Sheffield Hallam and Hertfordshire, who together will establish a new network, EMERGENCE.

The aim of the network is to create and catalyse a robotics for healthcare community, which connects researchers, health and social care professionals, service users, regulators and policy makers, to affect the wider use of healthcare robots to support people living with frailty in the community.

The EMERGENCE network will explore how robots can be used to support people to better self-manage the conditions that result from frailty and, by providing information and data to healthcare practitioners, enabling more timely interventions.