Nine researchers, working on innovative projects that promise to improve healthcare diagnosis and treatment, across a wide spread of issues, were today announced as the first recipients of the Engineering and Physical Sciences Research Council's (EPSRC) Healthcare Technologies Challenge Awards.
Their projects range from developing new ways of examining sperm to smart wound dressings that incorporate sensors, to tools to improve imaging, diagnosis and drug delivery to treat cancers.
The award winners will share in a £9 million fund allocated to support a cohort of next generation research leaders to establish a personal programme of high quality, creative, and multidisciplinary research across the EPSRC portfolio, and to build and grow their research groups.
The researchers will work with clinicians, companies and charities to speed up the process of translation and clinical adoption of their innovations, and to help them design their research so the barriers to its implementation in healthcare are minimal.
Life Sciences Minister George Freeman MP said: "From fertility diagnostics to disease detection, these award-winning projects - supported by Government's £6bn annual science budget - are great examples of how interdisciplinary collaboration can achieve game-changing results. By linking patients, technologists, clinicians and scientists, new tools and techniques to improve healthcare can be truly innovative which is why the UK is a world leader in life sciences."
EPSRC's Chief Executive, Professor Philip Nelson, said: "These Healthcare Technologies Challenge Award winners are our future research leaders who will be instrumental in ensuring the UK can meet the 21st century healthcare needs and thrive as a healthy nation."
Below are short descriptions of each of the projects in the researchers own words:-
David Smith, University of Birmingham - Rapid Sperm Capture
Infertility affects around one in six couples. Problems with sperm (swimming ability, abnormal shape) are one of the major causes. Treatment is difficult because diagnostics are imprecise; 'sperm counting' does not yet make use of cutting edge technologies. This project will bring together expertise from computing, maths, bioengineering and the clinic to develop a new device to examine sperm. The system will detect which sperm have the 'right stuff' - the ability to deliver a cargo of safely-packaged DNA to the egg - and to convert this information into better treatment decisions, saving distress and expense, and leading to more healthy births.
Robert Neely, University of Birmingham - Enzymatic tools for biotechnology and medicine
The early detection of diseases such as cancer is a significant challenge. Yet it also represents a significant opportunity for us to improve healthcare. In the case of cancer, early detection of malignancy can dramatically improve the prospects for those who are diagnosed. This project will develop biochemistry, analytical tools and state-of-the-art imaging solutions that will allow us to identify diseases like cancer in their early stages of development, in a non-invasive way. The project is a collaboration between chemists, medics and clinicians and aims to develop simple tests that will improve our ability to treat individual patients.
Asier Unciti-Broceta, University of Edinburgh - Palladium-Activated Prodrug Therapy
This proposal will exploit the biocompatibility and unique catalytic properties of Palladium to create implantable medical devices that will convert inactive drug precursors into anticancer agents just at the tumour site. By increasing the efficacy and reducing the adverse effects of existing chemotherapies, this revolutionary strategy will improve the quality of life and life expectancy of patients suffering from localised cancers of the prostate and the brain, for whom conventional therapeutic approaches have failed to provide a solution.
Ruchi Gupta, University of Hull - Wearable Organic Integrated Sensors for Healthcare: Smart Dressings, a Step Change in Wound Management
Chronic wounds pose significant societal challenges and currently cost ~£3 billion annually in the UK. The incidence of chronic wounds is predicted to increase due to lifestyle changes and an ageing population. Standard dressings do not provide insights into the status of the wound underneath and are often changed, which hampers the normal healing process, causes stress and pain to patients, and consumes a significant amount of healthcare professionals' time and dressing materials contributing to spiraling costs. This research will develop a smart dressing with an array of sensors for monitoring wounds' status to facilitate rapid healing while reducing costs.
James Walsh, University of Liverpool - Establishing a Centre for Plasma Microbiology
There is an unprecedented clinical need to establish new strategies to manage the colonisation of medical devices by complex bacterial communities 'biofilms'. Such contamination presents a particularly resilient reservoir of infection, shielded from antibiotics, that often leads to the emergence of multidrug-resistant colonies. This award will establish a multidisciplinary centre of excellence focused on the development of novel plasma based physical interventions to prevent biofilm formation on medical devices.
Antoine Jerusalem, University of Oxford - Electrophysiological-mechanical coupled pulses in neural membranes: a new paradigm for clinical therapy of SCI and TBI (NeuroPulse)
NeuroPulse will build the foundations of a new generation of disruptive and enabling healthcare technologies by exploring and using the interaction between the mechanical vibrational properties of neurons - a specialised cell in the body that transmits nerve impulses - and their electrophysiological functions. This endeavour is set to benefit the medical community in the diagnosis, prognosis, and treatment of Traumatic Brain Injury and Spinal Cord Injury, both major, global public health issues, while providing new avenues for non-invasive electrophysiological control, such as pain management.
David Clifton, University of Oxford - Machine Learning for Patient-Specific, Predictive Healthcare Technologies via Intelligent Electronic Health Records
With an ever-growing quantity of data being acquired during routine care throughout the healthcare system, there is an urgent need to develop integrated, intelligent healthcare technologies that exploit these data to improve patient outcomes. This programme in computational health informatics will develop a machine learning platform for fusing data from electronic health records, patient-worn sensors, and diagnostic data for (i) improved management of patients in hospitals and homes, and (ii) better identifying and tracking antibiotic resistance throughout the healthcare system.
Adrien Desjardins, UCL - All-Optical Pulse-Echo Ultrasound Imaging for Real-Time Guidance of Minimally Invasive Procedure
Ultrasound imaging can provide exquisite detail about patient anatomy to guide clinical procedures. Conventionally, ultrasound is transmitted and received electrically. This project is centred on a new paradigm in which ultrasound imaging is performed optically, using inexpensive optical fibres used in telecommunications. The ultrasound probes, developed in close collaboration with clinicians, will be the first to provide real-time optical ultrasound imaging. Integrated into devices such as needles and catheters, they will provide imaging from within the human body that was previously unavailable. There is strong potential to improve patient outcomes in a wide range of clinical contexts.
Silvia Schievano, UCL - A hub for device personalisation in the treatment of congenital diseases - A patient specific computational framework to customise paediatric interventions
Devices purposefully designed for treating children with congenital defects are rare due to the small size of the paediatric market compared to the adult population, but also to the huge variations that are encountered in birth defects compared to acquired diseases.
In this project, I will develop new devices and tools that can be customised in-house for the treatment of children with congenital diseases on demand.
Computational modelling based on routinely acquired clinical data will be used to study each patient dysfunctional site, and drive the device personalisation and optimisation process by simulating device implantation and interaction with the biological site.
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Notes for Editors:
The Engineering and Physical Sciences Research Council (EPSRC)
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