Life Sciences Minister George Freeman today (16 December) announced £10 million investment in five new research centres around the UK that will explore how mathematics and statistics can help clinicians to tackle serious health challenges such as cancer, heart disease and antibiotic resistant bacteria.
Located at universities in Liverpool, Glasgow, London, Cambridge and Exeter, researchers at the centres will develop new tools from predictive mathematical models to enable earlier diagnosis of chronic diseases such as epilepsy, and new systems to make clinical imaging more accurate and efficient.
Funded by the Engineering and Physical Sciences Research Council (EPSRC), the centres will enable mathematicians and statisticians to work closely with healthcare planners, clinicians, policy makers and industry partners across the UK to deliver high quality, multidisciplinary research that will help overcome some of the big challenges facing the NHS.
George Freeman, Minister for Life Sciences, said: "Maths and statistics aren't the first sciences that come to mind when we talk about healthcare innovation. But they have a very important part to play in developing 21st century solutions to the challenges facing clinicians every day in the NHS. That's why we are investing £10 million in five new Mathematical Sciences in Healthcare Research Centres up and down the country, to help doctors gain a better understanding of diseases, make faster diagnoses and plan better, more targeted treatment for patients."
Professor Philip Nelson, EPSRC's Chief Executive, said: "Maths research provides the foundation for so much of science and engineering, and new technologies, but this often goes unrecognised by those who benefit from results. These five new Mathematical Sciences in Healthcare Centres will lead the way in developing mathematical and statistical modelling for predicting the progression of diseases both in individuals and populations, as well as planning treatment strategies. The Centres will help us deal with the clinical and economic challenges facing the UK's healthcare system as the population ages."
The Centres are:
EPSRC Centre for Predictive Modelling in Healthcare - led by Professor John Terry (University of Exeter) - EP/N014391/1
The Centre brings together a world leading team of mathematicians, statisticians and clinicians with a range of industrial partners, patients and other stakeholders to focus on the development of new methods for managing and treating chronic health conditions using predictive mathematical models. As our population ages, the number of people living with a chronic disorder is forecast to rise dramatically, increasing an already unsustainable financial burden of healthcare costs on society and potentially a substantial reduction in quality of life for the many affected individuals. Critical to averting this are early and accurate diagnoses, optimal use of available medications, as well as new methods of surgery. The Centre will facilitate these through developing mathematical and statistical tools necessary to inform clinical decision making on a patient-by-patient basis which could lead to a revolution in diagnosis of epilepsy by enabling diagnosis from markers that are present even in the absence of seizures; reducing time spent in clinic and increasing accuracy of diagnosis. Indeed it may even make diagnosis in the GP clinic a reality.
EPSRC Centre for New Mathematical Sciences Capabilities for Healthcare Technologies - led by Professor K Chen (University of Liverpool) - EP/N014499/1
The Centre brings together a large and multidisciplinary team of applied and pure mathematicians and statisticians together with healthcare researchers, clinicians and industrialists, collaborating with 15 HEIs and 40 NHS trusts plus other industrial partners to address several key challenges in healthcare. These include improving our understanding of the interaction of cells and tissues, essential to improve treatment strategies for cancer, developing better algorithms for improved medical image processing to allow earlier and more accurate diagnosis and developing mathematical models to develop our understanding of the emergence of antibiotic resistance.
EPSRC Centre for Multiscale Soft Tissue Mechanics - with application to heart & cancer - led by Professor Raymond Ogden (University of Glasgow)-EP/N014642/1
The Centre brings together a world-leading interdisciplinary team focused on developing advanced mathematical models for understanding the development of two of the highest mortality diseases; cancer and cardiac disease. For example, the computational modelling of cancer will give surgeons greater insight into the specific properties of a breast cancer in a given patient, while research on changes in the heart following heart attacks will provide cardiologists with much more detailed information on heart injury and function, and greater understanding of individual patients' risk of heart failure and response to treatment, leading to more-refined patient-specific therapy.
EPSRC Centre for Mathematics of Precision Healthcare - led by Professor Mauricio Barahona (Imperial College London) - EP/N014529/1
The Centre aims to bring about improvements in precision healthcare (an approach that takes into account individual variability in genes, environment, and lifestyle from the individual to the population levels) which can have transformative effects on the UK's health and quality of life. The tools developed will enrich decision making in healthcare so that patients receive the care they need and want while minimising the inefficiencies of inadequate patient stratification. A population-level approach, complementing studies of patient journeys, will allow us to move towards truly joined up clinical intervention and improvements in national public health strategy.
EPSRC Centre for Mathematical and Statistical Analysis of Multimodal Clinical Imaging - led by Professor John Aston (University of Cambridge) - EP/N014588/1
In this new age of Big Data, traditional boundaries between applied maths and statistics need to be torn down. This Centre aims to achieve synergies between applied mathematics and statistics through a focus on the analysis of clinical imaging, particularly that arising in neurological, cardiovascular and oncology imaging. Current image analysis is based on techniques such as manual segmentation and technician reading of scans. The methodologies developed in this Centre will look to directly automate many of these steps. This will allow considerably greater flexibility in the types of clinical questions that can be addressed using populations of images.
Can soda taxes fight obesity? New research adds to the debate