We are collaborating with the Medical Research Council and the Engineering and Physical Sciences Research Council on an investment into four new research projects taking on the challenge of cancer early detection and diagnosis.
Four newly funded teams have been formed to develop cancer early detection approaches at a sandpit-style workshop held last year. The aim of the workshop was to stimulate novel and innovative approaches to triaging primary care patients who may be at risk of receiving a cancer diagnosis.
The event united the cancer research community with researchers from outside biomedicine such as computational and data scientists, engineers, chemists and physicists. Over the course of the workshop, participants teamed up to develop pilot study proposals which they then pitched to receive funding for.
Sarah Birch, research programme manager for early detection and diagnosis at Cancer Research UK, said: “We are so pleased to see the results of such a great sandpit event. It’s amazing to witness the rapid transition from initial brainstorming on day 1, to the generation of impactful project applications with the formation of new multidisciplinary teams on day 3. The sandpit participants really worked with such vigour, enthusiasm and commitment and as a result, will be working collaboratively to make significant strides forward in the ever-important field of early detection and diagnosis research.”
Four of these multidisciplinary teams were successful and will each receive up to £230,000 seed-funding to conduct feasibility work.
Dr Megan Dowie, MRC head of molecular and cellular medicine, said: “Working in partnership with CRUK and EPSRC on this sandpit enabled us to bring together health professionals and researchers from different disciplines, who collectively tackled the challenge put in front of them and formed exciting collaborations. MRC is delighted to be supporting these innovative projects – awards that directly address our goal of enhancing the early detection and diagnosis of disease.”
These high-risk, high-reward projects will explore innovative areas of research including; developing a multimodal sampling and imaging capsule for colorectal cancer detection, a toothbrush-style sensor for oral biomarker monitoring, an improved method for ctDNA detection for pancreatic cancer and a multimodal risk stratification method for GI cancer.
Dr Kedar Pandya, EPSRC director for cross-council programmes, said: “Bringing together different disciplines and health professionals, this research will advance data science and sensor technologies, leading to better integrated transformative technologies in the healthcare system to enhance prediction and early diagnosis for cancer.”
The funded teams
Samplecam
Elena Cojocaru (Royal Marsden Hospital), Sam Merriel (University of Exeter), Robert Kerrison (University of Surrey), Gerard Cummins (University of Birmingham), Heba Sailem (University of Oxford).
A multimodal electronic capsule for identification of visual and biological markers of early stage colorectal cancer.
Sens or pass
Paolo Bertoncello (Swansea University), Nicholas Turner (De Montfort University), Sam Merrie (University of Exeter), Paul Yousefi (University of Bristol), Zahraa Abdallah (University of Bristol), Stephen Mcgough (Newcastle University), Russell Harris (University of Leeds).
A sensor on a toothbrush that can recognise markers of cancer in gastrointestinal and upper respiratory tracts in saliva.
Epic dive
Maria Del Pilar Acedo Nuñez (University College London), Richard Luxton (University of the West of England), Joe Geraghty (Manchester Royal Infirmary (MRI), part of Manchester University NHS Foundation Trust), Robert Kerrison (University of Surrey), Amanda Winter (Newcastle Upon Tyne Hospitals NHS Foundation Trust), Matthew Suderman (University of Bristol).
Early pancreatic cancer diagnosis in vivo evaluation. Aims to show that it is possible to capture and amplify ctDNA in circulating blood, thus increasing the chances of detecting ctDNA in a blood sample.
Maars
Julia Hippisley-Cox (University of Oxford), Jun Wang (Queen Mary, University of London), Konstantin Nikolic (University of West London), Tingting Zhu (University of Oxford), Robert Kerrison (University of Surrey), Joe Geraghty (Manchester Royal Infirmary (MRI), part of Manchester University NHS Foundation Trust).
Multimodal active adaptive risk stratification for gastrointestinal cancer.
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