Published 08 Feb 2022

SBRI Healthcare announces £3.2 million in Funding for’s AI Technology for Cancer Detection



Award part of £9 million programme for late-stage innovation projects that advance the earlier and faster diagnosis of cancer 
London, February 8th 2022: Today, SBRI Healthcare, in partnership with the NHS Cancer Programme and the Accelerated Access Collaborative, announced that has secured £3.2 million in funding for late-stage innovation projects that aid in the earlier and faster diagnosis of cancer. This funding announcement follows recent comments from Sajid Javid, the Health and Social Care Secretary, where he declared “a national war on cancer” as the UK seeks to develop a new 10-year plan for cancer treatment.
With this SBRI funding, will demonstrate real-world evidence of AI-aided diagnosis of lung cancer based on triage of suspected lung nodules on chest X-rays and immediate reporting of the same for prompt follow through and confirmation. This will also lead to faster chest computed tomography (CT) scans for suspected cases and eventually impact early-stage lung cancer detection. Clinical and cost-effectiveness data will be used in a thorough prospective evaluation to establish clinical relevance before moving to wider adoption.
The project brings in lung cancer expertise under the clinical leadership of Prof David Baldwin, Chair, UK Clinical Expert Group for Lung Cancer, Dr Richard Lee, National Institute for Health Research Specialty Lead Screening, Prevention and Early Detection, Dr Neal Navani, Senior Clinical Lead of the UK National Lung Cancer Audit and Dr Nick Woznitza MBE, Consultant Radiographer from University College London Hospital NHS Trust and Canterbury Christ Church University.
Prof Baldwin said “Speed of diagnosis is critical to achieve the best outcomes in lung cancer and to reduce stress and worry for patients. AI solutions such as qXR should improve the pathway logistics by flagging irregularities on chest x-rays as soon as they are undertaken helping patients to progress rapidly through to CT scanning. This will also assist our incredibly busy workforce.”
Dr Richard Lee commented, “Lung cancer is the most common cause of cancer deaths worldwide. It is vital that we make every attempt to diagnose cancer earlier since treatment is much more effective and many more patients live longer, healthier lives if we can use more curative treatments in those diagnosed earlier. The SBRI funded collaboration with and other respiratory colleagues across the UK is an immensely valuable opportunity to demonstrate how artificial intelligence tools can lead to earlier lung cancer diagnosis and improve patient outcomes. Such techniques can sit alongside our other liquid biopsy research to improve cancer survival in a multi-pronged approach and ensure that those patients in whom we cannot detect lung cancer by screening in targeted lung health checks, can still benefit from the very latest innovations."
“We know that early, accurate and rapid diagnosis of lung cancer is critical if we are to improve outcomes for patients. With the number of chest X-rays performed each year in the NHS we need to evaluate how we can identify priority cases and this large-scale prospective study will provide robust clinical and health economic evidence on the role of AI in lung cancer imaging,” added Dr Nick Woznitza.
Qure would be collaborating with leading NHS Trusts in the UK that have a focus on lung cancer including the Nottingham University Hospital Trust, The Royal Marsden NHS Trust, University College London Hospital NHS Trust, University Hospitals Birmingham NHS Trust, and several other regional NHS Trusts.
“Lung cancer is the leading cause of cancer-related deaths in the United Kingdom. Although 5-year survival rates have improved recently, they remain low at roughly 14%, with 30% of patients dying within 90 days after diagnosis” said Prashant Warier, CEO and founder, “We support the Health and Social Care Secretary’s vision to fight cancer because we are optimistic that artificial intelligence (AI) can play a vital role in early identification of lesions which can lead to faster diagnosis through same-day CT scans. This initiative will look to demonstrate that it is possible to impact every step of the lung cancer diagnosis process through AI and assist in delivering better outcomes for patients.”’s qXR is a CE-approved chest X-ray interpretation AI solution built using millions of images and deep learning. It classifies chest X-rays as conventional or unconventional, identifies unconventional findings, and highlights them on the X-ray. It can detect and localize multiple findings in a chest X-ray including detection of multiple findings with the lungs, pleura, heart, bones, and diaphragm. The qXR algorithm detects lung nodules and assigns them a lung malignancy-risk score, reducing the chances of missed diagnosis. It is one of the most deployed AI solutions, with multiple peer-reviewed publications and clinical users in 40+ countries.
This competition marks the beginning of an anticipated annual series of multi-million-pound funding opportunities in support of the LTP cancer ambitions. Launched in March 2021, it is the first of its kind, and attracted 51 applications from the open market. It called for late-stage solutions to the challenges of improving the early detection and diagnosis of cancer; and diagnostic efficiency for cancer services. All winning technologies have already proven their clinical effectiveness, and through this programme, will be implemented either locally or nationally to prove they can be rolled out nationwide within the NHS.

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