AstraZeneca UK, Qure.ai and Greater Manchester Cancer Alliance Join Forces to Battle Lung Cancer Waiting Times Using Artificial Intelligence (AI) Technology
pharmafile | January 17, 2023 | News story | Business Services |
London, UK, 13 January 2023 – An initiative to improve earlier diagnosis of lung cancer has been launched by AstraZeneca UK, Qure.ai and Greater Manchester Cancer Alliance today. The project – which is part of AstraZeneca’s ambition to deliver the best possible patient outcomes – will see an artificial intelligence system read 250,000 chest X-rays of people in Greater Manchester and evaluate whether the technology can support radiologists in making faster and more accurate diagnoses of lung cancer. Early diagnosis improves cancer outcomes by providing care at the earliest possible stage, which could improve the patient’s quality of life and chances of survival.[i],[ii]
The technology used by Qure.ai – called qXR – interprets chest X-rays using deep-learning algorithms to detect cancer. qXR supports radiologists by classifying chest X-rays as remarkable or unremarkable, identifying abnormal findings, and highlighting them on the X-ray. The qXR algorithms have been trained on a large database of X-rays.[iii],[iv]
Lucy George, Head of Business Innovation Oncology at AstraZeneca UK, said: “This partnership speaks to the very heart of what we believe to be important to transform the patient experience. If we can bridge the gap between the NHS and innovative technology, such as Qure.ai’s qXR technology, to facilitate access to speedier diagnoses, then we’re a step closer to helping lung cancer patients receive the right treatment earlier in the patient pathway.”
Lung cancer is the UK’s biggest cancer killer, with around 35,000 people dying from the disease each year.[v] It is frequently diagnosed at a late stage, because early-stage disease may be asymptomatic, and therefore hard to detect.1 Today, one in five cancer diagnoses in England are detected after routine testing following referral to a hospital specialist.[vi] Unfortunately, many of these patients wait months for their diagnoses, and this wait is likely to result in poor patient experiences and lead to poorer outcomes.[vii] Patients on waiting lists may experience mental health consequences such as anxiety, which may manifest as heart palpitations and gastrointestinal symptoms.[viii]
“The Greater Manchester Cancer Alliance is testing a new technology to see if artificial intelligence can help us to identify and act on chest X-rays that are suspicious for lung cancer more rapidly. It is important to diagnose lung cancer as early and as quickly as possible to ensure the best possible treatment. It is vital that anyone with chest symptoms, such as a cough, breathlessness or chest/shoulder pain lasting three weeks or more is considered for a chest X-ray,” said Dr Matthew Evison, clinician lead for lung cancer at Greater Manchester Cancer Alliance. “This study will evaluate whether artificial intelligence can speed up the analysis of these X-rays when it is needed the most. This is a first for both us and the people of Greater Manchester, and it is hoped that the project will have a significant impact in the region.”
Qure.ai’s CEO and Co-founder, Prashant Warier, said: “The UK government recognises the importance of digital health technologies to help it improve outcomes in societies. Based on our experience in other countries and studies, qXR has become an integral component in the mission to make detection of lung cancer smarter and faster for everyone, everywhere.”
The pilot being launched in Manchester today builds on AstraZeneca and Qure.ai’s existing partnership which has existed since 2020 through the A.Catalyst Network; a global network of more than 20 AstraZeneca health innovation hubs committed to advancing cutting-edge science and building a sustainable future.
The pilot runs for six months, aiming to cover a population of three million people, and it is hoped that this pilot will generate further evidence showing how technology can benefit cancer patients across the UK and beyond.
[i] NHS England. Cancer. Early Diagnosis. Available at https://www.england.nhs.uk/cancer/early-diagnosis/.
Last accessed January 2023
[ii] WHO Promoting cancer early diagnosis. Available at https://www.who.int/activities/promoting-cancer-early-diagnosis. Last accessed: January 2023
[iii] Govindarajan A. et al. Role of an Automated Deep Learning Algorithm for Reliable Screening of Abnormality in Chest Radiographs: A Prospective Multicenter Quality Improvement Study. Diagnostics. 2022; 12, 2724. Available at: https://www.mdpi.com/2075-4418/12/11/2724. Last accesses January 2023
[iv] Putha P et al. Can Artificial Intelligence Reliably Report Chest X-Rays? arXiv:1807.07455v2. 2019. Available at: https://arxiv.org/pdf/1807.07455.pdf. Last accessed January 2023.
[v] Cancer Research UK ‘Lung Cancer Statistics’ https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/lung-cancer. Last Accessed: January 2023
[vi] NHS England. NHS gives GP teams direct access to tests to speed up cancer diagnosis. Available at https://www.england.nhs.uk/2022/11/nhs-gives-gp-teams-direct-access-to-tests-to-speed-up-cancer-diagnosis/. Last accessed: January 2023
[vii] UK Parliament. Health and Social Care Committee. Written evidence submitted by Cancer Research UK (NHS0023). Nov 2022. Available at: https://committees.parliament.uk/writtenevidence/113672/pdf/. Last accessed: January 2023
[viii] Gagliardi AR, et al. The psychological burden of waiting for procedures and patient-centred strategies that could support the mental health of wait-listed patients and caregivers during the COVID-19 pandemic: A scoping review. Health Expect. 2021; 24:978– 990. https://doi.org/10.1111/hex.13241. Last Accessed: January 2023
