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AI biomarkers, built for real-world impact and clinical trials. Meet us at ASCO 2026 | Booth #IH12.

Qure.ai Recognized Among TIME’s 100 Most Influential Companies of 2025

Qure.ai partners with Microsoft to increase access to its lung cancer detection and management suite in the U.S.

qTrack

CREATE is a
multi-country, prospective study led by
AstraZeneca and Qure.ai to assess the
impact of AI for triaging incidental
pulmonary nodules (IPN) detected on
routine chest X-rays and to expedite
appropriate downstream care for
suspicious nodules. Conducted across
23 centers in Egypt, India, Indonesia,
Mexico, and Turkey, CREATE is among
the largest real-world studies focused
on AI-enabled triage and loop closure
from CXR to lung cancer diagnosis.

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Study Reveals AI’s Ability to Detect Lung Cancer Risk in Younger, Non-Smoking Individuals

Lung cancer is the leading cause of cancer-related death worldwide, with diagnosis often occurring at late stages when treatment options are limited. This issue is particularly acute in resource-limited settings, where healthcare infrastructure is often underdeveloped,&nbsp;workforces are stretched, and economic constraints prevail.&nbsp;

A bold partnership between Qure.ai and AstraZeneca, as a commitment to the World Economic Forum’s EDISON Alliance 1 Billion Lives Challenge, set out to <a href="https://www.qure.ai/product/lung-nodule-management" target="_blank">apply AI to routine chest X-rays</a>, illustrating the role AI can play in providing a low-cost, scalable pathway to help identify lung cancer risk earlier.&nbsp;

<a href="https://www.qure.ai/news_press_coverages/A-new-era-for-lung-cancer-detection-AI-enabled-risk-assessment-reaches-5-million-people-around-the-world" target="_blank">Achieving the milestone of five million scans</a> across more than 20 countries, marks an important step forward. It provides real-world evidence for AI’s role in changing the lung cancer narrative that clinicians, healthcare providers, and country-level policy shapers can draw upon to enact positive change.&nbsp;&nbsp;

To gain your copy of an executive summary impact report, and dive into the data and real-life stories redefining early cancer care, register here:&nbsp;

Download Report - 'The Power of AI to evaluate lung cancer risk'

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Unlocking the Power of AI for Early Lung Cancer Detection

LungIMPACT trial starts gathering real-world evidence with aim of saving lives now and into the future.

A collaborative study between UK academia, NHS hospitals and AI innovator Qure.ai has commenced to gather real-world evidence of AI-assisted diagnosis of lung cancer, which could help save thousands of lives.&nbsp;

The ‘LungIMPACT’ trial is using Qure’s qXR (CE Class IIb per EU MDR certified) solution to triage chest X-rays referred by GPs with the aim of identifying the presence of suspected lung abnormalities and give immediate reporting. This may then enable a patient to be referred for a same-day CT scan if lung cancer is suspected, speeding up access to a confirmed diagnosis and treatment planning.&nbsp;&nbsp;

The trial is now underway with Qure’s AI tool implemented at two NHS hospital Trusts, further NHS sites will also be deployed and ready to contribute to the study in a couple of months.&nbsp;

“Every year in the UK more than 35,500 people lose their lives due to lung cancer. We know that the speed of diagnosis is critical to achieve the best outcomes in lung cancer and to reduce stress and worry for patients. We have previously found that only a 15-day reduction in time to diagnosis increases survival by 200 days and immediate action on a chest X-ray that is suspicious for lung cancer reduces time to diagnosis by 30 days. AI may be a way to identify suspicious chest X-rays rapidly. Studies with AI are needed to evaluate the clinical value and impact to ensure safe and effective implementation,” states Professor David Baldwin, Chair of the UK Clinical Expert Group for Lung Cancer and Mesothelioma; National Clinical Lead for Lung Cancer, NHSE/I; Clinical Advisor to the UK National Screening Committee, Department of Health and Social Care; Respiratory Consultant at Nottingham University Hospitals NHS Trust; and Honorary Professor of Medicine at the University of Nottingham.&nbsp;&nbsp;

“We are delighted that the first hospital sites involved in the LungIMPACT trial are now live and the collaboration is gathering pace. The earlier cancer can be detected, the better chance patients have of survival. AI can be helpful in expediting diagnosis, and we hope that studies like this will gather the evidence needed to validate its role,” states Darren Stephens, Senior Vice President &amp; Commercial Head UK and Europe of Qure.ai.&nbsp;

The work was commissioned and funded by the NHS Cancer Programme, with the support of SBRI Healthcare and the NHS Accelerated Access Collaborative.&nbsp;&nbsp;

The NHS and academic teams have designed the study and all data will be analysed and reported independently from Qure.ai. Nottingham is leading the research on the back of the pioneering work on national rapid diagnostic pathways, AI imaging research and cancer screening.&nbsp;

It is led jointly by Professor David Baldwin, and Dr Nick Woznitza, a Consultant Radiographer at University College London Hospitals (UCLH) NHS Foundation Trust, and Clinical Academic at Canterbury Christ Church University. It also involves the expertise of 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.&nbsp;&nbsp;

<b>Channel Partners:&nbsp;GE HealthCare, Magentus</b>

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Accelerating lung cancer diagnosis through LungIMPACT trial

Lung cancer remains one of the most pressing challenges in modern healthcare, being the leading cause of cancer mortality in the UK with approximately 47,000 new diagnoses each year. What's particularly concerning is that over a third of these patients are diagnosed only after presenting as emergency cases - often at late stages when treatment options are limited. Dr. Indrajeet Das, a consultant radiologist at the University of Leicester Hospital, recently shared insights into how artificial intelligence could transform lung cancer pathways and potentially save lives through earlier detection.

The current situation is sobering: patients presenting as emergencies are five times more likely to die within a year compared to those referred through primary care. This stark difference underscores the critical importance of early diagnosis. However, several challenges stand in the way of improving detection rates.

The UK faces a significant shortage of radiologists, with one of the lowest numbers of specialists per 100,000 people in the European Union. This shortage has led many hospitals, including Leicester, to outsource up to 60% of their X-ray reporting. While outsourcing helps manage workflow, ideally hospitals would prefer to keep abnormal cases in-house for faster response and better continuity of care.

This is where AI enters the picture. Dr. Das and his team have been exploring how AI tools could help triage chest X-rays, distinguishing between normal and abnormal cases to ensure the most critical cases receive immediate attention. However, Dr. Das emphasizes that AI alone isn't enough - it needs to be integrated into a comprehensive, streamlined pathway for patient care.

The Leicester team developed an innovative "straight to CT" pathway, where chest X-rays showing suspected lung cancer are fast-tracked. Patients receive early morning CT scans that are immediately reported, allowing for rapid assessment and intervention if needed. This approach has already shown promising results, with a 25% relative reduction in emergency presentations despite an increase in overall lung cancer diagnoses.

To validate the potential of AI in this pathway, Dr. Das's team partnered with Qure.ai, conducting a retrospective analysis of 1,448 GP-referred X-rays. The results were impressive: the AI system showed excellent ability to detect abnormalities and correctly identified eight out of ten confirmed lung cancer cases. While it missed two subtle cases, the system's performance suggested it could be valuable as a prioritization tool.

The success of this initial validation has led to a larger multi-center study funded by SBRI (Small Business Research Initiative), involving several leading UK hospitals. The goal is to achieve the ambitious target of reporting all routine or urgent chest X-rays within 24 hours, potentially revolutionizing the speed of lung cancer diagnosis.

What makes this approach particularly promising is its holistic nature. Rather than simply deploying AI as a standalone solution, the Leicester team has focused on integrating it into a comprehensive pathway that includes rapid CT scanning, expert reporting, and prompt clinical assessment. This integrated approach addresses not just the initial detection but the entire patient journey.

While some radiologists remain skeptical about AI's role in healthcare, the early results from Leicester suggest that when properly implemented as part of a well-designed pathway, AI tools can help address the critical challenges of radiologist shortages while potentially improving patient outcomes through earlier detection and treatment of lung cancer.

As we await the results of larger prospective trials, one thing is clear: the future of lung cancer detection likely lies in the thoughtful integration of AI tools with streamlined clinical pathways, supported by dedicated healthcare professionals working together to catch cancer earlier and save more lives.

<b>Channel Partners: GE Healthcare, Magentus</b>

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Determining the Value of AI in Lung Cancer Pathways | Dr Indrajeet Das, Leicester NHS Trust

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