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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

~The findings draw on state-level implementations to assess how AI is moving beyond pilots into routine public healthcare~

New Delhi, India | 16 February 2026: Qure.ai today unveiled its latest report, ‘AI in Action: Transforming Health Outcomes Across India’s Care Spectrum’, at the India AI Impact Summit, outlining how artificial intelligence is being deployed at scale across India’s public healthcare system to address critical challenges such as tuberculosis, lung cancer, and acute neurological conditions.

The report consolidates real-world evidence from large public health programmes, state-wide deployments, and multi-country clinical studies, demonstrating how AI, when embedded into existing healthcare workflows, can accelerate diagnosis, reduce system-level delays, and improve access to timely care without adding cost or operational complexity for patients or providers.

Central to the report is the role of state-level partnerships in enabling AI adoption at population scale. Across Maharashtra, Karnataka, Goa, Punjab and other states, governments and public health agencies have integrated AI into routine imaging and emergency care pathways to strengthen detection, triage and follow-up. 

●	In Maharashtra, AI-enabled incidental screening across public and private facilities contributed to an estimated 35% increase in tuberculosis detection, including among asymptomatic patients undergoing X-rays for unrelated reasons. 

●	In Karnataka, a government-led partnership enabled the incidental detection of over 6,400 TB cases alongside high-risk lung nodules through a single AI-driven workflow. 

●	In Goa, a statewide public health deployment screened over one lakh routine chest X-rays, leading to 20 confirmed lung cancer diagnoses through structured referral pathways. 

●	In Punjab, a state-supported hub-and-spoke stroke network reduced diagnostic turnaround time by up to 85%, protecting the critical “golden hour” even in district hospitals.

Beyond routine care delivery, the report illustrates how AI is being applied to large-scale disease surveillance and national public health initiatives. During the Maha Kumbh Mela, one of the world’s largest mass gatherings, AI-powered chest X-ray analysis was deployed for rapid tuberculosis surveillance in a high-density, high-risk environment. The system flagged abnormalities in 36% of X-rays, enabling early identification and triage of presumptive TB cases and offering a replicable model for mass gatherings and outbreak-prone settings.

Speaking at the launch of the report, Ankit Modi, Founding Member and Chief Strategy &amp; Growth Officer, Qure.ai, said, “What this report shows is not just where AI has been deployed, but where public healthcare is headed. Through state partnerships, AI is moving from being an intervention to becoming part of the system itself, built into how screening, surveillance, and emergency care are delivered. As these models scale, AI has the potential to consistently shift detection earlier, reduce delays across care pathways, and make continuity of care the default rather than the exception, using infrastructure that already exists.”

In addition to on-ground implementation outcomes, the report draws on independent Health Technology Assessment (HTA) evaluations conducted under the Government of India, which validate AI-powered chest X-ray screening as both clinically effective and cost-saving for tuberculosis detection. The assessments show a reduction of approximately ₹10,000 per TB case detected compared to existing diagnostic pathways, reinforcing the case for AI as a scalable intervention that can strengthen public health programmes without increasing system costs.

Taken together, the evidence presented in AI in Action points to a clear shift in how India’s public healthcare system can evolve, by embedding AI as a foundational layer across screening, surveillance, care coordination, and emergency response. As state partnerships deepen and these models scale, AI has the potential to move healthcare delivery from reactive to proactive, enabling earlier intervention, more reliable follow-up, and stronger system-wide resilience across India’s care continuum.

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Qure.ai Unveils ‘AI in Action’ Report at India AI Impact Summit, Mapping AI’s Role Across India’s Public Healthcare System

Over 10,500 lung nodules flagged through AI review of routine chest X-rays, reducing time to diagnosis by over 50%

The Government of Goa today shared early outcomes from its AI-enabled lung cancer screening programme implemented across the state’s public healthcare system. The initiative integrates artificial intelligence-based chest X-ray analysis into routine clinical workflows at government health facilities, enabling earlier detection of lung abnormalities without requiring additional tests or patient visits.

Lung cancer is one of the leading causes of cancer-related mortality in India, primarily due to late-stage diagnosis. Goa’s programme addresses this challenge by automatically reviewing every chest X-ray conducted in public health facilities for early signs of lung abnormalities, even when the scan is performed for unrelated clinical indications. This approach allows clinicians to identify potential lung cancer cases earlier and initiate timely follow-up.

Speaking on the programme, Shri Vishwajit Rane, Hon’ble Health Minister of Goa, said, “The Department of Health has been consistently advancing initiatives focused on early detection, preventive healthcare, and cancer screening to strengthen the public healthcare system. By embedding AI into routine diagnostic processes, Goa is reinforcing early detection in a structured and scalable manner. This programme ensures that advanced technology supports clinical decision-making without adding cost or complexity for patients. Early diagnosis must be accessible to all, and should not be limited by geography or affordability. Integrating AI into public healthcare represents the way forward in delivering timely, efficient, and equitable care to our people.”

The programme has been implemented in close coordination with clinicians across Goa’s public health system. Pulmonologists and radiologists from government hospitals have guided the clinical adoption of AI-enabled triaging, ensuring alignment with existing diagnostic pathways and follow-up protocols.

Since deployment, the initiative has analyzed 1,06,248 chest X-rays across 18 public healthcare sites in the state. The AI system flagged 10,564 lung nodules, including 1,619 classified as high-risk, enabling clinicians to prioritize patients requiring urgent evaluation. To date, this has led to 18 confirmed lung cancer diagnoses and reduced the average time to diagnosis by more than 50%.

Ankit Modi, Founding Member and Chief Product Officer, Qure.ai, said, “What makes Goa’s programme significant is its ability to deliver impact at scale using infrastructure that already exists within the public healthcare system. By leveraging routine chest X-rays, the state has enabled earlier identification of lung abnormalities without introducing additional tests or burden on patients. The outcomes reinforce that clinically guided, system-integrated AI can accelerate diagnosis and support more timely care across public health systems.”

Praveen Rao Akkinepally, Country President and Managing Director, AstraZeneca India, said, “This is a significant milestone for the state of Goa. We are honoured to partner with the Department of Health Services, Goa, and Qure.ai, and congratulate the team on surpassing 100,000 AI-enabled lung screening scans. It underscores our shared purpose of earlier detection and equitable access to healthcare. With AstraZeneca’s science, Goa’s public health leadership, and Qure.ai’s capability, we are bringing technology closer to patients, lowering barriers to care, and building scalable, data-driven pathways across India, so people are identified sooner and connected to the right care at the right time.”.

The Government of Goa plans to further expand the programme by integrating AI-enabled screening into mobile health units and community outreach services, reinforcing its commitment to strengthening early diagnosis and improving cancer care outcomes across the state.

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 Goa Crosses 1 Lakh Chest X-Rays Reviewed Using AI in Public Health System, Identifies 18 Lung Cancer Cases

End-to-end&nbsp;specialist&nbsp;AI to&nbsp;support high quality patient care&nbsp;&nbsp;

Horizon Health&nbsp;Network&nbsp;(Horizon), the operator of&nbsp;12 hospitals and more than 100 medical facilities and clinics across&nbsp;the&nbsp;province of&nbsp;New Brunswick&nbsp;in Canada,&nbsp;has&nbsp;entered into&nbsp;a partnership with global health innovator Qure.ai to evaluate and implement an end-to-end artificial intelligence (AI) lung cancer care suite.

This agreement&nbsp;supports Horizon's preparation for&nbsp;an anticipated&nbsp;province-wide low-dose CT lung cancer screening program for high-risk patients. The collaboration also enables proactive advancement in chest X-ray incidental lung cancer detection across a broader patient population.&nbsp;

Through this&nbsp;innovative&nbsp;partnership, Horizon is building the infrastructure, workflows, and clinical integration capabilities to be ready for coordinated provincial lung cancer screening initiatives.&nbsp;

Lung cancer is the leading cause of cancer death in&nbsp;North America, accounting for more cancer deaths than colon, breast, and prostate cancers combined.&nbsp;Early detection at stage I, rather than late stage III or IV,&nbsp;boosts survival rates and reduces the need for therapeutic or surgical intervention.&nbsp;&nbsp;

“This agreement&nbsp;with Qure.ai reflects our commitment to innovation and advancing patient care through rigorous evaluation of emerging technologies," states Zach Kilburn, Chief Digital Officer at Horizon Health Network. "The AI-powered software will integrate seamlessly with our existing&nbsp;infrastructure&nbsp;to support clinical confidence in decision-making and streamline patient management workflows. By building this infrastructure now,&nbsp;we're&nbsp;positioning our&nbsp;clinicians&nbsp;to support high-quality, coordinated lung cancer care across the health&nbsp;care ecosystem.”&nbsp;

“Proactive&nbsp;CT-based&nbsp;lung cancer&nbsp;screening&nbsp;strategies are&nbsp;a giant step forward, but&nbsp;only&nbsp;one part of the battle against&nbsp;lung&nbsp;cancer.&nbsp;AI has the power to cast&nbsp;a wider&nbsp;net, to&nbsp;identify&nbsp;small lung nodules that can be indicative of&nbsp;early-stage&nbsp;lung cancer on routine&nbsp;CT and&nbsp;X-rays that may be&nbsp;obtained&nbsp;for other&nbsp;indications. This can include pre-operative examinations or&nbsp;trauma related&nbsp;admissions,”&nbsp;states&nbsp;Jim Mercadante, Chief Commercial Officer&nbsp;at Qure.ai. “We are delighted to be entering into a progressive&nbsp;lung cancer&nbsp;AI partnership with Horizon Health Network&nbsp;in Canada&nbsp;and supporting them with digital transformation.”&nbsp;&nbsp;

Qure.ai is a global leader in healthcare AI and digital health boasting deployments&nbsp;in over 107&nbsp;countries across&nbsp;5200+ sites.&nbsp;The Qure.ai lung cancer solutions&nbsp;have class III medical device license approval from Health Canada&nbsp;and FDA clearance in the USA. They&nbsp;can be deployed as individual products, or collectively as a suite for a unified and cohesive workflow.&nbsp;qXR-LN&nbsp;powers the incidental detection of lung nodules on chest X-ray;&nbsp;qCT-Quant&nbsp;assesses&nbsp;and&nbsp;quantifies&nbsp;lung nodules&nbsp;on CT&nbsp;scans; and&nbsp;qTrack&nbsp;coordinates patient management to support lung nodule clinics or nurse navigators.&nbsp;&nbsp;&nbsp;

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Horizon Health Network and Qure.ai partner to advance province-wide early lung cancer detection in Canada 

Catharina Ziekenhuis &amp; UMC Utrecht go-live with Qure.ai&nbsp;&nbsp;

Two major Dutch hospitals, Catharina Ziekenhuis in Eindhoven and University Medical Center (UMC) Utrecht, are integrating artificial intelligence (AI) from <a href="https://www.qure.ai/" target="_blank">Qure.ai</a> into chest X-ray workflows to support earlier and more consistent detection of potentially cancerous lung nodules.&nbsp;

The hospitals are striding ahead by progressively adopting AI-enabled lung nodule programs to establish opportunistic screening pathways that can lead to earlier detection of lung cancer and reduce variation in referral decisions across experience levels. Qure.ai’s chest X-ray solution, qXR, strengthens this effort by flagging subtle nodules helping the radiologists with the detection of nodules, even when patients are scanned for unrelated reasons.&nbsp;

UMC Utrecht, one of the Netherlands’ foremost university hospitals, brings both academic and clinical weight to the initiative. UMC Utrecht is at the forefront of using AI in its radiology clinic and has a strong scientific track record in the radiological aspects of lung cancer and AI. As an academic hospital with a strong teaching mandate, it serves a broad patient base while also preparing future clinicians to work confidently with AI-enabled diagnostics.&nbsp;

&nbsp;“AI-enabled diagnostics in radiology are an important tool for today's radiology practice,” states Dr. Firdaus Mohamed Hoesein, Thoracic Radiologist and AI-expert at UMC Utrecht. “By integrating this AI program into our workflow, we can significantly enhance our ability to detect subtle lung nodules, which is paramount for the early diagnosis of lung cancer. This initiative directly aligns with our mission to find lung cancer at earlier stages and improve patient outcomes.”&nbsp;

Dr Joost Nederend, Radiologist at Catharina Ziekenhuis adds, “There is growing evidence that AI can improve detection rates without compromising - and potentially even improving - the positive predictive value for referrals. It can also be valuable in supporting consistent decision-making, especially when chest X-rays are interpreted by radiologists from different subspecialties, those in the earlier stages of their careers, or residents in training.”&nbsp;

Catharina Ziekenhuis is a public tertiary care hospital with advanced capabilities to treat lung cancer. A large share of chest X-rays originates from general practitioner referrals for symptoms like persistent cough or other concerns.&nbsp;&nbsp;

Earlier this year, Erasmus Medical Centre, one of the largest and most authoritative scientific university medical centres in Europe, located in Rotterdam, extended its long-term collaboration with Qure.ai by commencing an innovative Chest X-ray AI study.&nbsp;&nbsp;

&nbsp;&nbsp;Bhargava Reddy, Chief Business Officer, Oncology at Qure.ai states, “Lung cancer remains the leading cause of cancer-related deaths worldwide, including in the Netherlands. To fight back, we need to shift the focus to early detection. Specialist healthcare AI can accelerate this transformation by acting as a tireless second set of eyes, spotting small lung nodules on X-rays that might otherwise be missed. At the same time, it builds knowledge and know-how that drive clinical, operational, and economic value within hospitals and across health systems.”

He continues, “The momentum in the Netherlands is unmistakable. From Erasmus Medical Centre to Catharina Ziekenhuis and UMC Utrecht. Institutions are confidently deploying AI that both elevates clinical standards and aims to future-proof Dutch healthcare.”&nbsp;

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Momentum builds in the Netherlands for AI-driven early lung cancer detection 

New evidence presented at ESMO AI conference highlights how AI can be a&nbsp;silent accelerator within diagnostic pathways&nbsp;&nbsp;

A new study presented at the European Society for Medical Oncology (ESMO) AI Congress&nbsp;demonstrates&nbsp;how AI&nbsp;can help&nbsp;identify&nbsp;patients&nbsp;passively&nbsp;at risk of&nbsp;early-stage&nbsp;lung cancer&nbsp;coming to different&nbsp;departments,&nbsp;long before traditional pathways might flag a concern.&nbsp;

Lung cancer&nbsp;remains&nbsp;the leading cause of cancer deaths&nbsp;In Europe. While proactive low-dose CT screening for lung cancer is&nbsp;established&nbsp;in some countries, it is not globally standard. This research provides compelling evidence that AI-assisted chest X-rays&nbsp;detection&nbsp;could bridge the gap, turning every hospital radiology department into a potential early detection point&nbsp;The main advantage is its passive nature and the fact that the&nbsp;huge volumes of&nbsp;Chest&nbsp;X-rays&nbsp;of the&nbsp;patients coming to different departments can be&nbsp;.passively looked for risk of Lung Cancer&nbsp;and can be flagged..&nbsp;

The study analysed over 30,000 chest X-rays taken for a wide range of clinical indications. Using&nbsp;Qure.ai’s&nbsp;AI-powered algorithm for chest x-ray interpretation, 71 individuals were flagged as high-risk for malignancy. Follow-up CT scans and biopsies confirmed five lung cancer cases, ranging from early to advanced stages. One case was detected at&nbsp;a very early&nbsp;stage (Stage IA3), allowing&nbsp;timely&nbsp;treatment&nbsp;of the patient which could have been missed if AI&nbsp;was&nbsp;not used&nbsp;

“These findings illustrate how AI can act as a silent accelerator within the diagnostic pathway,” said&nbsp;Dr. Rahul Ravind, Medical Oncologist, Renai&nbsp;Medicity,&nbsp;Kochi&nbsp;and lead investigator. “By embedding AI into everyday hospital workflows, clinicians can catch potential cancers much earlier, even when tests were ordered for non-oncological reasons. AI can help extend the benefits of early diagnosis beyond formal screening programs, making it possible even in hospitals that may not have dedicated lung cancer pathways or CT-based screening access.”&nbsp;

“We’re&nbsp;seeing AI bridge one of healthcare’s biggest gaps – the time between the first test and the right diagnosis. That acceleration can completely change outcomes for patients. This study underscores AI’s potential to transform opportunistic screening using chest X-rays that are already part of routine care. By alerting clinicians to suspicious findings in real time, AI can shorten diagnostic timelines and enable faster&nbsp;referral,&nbsp;improving chances of&nbsp;early treatment,” says&nbsp;Sagar Sen, VP, life sciences, Qure.ai&nbsp;&nbsp;

The findings are based on real-world data from Renai&nbsp;Medicity, a tertiary care hospital in Kochi, India, collected between March 2024 and July 2025.&nbsp;

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AI cuts diagnostic delays in lung cancer detection, offering a blueprint for faster, smarter hospital care 

Yashoda Hospital, Hitech City, in collaboration with Qure.ai and AstraZeneca, has launched an AI-enabled Lung Nodule Clinic to support earlier identification and timely management of lung cancer and other pulmonary diseases.

Lung cancer is one of the leading causes of cancer-related deaths in India¹. Most patients are diagnosed at an advanced stage because early disease often has no symptoms and is easily missed on routine imaging². A large proportion of cases in India present late, which limits the chances of curative treatment². India does not have a national lung cancer screening program for high-risk individuals³, which makes structured imaging pathways an important way to support earlier detection. 

Pulmonary nodules are often subtle findings that can vary in size, density, and location, which makes them challenging to identify consistently on routine chest imaging. The new Lung Nodule Clinic at Yashoda Hospital, Hitech City, integrates Qure.ai’s AI solutions into chest X-ray workflows to flag, risk assess, and track these findings in a structured manner. Nodules can be indicators of early lung cancer or other conditions such as tuberculosis, sarcoidosis, or lymphoma. The AI-supported pathway helps clinicians prioritise higher-risk cases and ensure timely and consistent follow-up.

“This program shows how AI can be integrated into clinical workflows to support earlier identification and structured management of lung disease,” said Dr. V. Nagarjuna Maturu, Head of Department, Pulmonology, Yashoda Hospital, Hitech City. “The pathway ensures that incidental findings are consistently tracked and followed up. Embedding AI into routine workflows has helped Yashoda Hospital create a scalable model for proactive lung health. This shows how coordinated use of data and clinical expertise can improve real-world diagnosis and outcomes.”

A nurse navigator model supports the system and helps patients move from AI flagging to counselling, review, and next steps. “Standardised workflows help avoid delays and ensure consistent communication and documentation,” added Dr. Vipul Garg, lead Consultant, Yashoda Hospitals Nodule Clinic.

Since deployment, more than 17,000 chest X-rays have been analysed using Qure.ai’s AI. The program has identified over 960 nodules. Of these, 136 were classified as high risk and 77 patients were sent for expedited CT scans and pulmonology review. Confirmed diagnoses include lung cancers as well as other significant lung diseases, highlighting the broader value of this pathway for proactive lung health. 

“AI is becoming an important part of how health systems strengthen early diagnosis and reduce the burden of late stage lung disease,” said Sagar Sen, Vice President, Life Sciences, Qure.ai. “By integrating intelligence into routine imaging, hospitals can turn everyday X-rays into an opportunity for earlier detection and more coordinated care. The Lung Nodule Clinic at Yashoda Hospital is a strong example of how technology and clinical expertise can work together to create a more proactive approach to lung health.”

The AI supported pathway represents an important move toward structured, data driven lung health and demonstrates the role of modern diagnostic tools in improving early detection in high volume hospital settings.

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Yashoda Hospital Hitech City and Qure.ai Launch AI-Enabled Lung Nodule Clinic to Strengthen Early Lung Cancer Detection and Lung Health

New Case Series presented at World Conference of
Lung Cancer 2025

A <a href="https://share.hsforms.com/171ituW2FQM-jh5MzighC7gcxdki">new clinical case
study,</a> presented today by <a href="https://www.qure.ai/">Qure.ai</a> and Hacettepe
University, Turkey, at the IASLC World Conference on Lung Cancer 2025 in
Barcelona, shows that Artificial Intelligence (AI) can detect potentially
malignant pulmonary nodules on routine chest X-rays (CXRs), even when the
imaging was ordered for unrelated, non-respiratory conditions.

This adds to the growing
body of evidence that AI can act as a disruptor in early lung cancer detection
strategies. It can provide an early warning system in countries without formal
lung cancer screening programs or complement CT-based screening programs by
going beyond smoker/ex-smoker cohorts. 

By expanding and
improving the number of early-detected lung cancer patients, survival rates
will increase through early surgical or pharmaceutical interventions. 

“By finding high-risk
nodules earlier and diagnose
lung cancer at early stages, AI not only improves, but also accelerates
diagnosis and treatment,” said Dr. Deniz Koksal at Hacettepe University in Ankara, Turkey. This
enables early surgical interventions while reducing the need for more
expensive treatments such as targeted therapies and immunotherapies.”

The&nbsp;case series, ‘Chest X-Ray Analysis
with Artificial Intelligence Software Aids in the Early Diagnosis of Lung
Cancer’, conducted at Hacettepe University in Ankara, Turkey,&nbsp;utilised
data from the CREATE study—a coordinated, five-country research initiative. The
three highlighted cases showed how AI-flagged suspicious nodules in patients
with no prior suspicion of lung cancer. They had entered the chest X-ray
imaging pathway via the Emergency Room with fever; as a routine radiology CXR
prior to treatment for ulcerative colitis; and CXR as part of a routine smoking
cessation program. The AI-powered finding enabled timely referral for CT
imaging confirmation and biopsy, confirming early-stage lung cancer in all
cases. Each patient underwent curative surgical intervention with favourable
outcomes. 

“This new evidence
presented at the World Conference of Lung Cancer has the potential to position
every chest X-ray as a chance to save a life,” states Prashant Warier,
Founder and CEO of Qure.ai. “AI can help to expand the early lung cancer
detection funnel by identifying high-risk pulmonary nodules that would
otherwise go unnoticed until it’s too late.”

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AI-Powered Chest X-Rays Catch Hidden Lung Cancer Risks — Even When No One’s Looking

Government of Goa Expands AI-powered Lung Cancer Screening with Qure.ai and AstraZeneca, Launches Innovative Pricing Policy for Lifesaving Therapies

This landmark decision supports affordability of high-cost therapies, starting with lung cancer and will continue to cover rare and complex non-communicable diseases across the state, making healthcare accessible to all

13 August, 2025 –&nbsp;In a progressive step toward making advanced, high-cost medical treatments more accessible, the Government of Goa is set to implement&nbsp;Pricing Policy for Innovative Lifesaving Therapies (PPILT). The policy aims to ensure fair and sustainable pricing for critical healthcare needs including medical devices, diagnostics, medicines etc, making them more affordable and within reach for all patients, especially those battling rare or complex diseases.

The policy was announced at the CME event organised on the topic: AI’s use in diagnosing Lung Cancer Early in Goa. 

Goa will be the first state in India to adopt this policy framework, which enables confidential and outcome-linked pricing agreements between the government and pharmaceutical innovators. The rollout will begin with lung cancer treatment. This progressive approach allows the state to procure advanced therapies at significantly reduced costs, enabling many more patients to benefit from the existing public healthcare budget.

“Innovative therapies for diseases like cancer, rare genetic disorders, and autoimmune conditions can cost upwards of INR 50 lakhs per year, placing them difficult for patients especially from underserved communities. Goa’s adoption of this pricing policy is vital and a timely step to advance health equity in the state.&nbsp; A value-based approach to pricing will improve access for patients and marks a new era focusing on helping more and more patients”, said&nbsp;ShriVishwajit Rane,&nbsp;Health Minister of Goa.

Since 2024, artificial intelligence has been embedded into Goa’s public healthcare system across 18 government hospitals and health centres, delivering measurable results at scale. Through Qure.ai’s qXR AI solution, more than 70,000 chest X-rays have been screened, detecting over 6,000 pulmonary nodules and flagging more than 500 individuals with high risk for lung cancer. This early detection has already led to confirmed lung cancer diagnoses and timely treatment, saving lives and reducing costs. The programme, led by the Government of Goa in partnership with Qure.ai and AstraZeneca, is a working example of how public and private sectors can combine technology and expertise to create systemic change and inform future health policy.

Commenting on the partnership,&nbsp;Prashant Warier, CEO and Founder of Qure.ai&nbsp;said, “The integration of AI into Goa’s public health network shows that digital transformation can start with AI as the foundation, rather than waiting for complete infrastructure. By screening over 70,000 chest X-rays in government facilities, we have proven that advanced technology can work effectively in public health systems and deliver measurable outcomes. Goa’s new pricing policy addresses the next critical step by ensuring that, once diseases are detected early, patients can access advanced therapies without prohibitive costs. This three-way partnership has created a first-of-its-kind model in which pharma innovation, coupled with technology, has made an end-to-end lung cancer patient screening and monitoring pathway possible. It has the potential to serve as a blueprint for health systems around the world.

”By establishing a new age pricing framework, it encourages both global and Indian pharma organisation to introduce novel treatments in the state sustainable, backed by a predictable and collaborative procurement pathway. Proposed by Organisation of Pharmaceutical Producers of India (OPPI), an independent body representing research based global pharmaceutical companies in India, this critical policy is expected to strengthen Goa’s preparedness for future health challenges and ensure long-term resilience by integrating affordability, innovation, and public health priorities.



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Government of Goa Expands AI-powered Lung Cancer Screening with Qure.ai and AstraZeneca, Launches Innovative Pricing Policy for Lifesaving Therapies

Newly accredited training program equips imaging related professionals with the knowledge and skills to maximize return on AI investment&nbsp;&nbsp;

To prepare healthcare workforces and providers for an AI-driven future, Qure.ai has expanded its Global AI Super User Training, to the United States. It has received approval from the American Society of Radiologic Technologists (ASRT). The Super User training equips Healthcare Professionals with the knowledge and skills to effectively apply AI in practice, transform clinical operations, optimize patient care, gain a solid return on AI investment, and foster positive partnerships within the medical community.&nbsp;

The <a href="https://www.qure.ai/us" target="_blank">Qure.ai USA</a> Super User initiative builds on global success in regions such as the UK and its National Health Service (NHS). ASRT has approved the program for Category A CE credits, granting participants 4 Continuing Education (CE) credits for course completion. This recognition aligns with the American Registry of Radiologic Technologists’ (ARRT) rigorous standards for professional development.&nbsp;

“Our expansion of the AI Super User Training program represents Qure.ai’s dedication to continuous learning and professional development within the imaging community,” said Samir Shah MD, Chief Medical Officer at Qure.ai. “With educational endorsements, we are now able to deliver formalized, professionally recognized training directly to hospitals, providing imaging professionals with an opportunity to gain CE credits while enhancing their skills in AI implementation and scaling adoption. By investing in the ongoing education of these caregivers, we can leverage AI as a transformative force, driving impactful partnerships within clinical environments.”&nbsp;

The Super User Training Program will have a critical focus on understanding how AI tools are integrated into the existing radiology workflows, including their intended use, strengths, and constraints. Participants will also engage with the regulatory and ethical frameworks governing AI deployment, alongside protocols for clinical review and post-market surveillance. The importance of patient and public involvement in AI-driven initiatives will be highlighted. The program will also include a practical demonstration of the deployed system in a clinical setting.&nbsp;

“This program is designed to build a foundational understanding of AI and its evolving role in radiology. AI is reshaping radiology fast and users need to be at the centre of that shift. This program is built to give, not just a working knowledge of AI, but the confidence to use it, and lead its integration into clinical practice”, said Shamie Kumar, Senior Director and Radiographer, Qure.ai.&nbsp;&nbsp;

The Qure.ai Super User endorsements in the US validate educational quality and professional value. These accreditations ensure radiographers and radiology technicians are equipped to integrate AI into their practices confidently, supporting digital evolution while fulfilling Continuing Education and professional development obligations.&nbsp;

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Qure.ai introduces Lung Cancer AI training with ASRT approval to support USA deployments

An innovative artificial intelligence (AI) system developed by Indian company <a href="http://qure.ai">Qure.ai</a> is set for trials in <a href="https://inews.co.uk/news/science/nhs-trial-ai-system-cut-lung-cancer-diagnosis-time-half-1465149">NHS hospitals</a>, expected to halve the time required for lung cancer diagnosis. The system, which uses AI to scrutinize chest X-rays, is projected to expedite treatment for many by focusing on more salient cases and thus accelerating the process from the first X-ray to diagnosis from 60 to 30 days.

“This has the potential to help huge numbers of people in the UK every year,” said Nick Woznitza of Canterbury Christ Church University.

The technology identifies suspicious lung nodules within minutes, expediting the path to a more detailed CT scan and diagnosis. Patients wait approximately two days for X-ray results and then need to schedule a separate CT scan if a cancer risk is detected.

Early diagnosis can make a significant difference for the thousands of patients diagnosed with lung cancer each year, with a third dying within 90 days of detection.

The AI system, funded by a £ 3.2 million NHS grant from SBRI Healthcare, will be piloted in seven hospitals until June 2023.

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NHS to trial AI system that could cut lung cancer diagnosis time by half

Health tech company <a href="http://qure.ai">Qure.ai</a> has been awarded a £3.2 million grant from the U.K. government's Small Business Research Initiative Healthcare in collaboration with the <a href="https://tech.eu/2022/02/07/med-tech-startup-bags-ps32-million-for-early-cancer-diagnosis-from-the-uk-government/">NHS Cancer Programme</a> and the Accelerated Access Collaborative. This funding aims to bolster Qure.ai's efforts in developing technology for the early detection and diagnosis of lung cancer.

The grant is a part of the SBRI competition, which launched in March 2021, and Qure.ai was among the select group of eight startups to receive funding. Their projects focus on leveraging advanced technologies to enable faster and more accurate identification of cancer.

With the new capital infusion, Qure.ai plans to conduct an extensive research program that will analyze the detection of lung nodules on chest X-rays, a key indicator of lung cancer. The program aims to gather evidence and better understand the feasibility of using artificial intelligence (AI) for triaging chest X-rays that raise concerns, allowing for prompt reporting.

CEO and Co-founder Prashant Warier emphasized the urgent need for improved lung cancer detection. He highlighted the aggressive nature of the disease and the lack of early visible signs, which often lead to delays in diagnosis and treatment, resulting in poor outcomes. The current five-year survival rate is a meager 14%, with 30% of patients succumbing within 90 days of diagnosis.

Warier believes that AI technology can revolutionize the early detection of potentially cancerous nodules from chest X-rays. By identifying lung cancer at earlier stages, survival rates can improve significantly, enabling the implementation of less toxic treatments and interventions. However, the varying protocols and high workloads pose challenges, making AI-based solutions invaluable in streamlining detection.

Qure.ai's cancer detection solution is already operational in over 50 countries, serving 500 sites worldwide and benefiting approximately four million patients. This new grant will help the company expand its research and development efforts, bringing them closer to its goal of saving lives through early lung cancer detection and diagnosis.

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Med tech startup bags £3.2 million for early cancer diagnosis from the U.K. government

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