Qure.ai Powers India's First AI-Led Incidental Pulmonary Nodule Clinic at Thangam Cancer Centre

VMPL
New Delhi [India], March 19: Qure.ai, a global leader in artificial intelligence (AI) for healthcare, today announced the launch of India's first AI-led Incidental Pulmonary Nodule (IPN) Detection Clinic at Thangam Cancer Centre in Namakkal, Tamil Nadu.
This initiative is part of Project BreatheEZ, a broader strategic collaboration between Qure.ai and Johnson & Johnson MedTech, India, designed to establish AI-powered IPN Clinics across leading hospitals in India. These clinics will act as integrated screening hubs, optimizing early detection, triaging, and follow-up care for lung cancer patients.
The Thangam Cancer Centre IPN Clinic is India's first dedicated Incidental Pulmonary Nodule (IPN) clinic designed to systematically detect and track lung nodules using Qure.ai's FDA-cleared qXR solution as part of an integrated screening and care pathway. This structured, AI-powered incidental screening program, established within a hospital setting will enable the detection of nodules as small as 6mm from routine chest X-rays. This minimally invasive, cost-effective approach unlocks the possibility of diagnosing lung cancer at an early stage, giving patients significantly better chances of survival and improved outcomes.
Speaking about the launch, Dr. Saravana Rajamanickam MS, MCh, Director, Surgical Thoracic Oncology, Thangam Cancer Centre & Research Institute, said, "Our vision has always been to bring the best of global healthcare technology to the people. With the launch of this AI-powered clinic, we are not only enhancing our ability to detect lung cancer early but also redefining cancer care for millions in India. Combining the precision of AI with advanced surgical techniques like robotics gives us a comprehensive pathway from early detection to advanced treatment, all under one roof."
Qure.ai's qXR technology works by automatically flagging pulmonary nodules, often early indicators of lung cancer, on routine chest X-rays. The AI system also assists radiologists by providing malignancy risk scores, tracking nodule progression over time, and ensuring seamless care coordination between radiology, pulmonology, and oncology teams.
Prashant Warier, CEO and Co-Founder, Qure.ai, said, "At Qure.ai, we are committed to bridging critical healthcare gaps with AI. The partnership with Thangam Cancer Centre to turn routine chest X-rays into early warning tools is a powerful example of the potential of our AI solutions. We look forward to scaling this model across India's healthcare ecosystem."
This hub-and-spoke model, piloted at Thangam Cancer Centre, is expected to serve as a blueprint for similar AI-powered clinics across India, supported by Johnson & Johnson MedTech, India.
Lung cancer remains one of world's deadliest cancers, largely due to late-stage diagnosis. India clocks ~112,000 new lung cancer cases1, annually with only ~4% cases2 detected at an early stage. Most patients are detected only when symptoms appear, by which time treatment options are limited. This first-of-its-kind AI-powered clinic brings hope for earlier detection, especially for non-smoking patients, who now make up a growing proportion of lung cancer cases in India and the rest of the world.
About Qure.ai
Qure.ai is a health tech company that uses deep learning and Artificial Intelligence (AI) to make healthcare more accessible and equitable for patients worldwide. Our solutions power the efficient identification and management of Tuberculosis (TB), Lung Cancer and Stroke to support clinicians and propel developments in the pharmaceutical and medical device industries. We empower healthcare by helping to identify conditions fast, prioritize treatment planning and ultimately improve quality of patient life.
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Amrutha Joseph - Amrutha.joseph@qure.ai
Reference:
1 https://journals.lww.com/ijmr/fulltext/2022/02000/a_clinicoepidemiological_profile_of_lung_cancers.7.aspx
2 https://journals.lww.com/lungindia/fulltext/2023/01000/navigating_patient_journey_in_early_diagnosis_of.9.aspx
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