iOncology.ai: Indian AI Platform Showcased in BRICS Health Journal
iOncology.ai, an AI platform for cancer care, is spotlighted in the BRICS Health Journal, highlighting its potential in transforming oncology in emerging economies.
An Indian artificial intelligence platform, iOncology.ai, developed to enhance cancer care, has gained international attention with its inclusion in the BRICS Health Journal. This feature coincided with the BRICS Summit held on September 12-13, 2026, where the platform's capabilities and potential impact were discussed.
Collaboration and Development
The platform is a collaborative effort by the All India Institute of Medical Sciences (AIIMS), New Delhi, and the Centre for Development of Advanced Computing (C-DAC), Pune. It has received backing from the Ministry of Electronics and Information Technology. iOncology.ai is designed to integrate and analyze cancer-related clinical data, facilitating early detection, risk assessment, treatment planning, and patient-data management.
Review Highlights and Future Plans
A review titled “Transforming cancer care in emerging economies: India’s AI innovation” by Ashok Sharma and his team from AIIMS and C-DAC explores how AI can improve cancer screening and diagnosis. The platform is currently in the pilot stage of clinical validation to determine its effectiveness and potential application in real-world clinical settings.
Dr. Ashok Sharma emphasized the platform’s role in addressing cancer-care disparities, particularly in the Global South. He noted the importance of strengthening cancer prevention, diagnosis, and treatment through evidence-based solutions tailored for emerging economies. BRICS countries, accounting for over 40% of the global population, face significant challenges in cancer care, with 9 million new cases and 4.66 million deaths annually.
Integration and Validation
iOncology.ai is part of India’s broader initiative to enhance cancer control and digital health infrastructure. It utilizes curated clinical, radiological, and histopathological datasets, with plans to incorporate genetic data and interoperability with electronic health records. However, the platform is still under evaluation in research mode and lacks peer-reviewed evidence of its diagnostic accuracy and clinical utility. Multicentre validation is necessary before it can be widely adopted in clinical practice.