Colombo, Sri Lanka – May 8, 2026 – A team of Sri Lankan-American researchers affiliated with the University of Colombo and Massachusetts Institute of Technology has unveiled an innovative artificial intelligence system capable of detecting chronic kidney disease (CKD) in its earliest stages, potentially revolutionizing preventive healthcare for millions worldwide.
The AI-powered diagnostic tool, named “NephroScan,” analyzes routine blood and urine test results with unprecedented accuracy, identifying biomarkers associated with kidney dysfunction up to two years before traditional diagnostic methods can detect the condition. In clinical trials involving over 10,000 patients across Sri Lanka, India, and the United States, the system demonstrated 94% accuracy in predicting CKD progression, significantly outperforming current standard screening approaches.
Dr. Amara Jayawardene, lead researcher and professor of Biomedical Engineering at the University of Colombo, explained the significance of the breakthrough: “Chronic kidney disease affects approximately 850 million people globally, yet early detection remains challenging because symptoms often don’t appear until substantial kidney damage has occurred. NephroScan changes this paradigm by enabling intervention during the reversible stages of the disease, potentially preventing or delaying the need for dialysis or transplantation.”
The technology employs machine learning algorithms trained on diverse datasets representing various ethnicities, ages, and risk factors, addressing a critical limitation of many existing AI diagnostic tools that perform poorly on underrepresented populations. Special attention was given to ensuring the system works effectively for South Asian populations, who face disproportionately high rates of kidney disease due to genetic and environmental factors.
Healthcare officials in Sri Lanka’s Ministry of Health have expressed interest in piloting NephroScan in government hospitals later this year, particularly in rural clinics where access to specialized nephrologists is limited. The AI system requires only standard laboratory equipment and can be integrated into existing hospital information systems, making it cost-effective for resource-constrained settings.
Beyond kidney disease, the research team is adapting the underlying technology for early detection of other chronic conditions including diabetes-related complications and cardiovascular disorders. They plan to seek regulatory approval from both the Sri Lankan Pharmacy Board and the U.S. Food and Drug Administration within the next 18 months.
As healthcare systems worldwide grapple with rising chronic disease burdens, innovations like NephroScan represent a promising shift toward preventive, AI-enhanced medicine that could improve outcomes while reducing long-term treatment costs.