This technology provides a non-invasive diagnostic method using a panel of eight volatile organic compounds (VOCs) in urine, for the detection of Bladder Cancer. These VOCs are extracted from the urine analysed via Gas chromatrography-mass spectrometry (GC-MS) and data is interpreted with machine learning algorithms to distinguish between cancerous and non-cancerous samples.
Bladder cancer detection currently relies on cystoscopy, urine cytology, and imaging techniques. More recently, molecular assays such as UroVysion and NMP22 have also been approved by regulatory authorities. However, both conventional and newer methods remain costly, invasive, and often show limited sensitivity in early-stage disease. Accordingly, there is an unmet need for more accessible, accurate, and cost-effective diagnostic approaches.
First of its kind: No existing diagnostic method uses VOCs for bladder cancer detection; Non-invasive diagnostic method; 91% accuracy.
Early screening in Clinical diagnostics; Monitoring progression or recurrence; Diagnostic test in labs.
