The study, led by Professor Riccardo Finotello, analyzed 139 dogs across Italian veterinary centers to validate the proprietary SINO platform developed by LatusPet. Unlike traditional diagnostic methods that compare a single disease against a healthy control group, this trial tested the platform against a complex mix of concurrent conditions and healthy subjects. This approach mimics the unpredictable nature of everyday clinical practice, providing a more rigorous assessment of the technology's diagnostic reliability.
Oxford Startup Unveils AI-Driven Blood Test for Canine Disease Detection
A single blood sample can now reveal a spectrum of canine health risks, according to a peer-reviewed study published in Frontiers in Veterinary Science. Researchers from the University of Oxford and Link University successfully combined NMR metabolomic analysis with machine learning to identify cancer and cardiovascular disease with 90% accuracy.
By reading the chemical signatures left in the blood, the system offers a window into a pet's health before physical symptoms emerge. Dr. Simone Scoccianti, Chief Veterinary Officer at LatusPet, noted that the technology aims to shift veterinary medicine from reactive treatment to proactive care. Beyond initial screening, the research team is currently exploring the platform's utility in monitoring treatment responses and tracking disease remission over time. LatusPet intends to expand the number of detectable conditions annually and is actively seeking veterinary partnerships to integrate the platform into routine clinical check-ups.
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