L2M - NSERC Development of a tool for diagnosis of diabetic complications

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The researchers here propose developing a software application that can leverage artificial intelligence and machine learning to diagnose a disease using inputted biomarker levels. The software application would first be customized for disease causing blindness in diabetes, also known as diabetic retinopathy (DR). Dr. Chakrabarti and his team, with the assistance of WORLDiscoveries, have filed for a patent currently at the PCT stage (PCT/CA2021/050924). The current technology uses expression levels of a set of genes to diagnose if the patient has developed DR and what stage they are at. Patient differences exist, and the team is currently testing 500 additional patients to validate the biomarker technology (patent application filed). The data from this study will be fed into the current software application that has been planned to be developed. This will allow with much accuracy, family physicians and ophthalmologists to enter the data from the laboratory test into this system to accurately diagnose the progression of the disease.Furthermore, the application will also be developed for other disease diagnoses that are biomarker level dependent. The current software application algorithm will be tailored to disease-specific use. The goal will be to partner with biomarker testing panels and centres to integrate the existing software into their workflow. The current technology as a software application would the first of its kind to be used in the rapidly growing field of using biomarkers to identify and validate diseases.