A commercialization-ready technology for the rapid precision diagnosis of urinary tract infections - solving scalability and reproducibility challenges

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Urinary tract infections (UTIs) are the most common infections treated in the community, with about 2% of all community consultations being related to UTIs. Today's clinical methods for diagnosing UTIs and selecting treatment rely on lengthy (> 16 hours) bacterial growth cultures. This results in treatment delays or the empirical administration of antibiotics before detecting or identifying the cause of the infection. The delayed or ineffective use of antibiotics leads to serious consequences such as kidney infections or urosepsis, and the excessive use of antibiotics increases the rate of antibiotic-resistant infections. The existing rapid UTI tests, relying on urine dip sticks, do not provide the species identification that is needed for treatment selection. There is an urgent unmet need for a platform that can detect and identify the causative UTI pathogens during a single doctor's consultation to enable the prescription of precision treatments. This poses the requirement for a reliable yet simple, rapid, and cost-effective test for detecting and identifying pathogens that cause UTI. We have been developing such rapid test, based on an electrochemical chip functionalized with bacterium-capturing functional DNA sequences, for detecting and identifying the leading organisms that cause UTIs, and have demonstrated clinically-acceptable sensitivity and specificity. In this proposal, we will aim at developing a market-ready chip-based prototype that detects a panel of bacteria using different functional nucleic acid sequences (i.e. is multiplexed) and can be manufactured using the scalable screen printing technology. We will then run a small pilot study to assess the feasibility of this multiplexed and scalable system in analysing clinical urine samples for detecting and identifying UTI-causing pathogens. The market translation of this Canadian technology is expected to (1) enable patient-centered