The fight against antibiotic resistance, one of the most pressing healthcare concerns worldwide, will require an all-of-the-above approach, with one important element being the development of innovative rapid diagnostics. PhAST Corp. has developed a new antibiotic susceptibility testing (AST) approach that has promise to significantly accelerate AST, from tens of hours to tens of minutes. It is based on the quantification of changes in single-cell pathogen phenotypes upon antibiotic exposure through single-cell, time-lapse imaging. By systematically using multiple single-cell phenotypes, either individually or in combination, the method is broadly applicable to a wide range of pathogens. Initial data obtained with reference strains, clinical isolates and direct patient samples have revealed clear phenotypic changes consistently within 15?90 min of antibiotic exposure, a considerable reduction over the many hours or days typically required by current approaches. Importantly, the PhAST diagnostic platform works directly from patient samples, entirely bypassing the time-consuming isolation and growth step that can last 1-2 days in gold standard assays and is still required also in all recently developed rapid AST approaches. The goal of this project is to develop and extensively validate PhAST's direct-from-sample approach, focusing on urinary tract infections (UTIs), one of the most common bacterial infections associated with significant morbidity and healthcare costs due to the high rates of antibiotic resistance. The work will be structured around two aims, focusing on (Aim 1) validating PhAST with reference strains and clinical isolates, in order to develop a mathematical model that determines susceptibility from changes in single-cell phenotypes;
and (Aim 2) validating PhAST using a large set of direct patient urine samples. Our initial focus will be on the first and second line UTI treatment options, including nitrofurantoin, trimethoprim/sulfamethoxazole and ciprofloxacin, though the method applies broadly to antibiotics of all mechanisms of action. The approach will provide both qualitative results (susceptible / intermediate / resistance categorization) and quantitative results (Minimum Inhibitory Concentration or MIC determination). Performance will be evaluated by comparison with the gold-standard broth microdilution method to obtain categorical agreement, essential agreement and error rates (minor / major / very major errors). The proposed work will in particular include extensive testing with resistant strains, including multi-drug resistant strains. Ample preliminary data on a wide range of pathogen-antibiotic combinations and direct patient urine samples has contributed to significantly de-risk the use of this new and potentially transformative method for AST, paving the way for its extensive validation for the case of UTIs, proposed here. A successful outcome of the proposed work will be the ability to obtain substantially equivalent diagnostic performance compared to gold standards, within 60?90 minutes and directly from patient urine samples. Success will pave the way for a future Phase II proposal that focuses on readying the hardware for multi-site clinical validation studies, in preparation for regulatory approval. The long-term goal of this work is to use the new concept and technology underpinning PhAST to accelerate the time-to-decision for antibiotic treatment options and thereby enhance antibiotic stewardship not only for UTIs, but for a broad range of infections. The fight against antimicrobial resistance demands new ideas for considerable acceleration in diagnostics: PhAST has the potential to help address this challenge.
) Antibiotic resistance is one of the most urgent healthcare threats worldwide. Faster diagnostic methods to test the antibiotic susceptibility of pathogens are critical for healthcare providers to determine the best treatment option and to avoid mis- and over-usage of antibiotics. We will develop a diagnostic method ? PhAST ? that rapidly tests a pathogen's antibiotic susceptibility directly from a patient sample, by measuring changes in its single-cell phenotypes upon antibiotic exposure using time-lapse imaging.