Complicated urinary tract infections are severe or life-threatening infections that extend beyond a simple bladder infection and occur most frequently in hospitalized patients. There are over 2.8 million cases of complicated urinary tract infections in the U.S. each year, with 20% of cases progressing to urosepsis, leading to nearly 150,000 deaths each year. Effective management of complicated urinary tract infections requires the rapid identification of the causative bacterial pathogen(s) and the associated antibiotic resistance profile. The current standard of care, however, is urine culture, which requires 2-3 days from specimen collection until actionable information to guide patient treatment is generated. Hence, there is an urgent need for diagnostic tools that will allow for the rapid identification of uropathogens and their antimicrobial resistance/sensitivity profile(s). To address this unmet need, Day Zero Diagnostics (DZD) is developing a diagnostic workflow that leverages whole genome sequencing and machine learning to deliver high resolution species identification and antimicrobial resistance and susceptibility profiling from a patient sample without the need for urine culture. These data will guide evidence-based treatment decisions to improve patient care. The aims of this proposal are to (1) demonstrate ultra-high enrichment of bacterial DNA from a diverse range of species from urine samples and (2) optimize a sample preparation pipeline to deliver an actionable result in six hours or less, a clinically relevant timeframe for complicated urinary tract infection. The proposed Specific Aims, with quantifiable target metrics, are designed to demonstrate proof-of-concept in advance of the development of a commercial in vitro diagnostic. Upon Phase I completion, Phase II will focus on optimizing the workflow, expanding test capabilities, and analytical and clinical validation studies.