New York-based Biotia has published a clinical validation study in Microbiology Spectrum (American Society for Microbiology) for its next-generation sequencing and machine learning-based urinary tract infection test, achieving 97.2% sensitivity and 99.6% specificity across 1,470 clinical specimens.
The BIOTIA-ID Urine Test addresses a persistent diagnostic gap: standard culture-based UTI testing frequently misses fastidious organisms, particularly in recurrent or complicated cases – leading to misdiagnosis, underdiagnosis, and inappropriate antibiotic use. Biotia’s approach enables culture-independent detection of bacteria and fungi alongside antimicrobial resistance gene profiling to guide targeted therapy. The company’s proprietary machine learning classifier, BIOTIA-DX, reduces false positives by filtering out contamination and commensal organisms.
UTIs are one of the most common infections globally and disproportionately affect women – roughly 50-60% of women will experience at least one UTI in their lifetime, and recurrent UTIs remain notoriously difficult to manage. Misdiagnosis with standard cultures is a major driver of the cycle of recurring infections and repeated antibiotic courses that many women experience.
“By combining clinical metagenomic sequencing with machine learning, we can detect a broader range of pathogens with high confidence and support more precise, data-driven care,” said chief scientific officer Mara Couto-Rodriguez. “These findings highlight the potential of NGS-based diagnostics to advance UTI care, reduce diagnostic uncertainty, and support antimicrobial stewardship.”
The BIOTIA-ID Urine Test is approved by New York State as a laboratory-developed test and is already available for clinicians and patients. Biotia, a spinout of Cornell Tech, also recently launched a “test to treat” offering for recurrent UTI patients. The company operates a CLIA/CLEP lab in New York.
