Read our work on the BIOTIA-ID Urine Test, including peer-reviewed publications, white papers, conference posters, and more.
Many patients with recurrent, chronic, or complicated urinary tract infections experience frustration when their lab cultures come back negative despite ongoing symptoms. As many as 1 in 3 urine cultures return negative …
Urinary tract infections affect an estimated 404 million people globally each year, including 11 million in the United States. While most UTIs are uncomplicated, a significant subset progresses to complicated or recurren…
Analytical validation of the BIOTIA-DX mNGS platform across 368 urine samples in a Thai tertiary hospital. Demonstrated 98.7% sample-level sensitivity and 94.6% organism-level sensitivity vs. culture, detected 264 additional organisms in culture-negative samples (predominantly anaerobes and fastidious species), and achieved 81–94% genotype–phenotype concordance for AMR prediction across major antibiotic classes — supporting transportability to Southeast Asian populations with distinct microbial epidemiology.
Clinical validation of BIOTIA-ID across 1,470 urine specimens and >14,500 analytes, with 97.2% sensitivity and 99.6% specificity, plus AMR profiling on a 332-specimen subset. Demonstrates a comprehensive, end-to-end NGS diagnostic with notable advantages over culture.
Evaluation of the clinical-grade BIOTIA-ID Urine NGS Assay for comprehensive AMR gene detection across 168 culture-positive and 201 culture-negative urine specimens. NGS-identified AMR genes were confirmed by qPCR, demonstrating an evolution-proof alternative to PCR panels for rapid, broad AMR diagnosis in urinary tract infections.
Assessment of the BIOTIA-ID Urine NGS Assay as a tool to diagnose bacterial vaginosis (BV) directly from urine. The team developed an NGS-based Nugent-style score from the compositional dynamics of lactobacilli and BV-associated organisms across 201 culture-negative urine specimens from symptomatic patients and 20 healthy donors — extending UTI workup to include vaginal dysbiosis.
Development of an end-to-end clinical-grade metagenomics pipeline for UTI diagnostics combining an internal process control, QIACube-MDx extraction, Illumina NextSeq sequencing, and the BIOTIA-DX interpretable machine-learning analytic. Trained and benchmarked against clinical culture and qPCR, the workflow improves sensitivity for organisms that are difficult to culture or confirm.
