Automated, compact system to detect TB and drug resistance quickly
Official title: Development of an automated, compact sample-to-sequencer ready system for extensively/multi drug-resistant TB detection
Funded at Redbud Labs, INC. · NIH-11262033 · Data updated 2026-11-12
A new automated device aims to rapidly detect tuberculosis and key drug-resistance genes in patient samples to help start the right treatment sooner.
Quick facts
| Grant type | Sbir 1 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Redbud Labs, INC. NIH-funded |
| Lab location | 1 site (Durham, UNITED STATES) |
| Project start | September 30, 2026 |
| Project end | September 29, 2027 |
| Funding year | 2025 |
| Award (this year) | $306,872 |
| NIH project number | 1R43JG000001-01A1 |
| Project ID | NIH-11262033 on NIH RePORTER |
Who could benefit from this research
✓Could help
Individuals with suspected TB or known exposure, and clinicians needing rapid drug-resistance information.
✕Less likely to help
Patients without suspected TB or where a rapid test is not indicated would not directly benefit.
What this research studies
This project focuses on creating a compact, automated platform that can take patient sputum samples, prepare them, and perform long-read sequencing to identify TB and resistance genes in under 30 minutes. It addresses the challenge of processing uncultured sputum without extensive genome shearing, aiming to make testing faster and more accessible, even in resource-limited settings. If successful, it could shorten time to diagnosis and tailor treatments to avoid ineffective antibiotics. The work blends innovation in sample prep with sequencing technology to bring faster, actionable results to clinicians and patients.
Why it matters
Potential benefit: If successful, patients with TB could receive faster and more accurate diagnoses and personalized treatment sooner.
How similar studies have gone: Previous platforms struggle with providing comprehensive M/XDR gene detection and rapid results; this project represents a novel integration of automated sample prep with long-read sequencing.
Where this research is happening
-
Redbud Labs, INC.
Durham, United States Active
Researchers
- Principal investigator: Fisher, Jay Kenneth — Redbud Labs, INC.
- Study coordinator: Fisher, Jay Kenneth
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.