Low-cost, high-sensitivity rapid COVID testing.
PCR-quality, CLIA-waived COVID testing with lower per-test cost than other CLIA-waived NAATs. Travel-ready RT-LAMP test with 96.1% Accuracy. Online patient scheduling and SMS delivery of patient results available as well*.
Uh-Oh Labs does not provide COVID testing services.
A new test for the new normal.
The UOL COVID-19 Test uses a new, patented chemistry which is ideally suited for detection of infectious disease: Loop-de-Loop™ RT-LAMP.
Loop-de-Loop™ RT-LAMP allows for the power of PCR without complex equipment. The result? Lower costs while maintaining accuracy.
Meeting your testing needs today
(and tomorrow).
Test Features
Fast Results: Positive results in as fast as 12 minutes, negative results in 40 minutes.
Highly Accurate: 96.1% Accuracy with no false positives when compared to a highly-sensitive PCR test.
Powerful Detection: Analytical sensitivity over 20,000x higher than some commercially-available rapid antigen tests.
Easy Workflow: Anterior nasal swab sample collection, set up and run a test in under 5 minutes.
Clear Results: Mobile app automatically interprets data with clear-text results.
Tech Enabled: Patient registration, SMS result delivery, and automated reporting also available*.
Beyond COVID: Additional tests utilizing the UOL COVID-19 Instrument in development
*requires additional software integration, contact sales for more info.
Accessible testing for all healthcare providers.
New services in pharmacies
Rapid results for primary care
Lower costs at rapid test sites
Curious how UOL can help your organization?
Supported by leading institutions and investors.
Uh-Oh Labs is developing diagnostic tests through our Loop-de-Loop™ platform which enables simplicity, speed, and lower costs while providing accurate, lab-grade results.
We are led by a team of experts in molecular diagnostics and bioengineering and are supported by the National Institute of Health’s Rapid Acceleration of Diagnostics (RADx) initiative and private investors, including Y Combinator.
With Support From
