# Adapting KS-Detect technology to high-throughput COVID-19 screening

> **NIH NIH UH3** · CORNELL UNIVERSITY · 2020 · $153,746

## Abstract

Abstract
The COVID-19 pandemic represents a worldwide infectious disease challenge that disrupted our economic,
educational, and social norms in a way that was largely unimaginable just months ago. At present the most
efficacious method of limiting the spread of the disease has been to test those that exhibit symptoms – typically
by nucleic acid based viral identification methods – and isolate those that are positive. Even at this early stage
this approach has put significant strain on the diagnostic infrastructure of advanced countries, let alone those
with fewer resources. As we move beyond symptom-initiated confirmation diagnoses to the larger scale
screening that may be required to identify asymptomatic carriers and to restart sections of our economy, much
more rapid and higher throughput techniques will be required.
Under ongoing NIH/NCI UH2/UH3 (UH3CA202723) funding we have been developing TINY (Tiny Isothermal
Nucleic acid quantification sYstem). The TINY system is a self-contained, portable device for the detection and
LAMP-based quantification of viral nucleic acids designed for use in settings with limited resources. Through that
program, the system is currently deployed within Uganda for identifying Kaposi’s Sarcoma Herpes Virus (KSHV)
in human biopsies as a novel diagnostic technique for Kaposi’s Sarcoma. The system has been validated on
over 500 samples showing sensitivity and specificity of 93% and 95%.
Through this supplement request, we propose to upscale the TINY system to enable much high-throughput
screening – from 6 parallel samples to 96 - and adapt it to a run a recently developed LAMP assay for SARS-
CoV-2 detection which has already been validated on 182 patients in New York City. We believe that this will
simultaneously contribute to the need for higher throughout COVID-19 diagnostics and advance the NCIs desire
for platforms that can enable broader screening for viruses which are known to cause cancers (e.g. HPV in the
case of cervical cancer).

## Key facts

- **NIH application ID:** 10150981
- **Project number:** 3UH3CA202723-05S1
- **Recipient organization:** CORNELL UNIVERSITY
- **Principal Investigator:** David Carl Erickson
- **Activity code:** UH3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $153,746
- **Award type:** 3
- **Project period:** 2016-08-17 → 2021-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10150981

## Citation

> US National Institutes of Health, RePORTER application 10150981, Adapting KS-Detect technology to high-throughput COVID-19 screening (3UH3CA202723-05S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10150981. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*