# Rapid and Simple Paper Strip Test for the Multiplexed Detection of Gastrointestinal Pathogens at the Point-of-Need

> **NIH NIH R44** · GODX, INC. · 2020 · $239,594

## Abstract

Project Summary GoDx Phase 2
Rapid and Simple Paper Strip Test for the Multiplexed Detection of Gastrointestinal
Pathogens at the Point-of-Need
In this Phase 2 SBIR project, we will be developing the prototype multiplexed paper strip device
for the detection of gastrointestinal pathogens at the point-of-need in < 30 minutes. We have
demonstrated the feasibility of a novel and simple stool sample preparation using hollow
microsphere “molecular buoys”, and the multiplexed detection of DNA using isothermal
amplification in Phase 1. In Phase 2, we will develop and evaluate our multiplexed prototype
device. We will evaluate the prototype device using 800 samples from an NIH-IRB approved
protocol through our CRADA collaboration with Dr. Wendy A. Henderson at the NIH. We expect
a sensitivity (>90%) and specificity (>90%) to the Biofire PCR GI Panel data on the same
samples. The goal of the Phase 2 project is to develop an optimized prototype that will be
evaluated in the IDE-exempt NIH clinical study. We will also develop for commercialization a
Research Use Only kit for the point-of-need purification of nucleic acids using our microsphere
sample preparation technology.

## Key facts

- **NIH application ID:** 10052033
- **Project number:** 3R44TR001912-03S1
- **Recipient organization:** GODX, INC.
- **Principal Investigator:** Chang Hee Kim
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $239,594
- **Award type:** 3
- **Project period:** 2017-04-15 → 2021-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10052033

## Citation

> US National Institutes of Health, RePORTER application 10052033, Rapid and Simple Paper Strip Test for the Multiplexed Detection of Gastrointestinal Pathogens at the Point-of-Need (3R44TR001912-03S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10052033. Licensed CC0.

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