# Rolosense: An innovative platform for automatic mobile phone readout of active SARS-CoV-2 particles (RADx-rad / SEED Administrative Supplement)

> **NIH NIH U01** · EMORY UNIVERSITY · 2022 · $500,000

## Abstract

Project summary:
The supplement application is in response to the RADx-rad announcement on the opportunity of
additional resources and funding support to facilitate the pathway to commercialization. As part
of this supplement we will pursue specific milestones to de-risk the Rolosense technology and
further move it toward commercialization. A major goal will be to introduce multiplexing
capabilities to simultaneously detect multiple viral targets from the same sample. Encoded
Rolosense particles with unique virus-binding ligands will be employed to achieve this goal.
Multiplexing to detect multiple viral targets will help distinguish the capabilities of Rolosense from
that of the current state-of-the-art. Another goal is to increase the speed and robustness of the
assay to facilitate direct sensing from breath condensate samples. This second goal will be
pursued by further developing fuel-free Rolosense that eliminates the need for RNA and RNaseH
enzyme in the assay. We see this as a critical step to reduce the cost of the assay and to increase
rigor and reproducibility to achieve the commercialization goals without concern for RNaseA found
in most biological samples.

## Key facts

- **NIH application ID:** 10648924
- **Project number:** 3U01AA029345-02S1
- **Recipient organization:** EMORY UNIVERSITY
- **Principal Investigator:** Khalid S. Salaita
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $500,000
- **Award type:** 3
- **Project period:** 2022-06-17 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10648924

## Citation

> US National Institutes of Health, RePORTER application 10648924, Rolosense: An innovative platform for automatic mobile phone readout of active SARS-CoV-2 particles (RADx-rad / SEED Administrative Supplement) (3U01AA029345-02S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10648924. Licensed CC0.

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