# Single clone discovery using an image-based cell isolation platform

> **NIH NIH R44** · ENRICH THERAPEUTICS, INC. · 2021 · $829,125

## Abstract

Abstract
Characterizing both functional and genetic heterogeneity among a pool of cells remains
a major scientific challenge in immunology, cancer research, neurobiology and
developmental biology. Isolating cells with the same phenotype is key to understand
such heterogeneity. We would like to develop a non-fluidic, unique technology, LCD
aided selection under microscope (LASUM, Fig.1) to address this need. During the
phase I of this project, we completed the alpha version of prototype design and
demonstrated its utility in three proof-of-concept experiments: (a) blood cell removal; (b)
phage enrichment on single beads; (c) isolation of tumor-killing immune cell clones. We
would like to continue our effort to bring this technology to market, which will be low-cost,
high throughput, debris resistant, image-based with operation simplicity as preparing a
microscope slide or washing a microtiter plate. Besides the device, we will unify the
fragmentated cell isolation market using two associated kits: Enrich-Live and Enrich-
Seq. The successful commercialization of this device/kits will enable thousands of cell-
biology labs and hospitals in manipulating single cells on a computer screen.

## Key facts

- **NIH application ID:** 10239253
- **Project number:** 5R44AI147734-03
- **Recipient organization:** ENRICH THERAPEUTICS, INC.
- **Principal Investigator:** QI ZHAO
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $829,125
- **Award type:** 5
- **Project period:** 2020-08-14 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10239253

## Citation

> US National Institutes of Health, RePORTER application 10239253, Single clone discovery using an image-based cell isolation platform (5R44AI147734-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10239253. Licensed CC0.

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