# Hydrogel nanovial technology for single-cell sorting based on extracellular vesicle production

> **NIH NIH R21** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2021 · $176,084

## Abstract

SUMMARY
Secreted extracellular vesicles (EVs) are an emerging therapeutic category with significant potential in the
treatment of disease. However, critical challenges remain with the study and production of these cell-derived
therapeutics. Heterogeneous populations of cells, like mesenchymal stem cells (MSCs) that produce different
amounts and types of EVs along with unknown mechanisms of their biogenesis hamper the scaling of uniform
EV products for clinical translation. Sorting based on EV-secretion rate can enable the study of genetic
underpinnings that lead to high EV biogenesis. Producer cells that are transfected to secrete biologics, such as
antibody-based therapeutics, are traditionally sorted based on their secretion rate to isolate clones that produce
large quantities of antibody, and similar approaches to sort and select highly-secreting populations will be
advantageous for obtaining high quality EV-secreting cells. However, methods to rapidly sort out single cells
secreting high levels of EVs are not currently available and cell-to-cell variability cannot be assessed in bulk,
such that the separation of cells that produce EVs at higher rates or with more uniform contents is not feasible.
We propose to develop a lab on a particle platform to sort MSCs based on EV secretion at the single-cell level
using standard fluorescence activated cell sorters (FACS). Our approach leverages cavity-containing hydrogel
microparticles, or nanovials, that allow seeding and adhesion of MSCs followed by the uniform formation of
droplets around the nanovials with simple pipetting steps to confine secreted EVs for capture on the particles.
Captured EVs can be stained and the corresponding secreting cells sorted based on the level of EVs secreted
using commercial FACS machines. We propose to develop the on-nanovial immunoassay to detect secreted
EVs and evaluate it in sorting of human MSCs that secrete the highest levels of EVs. We will identify the
timeframe over which MSCs selected for this high secretion phenotype is stable. Our technology can aid in
clinical studies for EV-based therapeutics, defining populations of cells that produce uniform EV therapeutics at
high rates, and will further expand the ability to define the cellular underpinnings of EV-based products. Improved
EV production can enable MSC derived EV-based (MSC-EV) treatments which have shown initial efficacy in one
clinical trial for chronic kidney disease, and there are currently 10 on-going trials including two for COVID-19.

## Key facts

- **NIH application ID:** 10193200
- **Project number:** 1R21GM142174-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Dino Di Carlo
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $176,084
- **Award type:** 1
- **Project period:** 2021-06-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10193200

## Citation

> US National Institutes of Health, RePORTER application 10193200, Hydrogel nanovial technology for single-cell sorting based on extracellular vesicle production (1R21GM142174-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10193200. Licensed CC0.

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