# Development of platforms for sorting, production, editing of beta cells

> **NIH NIH R01** · BROAD INSTITUTE, INC. · 2024 · $623,544

## Abstract

PROJECT SUMMARY
Patients suffering from type 1 diabetes must undergo burdensome, often lifelong, exogenous insulin
dependence. Up to now, the only available replacement therapy is to transplant islets from cadaveric donors.
However, such procedures present hurdles such as the scarcity of available donors and the rejection of
transplanted cells by the patient’s immune system. Also, over time, the transplanted islets tend to die. Several
types of stem cells, including embryonic stem cell and induced pluripotent stem cell, have been extensively
studied to generate glucose-responsive insulin-secreting cells and represents a more tenable source of islets.
However, a significant concern for transplantation therapy is the need for immunosuppressive drugs, which
exhibit long term side effects and hinders the feasibility of this approach to the large population of T1D patients.
Furthermore, cost-effective and large-scale production of these stem cell-derived beta cells is still a major
challenge. We propose to apply chemical biology and genome engineering approaches to develop platforms
for efficient sorting, production, and editing of these beta cells.
PHS 398/2590 (Rev. 06/09) 1 Continuation Format Page

## Key facts

- **NIH application ID:** 10920460
- **Project number:** 5R01DK132900-02
- **Recipient organization:** BROAD INSTITUTE, INC.
- **Principal Investigator:** Amit Choudhary
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $623,544
- **Award type:** 5
- **Project period:** 2023-09-05 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10920460

## Citation

> US National Institutes of Health, RePORTER application 10920460, Development of platforms for sorting, production, editing of beta cells (5R01DK132900-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10920460. Licensed CC0.

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