# ADEPT-STAR therapy for high risk neuroblastoma

> **NIH NIH R43** · EXPRESSION THERAPEUTICS · 2023 · $400,000

## Abstract

PROJECT SUMMARY
Cancer remains a primary health concern despite significant advancements in treatment. In the past decade, cell
and gene (C&G) therapies along with immuno-oncology (I-O) therapies have transformed treatment expectations
by extending cancer free survival and complete remissions. Despite these remarkable successes, they are limited
to a subset of cancers and many significant challenges remain for broader application and to unlock the perceived
medical and commercial potential. Expression Therapeutics, Inc. (ET) is a fully integrated C&G therapy company
addressing these unmet clinical needs by using proprietary and complementary platform technologies that
optimize therapeutic transgene expression and gene delivery for the development of off-the-shelf allogeneic-
based gene therapies. These technologies address major challenges being encountered in C&G I-O: identification
of safe and effective tumor targets, maximizing treatment durability and efficacy and reducing the cost of goods.
Results of preliminary in vitro and in vivo studies support feasibility of the proposed application and the successful
development of this robust platform for the treatment of pediatric neuroblastomas and other forms of
neuroendocrine tumors (NETs) proposed in this application.

## Key facts

- **NIH application ID:** 10760738
- **Project number:** 1R43CA281633-01A1
- **Recipient organization:** EXPRESSION THERAPEUTICS
- **Principal Investigator:** Christopher Bradley Doering
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $400,000
- **Award type:** 1
- **Project period:** 2023-09-19 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10760738

## Citation

> US National Institutes of Health, RePORTER application 10760738, ADEPT-STAR therapy for high risk neuroblastoma (1R43CA281633-01A1). Retrieved via AI Analytics 2026-06-04 from https://api.ai-analytics.org/grant/nih/10760738. Licensed CC0.

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