# Novel immunotherapy against MOG antibody disease

> **NIH NIH R44** · EVOQ THERAPEUTICS, INC. · 2024 · $1,000,000

## Abstract

PROJECT SUMMARY/ABSTRACT
Myelin oligodendrocyte glycoprotein (MOG) antibody disease (MOGAD) is a rare disease characterized as a
neurological, inflammatory, demyelinating disorder of the central nervous system. The symptoms of MOGAD
include vision loss, symptoms associated with damage to the spinal cord, as well as seizures. While the current
standard of care against MOGAD includes steroids and immunosuppressants, they are associated with systemic
immunosuppression with complications and frequent debilitating relapses. Thus, there is an urgent need for new
targeted treatment options for MOGAD patients. As MOG is the sole target antigen in MOGAD patients, MOG is
an attractive target. Here, we propose to develop a novel nanoparticle platform for the treatment of MOGAD.
Toward this goal, we have developed synthetic high-density lipoprotein NanoDiscs for efficient delivery of antigen
peptides to lymph nodes. Our preliminary data shows that NanoDiscs induce robust antigen-specific immune
tolerance and disease modification in murine models of experimental autoimmune encephalomyelitis (EAE) and
another autoimmune disorder, type 1 diabetes (T1D). Based on our compelling proof-of-concept data, here we
propose to further develop NanoDiscs for the treatment of MOGAD.

## Key facts

- **NIH application ID:** 11007654
- **Project number:** 9R44TR005293-02
- **Recipient organization:** EVOQ THERAPEUTICS, INC.
- **Principal Investigator:** Weston Daniel
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,000,000
- **Award type:** 9
- **Project period:** 2022-07-15 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11007654

## Citation

> US National Institutes of Health, RePORTER application 11007654, Novel immunotherapy against MOG antibody disease (9R44TR005293-02). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/11007654. Licensed CC0.

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