# A first in human clinical study of TT101, a synthetic immunomodulatory material to build new functional tissue over exposed bone as a one time treatment for diabetic limb preservation patients

> **NIH NIH R44** · TEMPO THERAPEUTICS, INC. · 2021 · $1,368,090

## Abstract

SUMMARY / ABSTRACT
According to the United States Centers for Disease Control, 34 million Americans have diabetes. One of the
most prevalent complications of diabetes is the diabetic foot ulcer (DFU). Approximately 25% of diabetics will
develop a non-healing foot ulcer in their lifetime. DFUs are highly susceptible to infection and tissue necrosis
that require extreme surgical interventions to remove extensive dead tissue and preserve the limb. Unfortunately,
tissue damage is often so extensive that these surgical procedures leave behind complex wounds with
exposed bone, tendon, and or fascia – which are notoriously difficult to heal and where current bioengineered
skin products do not have benefit. Indeed, foot ulceration is the most common single precursor of lower extremity
amputations among persons with diabetes and is a precursor to approximately 85% of the lower extremity
amputations within this population – exceeding 100K every year in the US alone. Furthermore, reported mortality
rates for DFU patients range from 55 to 74% after 5 years, which are above cancers such as prostate, breast,
and colon.
The current treatment options for complex wounds are scarce. Bioengineered skin sheets are unable to build
new tissue over these exposed bone surfaces, and basic wound care has little effect as well. Negative Pressure
Wound Therapy (NPWT) has shown improved healing, but this management tool requires intensive outpatient
care and is cumbersome. There is a clear need for a regenerative therapy that can have effect in the ‘vertical’
phase of wound healing, where building new tissue volume is paramount to success. This significant clinical
need creates a considerable market opportunity.
To answer this market need, Tempo Therapeutics has developed the MAP Wound Matrix – a flowable synthetic
tissue scaffold based on our proprietary Microporous Annealed Particle (MAP) technology. MAP Wound Matrix
is flowable (ease of application) and fills wounds of any shapes and sizes, and then converts to a hyper-porous
sponge-like network in the wound site after exposure to white light. The hyper-porosity geometry promotes fast
granulation tissue, and early vascularization, when compared to leading decellularized tissue-based matrices,
with minimal inflammatory response in multiple animal models including diabetic pigs. Unlike most of these
matrices, MAP does not require multiple applications. Tempo has already completed the necessary studies to
support clinical trial application to FDA with safety and performance data and has completed initial scale-up of
product manufacturing.
In the proposed Direct-to-Phase II work, we will pursue the development of MAP Wound Matrix and conduct a
multicenter, randomized pilot clinical study to evaluate its efficacy and safety to treat complex wounds in diabetic
patients. Successful completion of this study will bring clinical evidence of the performance of MAP Wound Matrix
as well as crucial information to set the next larger cl...

## Key facts

- **NIH application ID:** 10326178
- **Project number:** 1R44DK130778-01
- **Recipient organization:** TEMPO THERAPEUTICS, INC.
- **Principal Investigator:** Stephanie Deshayes
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,368,090
- **Award type:** 1
- **Project period:** 2021-09-15 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10326178

## Citation

> US National Institutes of Health, RePORTER application 10326178, A first in human clinical study of TT101, a synthetic immunomodulatory material to build new functional tissue over exposed bone as a one time treatment for diabetic limb preservation patients (1R44DK130778-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10326178. Licensed CC0.

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