# Toxicological screening in a single animal format

> **NIH NIH R43** · THERAMIX, LLC · 2022 · $259,613

## Abstract

Abstract
Toxicity testing with animals has limitations with regards to cost, time, reliability, and animal
welfare. We propose to develop a novel toxicological screening approach in a single animal format
for quickly assessing the safety of chemicals with reduction of animal use and improved animal
welfare. We will develop a new testing procedure with which we could perform tests in only one
animal to obtain information on the effective doses, impacted tissues, and organs, and
toxicodynamics of toxicants, which usually need experimenting on hundreds of animals, months
to years efforts, and enormous biochemical and pathological analyses in the traditional
toxicological study. The breakthrough technique is a reporter system for real-time mapping cellular
damage caused by chemical substances in the whole body. It can detect the toxic effects of
substances as early as cellular damage occurs in the body. Whereas in traditional animal testing,
adverse effects only become detectable/measurable in animals exhibiting significant degrees of
adverse health effects after receiving high doses of test chemicals. Instead of taking the animal
body as a "black box" in the traditional testing, our new technique enables real-time monitoring
responses to a chemical by making the animal body transparent for directly observing adverse
effects at the cellular level.

## Key facts

- **NIH application ID:** 10483244
- **Project number:** 1R43ES034324-01
- **Recipient organization:** THERAMIX, LLC
- **Principal Investigator:** Guochun He
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $259,613
- **Award type:** 1
- **Project period:** 2022-09-23 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10483244

## Citation

> US National Institutes of Health, RePORTER application 10483244, Toxicological screening in a single animal format (1R43ES034324-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10483244. Licensed CC0.

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