# Development and Validation of Animal Models and/or Outcome Measures

> **NIH NIH U19** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2024 · $767,756

## Abstract

ABSTRACT
Research Component (RC) 2 includes the development and validation of novel animal models that model a
specific pain type, and/or the development and validation of novel outcome measures. Dr. Scherrer has
participated in a consensus meeting of the Preclinical Pain Research Consortium for Investigating Safety and
Efficacy (PPRECISE) Working Group, sponsored by the Analgesic, Anesthetic, and Addiction Clinical Trial
Translations, Innovations, Opportunities, and Networks (ACTTION), a public-private partnership with the U.S.
Food and Drug Administration. This working group was tasked with making recommendations to improve
experimental design and reporting transparency and minimize conscious and unconscious experimental bias to
increase scientific rigor, reproducibility, and translatability in the pain field. Based on the conclusions of this
working group, we propose to develop and validate three novel outcome measures that bring innovative, state-
of-the-art machine learning, optical recording of neural activity in behaving mice, and analytic methods from the
systems neuroscience field into the field of pain drug discovery. These novel outcome measures will be used in
RC5 in vivo efficacy studies to elevate the scientific rigor and translatability of our antinociceptive NTSR1 asset
discoveries. In Aim 1, we implement machine learning–based outcome measures to standardize and automate
in vivo efficacy studies of NTSR1 assets. Manual scoring of rodent nocifensive behaviors by humans is inherently
subjective and varies considerably between experimenters, weakening data robustness and leading to
reproducibility issues. Another limitation of manual scoring is the low throughput of the method. We will develop
and validate the use of DeepEthogram, a machine learning pipeline for supervised behavior classification from
raw pixels, to reproducibly and automatically score reflexive and affective-motivational pain behaviors to evaluate
the antinociceptive efficacy of drugs. In Aim 2, we develop Ca2+ imaging methods to simultaneously test the
effect of NTSR1 assets on pain behaviors and on amygdalar activity. Because a number of factors can contribute
to reducing nocifensive motor responses following administration of an asset, relying exclusively on behavioral
outcome measures in rodent efficacy studies may not suffice to predict translatability. Here, we will develop and
validate methods to use the miniature microscope (miniscope) technology and express the Ca2+ indicator
GCaMP8f in NTSR1-expressing amygdalar neurons to simultaneously record both the activity of these neurons
and pain behaviors in response to antinociceptive drugs. In Aim 3, to further test the effect of NTSR1 assets
against pain experience, we will develop and validate the use of the “Crystal Skull” technology to image the effect
of antinociceptive drugs on pain representation in neocortex, including areas implicated in the sensory-
discriminative and affective-motivational aspects of...

## Key facts

- **NIH application ID:** 10974396
- **Project number:** 1U19NS138975-01
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** Gregory Scherrer
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $767,756
- **Award type:** 1
- **Project period:** 2024-09-19 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10974396

## Citation

> US National Institutes of Health, RePORTER application 10974396, Development and Validation of Animal Models and/or Outcome Measures (1U19NS138975-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10974396. Licensed CC0.

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