# Integrating findings across stages of medication development for AUD

> **NIH NIH R21** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2021 · $212,801

## Abstract

ABSTRACT
Medication development for alcohol use disorder (AUD) is a time-consuming and costly process. Unfortunately,
no new medications for AUD have been approved in the past two decades, despite significant investments. A
typical path to developing a new medication for AUD includes testing in animals, followed by safety testing in
humans, followed by randomized clinical trials. Recently, it has been proposed that testing in humans using
experimental psychopharmacology paradigms can detect the initial efficacy of a compound under
development. As such, the “signal” of medication benefit over placebo is initially identified in animal models,
followed by human laboratory testing, and ultimately tested in randomized clinical trials (RCT). In essence, at
each phase in testing, scientists are tasked with making “go/no-go” decisions about candidate
pharmacotherapies. In this context, approval by the FDA constitutes the final “go” decision and requires
compelling efficacy demonstration in RCTs, which is the gold standard. While a host of factors are involved in
making “go/no-go” decisions, the paradigms used in animal and human testing to detect an efficacy signal are
crucial to the success of medication development. Further, how to evaluate the preclinical and human evidence
for a compound in order to decide, is of paramount importance. To date, the question of which models should
be used in preclinical studies and human laboratory studies and how the evidence they provide should be
evaluated remains highly subjective. Scientists can argue for models they are most familiar with and
preliminary data can be presented with a range of plausible interpretation, all of which is inherently subjective.
The proposed R21 application seeks to conduct novel meta-analytic models to test the relationship between
AUD medication effect sizes obtained in animal models, human laboratory models, and randomized clinical
trials (RCTs). These analyses will test the degree to which models used at each stage of medication
development for AUD are predictive of clinical outcomes in RCTs, the gold standard for improving healthcare.

## Key facts

- **NIH application ID:** 10353926
- **Project number:** 1R21AA029771-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** LARA A. RAY
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $212,801
- **Award type:** 1
- **Project period:** 2021-09-20 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10353926

## Citation

> US National Institutes of Health, RePORTER application 10353926, Integrating findings across stages of medication development for AUD (1R21AA029771-01). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/10353926. Licensed CC0.

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