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Related Experiment Video

Updated: Jun 7, 2026

Murine Drinking Models in the Development of Pharmacotherapies for Alcoholism: Drinking in the Dark and Two-bottle Choice

Murine Drinking Models in the Development of Pharmacotherapies for Alcoholism: Drinking in the Dark and Two-bottle Choice

Published on: January 7, 2019

Improving translational insight using sequential sampling models in drug choice.

Bart J Cooley¹, E Zayra Millan¹, Gavan P McNally²

¹School of Psychology, UNSW Sydney, Sydney, Australia.

Psychopharmacology

|June 5, 2026

Summary

Translating alcohol use disorder (AUD) treatments is difficult. Formalizing preclinical choice procedures with decision-making models can improve treatment screening and translational insight for AUD pharmacotherapy.

Keywords:

Addiction Choice Sequential sampling models Translation

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Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

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Published on: December 11, 2016

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Last Updated: Jun 7, 2026

Murine Drinking Models in the Development of Pharmacotherapies for Alcoholism: Drinking in the Dark and Two-bottle Choice

Murine Drinking Models in the Development of Pharmacotherapies for Alcoholism: Drinking in the Dark and Two-bottle Choice

Published on: January 7, 2019

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

Area of Science:

Neuroscience
Pharmacology
Decision Science

Background:

Translating pharmacological treatments for alcohol use disorder (AUD) remains a significant challenge.
Advances in neuroscientific and molecular sciences offer new analytical approaches but require better integration for treatment development.

Purpose of the Study:

To propose formal characterization of preclinical discrete choice procedures using human decision-making models as a solution for AUD treatment translation.
To review the utility of choice procedures in pharmacological treatment screening and the applicability of sequential sampling models.

Main Methods:

Reviewing evidence for choice procedures in treatment screening.
Examining the success of sequential sampling models in explaining decision-making across species and tasks.
Demonstrating a practical tutorial using open-source software for implementation.

Main Results:

Sequential sampling models successfully explain decision-making, suggesting shared cognitive laws applicable to AUD.
Formal approaches can integrate diverse datasets to clarify treatment effects.
These methods are straightforward to implement.

Conclusions:

Formal characterization of preclinical choice procedures with decision-making models offers a promising avenue for improving AUD treatment translation.
Leveraging shared cognitive laws of decision-making can enhance the screening and development of pharmacological interventions for AUD.
The proposed methods provide a practical framework for integrating data and advancing AUD pharmacotherapy research.