Enhancing translation: A need to leverage complex preclinical models of addictive drugs to accelerate substance use treatment options.

Preclinical models of addictive drugs have been developed for decades to model aspects of the clinical experience in substance use disorders (SUDs). These include passive exposure as well as volitional intake models across addictive drugs and have been utilized to also measure withdrawal symptomatology and potential neurobehavioral mechanisms underlying relapse to drug seeking or taking. There are a number of Food and Drug Administration (FDA)-approved medications for SUDs, however, many demonstrate low clinical efficacy as well as potential sex differences, and we also note gaps in the continuum of care for certain aspects of clinical experiences in individuals who use drugs. In this review, we provide a comprehensive update on both frequently utilized and novel behavioral models of addiction with a focus on translational value to the clinical experience and highlight the need for preclinical research to follow epidemiological trends in drug use patterns to stay abreast of clinical treatment needs. We then note areas in which models could be improved to enhance the medications development pipeline through efforts to enhance translation of preclinical models. Next, we describe neuroscience efforts that can be leveraged to identify novel biological mechanisms to enhance medications development efforts for SUDs, focusing specifically on advances in brain transcriptomics approaches that can provide comprehensive screening and identification of novel targets. Together, the confluence of this review demonstrates the need for careful selection of behavioral models and methodological parameters that better approximate the clinical experience combined with cutting edge neuroscience techniques to advance the medications development pipeline for SUDs.
Competing Interests: Declaration of competing interest None.
(Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)