Abstract
Opioid use disorder (OUD) affects millions of people throughout the United States, yet there are only three Food and Drug Administration-approved pharmacological treatments. Though these treatments have been shown to be effective, the number of overdose deaths continues to rise. The increase of fentanyl, fentanyl analogs, and adulterants in the illicit drug supply has further complicated treatment strategies. Preclinical researchers strive to model OUD to better understand this complicated disorder, and this research is a critical enabler for the development of novel treatments. As a result, there are many different preclinical models of OUD. Often, researchers form strong opinions on what they believe to be the "best" model to mimic the human condition. Here, we argue that researchers should be supportive of multiple models to promote new perspectives and discoveries and always consider the trends in human opioid use when designing preclinical studies. We describe the benefits of contingent and noncontingent models as well as models of opioid withdrawal and how each of these can help illuminate different components of OUD.