Advancing medication development for alcohol use disorder: A narrative review integrating preclinical, human laboratory, and clinical trials.

Medication development for alcohol use disorder (AUD) represents a challenging, costly, and time-consuming process. A typical development trajectory involves testing compounds in animal models, human laboratory studies, and randomized clinical trials (RCTs). This paper reviews a series of data-driven studies seeking to evaluate best practices in medication development for AUD at each of the three levels of analysis. First, we evaluate the role of behavioral pharmacology paradigms in early efficacy testing and highlight the importance of preclinical and human laboratory evidence in making critical "go/no-go" decisions throughout the development process. Second, we discuss a recent translational meta-analytic approach that integrates preclinical, human laboratory, and RCT data to inform AUD medication development. This narrative review synthesizes findings from systematic reviews, meta-regression analyses, and integrated data across stages of medication testing. Findings from this work suggest that factors such as sample characteristics and study design influence the detection of medication effects on AUD outcomes, emphasizing the need for standardized methodologies. Furthermore, findings suggest that early efficacy signals in animal models and human laboratory studies can predict specific clinical trial outcomes, offering valuable insights for data-informed decision making in medication development. Together, these studies bridge the gap between the preclinical and clinical stages, facilitating more efficient medication development for AUD.