Innovating Alcohol Research and Care Through Data Science
In 2019, prior to the mandatory NIH Data Management and Sharing Policy, NIAAA established a new repository for data generated by NIAAA-funded studies in humans, the NIAAA Data Archive, housed within the National Institute of Mental Health (NIMH) Data Archive. This growing archive will eventually contain data from thousands of NIAAA-funded studies, which will be made available to the research community. In addition to facilitating rigor and reproducibility of research, the NIAAA Data Archive will provide a rich resource for secondary analyses—a strategy that supports the optimal use of research resources.
Artificial intelligence (AI) will be critical for developing new statistical and analytical models for alcohol research. Such new models will be important for real-time data analysis, prediction, automated tools for data harmonization and management, and the generation of interactive tools for the prevention of alcohol misuse, individualized alcohol use disorder (AUD) treatment, and guidance of recovery. In particular, multi-omic approaches combined with data science approaches also hold promise for identifying biomarkers or algorithms of biomarkers that could help predict vulnerability to alcohol misuse, individualize AUD treatment, and guide recovery.