National Institute on Alcohol Abuse and Alcoholism (NIAAA)
The purpose of this Request for Information (RFI) is to solicit information from the broad community of alcohol researchers, clinicians, patients and advocates about data sources and data science questions related to alcohol use and its consequences for human health. Specifically, NIAAA requests input to help identify the most important research questions that data science can be leveraged to answer. The NIAAA mission and strategic plan provide the current research focus areas.
Background
NIAAA has supported studies in large scale analytic techniques (genomics, proteomics, metabolomics, et al.), imaging, electrophysiology and optogenetics, electronic health records, and social and behavioral measures (from personal wearable devices, state and local government policy analyses, and geographic information systems). The data collections from those research areas present opportunities for discovery, as well as challenges in analyses and interpretations. The NIAAA Data Archive (NIAAADA) data sharing policy (NOT-AA-19-020: https://grants.nih.gov/grants/guide/notice-files/NOT-AA-19-020.html), effective January 25, 2019, expects that NIAAA-funded investigators contribute their grant-related human subjects data to the NIAAADA (https://nda.nih.gov/niaaa). The future data sources will be combined with significant current data repositories and archives, including: database of Genotypes and Phenotype, dbGaP, https://www.ncbi.nlm.nih.gov/gap, Collaborative Studies on Genetics of Alcoholism (COGA), https://niaaagenetics.org/, National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III), and the National Health and Nutrition Examination Survey, NHANES, to form a large and rich source of data about alcohol use, suitable for analysis by data science methods.
Data science includes and extends beyond bioinformatics, population studies, and computational neuroscience to discover new relationships and pathways for complex systems of normal human function and during adaptations due to disorders or disease. NIAAA is seeking more information about the potential for how using tools such as machine learning, deep learning and artificial intelligence can transform alcohol research and answer research questions that a single data source cannot. Some examples include identification of biomarkers of alcohol use disorder and long-term health effects of alcohol use, finding new therapeutic targets for prevention or treatment of alcohol use disorder, and predicting the most effective treatment strategies for individuals with alcohol use disorder. NIAAA will embrace the capabilities of data science to include features across lifespan, human populations (including racial and ethnic attributes), geographic locations, species and experimental techniques. However, before embarking on this scientific revolution, NIAAA requests information from our community about the research areas or topics that are best suited for these large-scale data analysis approaches.
Information Requested
NIAAA is soliciting input from all interested stakeholders including researchers, health care providers, data scientists and individuals with alcohol use disorder. Individuals with relevant expertise are invited to submit comments. The NIAAA mission is to generate and disseminate fundamental knowledge about the effects of alcohol on health and well-being, and apply that knowledge to improve diagnosis, prevention, and treatment of alcohol-related problems, including alcohol use disorder, across the lifespan.
Input sought through this RFI includes, but is not limited to:
Elizabeth Powell, PhD
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Telephone: 301-443-0786
Email: elizabeth.powell3@nih.gov