The Application of Big Data Analytics to Drug Abuse Research (R01)

PA-16-119
The Application of Big Data Analytics to Drug Abuse Research (R01)
Department of Health and Human ServicesRx-Drugs
National Institutes of Health

Nature of the Research Opportunity

Big Data is used here to refer to computational analytic techniques able to recognize patterns in information which surpass the limits of human intuition.  This FOA focuses on applying Big Data analytics to reveal deeper or novel insights into the biological and behavioral processes associated with substance abuse and its treatment, and the relationships among them.   This FOA does not seek applications that propose to perform secondary analyses of data without using Big Data analytics (e.g. this FOA does not seek applications re-applying traditional methods to ascertain un-analyzed distinctions between study subpopulations) and applicants may consider submitting these applications to PA-13-080.  This FOA also is intended to distinguish itself from PA-13-080 in that the computational tools (e.g. aggregated datasets, standards, analytic software) developed to answer new scientific questions are able to be applied again to future research studies acquiring similar types of data, such that the end result of these funded grants increase the computational armamentarium available to addiction research.

Background

National investments in basic research, including President Obama’s BRAIN and Precision Medicine Initiatives, are poised to accelerate discoveries in neuroscience, genetics, and health services research.  In addition, a shift in culture, driven by the NIH Big Data to Knowledge Initiative, is promoting open access and data sharing to allow diverse data sets to be broadly accessible to researchers. Advances in information technologies and analytics capabilities are producing extraordinary capacity to integrate and analyze these data and enable novel research into the complexity of disorders such as drug abuse and addiction that are driven by the dynamic interactions of diverse biological, social, organizational, environmental, and behavioral mediators.   The result is a new, data-intensive era of research characterized by a heretofore unseen influx of data presenting new computational challenges which delay important discoveries due to bottlenecks in data analysis.  Big Data analytics provides new opportunities to maximize the value of research results by providing researchers the ability to analyze huge amounts of data in new ways – turning vast datasets of complex information into knowledge.

General Information

Document Type: Grants Notice
Funding Opportunity Number: PA-16-119
Funding Opportunity Title: The Application of Big Data Analytics to Drug Abuse Research (R01)
Opportunity Category: Discretionary
Opportunity Category Explanation:
Funding Instrument Type: Grant
Category of Funding Activity: Education
Health
Category Explanation:
Expected Number of Awards:
CFDA Number(s): 93.279 — Drug Abuse and Addiction Research Programs
Cost Sharing or Matching Requirement: No
Posted Date: Mar 09, 2016
Last Updated Date: Mar 09, 2016
Original Closing Date for Applications: May 07, 2019  
Current Closing Date for Applications: May 07, 2019  
Archive Date: Jun 07, 2019
Estimated Total Program Funding:
Award Ceiling:
Award Floor:

Eligibility

Eligible Applicants:
Special district governments
Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education
Native American tribal organizations (other than Federally recognized tribal governments)
Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education
Public housing authorities/Indian housing authorities
For profit organizations other than small businesses
Independent school districts
Public and State controlled institutions of higher education
City or township governments
Others (see text field entitled “Additional Information on Eligibility” for clarification)
Private institutions of higher education
Native American tribal governments (Federally recognized)
State governments
County governments
Small businesses
Additional Information on Eligibility: Other Eligible Applicants include the following: Alaska Native and Native Hawaiian Serving Institutions; Asian American Native American Pacific Islander Serving Institutions (AANAPISISs); Eligible Agencies of the Federal Government; Faith-based or Community-based Organizations; Hispanic-serving Institutions; Historically Black Colleges and Universities (HBCUs); Indian/Native American Tribal Governments (Other than Federally Recognized); Non-domestic (non-U.S.) Entities (Foreign Organizations); Regional Organizations; Tribally Controlled Colleges and Universities (TCCUs) ; U.S. Territory or Possession.

Additional Information

Agency Name: National Institutes of Health
Description: The purpose of this FOA is to encourage the application of Big Data analytics to reveal deeper or novel insights into the biological and behavioral processes associated with substance abuse and addiction.NIDA recognizes that to accelerate progress toward understanding how the human brain and behavior is altered by chronic drug use and addiction, it is vital to develop more powerful analytical methods and visualization tools that can help capture the richness of data being generated from genetic, epigenetic, molecular, proteomic, metabolomic, brain-imaging, micro-electrode, behavioral, clinical, social, services, environmental studies as well as data generated from electronic health records.Applications for this FOA should develop and/or utilize computational approaches for analyzing large, complex datasets acquired from drug addiction research.The rapid increase of technologies to acquire unprecedented amounts of neurobiological and behavioral data, and an expanding capacity to store those data, results in great opportunity to bring to bear the power of the computational methods of Big Data analytics on drug abuse and addiction.
Link to Additional Information: http://grants.nih.gov/grants/guide/pa-files/PA-16-119.html
Contact Information: If you have difficulty accessing the full announcement electronically, please contact:

NIH OER Webmaster FBOWebmaster@OD.NIH.GOV
If you have any problems linking to this funding announcement, please contact the NIH OER Webmaster

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