Opportunity Information: Apply for PA 16 119
Apply for PA 16 119
- The HHS-NIH11 in the education, health sector is offering a public funding opportunity titled "The Application of Big Data Analytics to Drug Abuse Research (R01)" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.279.
- This funding opportunity was created on Mar 09, 2016 and posted on Mar 09, 2016.
- Applicants must submit their applications by May 07, 2019. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Eligible applicants include: State governments, County governments, City or township governments, Special district governments, Independent school districts, Public and State controlled institutions of higher education, Native American tribal governments (Federally recognized), Public housing authorities/Indian housing authorities, Native American tribal organizations (other than Federally recognized tribal governments), Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education, Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education, Private institutions of higher education, For profit organizations other than small businesses, Small businesses, Others (see text field entitled Additional Information on Eligibility for clarification).
[Watch] Creating a grant proposal using the step-by-step wizard inside the applicant portal:
Opportunity Summary:
The Application of Big Data Analytics to Drug Abuse Research (R01) (Funding Opportunity Number PA-16-119) is a discretionary NIH grant opportunity from HHS/NIH, specifically aligned with NIDA's goal of accelerating discoveries in substance use and addiction science by pushing more advanced, data-intensive analytics into mainstream drug abuse research. The central idea is that addiction is shaped by complex biological and behavioral processes, and those processes are now being measured at a scale and resolution that traditional methods often cannot fully handle. This FOA is meant to fund projects that develop new computational methods, adapt existing big-data approaches, and/or apply sophisticated analytics and visualization techniques to large, complex datasets in order to generate deeper, more integrated, or entirely new insights into substance use, misuse, and addiction.
A key emphasis of the opportunity is the breadth of data types now available in addiction research and the need to analyze them in ways that capture their full richness. NIDA highlights data streams spanning genetics and epigenetics, molecular and cellular measures, proteomics and metabolomics, brain imaging, micro-electrode and other neurophysiology recordings, as well as behavioral, clinical, social, health services, and environmental datasets. The FOA also explicitly calls out electronic health records as an increasingly important source of real-world clinical information that can be leveraged for addiction-related discovery. In practical terms, the projects supported under this announcement are expected to tackle the challenges that come with scale, complexity, and heterogeneity: integrating multi-modal data, handling high dimensionality, building models that can find subtle patterns, and creating visualization tools that make complex relationships understandable and scientifically useful.
The grant uses the R01 mechanism, meaning it is structured to support full research projects rather than small pilot efforts, with the expectation that applicants will propose a rigorous scientific plan where big-data analytics is essential to the aims. Competitive applications under this FOA would typically frame a clear addiction-related research question and then justify why advanced computational approaches are necessary, whether that means machine learning, network-based modeling, advanced statistical methods, scalable data engineering, novel visualization interfaces, or other approaches suited to very large datasets. The overarching expectation is not just to process data, but to generate interpretable findings that advance understanding of how chronic drug exposure and addiction alter brain function and behavior, and how those changes interact with clinical, social, and environmental factors.
Eligibility is broad and includes many types of organizations that can carry out research, such as state, county, city, township, and special district governments; public and state-controlled institutions of higher education; private institutions of higher education; independent school districts; federally recognized Native American tribal governments; other Native American tribal organizations; public housing authorities/Indian housing authorities; nonprofit organizations with or without 501(c)(3) status; for-profit organizations other than small businesses; small businesses; and other applicants as allowed under the announcement's additional eligibility guidance. The program is associated with CFDA number 93.279, was posted and created on March 9, 2016, and lists a closing date of May 7, 2019 in the provided source details (with the original and current closing date matching).
Overall, this FOA is best understood as an effort to bring modern big-data thinking directly into addiction science: building or applying computational tools that can keep pace with rapidly expanding neurobiological and behavioral datasets, improve the ability to detect meaningful patterns across multiple levels of analysis, and ultimately support faster progress toward understanding, preventing, and treating substance use disorders.
Frequently Asked Questions (FAQs)
What is the name of this funding opportunity?
The opportunity is titled The Application of Big Data Analytics to Drug Abuse Research (R01).
What is the Funding Opportunity Number (FON)?
The Funding Opportunity Number is PA-16-119.
Which agency is offering this grant?
This is a discretionary NIH grant opportunity from HHS/NIH, aligned with the mission and research goals of NIDA (National Institute on Drug Abuse).
What is the main purpose of this FOA?
The FOA aims to accelerate discoveries in substance use and addiction science by funding projects that develop, adapt, and/or apply advanced big-data analytics, computational methods, and visualization approaches to large, complex addiction-related datasets.
What kind of grant mechanism does this FOA use?
This FOA uses the R01 mechanism, which is intended to support full research projects (not small pilot efforts).
What types of projects are expected to be competitive under this FOA?
Competitive projects typically present a clear, addiction-related scientific question and explain why big-data analytics is essential to the aims. Examples of approaches mentioned include machine learning, network-based modeling, advanced statistical methods, scalable data engineering, novel visualization tools, and other methods suited to very large and complex datasets.
Is the FOA focused on creating new methods, applying existing methods, or both?
Both. The FOA supports projects that develop new computational methods, adapt existing big-data approaches, and/or apply sophisticated analytics and visualization techniques to large, complex datasets.
What is the underlying scientific motivation for using big-data analytics in addiction research?
The FOA is based on the idea that addiction is shaped by complex biological and behavioral processes that are now being measured at a scale and resolution that traditional analytic approaches may not fully handle.
What kinds of data does NIDA highlight as relevant to this opportunity?
NIDA highlights a wide range of data streams, including genetics and epigenetics; molecular and cellular measures; proteomics and metabolomics; brain imaging; micro-electrode and other neurophysiology recordings; behavioral, clinical, social, health services, and environmental datasets.
Are electronic health records (EHRs) specifically mentioned?
Yes. The FOA explicitly calls out electronic health records as an increasingly important source of real-world clinical information that can be leveraged for addiction-related discovery.
What big-data challenges are applicants expected to address?
Projects are expected to tackle challenges related to scale, complexity, and heterogeneity, such as integrating multi-modal data, handling high dimensionality, building models that can detect subtle patterns, and creating visualization tools that make complex relationships understandable and scientifically useful.
What does the FOA expect beyond basic data processing?
The FOA emphasizes generating interpretable findings that advance understanding of how chronic drug exposure and addiction alter brain function and behavior, and how those changes interact with clinical, social, and environmental factors.
What areas of addiction science does this FOA aim to advance?
The FOA aims to support faster progress toward understanding, preventing, and treating substance use disorders by bringing modern big-data approaches into mainstream drug abuse research.
Who is eligible to apply?
Eligibility is broad and includes: state, county, city, township, and special district governments; public and state-controlled institutions of higher education; private institutions of higher education; independent school districts; federally recognized Native American tribal governments; other Native American tribal organizations; public housing authorities/Indian housing authorities; nonprofit organizations (with or without 501(c)(3) status); for-profit organizations other than small businesses; small businesses; and other applicants as allowed under the announcement's additional eligibility guidance.
Is eligibility limited to nonprofits or universities?
No. The eligibility list includes nonprofits, multiple levels of government, universities and colleges (public and private), tribal entities, public housing authorities/Indian housing authorities, and for-profit organizations (including small businesses).
What is the CFDA number associated with this program?
The program is associated with CFDA 93.279.
When was this funding opportunity posted/created?
The provided source details list a posted and created date of March 9, 2016.
What is the closing date listed in the provided details?
The provided source details list a closing date of May 7, 2019, and note that the original and current closing date match.
What is the overall theme of the FOA in plain terms?
In practical terms, this FOA is about bringing modern, data-intensive analytics directly into addiction science so researchers can work effectively with rapidly expanding neurobiological, behavioral, clinical, and real-world datasets and uncover meaningful patterns across multiple levels of analysis.
Browse more opportunities from the same agency: HHS-NIH11
Browse more opportunities from the same category: Education, Health
Next opportunity: Community Programs Expansion, NPS Centennial
Previous opportunity: CENTER OF EXCELLENCE: Multi-Fidelity Modeling of Combustion Instabilities
USGrants.org Applicant Portal:
Are you interested in learning about about how to apply for this government funding opportunity? You can create a free applicant account and receive instant access to our applicant portal that many business owners like you have benefited from.
Apply for PA 16 119
[Watch] how do funding administrators access proposals?
Applicants also applied for:
Applicants who have applied for this opportunity (PA 16 119) also looked into and applied for these:
| Funding Opportunity |
|---|
| Emerging Questions in Cancer Systems Biology (U01) Apply for PAR 16 131 Funding Number: PAR 16 131 Agency: HHS-NIH11 Category: Education, Health Funding Amount: Case Dependent |
| Cancer Research Education Grants Program to Promote Diversity - Research Experiences (R25) Apply for PAR 16 138 Funding Number: PAR 16 138 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $300,000 |
| The Early Detection Research Network: Biomarker Developmental Laboratories (U01) Apply for RFA CA 16 009 Funding Number: RFA CA 16 009 Agency: HHS-NIH11 Category: Education, Health Funding Amount: Case Dependent |
| Coordinating Center for Barrett's Esophagus Translational Research Network (BETRNet)(U24) Apply for RFA CA 16 007 Funding Number: RFA CA 16 007 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $250,000 |
| Cancer Research Education Grants Program to Promote Diversity - Courses for Skills Development (R25) Apply for PAR 16 139 Funding Number: PAR 16 139 Agency: HHS-NIH11 Category: Education, Health Funding Amount: Case Dependent |
| Research Centers for Barretts Esophagus Translational Research Network (BETRNet)(U54) Apply for RFA CA 16 006 Funding Number: RFA CA 16 006 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $900,000 |
| Population Health Interventions: Integrating Individual and Group Level Evidence (R21) Apply for PA 16 147 Funding Number: PA 16 147 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $200,000 |
| Role of Astrocytes and Astrocytic Networks in Drug Abuse (R21) Apply for PA 16 145 Funding Number: PA 16 145 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $200,000 |
| Population Health Interventions: Integrating Individual and Group Level Evidence (R01) Apply for PA 16 146 Funding Number: PA 16 146 Agency: HHS-NIH11 Category: Education, Health Funding Amount: Case Dependent |
| Role of Astrocytes and Astrocytic Networks in Drug Abuse (R01) Apply for PA 16 144 Funding Number: PA 16 144 Agency: HHS-NIH11 Category: Education, Health Funding Amount: Case Dependent |
| Revision Applications to R01 Awards for Research on the NCI's Provocative Questions (R01) Apply for RFA CA 16 010 Funding Number: RFA CA 16 010 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $150,000 |
| Revisions to Add Provocative Question-Relevant Research to Active Research Projects (P01) Apply for RFA CA 16 013 Funding Number: RFA CA 16 013 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $150,000 |
| Revisions Applications to P50 Awards for Research on NCI's Provocative Questions (P50) Apply for RFA CA 16 012 Funding Number: RFA CA 16 012 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $150,000 |
| Revision Applications to U01 Awards for Research on the NCI's Provocative Questions (U01) Apply for RFA CA 16 011 Funding Number: RFA CA 16 011 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $150,000 |
| Integrating Biospecimen Science into Clinical Assay Development (U01) Apply for PAR 16 166 Funding Number: PAR 16 166 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $250,000 |
| Novel Strategies for Targeting HIV-CNS Reservoirs without Reactivation (R01) Apply for RFA MH 17 101 Funding Number: RFA MH 17 101 Agency: HHS-NIH11 Category: Education, Health Funding Amount: Case Dependent |
| Novel Strategies for Targeting HIV-CNS Reservoirs without Reactivation (R21) Apply for RFA MH 17 100 Funding Number: RFA MH 17 100 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $200,000 |
| Pilot and Feasibility Studies Evaluating the Role of RNA Modifications (the 'epitranscriptome') in Cancer Biology (R21) Apply for PA 16 177 Funding Number: PA 16 177 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $200,000 |
| Exploratory Grants in Cancer Epidemiology and Genomics Research (R21) Apply for PA 16 175 Funding Number: PA 16 175 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $200,000 |
| NCI Clinical and Translational Exploratory/Developmental Studies (R21) Apply for PAR 16 176 Funding Number: PAR 16 176 Agency: HHS-NIH11 Category: Education, Health Funding Amount: $200,000 |
Grant application guides and resources
It is always free to apply for government grants. However the process may be very complex depending on the funding opportunity you are applying for. Let us help you!
Apply for Grants
Premium leads for funding administrators, grant writers, and loan issuers
Thousands of people visit our website for their funding needs every day. When a user creates a grant proposal and files for submission, we pass the information on to funding administrators, grant writers, and government loan issuers.
If you manage government grant programs, provide grant writing services, or issue personal or government loans, we can help you reach your audience.
Subscribe to Leads
Request more information:
Would you like to learn more about this funding opportunity, similar opportunities to "PA 16 119", eligibility, application service, and/or application tips? Submit an inquiry below:
Don't forget to subscribe to our grant alerts mailing list to receive weekly alerts on new and updated grant funding opportunities like this one in your email.