# Howard University Research Center for Minority Health and Health Disparities

> **NIH NIH U54** · HOWARD UNIVERSITY · 2021 · $193,125

## Abstract

Principal Investigator/Program Director: John Kwagyan, PhD
Project Summary
Advances in technologies and computational tools has made it possible to generate and store large, complex,
and diverse datasets. The behavioral, biomedical and health research enterprise is increasingly becoming data-
intensive and data-driven. As a result, recognizing, understanding, and using big data for behavioral, biomedical,
and health related research has become necessary to arrive at best evidence and enhance translation. Applied
data science starts with identifying relevant data sources, developing algorithms and/or utilization of existing
software tools to access these data and employing advanced data analytical skills for knowledge discovery and
dissemination of information. In biomedical and healthcare areas, big data methodology is used in several fields
including but not limited to medical imaging studies, drug discovery, genomics, predictive diagnosis and cost
effectiveness studies. Data science also allows researchers to assess patient/population heterogeneity, through
the integration of large data from published literature and meta-analysis to reach conclusions that can be used
to inform clinical practice and guide public health policy. Despite the importance of the emerging field of data
science and the recent rapid rise of its use, many minority institutions do not offer specialized training in data
science. Moreover, though the approach is highly developed, there are few who possess the necessary skill set
in this highly quantitative and technical field and training opportunities are uncommon and there exist disparities
in data science expertise. Skill sets in data science, from ethical practices in data collection, use of complex
computational and analytic techniques including machine learning, to data visualization and reporting, are
particularly critical for advancing the science of minority health and health disparities. To bridge this gap, and
address disparities in acquiring data science skills and its applications, we created the Howard University, HU
RCMI Virtual Applied Data Science Training Institute, VADSTI. VADSTI, drew faculty with complementary
experts in the conduct and application of data science from across different institutions and in partnership with
the NIH Office of Data Science Strategy, delivered a well-attended and successful 8-week comprehensive data
science training. The ability of behavioral, biomedical and clinical researchers to recognize, and use big data is
still limited in minority serving institutions, for various reasons including lack of exposure to relevant databases
and knowledge of programming techniques and access to relevant software, tools, and expertise in data
analytics. The need for creation of an ecosystem of data science resources and useful tools at minority serving
institutions is warranted. The goals of the current application are, (i) to attract, train and engage the next
generation of investigators in...

## Key facts

- **NIH application ID:** 10452038
- **Project number:** 3U54MD007597-33S2
- **Recipient organization:** HOWARD UNIVERSITY
- **Principal Investigator:** William M. Southerland
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $193,125
- **Award type:** 3
- **Project period:** 1997-09-30 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10452038

## Citation

> US National Institutes of Health, RePORTER application 10452038, Howard University Research Center for Minority Health and Health Disparities (3U54MD007597-33S2). Retrieved via AI Analytics 2026-06-08 from https://api.ai-analytics.org/grant/nih/10452038. Licensed CC0.

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