# Howard University Research Center for Minority Health and Health Disparities > **NIH NIH U54** · HOWARD UNIVERSITY · 2020 · $150,000 ## 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 have 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. The methodology is highly developed and is utilized in various areas of research, insurance, business, and healthcare. 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. Skill sets in data science are also particularly critical for advancing the science of minority health and health disparities. Despite the importance of the emerging field of data science and the recent rapid rise of its use, many minority-serving 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. Additionally, there exist disparities in data science expertise and training opportunities in minority-serving institutions. The two major goals of this application are therefore to (i) enhance capacity building in data science by offering a comprehensive training series that engages new and established researchers of various disciplines, and (ii) foster collaboration in data science research among researchers in RCMIs and other minority-serving institutions. The goals will be accomplished through the creation of the Virtual Applied Data Science Training Institute, VADSTI. The proposed VADSTI, will draw faculty with complementary expertise in the conduct and application of data science from multiple institutions as well as partner with the NIH Office of Data Science Strategy to launch an 8-week comprehensive training in a virtual (online) environment. The objective is to address and close the gap in disparities in knowledge, understanding and application of data science in RCMI institutions and other minority-serving institutions. PHS 398 (Rev. 01/18 Approved Through 03/31/2020) Page 1 OMB No. 0925-0001 ## Key facts - **NIH application ID:** 10261889 - **Project number:** 3U54MD007597-32S3 - **Recipient organization:** HOWARD UNIVERSITY - **Principal Investigator:** William M. Southerland - **Activity code:** U54 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $150,000 - **Award type:** 3 - **Project period:** 1997-09-30 → 2024-01-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10261889 ## Citation > US National Institutes of Health, RePORTER application 10261889, Howard University Research Center for Minority Health and Health Disparities (3U54MD007597-32S3). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10261889. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*