# Quantitative Methods for HIV/AIDS Research

> **NIH NIH R25** · DUKE UNIVERSITY · 2024 · $362,216

## Abstract

Teams of HIV/AIDS biomedical researchers who perform their own data analysis and consult with
biostatisticians as needed, are increasingly finding standard consultations inadequate because of the need to
1) tackle complex research questions, 2) make sense of big data, and 3) ensure that analysis is rigorous.
There is a critical need to train the future HIV/AIDS workforce for an interdisciplinary big data environment in
which quantitative experts with specialized methodological expertise are partnering on collaborative projects as
appropriate. Researchers need to be trained to identify their own knowledge gaps and identify collaborators
with the necessary expertise, which is getting more complex as quantitative expertise areas are becoming
more and more specialized. To address this, the HIV/AIDS community needs to develop programs that train
researchers and quantitative scientists — statisticians, computer scientists, mathematicians, engineers etc. —
to work cohesively in team science. We propose a program to cross-train HIV/AIDS researchers in
fundamental concepts of quantitative analysis, and quantitative scientists in the biological, clinical, and socio-
behavioral context of HIV/AIDS research. This program capitalizes on the breadth and depth of resources in
HIV/AIDS and in quantitative science at Duke to offer real-world HIV/AIDS research experiences with expert
quantitative mentoring not only to Duke trainees, but also trainees from regional institutions in North Carolina
who may not otherwise have access to these resources. It is designed to provide biomedical and quantitative
trainees with the Skills, Opportunities, Access, and Resources (SOAR) for interdisciplinary HIV/AIDS team
science. In the past project period, we taught data science, statistics, and assay bioinformatics to over 100
junior HIV/AIDS researchers through a series of 18 workshops we developed and implemented each year. We
were also able to introduce 50 graduate students in statistics, mathematics, and computer science to
multidisciplinary HIV/AIDS research through our summer internship program. To build upon this work, we are
proposing a novel research education program designed to fulfill several key objectives: First, we will provide
training for biomedical trainees interested in HIV/AIDS research to build up their skills in data science,
predictive modeling, and assay analysis through a series of workshops centered on real-world HIV case
studies. Second, we will implement a structured internship training program for quantitative graduate students
to have an enhanced mentoring and team science experience working on real-world research problems with
leading HIV/AIDS investigators. Third, we will develop a dedicated mentoring program for biomedical trainees
and provide interdisciplinary professional development training opportunities, including long-term expert
quantitative mentoring for trainees with data-driven research projects. This program will provide an exemplar
fo...

## Key facts

- **NIH application ID:** 10866489
- **Project number:** 5R25AI140495-07
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Cliburn C Chan
- **Activity code:** R25 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $362,216
- **Award type:** 5
- **Project period:** 2018-08-21 → 2028-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10866489

## Citation

> US National Institutes of Health, RePORTER application 10866489, Quantitative Methods for HIV/AIDS Research (5R25AI140495-07). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10866489. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*