Predicting how HIV levels rebound after stopping treatment
Official title: Modeling of Viral Load Trajectories for HIV Cure Research
Funded at Harvard Pilgrim Health Care, INC. · NIH-11159521 · Data updated 2026-11-12
Researchers are creating models to predict how viral load changes after people with HIV stop antiretroviral therapy.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Harvard Pilgrim Health Care, INC. NIH-funded |
| Lab location | 1 site (Canton, UNITED STATES) |
| Project start | August 24, 2022 |
| Project end | July 31, 2026 |
| Funding year | 2025 |
| Award (this year) | $402,803 |
| NIH project number | 5R01AI170254-04 |
| Project ID | NIH-11159521 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are people with HIV who have undergone or may join cure trials that include planned antiretroviral treatment interruption and who can share viral load and clinical data.
✕Less likely to help
People who stay on stable ART with no treatment interruption or those without available viral load/clinical data are unlikely to directly benefit from this specific work.
What this research studies
From a patient's view, the team will combine viral load and clinical data from several HIV studies to map how the virus rises, peaks, and settles after treatment is stopped. They will use new statistical methods to handle gaps in measurements, tests that can't detect very low virus, and small sample sizes from individual trials. By pooling data from the AIDS Clinical Trials Group and a Zurich cohort, they will look for host, viral, and immune features that help predict time to rebound and the viral set point. The goal is better tools for interpreting treatment-interruption results and for planning future cure trials.
Why it matters
Potential benefit: If successful, this work could help identify who might control HIV without continuous therapy and improve the safety and design of treatment-interruption cure trials.
How similar studies have gone: Prior modeling studies have given useful insights into viral rebound, but pooling multiple trial datasets and using new methods here is a relatively novel step that may improve prediction.
Where this research is happening
-
Harvard Pilgrim Health Care, INC.
Canton, United States Active
Researchers
- Principal investigator: Wang, Rui — Harvard Pilgrim Health Care, INC.
- Study coordinator: Wang, Rui
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.