Using machine learning to understand how HIV controls its dormant state
Machine learning of time-series single-cell drug screening to elucidate HIV latency control mechanisms
['FUNDING_R21'] · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · NIH-10674721
This study is looking at how HIV can stay hidden in the body without causing active infection, using advanced computer techniques to understand how the virus reacts to different treatments, which could help develop better therapies for patients living with HIV.
Quick facts
| Phase | ['FUNDING_R21'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN (nih funded) |
| Locations | 1 site (CHAMPAIGN, UNITED STATES) |
| Trial ID | NIH-10674721 on ClinicalTrials.gov |
What this research studies
This research investigates the mechanisms by which HIV maintains latency, a state where the virus is present in the body but not actively replicating. By applying machine learning techniques to analyze time-series gene expression data from single cells, the study aims to uncover the biological processes that govern HIV's behavior in response to various drug treatments. This interdisciplinary approach combines insights from virology, systems biology, and chemical sciences to enhance our understanding of HIV and improve drug discovery efforts. Patients may benefit from the findings as they could lead to more effective therapies targeting latent HIV.
Who could benefit from this research
Good fit: Ideal candidates for participation or benefit from this research include individuals living with HIV, particularly those experiencing challenges with treatment adherence or viral suppression.
Not a fit: Patients who are not living with HIV or those who have achieved complete viral suppression may not receive direct benefits from this research.
Why it matters
Potential benefit: If successful, this research could lead to breakthroughs in HIV treatment by identifying new strategies to eliminate latent virus reservoirs.
How similar studies have performed: Other research has shown promise in using machine learning to analyze biological data, indicating that this approach could yield valuable insights into HIV latency.
Where this research is happening
CHAMPAIGN, UNITED STATES
- UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN — CHAMPAIGN, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: SHUKLA, DIWAKAR — UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
- Study coordinator: SHUKLA, DIWAKAR
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 below.