Predicting how COVID-19 changes inside people living with HIV

A Phylodynamic Artificial Intelligence framework to predict evolution of SARS-CoV-2 variants of concern in Immunocompromised persons with HIV (PhAI-CoV)

['FUNDING_R01'] · UNIVERSITY OF FLORIDA · NIH-11124691

This project uses artificial intelligence and virus genetics to predict how SARS-CoV-2 may evolve over time in people with HIV who have weakened immune systems.

Quick facts

Phase['FUNDING_R01']
Study typeNih_funding
SexAll
SponsorUNIVERSITY OF FLORIDA (nih funded)
Locations1 site (GAINESVILLE, UNITED STATES)
Trial IDNIH-11124691 on ClinicalTrials.gov

What this research studies

You would be part of work that looks at viral genetic sequences from people living with HIV to see how the coronavirus changes inside a person over time. Researchers will combine evolutionary models (phylodynamics) with AI algorithms to spot patterns that signal the emergence of new, potentially dangerous variants. The project relies on viral samples and linked clinical data from immunocompromised patients to train and test the models. The goal is to identify situations where persistent infection could lead to variants so clinicians and public health teams can respond sooner.

Who could benefit from this research

Good fit: Ideal candidates would be people living with HIV who have weakened immune systems and who have had prolonged or repeated SARS-CoV-2 infection or who are willing to provide viral samples and clinical information.

Not a fit: People without HIV or those with healthy immune systems and no history of prolonged COVID-19 infection are unlikely to gain direct benefit from participating.

Why it matters

Potential benefit: If successful, this could help identify when a person is likely to produce new viral variants so doctors can tailor treatment and public health responses to reduce risk.

How similar studies have performed: Case reports and small studies have shown SARS-CoV-2 can evolve inside immunocompromised people, but combining phylodynamics with AI for systematic prediction is a newer, less-tested approach.

Where this research is happening

GAINESVILLE, UNITED STATES

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.

View on NIH RePORTER →

Conditions: Acquired Immune Deficiency Syndrome Virus, Acquired Immunodeficiency Syndrome Virus

Last reviewed 2026-05-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.