# Mathematical modeling of optimal therapeutic combinations for HIV cure

> **NIH NIH R01** · FRED HUTCHINSON CANCER RESEARCH CENTER · 2022 · $95,513

## Abstract

PROJECT SUMMARY
Antiretroviral therapy (ART) suppresses HIV replication and allows a normal lifespan for infected persons, but
daily pill ingestion is required to avoid progression to AIDS and further HIV transmission. Multiple therapeutic
strategies are being considered to achieve a functional cure for HIV. However, to date, no single approach has
achieved sufficient potency for an HIV functional cure. Therefore, there is increasing agreement that an HIV cure
will require a multi-pronged approach. This proposal has the objective to identify optimal and feasible
combinations of investigational therapeutic approaches to achieve functional cure of HIV using data-validated
mathematical models. Our hypothesis is that data-validated mathematical models can identify specific
mechanisms of therapeutic combinations, by linking observed kinetics and potency with various quantifiable
outcome measures. Our specific aims will validate this hypothesis by fitting different mathematical models that
encapsulate competing possible mechanisms to outcome data from curative interventions currently under study,
including levels of different reservoir cellular subset, viral quantities, viral diversity and time to viral rebound.
Model selection theory will be used to identify the most parsimonious models that reliably explain experimental
results. We will use the most parsimonious model that recapitulated the data from each study to perform in silico
experiments. We will list all plausible combinations of therapeutic approaches and model each combination. We
will create combinatorial dose-response curves by running simulations for each combination by using the
parameterization obtained from the fits and by tuning the parameters for each therapy including dosing,
scheduling, and order of treatment. This proposal is significant because testing all possible combinations of
approaches is impractical, excessively time consuming and expensive. The inability to rigorously assess all
potential approaches is a critical barrier to achieve optimal outcomes. Therefore, our proposal is innovative
because we propose a rigorous, quantitative framework in which plausible combinations of available
interventions are considered and compared with the potential to identify which combination therapies most likely
will achieve a functional cure.

## Key facts

- **NIH application ID:** 10312707
- **Project number:** 5R01AI150500-03
- **Recipient organization:** FRED HUTCHINSON CANCER RESEARCH CENTER
- **Principal Investigator:** Erwing Fabian Cardozo Ojeda
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $95,513
- **Award type:** 5
- **Project period:** 2019-12-16 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10312707

## Citation

> US National Institutes of Health, RePORTER application 10312707, Mathematical modeling of optimal therapeutic combinations for HIV cure (5R01AI150500-03). Retrieved via AI Analytics 2026-06-14 from https://api.ai-analytics.org/grant/nih/10312707. Licensed CC0.

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