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.
The proposed research is relevant to public health because understanding which plausible combinations of current therapeutic strategies may achieve an HIV functional cure using data-validated mathematical models may significantly optimize the design of experiments and clinical trials geared to that purpose. Thus, this proposal is relevant to the part of NIH?s mission that pertains to fostering fundamental creative discoveries and innovative research strategies as a basis for ultimately protecting health.
