Until recently a cure for HIV did not seem possible. However, recent developments suggest that some patients have been cured or demonstrate post-treatment control (PTC) of viremia to undetectable levels, corresponding to a functional cure. Further, there are important new ideas on how to safely activate the HIV-1 latent reservoir, which is believed to be the main obstacle to HIV-1 eradication from a patient. To advance the goal of cure we need to understand these recent clinical observations in quantitative detail. This grant aims to address this gap in knowledge, by leveraging the power of mathematical modeling to understand the dynamics of PTC and activation of the latent reservoir, to compare different biological mechanisms at play in those phenomena and to propose new protocols to advance the HIV cure agenda. We also propose to use mathematical modeling to advance the cure agenda for another chronic infection, hepatitis C virus (HCV). Our hypotheses are: i) that patients whose latent reservoir decays to sufficiently small levels on treatment are more likely to exhibit PTC, and thus we will develop models to understand the biological and dynamic processes that link latency and PTC; ii) that analyzing viral and infected cell kinetics under new therapeutic protocols aiming at activating latently infected cells will lead to new insights into hw to reduce or eliminate this reservoir, and thus we propose to develop a quantitative understanding of these therapies by modeling clinical trial data; iii) that by modeling the effects of new potent direct-acting antivirals for HCV, which target specific viral proteins and have multiple synergistic effects, we will be able to help design the potent drug combinations that are necessary for HCV cure. Altogether, our objectives are to assist clinical collaborators in studies involving HIV (as well as HCV) whenever we feel that rigorous analysis can lead to new insights or to improved treatments for patients. These studies may also raise interesting theoretical questions and drive future modeling efforts.

Public Health Relevance

HIV-1 is still an important health burden, in terms of mortality, morbidity and financially, in the USA and around the world. We will analyze state-of-the-art therapeutic protocols, which for the first time are aimed at generating a cure or functional cure (when the infection is controlled without treatment) for HIV-1. We will develop models of HIV-1 dynamics in the context of these new protocols to help define those that will provide the most clinical benefit. Similarly, we will develop models of new direct-acting therapeutic agents for hepatitis C virus infection that may help increase the HCV cure rate.

Agency
National Institute of Health (NIH)
Institute
Office of The Director, National Institutes of Health (OD)
Type
Research Project (R01)
Project #
5R01OD011095-24
Application #
9064245
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Moro, Manuel H
Project Start
1991-04-19
Project End
2019-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
24
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Los Alamos National Lab
Department
Type
DUNS #
175252894
City
Los Alamos
State
NM
Country
United States
Zip Code
87545
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Best, Katharine; Perelson, Alan S (2018) Mathematical modeling of within-host Zika virus dynamics. Immunol Rev 285:81-96
Ke, Ruian; Li, Hui; Wang, Shuyi et al. (2018) Superinfection and cure of infected cells as mechanisms for hepatitis C virus adaptation and persistence. Proc Natl Acad Sci U S A 115:E7139-E7148
Ke, Ruian; Conway, Jessica M; Margolis, David M et al. (2018) Determinants of the efficacy of HIV latency-reversing agents and implications for drug and treatment design. JCI Insight 3:
Aunins, Thomas R; Marsh, Katherine A; Subramanya, Gitanjali et al. (2018) Intracellular Hepatitis C Virus Modeling Predicts Infection Dynamics and Viral Protein Mechanisms. J Virol 92:
Vaidya, Naveen K; Ribeiro, Ruy M; Liu, Pinghuang et al. (2018) Correlation Between Anti-gp41 Antibodies and Virus Infectivity Decay During Primary HIV-1 Infection. Front Microbiol 9:1326

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