Optimal drug treatment regimens for HIV depend on adherence

Drug therapies aimed at suppressing the human immunodeficiency virus (HIV) are highly effective, often reducing the viral load to below the limits of detection for years. Adherence to such antiviral regimens, however, is typically far from ideal. We have previously developed a model that predicts optimal treatment regimens by weighing drug toxicity against CD4+ T-cell counts, including the probability that drug resistance will emerge. We use this model to investigate the influence of adherence on therapy benefit. For a drug with a given half-life, we compare the effects of varying the dose amount and dose interval for different rates of adherence, and compute the optimal dose regimen for adherence between 65% and 95%. Our results suggest that for optimal treatment benefit, drug regimens should be adjusted for poor adherence, usually by increasing the dose amount and leaving the dose interval fixed. We also find that the benefit of therapy can be surprisingly robust to poor adherence, as long as the dose interval and dose amount are chosen accordingly.     

Costs versus benefits: best possible and best practical treatment regimens for HIV

Current HIV therapy, although highly effective, may cause very serious side effects, making adherence to the prescribed regimen difficult. Mathematical modeling may be used to evaluate alternative treatment regimens by weighing the positive results of treatment, such as higher levels of helper T cells, against the negative consequences, such as side effects and the possibility of resistance mutations. Although estimating the weights assigned to these factors is difficult, current clinical practice offers insight by defining situations in which therapy is considered “worthwhile”. We therefore use clinical practice, along with the probability that a drug-resistant mutation is present at the start of therapy, to suggest methods of rationally estimating these weights. In our underlying model, we use ordinary differential equations to describe the time course of in-host HIV infection, and include populations of both activated CD4⁺ T cells and CD8⁺ T cells. We then determine the best possible treatment regimen, assuming that the effectiveness of the drug can be continually adjusted, and the best practical treatment regimen, evaluating all patterns of a block of days “on” therapy followed by a block of days “off” therapy. We find that when the tolerance for drug-resistant mutations is low, high drug concentrations which maintain low infected cell populations are optimal. In contrast, if the tolerance for drug-resistant mutations is fairly high, the optimal treatment involves periods of reduced drug exposure which consequently boost the immune response through increased antigen exposure. We elucidate the dependence of the optimal treatment regimen on the pharmacokinetic parameters of specific antiviral agents.     

Principles of Drug Therapy in Patients with Renal Disease

Patients with reduced renal function commonly require drug therapy for various associated conditions. Most drugs are fully or partially excreted by the kidney; therefore, drug dosage regimens often need to be adjusted in order to provide safe yet effective treatment for patients with renal disease. In addition, certain therapeutic agents have potential nephrotoxicity and pharmacologic actions that may jeopardize already compromised renal function. Understanding of drug pharmacology, the therapeutic dose and the speed of drug elimination in a given patient will lead to correct assessment of the drug regimen.     

Within-Host Virus Models with Periodic Antiviral Therapy

This paper investigates the effect of drug treatment on the standard within-host virus model, assuming that therapy occurs periodically. It is shown that eradication is possible under these periodic regimens, and we quantitatively characterize successful drugs or drug combinations, both theoretically and numerically. We also consider certain optimization problems, motivated for instance, by the fact that eradication should be achieved at acceptable toxicity levels to the patient. It turns out that these optimization problems can be simplified considerably, and this makes calculations of the optima a fairly straightforward task. All our results will be illustrated on an HIV model by means of numerical examples based on up-to-date knowledge of parameter values in the model. Supported in part by NSF grant DMS-0614651.     

An In-Depth Comparison of Latent HIV-1 Reactivation in Multiple Cell Model Systems and Resting CD4+ T Cells from Aviremic Patients

The possibility of HIV-1 eradication has been limited by the existence of latently infected cellular reservoirs. Studies to examine control of HIV latency and potential reactivation have been hindered by the small numbers of latently infected cells found in vivo. Major conceptual leaps have been facilitated by the use of latently infected T cell lines and primary cells. However, notable differences exist among cell model systems. Furthermore, screening efforts in specific cell models have identified drug candidates for “anti-latency” therapy, which often fail to reactivate HIV uniformly across different models. Therefore, the activity of a given drug candidate, demonstrated in a particular cellular model, cannot reliably predict its activity in other cell model systems or in infected patient cells, tested ex vivo. This situation represents a critical knowledge gap that adversely affects our ability to identify promising treatment compounds and hinders the advancement of drug testing into relevant animal models and clinical trials. To begin to understand the biological characteristics that are inherent to each HIV-1 latency model, we compared the response properties of five primary T cell models, four J-Lat cell models and those obtained with a viral outgrowth assay using patient-derived infected cells. A panel of thirteen stimuli that are known to reactivate HIV by defined mechanisms of action was selected and tested in parallel in all models. Our results indicate that no single in vitro cell model alone is able to capture accurately the ex vivo response characteristics of latently infected T cells from patients. Most cell models demonstrated that sensitivity to HIV reactivation was skewed toward or against specific drug classes. Protein kinase C agonists and PHA reactivated latent HIV uniformly across models, although drugs in most other classes did not.     

Predicting differential responses to structured treatment interruptions during HAART

Highly active antiretroviral therapy (HAART) has been used clinically in various administration schemes for several years. However, due to the development of drug resistance, evolution of viral strains, serious side effects, and poor patient compliance, the combination of drugs used in HAART fails to effectively contain virus long term in a high proportion of patients. Our group and others have suggested a change to the usual regimen of continuous HAART through structured treatment interruptions (STIs). STIs may provide similar clinical benefits as continuous treatment such as reduced viral loads and reestablishment of CD4⁺ T cells while allowing patients drug holidays. We explore the use of STIs using a previously published model that accurately represents CD4⁺ T-cell counts and viral loads during both untreated HIV-1 infection and HAART therapy. We simulate the effects of different STI regimens including weekly and monthly interruptions together with variations in treatment initiation time. We predict that differential responses to STIs as observed in conflicting clinical trial data are impacted by the duration of the interruption, stage of infection at initiation of treatment, strength of the immune system in suppressing virus, or pre-therapy CD4⁺ T-cell count or virus load. Our results indicate that dynamics occurring below the limit of detection (LOD) are influenced by these factors, and contribute to reemergence or suppression of virus during interruptions. Simulations predict that short-term viral suppression with varying interruptions strategies does not guarantee long-term clinical benefit.     

Modeling of HIV-1 Infection: Insights to the Role of Monocytes/Macrophages,Latently Infected T4 Cells,and HAART Regimes

A novel dynamic model covering five types of cells and three connected compartments, peripheral blood (PB), lymph nodes (LNs), and the central nervous system (CNS), is here proposed. It is based on assessment of the biological principles underlying the interactions between the human immunodeficiency virus type I (HIV-1) and the human immune system. The simulated results of this model matched the three well-documented phases of HIV-1 infection very closely and successfully described the three stages of LN destruction that occur during HIV-1 infection. The model also showed that LNs are the major location of viral replication, creating a pool of latently infected T4 cells during the latency period. A detailed discussion of the role of monocytes/macrophages is made, and the results indicated that infected monocytes/macrophages could determine the progression of HIV-1 infection. The effects of typical highly active antiretroviral therapy (HAART) drugs on HIV-1 infection were analyzed and the results showed that efficiency of each drug but not the time of the treatment start contributed to the change of the turnover of the disease greatly. An incremental count of latently infected T4 cells was made under therapeutic simulation, and patients were found to fail to respond to HAART therapy in the presence of certain stimuli, such as opportunistic infections. In general, the dynamics of the model qualitatively matched clinical observations very closely, indicating that the model may have benefits in evaluating the efficacy of different drug therapy regimens and in the discovery of new monitoring markers and therapeutic schemes for the treatment of HIV-1 infection.     

Drug-Sparing Regimens for HIV Combination Therapy: Benefits Predicted for “Drug Coasting”

Structured Treatment Interruptions (STI) during HIV drug therapy were thought to potentially reduce side effects and toxicity, boost immune involvement, and possibly lower the viral set-point. Clinical trials of STI regimens, however, have had mixed results. We use an established mathematical model of HAART to estimate possible therapeutic outcomes for STI and for other, similar patterns in HIV combination therapy. We perform an exhaustive search of patterns of up to 60 days, for triple-drug combinations involving accurate pharmacokinetics for 12 specific antiviral drugs. The results of this analysis are consistent with recent clinical trials which have demonstrated that STI-type patterns, involving therapy interruption of weeks or months, are rarely optimal. Our analysis predicts, however, that the benefit of treatment can often be improved by including very short drug-free periods, during which the patient effectively “coasts” for a day or two on adequate drug concentrations due to the long half-life of some pharmaceuticals. Our analysis predicts many cases in which this may be achieved without increasing the risk of drug-resistance. This suggests that “drug coasting” patterns, significantly shorter than STI patterns, may merit further clinical investigation in efforts to find drug-sparing regimens for HIV. Electronic Supplementary Material The online version of this article () contains supplementary material, which is available to authorized users.     

The decay of the latent reservoir of replication-competent HIV-1 is inversely correlated with the extent of residual viral replication during prolonged anti-retroviral therapy

Replication-competent HIV-1 can be isolated from infected patients despite prolonged plasma virus suppression by anti-retroviral treatment. Recent studies have identified resting, memory CD4+ T lymphocytes as a long-lived latent reservoir of HIV-1 (refs. 4,5). Cross-sectional analyses indicate that the reservoir is rather small, between 103 and 107 cells per patient. In individuals whose plasma viremia levels are well suppressed by anti-retroviral therapy, peripheral blood mononuclear cells containing replication-competent HIV-1 were found to decay with a mean half-life of approximately 6 months, close to the decay characteristics of memory lymphocytes in humans and monkeys. In contrast, little decay was found in a less-selective patient population. We undertook this study to address this apparent discrepancy. Using a quantitative micro-culture assay, we demonstrate here that the latent reservoir decays with a mean half-life of 6.3 months in patients who consistently maintain plasma HIV-1 RNA levels of fewer than 50 copies/ml. Slower decay rates occur in individuals who experience intermittent episodes of plasma viremia. Our findings indicate that the persistence of the latent reservoir of HIV-1 despite prolonged treatment is due not only to its slow intrinsic decay characteristics but also to the inability of current drug regimens to completely block HIV-1 replication.     

Modeling within-host HIV-1 dynamics and the evolution of drug resistance: trade-offs between viral enzyme function and drug susceptibility

There are many biological steps between viral infection of CD4(+) T cells and the production of HIV-1 virions. Here we incorporate an eclipse phase, representing the stage in which infected T cells have not started to produce new virus, into a simple HIV-1 model. Model calculations suggest that the quicker infected T cells progress from the eclipse stage to the productively infected stage, the more likely that a viral strain will persist. Long-term treatment effectiveness of antiretroviral drugs is often hindered by the frequent emergence of drug resistant virus during therapy. We link drug resistance to both the rate of progression of the eclipse phase and the rate of viral production of the resistant strain, and explore how the resistant strain could evolve to maximize its within-host viral fitness. We obtained the optimal progression rate and the optimal viral production rate, which maximize the fitness of a drug resistant strain in the presence of drugs. We show that the window of opportunity for invasion of drug resistant strains is widened for a higher level of drug efficacy provided that the treatment is not potent enough to eradicate both the sensitive and resistant virus.     

Disulfiram reactivates latent HIV-1 in a Bcl-2-transduced primary CD4+ T cell model without inducing global T cell activation

Highly active antiretroviral therapy (HAART) can reduce plasma HIV-1 levels to below the detection limit. However, due to the latent reservoir in resting CD4(+) cells, HAART is not curative. Elimination of this reservoir is critical to curing HIV-1 infection. Agents that reactivate latent HIV-1 through nonspecific T cell activation are toxic. Here we demonstrate in a primary CD4(+) T cell model that the FDA-approved drug disulfiram reactivates latent HIV-1 without global T cell activation. The extent to which disulfiram reactivates latent HIV-1 in patient cells is unclear, but the drug alone or in combination may be useful in future eradication strategies.     

Modelling the effects of adherence to the HIV fusion inhibitor enfuvirtide

Recently, the first drug in a new class of antiretroviral HIV drugs was approved, the fusion inhibitor enfuvirtide. We develop a mathematical model that describes the binding of the virus to T cells. We model the effect of enfuvirtide upon this process using impulsive differential equations. We find equilibria and determine stability in the case of no therapy and then when therapy is taken with perfect adherence. We determine analytical thresholds for the dosage and dosing intervals to ensure the disease-free equilibrium remains stable. We also explore the effects of partial adherence. Our theoretical results suggest that partial adherence may, at times, be worse than no therapy at all, but at other times may in fact as good as perfect adherence. It follows that patients should be counselled on the importance of adherence to this new antiretroviral drug.     

Mathematical analysis of delay differential equation models of HIV-1 infection

Models of HIV-1 infection that include intracellular delays are more accurate representations of the biology and change the estimated values of kinetic parameters when compared to models without delays. We develop and analyze a set of models that include intracellular delays, combination antiretroviral therapy, and the dynamics of both infected and uninfected T cells. We show that when the drug efficacy is less than perfect the estimated value of the loss rate of productively infected T cells, delta, is increased when data is fit with delay models compared to the values estimated with a non-delay model. We provide a mathematical justification for this increased value of delta. We also provide some general results on the stability of non-linear delay differential equation infection models.     

Can the viral reservoir of latently infected CD4<Superscript>+</Superscript> T cells be eradicated with antiretroviral HIV drugs?

The majority of cells infected with the human immunodeficiency virus are activated CD4⁺ T cells, which can be treated with antiretoviral drugs. However, an obstacle to eradication is the presence of viral reservoirs, such as latently infected CD4⁺ T cells. Such cells may be less susceptible to antiretroviral drugs and may persist at low levels during treatment. We introduce a model of impulsive differential equations that describe T cell and drug interactions. We make the extreme assumption that latently infected cells are unaffected by drugs, in order to answer the research question: Can the viral reservoir of latently infected cells be eradicated using current antiretroviral therapy? We analyse the model in both the presence and absence of drugs, showing that, if the frequency of drug taking is sufficiently high, then the number of uninfected CD4⁺ T cells approaches the number of T cells in the uninfected immune system. In particular, this implies that the latent reservoir will be eliminated. It follows that, with sufficient application of drugs, latently infected cells cannot sustain a viral reservoir on their own. We illustrate the results with numerical simulations.     

Evaluating the Cellular Targets of Anti-4-1BB Agonist Antibody during Immunotherapy of a Pre-Established Tumor in Mice

Background

Manipulation of the immune system represents a promising avenue for cancer therapy. Rational advances in immunotherapy of cancer will require an understanding of the precise correlates of protection. Agonistic antibodies against the tumor necrosis factor receptor family member 4-1BB are emerging as a promising tool in cancer therapy, with evidence that these antibodies expand both T cells as well as innate immune cells. Depletion studies have suggested that several cell types can play a role in these immunotherapeutic regimens, but do not reveal which cells must directly receive the 4-1BB signals for effective therapy.

Methodology/Principal Findings

We show that re-activated memory T cells are superior to resting memory T cells in control of an 8-day pre-established E.G7 tumor in mice. We find that ex vivo activation of the memory T cells allows the activated effectors to continue to divide and enter the tumor, regardless of antigen-specificity; however, only antigen-specific reactivated memory T cells show any efficacy in tumor control. When agonistic anti-4-1BB antibody is combined with this optimized adoptive T cell therapy, 80% of mice survive and are fully protected from tumor rechallenge. Using 4-1BB-deficient mice and mixed bone marrow chimeras, we find that it is sufficient to have 4-1BB only on the endogenous host αβ T cells or only on the transferred T cells for the effects of anti-4-1BB to be realized. Conversely, although multiple immune cell types express 4-1BB and both T cells and APC expand during anti-4-1BB therapy, 4-1BB on cells other than αβ T cells is neither necessary nor sufficient for the effect of anti-4-1BB in this adoptive immunotherapy model.

Conclusions/Significance

This study establishes αβ T cells rather than innate immune cells as the critical target in anti-4-1BB therapy of a pre-established tumor. The study also demonstrates that ex vivo activation of memory T cells prior to infusion allows antigen-specific tumor control without the need for reactivation of the memory T cells in the tumor.     

Modeling the role of macrophages in HIV persistence during antiretroviral therapy

HIV preferentially infects activated CD4+ T cells. Current antiretroviral therapy cannot eradicate the virus. Viral infection of other cells such as macrophages may contribute to viral persistence during antiretroviral therapy. In addition to cell-free virus infection, macrophages can also get infected when engulfing infected CD4+ T cells as innate immune sentinels. How macrophages affect the dynamics of HIV infection remains unclear. In this paper, we develop an HIV model that includes the infection of CD4+ T cells and macrophages via cell-free virus infection and cell-to-cell viral transmission. We derive the basic reproduction number and obtain the local and global stability of the steady states. Sensitivity and viral dynamics simulations show that even when the infection of CD4+ T cells is completely blocked by therapy, virus can still persist and the steady-state viral load is not sensitive to the change of treatment efficacy. Analysis of the relative contributions to viral replication shows that cell-free virus infection leads to the majority of macrophage infection. Viral transmission from infected CD4+ T cells to macrophages during engulfment accounts for a small fraction of the macrophage infection and has a negligible effect on the total viral production. These results suggest that macrophage infection can be a source contributing to HIV persistence during suppressive therapy. Improving drug efficacies in heterogeneous target cells is crucial for achieving HIV eradication in infected individuals.