Systems Pharmacology Approach Toward the Design of Inhaled Formulations of Rifampicin and Isoniazid for Treatment of Tuberculosis.

Conventional oral therapies for the treatment of tuberculosis are limited by poor antibiotic distribution in granulomas, which contributes to lengthy treatment regimens and inadequate bacterial sterilization. Inhaled formulations are a promising strategy to increase antibiotic efficacy and reduce dose frequency. We develop a multiscale computational approach that accounts for simultaneous dynamics of a lung granuloma, carrier release kinetics, pharmacokinetics, and pharmacodynamics. Using this computational platform, we predict that a rationally designed inhaled formulation of isoniazid given at a significantly reduced dose frequency has better sterilizing capabilities and reduced toxicity than the current oral regimen. Furthermore, we predict that inhaled formulations of rifampicin require unrealistic carrier antibiotic loadings that lead to early toxicity concerns. Lastly, we predict that targeting carriers to macrophages has limited effects on treatment efficacy. Our platform can be extended to account for additional antibiotics and provides a new tool for rapidly prototyping the efficacy of inhaled formulations.

Computational modeling of tuberculous meningitis reveals an important role for tumor necrosis factor-α.

Tuberculosis is a global health issue with annually about 1.5 million deaths and 2 billion infected people worldwide. Extra-pulmonary tuberculosis comprises 13% of all cases of which tuberculous meningitis is the most severe. It has a high mortality and is often diagnosed once irreversible neurological damage has already occurred. Development of diagnostic and treatment strategies requires a thorough understanding of the pathogenesis of tuberculous meningitis. This disease is characterized by the formation of a cerebral granuloma, which is a collection of immune cells that attempt to immunologically restrain, and physically contain bacteria. The cytokine tumor necrosis factor-α is known for its important role in granuloma formation. Because traditional experimental animal studies exploring tuberculous meningitis are difficult and expensive, another approach is needed to begin to address this important and significant disease outcome. Here, we present an in silico model capturing the unique immunological environment of the brain that allows us to study the key mechanisms driving granuloma formation in time. Uncertainty and sensitivity analysis reveals a dose-dependent effect of tumor necrosis factor-α on bacterial load and immune cell numbers thereby influencing the onset of tuberculous meningitis. Insufficient levels result in bacterial overgrowth, whereas high levels lead to uncontrolled inflammation being detrimental to the host. These findings have important implications for the development of immuno-modulating treatment strategies for tuberculous meningitis.

Macrophage response to Mycobacterium tuberculosis infection.

The immune response to Mycobacterium tuberculosis (Mtb) infection is the formation of multicellular lesions, or granolomas, in the lung of the individual. However, the structure of the granulomas and the spatial distribution of the immune cells within is not well understood. In this paper we develop a mathematical model investigating the early and initial immune response to Mtb. The model consists of coupled reaction-diffusion-advection partial differential equations governing the dynamics of the relevant macrophage and bacteria populations and a bacteria-produced chemokine. Our novel application of mathematical concepts of internal states and internal velocity allows us to begin to study this unique immunological structure. Volume changes resulting from proliferation and death terms generate a velocity field by which all cells are transported within the forming granuloma. We present numerical results for two distinct infection outcomes: controlled and uncontrolled granuloma growth. Using a simplified model we are able to analytically determine conditions under which the bacteria population decreases, representing early clearance of infection, or grows, representing the initial stages of granuloma formation.

Live attenuated HIV vaccines: predicting the tradeoff between efficacy and safety.

The utility of live attenuated vaccines for controlling HIV epidemics is being debated. Live attenuated HIV vaccines (LAHVs) could be extremely effective in protecting against infection with wild-type strains, but may not be completely safe as the attenuated strain could cause AIDS in some vaccinated individuals. We present a theoretical framework for evaluating the consequences of the tradeoff between vaccine efficacy (in terms of preventing new infections with wild-type strains) and safety (in terms of vaccine-induced AIDS deaths). We use our framework to predict, for Zimbabwe and Thailand, the epidemiological impact of 1,000 different (specified by efficacy and safety characteristics) LAHVs. We predict that paradoxically: (i) in Zimbabwe (where transmission is high) LAHVs would significantly decrease the AIDS death rate, but (ii) in Thailand (where transmission is low) exactly the same vaccines (in terms of efficacy and safety characteristics) would increase the AIDS death rate. Our results imply that a threshold transmission rate exists that determines whether any given LAHV has a beneficial or a detrimental impact. We also determine the vaccine perversity point, which is defined in terms of the fraction of vaccinated individuals who progress to AIDS as a result of the vaccine strain. Vaccination with any LAHV that causes more than 5% of vaccinated individuals to progress to AIDS in 25 years would, even 50 years later, lead to perversity (i.e., increase the annual AIDS death rate) in Thailand; these same vaccines would lead to decreases in the annual AIDS death rate in Zimbabwe.

Role of the thymus in pediatric HIV-1 infection.

Several lines of evidence suggest that HIV-1 is present in the thymus during HIV-1 infection. Precursors to mature CD4+ T lymphocytes develop in the thymus, which suggests that thymic infection may play a role in the CD4+ T-cell decline observed during the course of pediatric HIV-1 infection. We illustrate, through mathematical modeling, the potential effects of thymic infection on the course of pediatric AIDS disease progression. We find that infection in the thymus not only can supplement peripheral infection but can help explain the faster progression in pediatric cases, as well as the early and high viral burden.

Understanding drug resistance for monotherapy treatment of HIV infection.

The purpose of this study was to investigate strategies in the monotherapy treatment of HIV infection in the presence of drug-resistant (mutant) strains. A mathematical system is developed to model resistance in HIV chemotherapy. It includes the key players in the immune response to HIV infection: virus and both uninfected CD4+ and infected CD4+ T-cell populations. We model the latent and progressive stages of the disease, and then introduce monotherapy treatment. The model is a system of differential equations describing the interaction of two distinct classes of HIV--drug-sensitive (wild type) and drug-resistant (mutant)--with lymphocytes in the peripheral blood. We then introduce chemotherapy effects. In the absence of treatment, the model produces the three types of qualitative clinical behavior--an uninfected steady state, an infected steady state (latency), and progression to AIDS. Simulation of treatment is provided for monotherapy, during the progression to AIDS state, in the consideration of resistance effects. Treatment benefit is based on an increase or retention in CD4+ T-cell counts together with a low viral titer. We explore the following treatment approaches: an antiviral drug which reduces viral infectivity that is administered early--when the CD4+ T-cell count is > or = 300/mm3, and the late--when the CD4+ T-cell count is less than 300/mm3. We compare all results with data. When treatment is initiated during the progression to AIDS state, treatment prevents T-cell collapse, but gradually loses effectiveness due to drug resistance. We hypothesize that it is the careful balance of mutant and wild-type HIV strains which provides the greatest prolonged benefit from treatment. This is best achieved when treatment is initiated when the CD4+ T-cell counts are greater than 250/mm3, but less than 400/mm3 in this model (i.e. not too early, not too late). These results are supported by clinical data. The work is novel in that it is the first model to accurately simulate data before, during and after monotherapy treatment. Our model also provides insight into recent clinical results, as well as suggests plausible guidelines for clinical testing in the monotherapy of HIV infection.

Resistance, remission, and qualitative differences in HIV chemotherapy.

To understand the role of qualitative differences in multidrug chemotherapy for human immunodeficiency virus (HIV) infection in virus remission and drug resistance, we designed a mathematical system that models HIV multidrug chemotherapy including uninfected CD4+ T cells, infected CD4+ T cells, and virus populations. The model, which includes the latent and progressive stages of the disease and introduces chemotherapy, is a system of differential equations describing the interaction of two distinct classes of HIV (drug-sensitive [wild type] and drug-resistant [mutant]) with lymphocytes in the peripheral blood; the external lymphoid system contributes to the viral load. The simulations indicate that to preclude resistance, antiviral drugs must be strong enough and act fast enough to drive the viral population below a threshold level. The threshold depends upon the capacity of the virus to mutate to strains resistant to the drugs. Above the threshold, mutant strains rapidly replace wild-type strains. Below the threshold, resistant strains do not become established, and remission occurs. An important distinction between resistance and remission is the reduction of viral production in the external lymphoid system. Also the virus population rapidly rebounds when treatment is stopped even after extended periods of remission.

The dynamics of Helicobacter pylori infection of the human stomach.

Helicobacter pylori is a bacterial pathogen of the gastrointestinal tract of humans causing chronic superficial gastritis which persists for decades. The mechanism by which H. pylori is able to persist, despite environmental constraints, remains unknown. Therefore, a model is proposed describing the interactions of H. pylori with its host, involving an autoregulatory network in which inflammation leads to nutrient release. A determinist mathematical model examining the interactions necessary to maintain chronic infection indicates that this proposed autoregulatory network can produce steady-state solutions, and the model is robust in encompassing biological variations.

Dynamics of HIV infection of CD4+ T cells.

We examine a model for the interaction of HIV with CD4+ T cells that considers four populations: uninfected T cells, latently infected T cells, actively infected T cells, and free virus. Using this model we show that many of the puzzling quantitative features of HIV infection can be explained simply. We also consider effects of AZT on viral growth and T-cell population dynamics. The model exhibits two steady states, an uninfected state in which no virus is present and an endemically infected state, in which virus and infected T cells are present. We show that if N, the number of infectious virions produced per actively infected T cell, is less a critical value, Ncrit, then the uninfected state is the only steady state in the nonnegative orthant, and this state is stable. For N > Ncrit, the uninfected state is unstable, and the endemically infected state can be either stable, or unstable and surrounded by a stable limit cycle. Using numerical bifurcation techniques we map out the parameter regimes of these various behaviors. oscillatory behavior seems to lie outside the region of biologically realistic parameter values. When the endemically infected state is stable, it is characterized by a reduced number of T cells compared with the uninfected state. Thus T-cell depletion occurs through the establishment of a new steady state. The dynamics of the establishment of this new steady state are examined both numerically and via the quasi-steady-state approximation. We develop approximations for the dynamics at early times in which the free virus rapidly binds to T cells, during an intermediate time scale in which the virus grows exponentially, and a third time scale on which viral growth slows and the endemically infected steady state is approached. Using the quasi-steady-state approximation the model can be simplified to two ordinary differential equations the summarize much of the dynamical behavior. We compute the level of T cells in the endemically infected state and show how that level varies with the parameters in the model. The model predicts that different viral strains, characterized by generating differing numbers of infective virions within infected T cells, can cause different amounts of T-cell depletion and generate depletion at different rates. Two versions of the model are studied. In one the source of T cells from precursors is constant, whereas in the other the source of T cells decreases with viral load, mimicking the infection and killing of T-cell precursors.(ABSTRACT TRUNCATED AT 400 WORDS)