A perspective on modelling hepatitis C virus infection

Intracellular "In Silico Microscopes"-Comprehensive 3D Spatio-Temporal Virus Replication Model Simulations

Despite their small and simple structure compared with their hosts, virus particles can cause severe harm and even mortality in highly evolved species such as humans. A comprehensive quantitative biophysical understanding of intracellular virus replication mechanisms could aid in preparing for future virus pandemics. By elucidating the relationship between the form and function of intracellular structures from the host cell and viral components, it is possible to identify possible targets for direct antiviral agents and potent vaccines. Biophysical investigations into the spatio-temporal dynamics of intracellular virus replication have thus far been limited. This study introduces a framework to enable simulations of these dynamics using partial differential equation (PDE) models, which are evaluated using advanced numerical mathematical methods on leading supercomputers. In particular, this study presents a model of the replication cycle of a specific RNA virus, the hepatitis C virus. The diffusion-reaction model mimics the interplay of the major components of the viral replication cycle, including non structural viral proteins, viral genomic RNA, and a generic host factor. Technically, surface partial differential equations (sufPDEs) are coupled on the 3D embedded 2D endoplasmic reticulum manifold with partial differential equations (PDEs) in the 3D membranous web and cytosol volume. The membranous web serves as a viral replication factory and is formed on the endoplasmic reticulum after infection and in the presence of nonstructural proteins. The coupled sufPDE/PDE model was evaluated using realistic cell geometries based on experimental data. The simulations incorporate the effects of non structural viral proteins, which are restricted to the endoplasmic reticulum surface, with effects appearing in the volume, such as host factor supply from the cytosol and membranous web dynamics. Because the spatial diffusion properties of genomic viral RNA are not yet fully understood, the model allows for viral RNA movement on the endoplasmic reticulum as well as within the cytosol. Visualizing the simulated intracellular viral replication dynamics provides insights similar to those obtained by microscopy, complementing data from in vitro/in vivo viral replication experiments. The output data demonstrate quantitative consistence with the experimental findings, prompting further advanced experimental studies to validate the model and refine our quantitative biophysical understanding.

Incorporating Intracellular Processes in Virus Dynamics Models

In-host models have been essential for understanding the dynamics of virus infection inside an infected individual. When used together with biological data, they provide insight into viral life cycle, intracellular and cellular virus-host interactions, and the role, efficacy, and mode of action of therapeutics. In this review, we present the standard model of virus dynamics and highlight situations where added model complexity accounting for intracellular processes is needed. We present several examples from acute and chronic viral infections where such inclusion in explicit and implicit manner has led to improvement in parameter estimates, unification of conclusions, guidance for targeted therapeutics, and crossover among model systems. We also discuss trade-offs between model realism and predictive power and highlight the need of increased data collection at finer scale of resolution to better validate complex models.

Viral rebound occurrence immediately after drug discontinuation involving neither drug resistance nor latent reservoir

Some viruses exhibit "rebound" when the administration of antiviral drugs is discontinued. Viral rebound caused by resistance mutations or latent reservoirs has been studied mathematically. In this study, we investigated the viral rebound due to other causes. Since immunity is weaker during antiviral treatment than without the treatment, drug discontinuation may lead to an increase in the viral load. We analyzed the dynamics of the number of virus-infected cells, cytotoxic T lymphocytes, and memory cells and identified the conditions under which the viral load increased upon drug discontinuation. If drug is administered for an extended period, a viral rebound occurs when the ratio of viral growth rate in the absence to that in the presence of the antiviral drug exceeds the "rebound threshold." We analyzed how the rebound threshold depended on the patient's conditions and the type of treatment. Mathematical and numerical analyses revealed that rebound after discontinuation was more likely to occur when the drug effectively reduced viral proliferation, drug discontinuation was delayed, and the processes activating immune responses directly were stronger than those occurring indirectly through immune memory formation. We discussed additional reasons for drugs to cause viral rebound more likely.

Qualitative behaviour of a stochastic hepatitis C epidemic model in cellular level

In this paper, a mathematical model describing the dynamical of the spread of hepatitis C virus (HCV) at a cellular level with a stochastic noise in the transmission rate is developed from the deterministic model. The unique time-global solution for any positive initial value is served. The Ito's Formula, the suitable Lyapunov function, and other stochastic analysis techniques are used to analyze the model dynamics. The numerical simulations are carried out to describe the analytical results. These results highlight the impact of the noise intensity accelerating the extinction of the disease.

A multiscale model of virus pandemic: Heterogeneous interactive entities in a globally connected world

This paper is devoted to the multidisciplinary modelling of a pandemic initiated by an aggressive virus, specifically the so-called SARS-CoV-2 Severe Acute Respiratory Syndrome, corona virus n.2. The study is developed within a multiscale framework accounting for the interaction of different spatial scales, from the small scale of the virus itself and cells, to the large scale of individuals and further up to the collective behaviour of populations. An interdisciplinary vision is developed thanks to the contributions of epidemiologists, immunologists and economists as well as those of mathematical modellers. The first part of the contents is devoted to understanding the complex features of the system and to the design of a modelling rationale. The modelling approach is treated in the second part of the paper by showing both how the virus propagates into infected individuals, successfully and not successfully recovered, and also the spatial patterns, which are subsequently studied by kinetic and lattice models. The third part reports the contribution of research in the fields of virology, epidemiology, immune competition, and economy focussed also on social behaviours. Finally, a critical analysis is proposed looking ahead to research perspectives.

Within-host modeling of blood-stage malaria

Malaria infection continues to be a major health problem worldwide and drug resistance in the major human parasite species, Plasmodium falciparum, is increasing in South East Asia. Control measures including novel drugs and vaccines are in development, and contributions to the rational design and optimal usage of these interventions are urgently needed. Infection involves the complex interaction of parasite dynamics, host immunity, and drug effects. The long life cycle (48 hours in the common human species) and synchronized replication cycle of the parasite population present significant challenges to modeling the dynamics of Plasmodium infection. Coupled with these, variation in immune recognition and drug action at different life cycle stages leads to further complexity. We review the development and progress of "within-host" models of Plasmodium infection, and how these have been applied to understanding and interpreting human infection and animal models of infection.

Advanced Hepatitis C Virus Replication PDE Models within a Realistic Intracellular Geometric Environment

The hepatitis C virus (HCV) RNA replication cycle is a dynamic intracellular process occurring in three-dimensional space (3D), which is difficult both to capture experimentally and to visualize conceptually. HCV-generated replication factories are housed within virus-induced intracellular structures termed membranous webs (MW), which are derived from the Endoplasmatic Reticulum (ER). Recently, we published 3D spatiotemporal resolved diffusion⁻reaction models of the HCV RNA replication cycle by means of surface partial differential equation (sPDE) descriptions. We distinguished between the basic components of the HCV RNA replication cycle, namely HCV RNA, non-structural viral proteins (NSPs), and a host factor. In particular, we evaluated the sPDE models upon realistic reconstructed intracellular compartments (ER/MW). In this paper, we propose a significant extension of the model based upon two additional parameters: different aggregate states of HCV RNA and NSPs, and population dynamics inspired diffusion and reaction coefficients instead of multilinear ones. The combination of both aspects enables realistic modeling of viral replication at all scales. Specifically, we describe a replication complex state consisting of HCV RNA together with a defined amount of NSPs. As a result of the combination of spatial resolution and different aggregate states, the new model mimics a cis requirement for HCV RNA replication. We used heuristic parameters for our simulations, which were run only on a subsection of the ER. Nevertheless, this was sufficient to allow the fitting of core aspects of virus reproduction, at least qualitatively. Our findings should help stimulate new model approaches and experimental directions for virology.

Adaptive protocols based on predictions from a mechanistic model of the effect of IL7 on CD4 counts

In human immunodeficiency virus-infected patients, antiretroviral therapy suppresses the viral replication, which is followed in most patients by a restoration of CD4+ T cells pool. For patients who fail to do so, repeated injections of exogenous interleukin 7 (IL7) are experimented. The IL7 is a cytokine that is involved in the T cell homeostasis and the INSPIRE study has shown that injections of IL7 induced a proliferation of CD4+ T cells. Phase I/II INSPIRE 2 and 3 studies have evaluated a protocol in which a first cycle of three IL7 injections is followed by a new cycle at each visit when the patient has less than 550 CD4 cells/μL. Restoration of the CD4 concentration has been demonstrated, but the long-term best adaptive protocol is yet to be determined. A mechanistic model of the evolution of CD4 after IL7 injections has been developed, which is based on a system of ordinary differential equations and includes random effects. Based on the estimation of this model, we use a Bayesian approach to forecast the dynamics of CD4 in new patients. We propose four prediction-based adaptive protocols of injections to minimize the time spent under 500 CD4 cells/μL for each patient, without increasing the number of injections received too much. We show that our protocols significantly reduce the time spent under 500 CD4 over a period of two years, without increasing the number of injections. These protocols have the potential to increase the efficiency of this therapy.

Impact of Interferon Lambda 4 Genotype on Interferon-Stimulated Gene Expression During Direct-Acting Antiviral Therapy for Hepatitis C

New directly acting antivirals (DAAs) provide very high cure rates in most patients infected by hepatitis C virus (HCV). However, some patient groups have been relatively harder to treat, including those with cirrhosis or infected with HCV genotype 3. In the recent BOSON trial, genotype 3, patients with cirrhosis receiving a 16-week course of sofosbuvir and ribavirin had a sustained virological response (SVR) rate of around 50%. In patients with cirrhosis, interferon lambda 4 (IFNL4) CC genotype was significantly associated with SVR. This genotype was also associated with a lower interferon-stimulated gene (ISG) signature in peripheral blood and in liver at baseline. Unexpectedly, patients with the CC genotype showed a dynamic increase in ISG expression between weeks 4 and 16 of DAA therapy, whereas the reverse was true for non-CC patients. Conclusion: These data provide an important dynamic link between host genotype and phenotype in HCV therapy also potentially relevant to naturally acquired infection. (Hepatology 2018; 00:000-000).

Superinfection and cure of infected cells as mechanisms for hepatitis C virus adaptation and persistence

RNA viruses exist as a genetically diverse quasispecies with extraordinary ability to adapt to abrupt changes in the host environment. However, the molecular mechanisms that contribute to their rapid adaptation and persistence in vivo are not well studied. Here, we probe hepatitis C virus (HCV) persistence by analyzing clinical samples taken from subjects who were treated with a second-generation HCV protease inhibitor. Frequent longitudinal viral load determinations and large-scale single-genome sequence analyses revealed rapid antiviral resistance development, and surprisingly, dynamic turnover of dominant drug-resistant mutant populations long after treatment cessation. We fitted mathematical models to both the viral load and the viral sequencing data, and the results provided strong support for the critical roles that superinfection and cure of infected cells play in facilitating the rapid turnover and persistence of viral populations. More broadly, our results highlight the importance of considering viral dynamics and competition at the intracellular level in understanding rapid viral adaptation. Thus, we propose a theoretical framework integrating viral and molecular mechanisms to explain rapid viral evolution, resistance, and persistence despite antiviral treatment and host immune responses.

Mathematical Analysis of Viral Replication Dynamics and Antiviral Treatment Strategies: From Basic Models to Age-Based Multi-Scale Modeling

Viral infectious diseases are a global health concern, as is evident by recent outbreaks of the middle east respiratory syndrome, Ebola virus disease, and re-emerging zika, dengue, and chikungunya fevers. Viral epidemics are a socio-economic burden that causes short- and long-term costs for disease diagnosis and treatment as well as a loss in productivity by absenteeism. These outbreaks and their socio-economic costs underline the necessity for a precise analysis of virus-host interactions, which would help to understand disease mechanisms and to develop therapeutic interventions. The combination of quantitative measurements and dynamic mathematical modeling has increased our understanding of the within-host infection dynamics and has led to important insights into viral pathogenesis, transmission, and disease progression. Furthermore, virus-host models helped to identify drug targets, to predict the treatment duration to achieve cure, and to reduce treatment costs. In this article, we review important achievements made by mathematical modeling of viral kinetics on the extracellular, intracellular, and multi-scale level for Human Immunodeficiency Virus, Hepatitis C Virus, Influenza A Virus, Ebola Virus, Dengue Virus, and Zika Virus. Herein, we focus on basic mathematical models on the population scale (so-called target cell-limited models), detailed models regarding the most important steps in the viral life cycle, and the combination of both. For this purpose, we review how mathematical modeling of viral dynamics helped to understand the virus-host interactions and disease progression or clearance. Additionally, we review different types and effects of therapeutic strategies and how mathematical modeling has been used to predict new treatment regimens.

Quantitative Analysis of Hepatitis C NS5A Viral Protein Dynamics on the ER Surface

Exploring biophysical properties of virus-encoded components and their requirement for virus replication is an exciting new area of interdisciplinary virological research. To date, spatial resolution has only rarely been analyzed in computational/biophysical descriptions of virus replication dynamics. However, it is widely acknowledged that intracellular spatial dependence is a crucial component of virus life cycles. The hepatitis C virus-encoded NS5A protein is an endoplasmatic reticulum (ER)-anchored viral protein and an essential component of the virus replication machinery. Therefore, we simulate NS5A dynamics on realistic reconstructed, curved ER surfaces by means of surface partial differential equations (sPDE) upon unstructured grids. We match the in silico NS5A diffusion constant such that the NS5A sPDE simulation data reproduce experimental NS5A fluorescence recovery after photobleaching (FRAP) time series data. This parameter estimation yields the NS5A diffusion constant. Such parameters are needed for spatial models of HCV dynamics, which we are developing in parallel but remain qualitative at this stage. Thus, our present study likely provides the first quantitative biophysical description of the movement of a viral component. Our spatio-temporal resolved ansatz paves new ways for understanding intricate spatial-defined processes central to specfic aspects of virus life cycles.

3D Spatially Resolved Models of the Intracellular Dynamics of the Hepatitis C Genome Replication Cycle

Mathematical models of virus dynamics have not previously acknowledged spatial resolution at the intracellular level despite substantial arguments that favor the consideration of intracellular spatial dependence. The replication of the hepatitis C virus (HCV) viral RNA (vRNA) occurs within special replication complexes formed from membranes derived from endoplasmatic reticulum (ER). These regions, termed membranous webs, are generated primarily through specific interactions between nonstructural virus-encoded proteins (NSPs) and host cellular factors. The NSPs are responsible for the replication of the vRNA and their movement is restricted to the ER surface. Therefore, in this study we developed fully spatio-temporal resolved models of the vRNA replication cycle of HCV. Our simulations are performed upon realistic reconstructed cell structures-namely the ER surface and the membranous webs-based on data derived from immunostained cells replicating HCV vRNA. We visualized 3D simulations that reproduced dynamics resulting from interplay of the different components of our models (vRNA, NSPs, and a host factor), and we present an evaluation of the concentrations for the components within different regions of the cell. Thus far, our model is restricted to an internal portion of a hepatocyte and is qualitative more than quantitative. For a quantitative adaption to complete cells, various additional parameters will have to be determined through further in vitro cell biology experiments, which can be stimulated by the results deccribed in the present study.

Improvement of ALT decay kinetics by all-oral HCV treatment: Role of NS5A inhibitors and differences with IFN-based regimens

BACKGROUND

Intracellular HCV-RNA reduction is a proposed mechanism of action of direct-acting antivirals (DAAs), alternative to hepatocytes elimination by pegylated-interferon plus ribavirin (PR). We modeled ALT and HCV-RNA kinetics in cirrhotic patients treated with currently-used all-DAA combinations to evaluate their mode of action and cytotoxicity compared with telaprevir (TVR)+PR.

STUDY DESIGN

Mathematical modeling of ALT and HCV-RNA kinetics was performed in 111 HCV-1 cirrhotic patients, 81 treated with all-DAA regimens and 30 with TVR+PR. Kinetic-models and Cox-analysis were used to assess determinants of ALT-decay and normalization.

RESULTS

HCV-RNA kinetics was biphasic, reflecting a mean effectiveness in blocking viral production >99.8%. The first-phase of viral-decline was faster in patients receiving NS5A-inhibitors compared to TVR+PR or sofosbuvir+simeprevir (p<0.001), reflecting higher efficacy in blocking assembly/secretion. The second-phase, noted δ and attributed to infected-cell loss, was faster in patients receiving TVR+PR or sofosbuvir+simeprevir compared to NS5A-inhibitors (0.27 vs 0.21 d-1, respectively, p = 0.0012). In contrast the rate of ALT-normalization, noted λ, was slower in patients receiving TVR+PR or sofosbuvir+simeprevir compared to NS5A-inhibitors (0.17 vs 0.27 d-1, respectively, p<0.001). There was no significant association between the second-phase of viral-decline and ALT normalization rate and, for a given level of viral reduction, ALT-normalization was more profound in patients receiving DAA, and NS5A in particular, than TVR+PR.

CONCLUSIONS

Our data support a process of HCV-clearance by all-DAA regimens potentiated by NS5A-inhibitor, and less relying upon hepatocyte death than IFN-containing regimens. This may underline a process of "cell-cure" by DAAs, leading to a fast improvement of liver homeostasis.

In-host modeling

Understanding the mechanisms governing host-pathogen kinetics is important and can guide human interventions. In-host mathematical models, together with biological data, have been used in this endeavor. In this review, we present basic models used to describe acute and chronic pathogenic infections. We highlight the power of model predictions, the role of drug therapy, and advantage of considering the dynamics of immune responses. We also present the limitations of these models due in part to the trade-off between the complexity of the model and their predictive power, and the challenges a modeler faces in determining the appropriate formulation for a given problem.

Interferon-α-induced CD100 on naïve CD8+ T cells enhances antiviral responses to hepatitis C infection through CD72 signal transduction

Objectives We investigated the effects of CD100 on naïve CD8⁺ T cells during hepatitis C virus (HCV) infection after interferon-α (IFN-α) therapy to clarify the mechanism underlying the effect of IFN-α in enhancing the antiviral response. Methods The CD100 molecules on subsets of CD8⁺ T cells were analysed with flow cytometry. The effects of CD100-overexpressing naïve CD8⁺ T cells were determined with ELISAs and an MTT cytotoxicity assay. The role of CD100-CD72 signal transduction was analysed with a neutralization and transwell assays. Results HCV infection reduced CD100 expression on CD8⁺ T cells, whereas IFN-α treatment significantly increased CD100 expression on naïve CD8⁺ T cells. The increased CD100 interacted with the CD72 receptor and enhanced PBMC cytokine secretion (IFN-γ and tumour necrosis factor-α) and cytotoxicity. Conclusions IFN-α-induced CD100 on naïve CD8⁺ T cells promotes PBMC cytokine secretion and cytotoxicity through CD100-CD72 signalling during HCV infection.

Global dynamics of a viral infection model with full logistic terms and antivirus treatments

In this paper, mathematical analysis of the global dynamics of a viral infection model in vivo is carried out. Though the model is originally to study hepatitis C virus (HCV) dynamics in patients with high baseline viral loads or advanced liver disease, similar models still hold significance for other viral infection, such as hepatitis B virus (HBV) or human immunodeficiency virus (HIV) infection. By means of Volterra-type Lyapunov functions, we know that the basic reproduction number [Formula: see text] is a sharp threshold para-meter for the outcomes of viral infections. If [Formula: see text], the virus-free equilibrium is globally asymptotically stable. If [Formula: see text], the system is uniformly persistent, the unique endemic equilibrium appears and is globally asymptotically stable under a sufficient condition. Other than that, for the global stability of the unique endemic equilibrium, another sufficient condition is obtained by Li–Muldowney global-stability criterion. Using numerical simulation techniques, we further find that sustained oscillations can exist and different maximum de novo hepatocyte influx rate can induce different global dynamics along with the change of overall drug effectiveness. Finally, some biological implications of our findings are given.

Daclatasvir + asunaprevir + beclabuvir ± ribavirin for chronic HCV genotype 1-infected treatment-naive patients

BACKGROUND AND AIMS

This phase-2b study examined the safety and efficacy of an all-oral, interferon-free combination of the NS5A replication complex inhibitor daclatasvir (DCV), the NS3 protease inhibitor asunaprevir (ASV), and the nonnucleoside NS5B polymerase inhibitor beclabuvir (BCV) with or without ribavirin in patients with HCV genotype (GT) 1 infection.

METHODS

A total of 187 patients received 12 weeks of DCV 30 mg BID plus ASV 200 mg BID and BCV 150 mg BID (n = 86) or 75 mg BID with (n = 21) or without (n = 80) weight-based ribavirin BID. The primary endpoint was HCV RNA <25 IU/ml at post-treatment week 12 (SVR12).

RESULTS

Overall, 90% of patients (169/187) in the combined treatment groups achieved SVR on or after post-treatment week 12. SVR rates were similar across subgroups (by mITT analysis), i.e. patients with cirrhosis (88%, 14/16), HCV GT-1a (90%, 137/155), and IL28B non-CC genotype (90%, 115/128). There were no drug-related serious AEs or grade 4 AEs. The most frequently reported AEs were headache, diarrhoea, fatigue and nausea. Addition of ribavirin to DCV+ASV+BCV was associated with decreased haemoglobin, compared with DCV+ASV+BCV alone. There were six grade 3/4 laboratory abnormalities noted, all unrelated to the study drugs. Viral breakthrough occurred in 2.5-4.8% of patients across groups and appeared unrelated to BCV dose or ribavirin inclusion.

CONCLUSIONS

Results support phase 3 evaluation of a twice-daily, fixed-dose formulation of this DCV+ASV+BCV regimen with or without ribavirin in HCV GT-1-infected patients.

Markov cellular automata models for chronic disease progression

We analyze a Markov cellular automaton that models the spread of viruses that often progress to a chronic condition, such as human immunodeficiency virus (HIV) or hepatitis C virus (HCV). We show that the complex dynamical system produces a Markov process at the later stages, whose eigenvectors corresponding to the eigenvalue 1 have physical significance for the long-term prognosis of the virus. Moreover we show that drug treatment leads to chronic conditions that can be modeled by Markov shifts with more optimal eigenvectors.

A method to determine the duration of the eclipse phase for in vitro infection with a highly pathogenic SHIV strain

The time elapsed between successful cell infection and the start of virus production is called the eclipse phase. Its duration is specific to each virus strain and, along with an effective virus production rate, plays a key role in infection kinetics. How the eclipse phase varies amongst cells infected with the same virus strain and therefore how best to mathematically represent its duration is not clear. Most mathematical models either neglect this phase or assume it is exponentially distributed, such that at least some if not all cells can produce virus immediately upon infection. Biologically, this is unrealistic (one must allow for the translation, transcription, export, etc. to take place), but could be appropriate if the duration of the eclipse phase is negligible on the time-scale of the infection. If it is not, however, ignoring this delay affects the accuracy of the mathematical model, its parameter estimates, and predictions. Here, we introduce a new approach, consisting in a carefully designed experiment and simple analytical expressions, to determine the duration and distribution of the eclipse phase in vitro. We find that the eclipse phase of SHIV-KS661 lasts on average one day and is consistent with an Erlang distribution.

Modeling the effect of HIV coinfection on clearance and sustained virologic response during treatment for hepatitis C virus

BACKGROUND

HIV/hepatitis C (HCV) coinfection is a major concern in global health today. Each pathogen can exacerbate the effects of the other and affect treatment outcomes. Understanding the within-host dynamics of these coinfecting pathogens is crucial, particularly in light of new, direct-acting antiviral agents (DAAs) for HCV treatment that are becoming available.

METHODS AND FINDINGS

In this study, we construct a within-host mathematical model of HCV/HIV coinfection by adapting a previously published model of HCV monoinfection to include an immune system component in infection clearance. We explore the effect of HIV-coinfection on spontaneous HCV clearance and sustained virologic response (SVR) by building in decreased immune function with increased HIV viral load. Treatment is modeled by modifying HCV burst-size, and we use clinically-relevant parameter estimates. Our model replicates real-world patient outcomes; it outputs infected and uninfected target cell counts, and HCV viral load for varying treatment and coinfection scenarios. Increased HIV viral load and reduced CD4(+) count correlate with decreased spontaneous clearance and SVR chances. Treatment efficacy/duration combinations resulting in SVR are calculated for HIV-positive and negative patients, and crucially, we replicate the new findings that highly efficacious DAAs reduce treatment differences between HIV-positive and negative patients. However, we also find that if drug efficacy decays sufficiently over treatment course, SVR differences between HIV-positive and negative patients reappear.

CONCLUSIONS

Our model shows theoretical evidence of the differing outcomes of HCV infection in cases where the immune system is compromised by HIV. Understanding what controls these outcomes is especially important with the advent of efficacious but often prohibitively expensive DAAs. Using a model to predict patient response can lend insight into optimal treatment design, both in helping to identify patients who might respond well to treatment and in helping to identify treatment pathways and pitfalls.

Hepatitis C virus-specific cytotoxic T cell response restoration after treatment-induced hepatitis C virus control

Hepatitis C virus (HCV)-specific cytotoxic T cell (CTL) response plays a major role in viral control during spontaneous infection resolution. These cells develop an exhausted and pro-apoptotic status during chronic onset, being unable to get rid of HCV. The role of this response in contributing to sustained viral response (SVR) after anti-HCV is controversial. Recent studies show that after successful interferon-based anti-HCV treatment, HCV traces are still detectable and this correlates with a peak of HCV-specific CTL response activation, probably responsible for maintaining SVR by subsequent complete HCV clearing. Moreover, SVR patients’ serum is still able to induce HCV infection in naïve chimpanzees, suggesting that the infection could be under the control of the immune system after a successful treatment, being transmissible in absence of this adaptive response. At least theoretically, treatment-induced viral load decrease could allow an effective HCV-specific CTL response reestablishment. This effect has been recently described with anti-HCV interferon-free regimes, based on direct-acting antivirals. Nevertheless, this is to some extent controversial with interferon-based therapies, due to the detrimental immunoregulatory α-interferon effect on T cells. Moreover, HCV-specific CTL response features during anti-HCV treatment could be a predictive factor of SVR that could have clinical implications in patient management. In this review, the recent knowledge about the role of HCV-specific CTL response in the development of SVR after anti-HCV treatment is discussed.

Virologic response following combined ledipasvir and sofosbuvir administration in patients with HCV genotype 1 and HIV co-infection

IMPORTANCE

There is an unmet need for interferon- and ribavirin-free treatment for chronic hepatitis C virus (HCV) infection in patients co-infected with human immunodeficiency virus (HIV).

OBJECTIVE

To evaluate the rates of sustained virologic response (SVR) and adverse events in previously untreated patients with HCV genotype 1 and HIV co-infection following a 12-week treatment of the fixed-dose combination of ledipasvir and sofosbuvir.

DESIGN, SETTING, AND PARTICIPANTS

Open-label, single-center, phase 2b pilot study of previously untreated, noncirrhotic patients with HCV genotype 1 and HIV co-infection conducted at the Clinical Research Center of the National Institutes of Health, Bethesda, Maryland, from June 2013 to September 2014. Patients included those receiving antiretroviral therapy with HIV RNA values of 50 copies/mL or fewer and a CD4 T-lymphocyte count of 100 cells/mL or greater or patients with untreated HIV infection with a CD4 T-lymphocyte count of 500 cells/mL or greater. Serial measurements of safety parameters, virologic and host immune correlates, and adherence were performed.

INTERVENTIONS

Fifty patients with HCV genotype 1 never before treated for HCV were prescribed a fixed-dose combination of ledipasvir (90 mg) and sofosbuvir (400 mg) once daily for 12 weeks.

MAIN OUTCOMES AND MEASURES

The primary study outcome was the proportion of patients with sustained viral response (plasma HCV RNA level <12 IU/mL) 12 weeks after end of treatment.

RESULTS

Forty-nine of 50 participants (98% [95% CI, 89% to 100%]) achieved SVR 12 weeks after end of treatment, whereas 1 patient experienced relapse at week 4 following treatment. In the patient with relapse, deep sequencing revealed a resistance associated mutation in the NS5A region conferring resistance to NS5A inhibitors, such as ledipasvir. The most common adverse events were nasal congestion (16% of patients) and myalgia (14%). There were no discontinuations or serious adverse events attributable to study drug.

CONCLUSIONS AND RELEVANCE

In this open-label, uncontrolled, pilot study enrolling patients co-infected with HCV genotype 1 and HIV, administration of an oral combination of ledipasvir and sofosbuvir for 12 weeks was associated with high rates of SVR after treatment completion. Larger studies that also include patients with cirrhosis and lower CD4 T-cell counts are required to understand if the results of this study generalize to all patients co-infected with HCV and HIV.

TRIAL REGISTRATION

clinicaltrials.gov Identifier:NCT01878799.

Inferring viral dynamics in chronically HCV infected patients from the spatial distribution of infected hepatocytes

Chronic liver infection by hepatitis C virus (HCV) is a major public health concern. Despite partly successful treatment options, several aspects of intrahepatic HCV infection dynamics are still poorly understood, including the preferred mode of viral propagation, as well as the proportion of infected hepatocytes. Answers to these questions have important implications for the development of therapeutic interventions. In this study, we present methods to analyze the spatial distribution of infected hepatocytes obtained by single cell laser capture microdissection from liver biopsy samples of patients chronically infected with HCV. By characterizing the internal structure of clusters of infected cells, we are able to evaluate hypotheses about intrahepatic infection dynamics. We found that individual clusters on biopsy samples range in size from infected cells. In addition, the HCV RNA content in a cluster declines from the cell that presumably founded the cluster to cells at the maximal cluster extension. These observations support the idea that HCV infection in the liver is seeded randomly (e.g. from the blood) and then spreads locally. Assuming that the amount of intracellular HCV RNA is a proxy for how long a cell has been infected, we estimate based on models of intracellular HCV RNA replication and accumulation that cells in clusters have been infected on average for less than a week. Further, we do not find a relationship between the cluster size and the estimated cluster expansion time. Our method represents a novel approach to make inferences about infection dynamics in solid tissues from static spatial data.

Around 170 million people worldwide are chronically infected with the hepatitis C virus (HCV). Although partly successful treatment options are available, several aspects of HCV infection dynamics within the liver are still poorly understood. How many hepatocytes are infected during chronic HCV infection? How does the virus propagate, and how do innate immune responses interfere with the spread of the virus? We developed mathematical and computational methods to study liver biopsy samples of patients chronically infected with HCV that were analyzed by single cell laser capture microdissection, to infer the spatial distribution of infected cells. With these methods, we find that infected cells on biopsy sections tend to occur in clusters comprising 4–50 hepatocytes, and, based on their amount of intracellular viral RNA, that these cells have been infected for less than a week. The observed HCV RNA profile within clusters of infected cells suggests that factors such as local immune responses could have shaped cluster expansion and intracellular viral replication. Our methods can be applied to various types of infections in order to infer infection dynamics from spatial data.

Mathematical modeling of multi-drugs therapy: a challenge for determining the optimal combinations of antiviral drugs

In the current era of antiviral drug therapy, combining multiple drugs is a primary approach for improving antiviral effects, reducing the doses of individual drugs, relieving the side effects of strong antiviral drugs, and preventing the emergence of drug-resistant viruses. Although a variety of new drugs have been developed for HIV, HCV and influenza virus, the optimal combinations of multiple drugs are incompletely understood. To optimize the benefits of multi-drugs combinations, we must investigate the interactions between the combined drugs and their target viruses. Mathematical models of viral infection dynamics provide an ideal tool for this purpose. Additionally, whether drug combinations computed by these models are synergistic can be assessed by two prominent drug combination theories, Loewe additivity and Bliss independence. By combining the mathematical modeling of virus dynamics with drug combination theories, we could show the principles by which drug combinations yield a synergistic effect. Here, we describe the theoretical aspects of multi-drugs therapy and discuss their application to antiviral research.

On the laws of virus spread through cell populations

The dynamics of viral infections have been investigated extensively, often with a combination of experimental and mathematical approaches. Mathematical descriptions of virus spread through cell populations are well established in the literature and have yielded important insights, yet the formulation of certain fundamental aspects of virus dynamics models remains uncertain and untested. Here, we investigate the process of infection and, in particular, the effect of varying the target cell population size on the number of productively infected cells generated. Using an in vitro single-round HIV-1 infection system, we find that the established modeling framework cannot accurately fit the data. If the model is fit to data with the lowest number of cells and is used to predict data generated with larger cell populations, the model significantly overestimates the number of productively infected cells generated. Interestingly, this deviation becomes stronger under experimental conditions that promote mixing of cells and viruses. The reason for the deviation is that the standard model makes certain oversimplifying assumptions about the fate of viruses that fail to find a cell in their immediate proximity. We derive from stochastic processes a different model that assumes simultaneous access of the virus to multiple target cells. In this scenario, if no cell is available to the virus at its location, it has a chance to interact with other cells, a process that can be promoted by mixing of the populations. This model can accurately fit the experimental data and suggests a new interpretation of mass action in virus dynamics models.

IMPORTANCE

Understanding the principles of virus growth through cell populations is of fundamental importance to virology. It helps us make informed decisions about intervention strategies aimed at preventing virus growth, such as drug treatment or vaccination approaches, e.g., in HIV infection, yet considerable uncertainty remains in this respect. An important variable in this context is the number of susceptible cells available for virus replication. How does the number of susceptible cells influence the growth potential of the virus? Besides the importance of such information for clinical responses, a thorough understanding of this is also important for the prediction of virus levels in patients and the estimation of crucial patient parameters through the use of mathematical models. This paper investigates the relationship between target cell availability and the virus growth potential with a combination of experimental and mathematical approaches and provides significant new insights.

Using pharmacokinetic and viral kinetic modeling to estimate the antiviral effectiveness of telaprevir, boceprevir, and pegylated interferon during triple therapy in treatment-experienced hepatitis C virus-infected cirrhotic patients

Triple therapy combining a protease inhibitor (PI) (telaprevir or boceprevir), pegylated interferon (PEG-IFN), and ribavirin (RBV) has dramatically increased the chance of eradicating hepatitis C virus (HCV). However, the efficacy of this treatment remains suboptimal in cirrhotic treatment-experienced patients. Here, we aimed to better understand the origin of this impaired response by estimating the antiviral effectiveness of each drug. Fifteen HCV genotype 1-infected patients with compensated cirrhosis, who were nonresponders to prior PEG-IFN/RBV therapy, were enrolled in a nonrandomized study. HCV RNA and concentrations of PIs, PEG-IFN, and RBV were frequently assessed in the first 12 weeks of treatment and were analyzed using a pharmacokinetic/viral kinetic model. The two PIs achieved similar levels of molar concentrations (P=0.5), but there was a significant difference in the 50% effective concentrations (EC50) (P=0.008), leading to greater effectiveness for telaprevir than for boceprevir in blocking viral production (99.8% versus 99.0%, respectively, P=0.002). In all patients, the antiviral effectiveness of PEG-IFN was modest (43.4%), and there was no significant contribution of RBV exposure to the total antiviral effectiveness. The second phase of viral decline, which is attributed to the loss rate of infected cells, was slow (0.19 day(-1)) and was higher in patients who subsequently eradicated HCV (P=0.03). The two PIs achieved high levels of antiviral effectiveness. However, the suboptimal antiviral effectiveness of PEG-IFN/RBV and the low loss of infected cells suggest that a longer treatment duration might be needed in cirrhotic treatment-experienced patients and that a future IFN-free regimen may be particularly beneficial in these patients.

A pharmacokinetic-viral kinetic model describes the effect of alisporivir as monotherapy or in combination with peg-IFN on hepatitis C virologic response

Alisporivir is a cyclophilin inhibitor with demonstrated in vitro and in vivo activity against hepatitis C virus (HCV). We estimated the antiviral effectiveness of alisporivir alone or in combination with pegylated interferon (peg-IFN) in 88 patients infected with different HCV genotypes treated for 4 weeks. The pharmacokinetics of the two drugs were modeled and used as driving functions for the viral kinetic model. Genotype was found to significantly affect peg-IFN effectiveness (ɛ = 86.3 and 99.1% for genotypes 1/4 and genotypes 2/3, respectively, P < 10(-7)) and the loss rate of infected cells (δ = 0.22 vs. 0.39 per day in genotype 1/4 and genotype 2/3 patients, respectively, P < 10(-6)). Alisporivir effectiveness was not significantly different across genotypes and was high for doses ≥600 mg q.d. We simulated virologic responses with other alisporivir dosing regimens in HCV genotype 2/3 patients using the model. Our predictions consistently matched the observed responses, demonstrating that this model could be a useful tool for anticipating virologic response and optimizing alisporivir-based therapies.

Viral kinetic modeling: state of the art

Viral kinetic (VK) modeling has led to increased understanding of the within host dynamics of viral infections and the effects of therapy. Here we review recent developments in the modeling of viral infection kinetics with emphasis on two infectious diseases: hepatitis C and influenza. We review how VK modeling has evolved from simple models of viral infections treated with a drug or drug cocktail with an assumed constant effectiveness to models that incorporate drug pharmacokinetics and pharmacodynamics, as well as phenomenological models that simply assume drugs have time varying-effectiveness. We also discuss multiscale models that include intracellular events in viral replication, models of drug-resistance, models that include innate and adaptive immune responses and models that incorporate cell-to-cell spread of infection. Overall, VK modeling has provided new insights into the understanding of the disease progression and the modes of action of several drugs. We expect that VK modeling will be increasingly used in the coming years to optimize drug regimens in order to improve therapeutic outcomes and treatment tolerability for infectious diseases.

Comparison of daclatasvir resistance barriers on NS5A from hepatitis C virus genotypes 1 to 6: implications for cross-genotype activity

A comparison of the daclatasvir (DCV [BMS-790052]) resistance barrier on authentic or hybrid replicons containing NS5A from hepatitis C virus (HCV) genotypes 1 to 6 (GT-1 to -6) was completed using a replicon elimination assay. The data indicated that genotype 1b (GT-1b) has the highest relative resistance barrier and genotype 2a (GT-2a M31) has the lowest. The rank order of resistance barriers to DCV was 1b>4a≥5a>6a≅1a>2a JFH>3a>2a M31. Importantly, DCV in combination with a protease inhibitor (PI) eliminated GT-2a M31 replicon RNA at a clinically relevant concentration. Previously, we reported the antiviral activity and resistance profiles of DCV on HCV genotypes 1 to 4 evaluated in the replicon system. Here, we report the antiviral activity and resistance profiles of DCV against hybrid replicons with NS5A sequences derived from HCV GT-5a and GT-6a clinical isolates. DCV was effective against both GT-5a and -6a hybrid replicon cell lines (50% effective concentrations [EC50s] ranging from 3 to 7 pM for GT-5a, and 74 pM for GT-6a). Resistance selection identified amino acid substitutions in the N-terminal domain of NS5A. For GT-5a, L31F and L31V, alone or in combination with K56R, were the major resistance variants (EC50s ranging from 2 to 40 nM). In GT-6a, Q24H, L31M, P32L/S, and T58A/S were identified as resistance variants (EC50s ranging from 2 to 250 nM). The in vitro data suggest that DCV has the potential to be an effective agent for HCV genotypes 1 to 6 when used in combination therapy.

HCV-specific CD8+ cell detection at week 12 of chronic hepatitis C treatment with PEG-interferon-α2b/ribavirin correlates with infection resolution

Lower than 2-log viral-load (VL) decrease at week 12 (w12) of chronic hepatitis C (CHC) treatment with Peg-interferon/ribavirin has 100% negative predictive value (PV) of sustained virologic response (SVR), and this could be related with absence of HCV-specific cytotoxic T lymphocyte (CTL) response. In this study, percentage of cases with SVR, according to peripheral HCV-specific cytotoxic response at w12, was analysed (Group-1: detection(+), Group-2: detection(-)). SVR was higher in group-1 (93%) than in group-2 (47%) (p=0.003). An increase on HCV-specific CTL frequency between baseline and w12 and higher specific reactivity were observed in group-1 (p=0.011 and p=0.025). HCV-specific CTL detection at w12 correlated with level of VL decrease (p=0.016, r=0.389), and among HCV genotype-1 patients with either early or delayed virologic response (EDVR), 100% positive PV of SVR was observed. In summary, HCV-specific CTL detection at w12 of Peg-interferon/ribavirin treatment correlates with SVR and in EDVR genotype-1 cases predicts SVR.

Quantification of viral infection dynamics in animal experiments

Analyzing the time-course of several viral infections using mathematical models based on experimental data can provide important quantitative insights regarding infection dynamics. Over the past decade, the importance and significance of mathematical modeling has been gaining recognition among virologists. In the near future, many animal models of human-specific infections and experimental data from high-throughput techniques will become available. This will provide us with the opportunity to develop new quantitative approaches, combining experimental and mathematical analyses. In this paper, we review the various quantitative analyses of viral infections and discuss their possible applications.

Deep sequencing analysis of HCV NS3 resistance-associated variants and mutation linkage in liver transplant recipients

Viral variants with decreased susceptibility to HCV protease inhibitors (PIs) occur naturally and preexist at low levels within HCV populations. In patients failing PI monotherapy, single and double mutants conferring intermediate to high-level resistance to PIs have been selected in vivo. The abundance, temporal dynamics and linkage of naturally occurring resistance-associated variants (RAVs), however, have not been characterized in detail. Here, using high-density pyrosequencing, we analyzed HCV NS3 gene segments from 20 subjects with chronic HCV infection, including 12 subjects before and after liver transplantation. Bioinformatics analysis revealed that Q80 substitution was a dominant variant in 40% of the subjects, whereas other RAVs circulate at low levels within quasispecies populations. Low frequency mutation linkage was detectable by Illumina paired-end sequencing in as low as 0.5% of the mock populations constructed from in vitro RNA transcripts but were uncommon in vivo. We show that naturally occurring RAVs are common and can persist long term following liver transplant at low levels not readily detectable by conventional sequencing. Our results indicate that mutation linkage at low levels could be identified using the Illumina paired-end approach. The methods described here should facilitate the analysis of low frequency HCV drug resistance, mutation linkage and evolution, which may inform future therapeutic strategies in patients undergoing direct acting antiviral therapies.

Discovery and Clinical Validation of HCV Inhibitors Targeting the NS5A Protein

HCV non‐structural protein 5A (NS5A) is a multifunctional protein that plays a diverse set of roles in the replication cycle of the virus. Although a significant level of effort has been invested over the past decade at characterizing this protein, our understanding and appreciation of its full structure and function remain far from complete. Despite these drawbacks, however, great strides have been made towards discovering potent HCV NS5A inhibitors that have exhibited promising efficacy in early clinical trials, and these inhibitors have the potential to become an integral component of effective combination therapies that are expected to emerge in the near future. Highlights of the biochemical characterization of the HCV NS5A protein, aspects of the seminal drug discovery effort that culminated in the identification of daclatasvir with which clinical proof‐of‐concept was obtained for NS5A as a target and the follow‐up efforts that identified additional inhibitors, along with findings from mode‐of‐action studies, are discussed.

Mathematical analysis of multiscale models for hepatitis C virus dynamics under therapy with direct-acting antiviral agents

Chronic hepatitis C virus (HCV) infection remains a world-wide public health problem. Therapy with interferon and ribavirin leads to viral elimination in less than 50% of treated patients. New treatment options aiming at a higher cure rate are focused on direct-acting antiviral agents (DAAs), which directly interfere with different steps in the HCV life cycle. In this paper, we describe and analyze a recently developed multiscale model that predicts HCV dynamics under therapy with DAAs. The model includes both intracellular viral RNA replication and extracellular viral infection. We calculate the steady states of the model and perform a detailed stability analysis. With certain assumptions we obtain analytical approximations of the viral load decline after treatment initiation. One approximation agrees well with the prediction of the model, and can conveniently be used to fit patient data and estimate parameter values. We also discuss other possible ways to incorporate intracellular viral dynamics into the multiscale model.

Characterization of virologic escape in hepatitis C virus genotype 1b patients treated with the direct-acting antivirals daclatasvir and asunaprevir

BACKGROUND & AIMS

Daclatasvir and asunaprevir are NS5A and NS3 protease-targeted antivirals currently under development for treatment of chronic hepatitis C virus infection. Clinical data on baseline and on-treatment correlates of drug resistance and response to these agents are currently limited.

METHODS

Hepatitis C virus genotype 1b Japanese patients (prior null responders to PegIFN-α/RBV [n=21] or PegIFN-α/RBV ineligible or intolerant [n=22]) were administered daclatasvir/asunaprevir for 24 weeks during a phase 2a open-label study. Genotypic and phenotypic analyses of NS3 and NS5A substitutions were performed at baseline, after virologic failure, and post-treatment through follow-up week 36.

RESULTS

There were three viral breakthroughs and four relapsers. Baseline NS3 polymorphisms (T54S, Q80L, V170M) at amino acid positions previously associated with low-level resistance (<9-fold) to select NS3 protease inhibitors were detected in four null responders and three ineligibles, but were not associated with virologic failure. Baseline NS5A polymorphisms (L28M, L31M, Y93H) associated with daclatasvir resistance (<25-fold) were detected in five null responders and six ineligibles. All three viral breakthroughs and 2/4 relapsers carried a baseline NS5A-Y93H polymorphism. NS3 and NS5A resistance-associated variants were detected together (NS3-D168A/V, NS5A-L31M/V-Y93H) after virologic failure. Generally, daclatasvir-resistant substitutions persisted through 48weeks post-treatment, whereas asunaprevir-resistant substitutions were no longer detectable. Overall, 5/10 patients with baseline NS5A-Y93H experienced virologic failure, while 5/10 achieved a sustained virologic response.

CONCLUSIONS

The potential association of a pre-existing NS5A-Y93H polymorphism with virologic failure on daclatasvir/asunaprevir combination treatment will be examined in larger studies. The persistence of treatment-emergent daclatasvir- and asunaprevir-resistant substitutions will require assessment in longer-term follow-up studies.

Analysis of hepatitis C virus decline during treatment with the protease inhibitor danoprevir using a multiscale model

The current paradigm for studying hepatitis C virus (HCV) dynamics in patients utilizes a standard viral dynamic model that keeps track of uninfected (target) cells, infected cells, and virus. The model does not account for the dynamics of intracellular viral replication, which is the major target of direct-acting antiviral agents (DAAs). Here we describe and study a recently developed multiscale age-structured model that explicitly considers the potential effects of DAAs on intracellular viral RNA production, degradation, and secretion as virus into the circulation. We show that when therapy significantly blocks both intracellular viral RNA production and virus secretion, the serum viral load decline has three phases, with slopes reflecting the rate of serum viral clearance, the rate of loss of intracellular viral RNA, and the rate of loss of intracellular replication templates and infected cells, respectively. We also derive analytical approximations of the multiscale model and use one of them to analyze data from patients treated for 14 days with the HCV protease inhibitor danoprevir. Analysis suggests that danoprevir significantly blocks intracellular viral production (with mean effectiveness 99.2%), enhances intracellular viral RNA degradation about 5-fold, and moderately inhibits viral secretion (with mean effectiveness 56%). The multiscale model can be used to study viral dynamics in patients treated with other DAAs and explore their mechanisms of action in treatment of hepatitis C.

Chronic infection with hepatitis C virus (HCV) remains an important health-care problem worldwide despite significant progress in the development of HCV therapy since the discovery of the virus in 1989. Current treatment options are focused on direct-acting antiviral agents (DAAs) that target specific steps of the HCV life cycle. Danoprevir, one of the DAAs that inhibit the HCV NS3-4A protease, has induced substantial viral load reductions in patients receiving therapy. We study the viral decline during therapy using a multiscale age-structured model that accounts for the dynamics of intracellular viral replication, and which includes the major steps in the HCV life cycle that are targeted by DAAs. We examine the biological parameters contributing to different phases of the viral decline after treatment initiation. We also explore the mechanisms of action of danoprevir and estimate its treatment effectiveness. The multiscale model provides a theoretical framework for studying virus dynamics in hepatitis C patients treated with other DAAs currently in clinical development, and may help one to optimally combine drugs with complementary modes of action to maximize the HCV cure rate.

Persistence of resistant variants in hepatitis C virus-infected patients treated with the NS5A replication complex inhibitor daclatasvir

Daclatasvir (DCV; BMS-790052) is a hepatitis C virus (HCV) NS5A replication complex inhibitor (RCI) with picomolar to low nanomolar potency and broad genotypic coverage in vitro. Viral RNA declines have been observed in the clinic for both alpha interferon-ribavirin (IFN-α-RBV) and IFN-RBV-free regimens that include DCV. Follow-up specimens (up to 6 months) from selected subjects treated with DCV in 14-day monotherapy studies were analyzed for genotype and phenotype. Variants were detected by clonal sequencing in specimens from baseline and were readily detected by population sequencing following viral RNA breakthrough and posttreatment. The major amino acid substitutions generating resistance in vivo were at residues M28, Q30, L31, and Y93 for genotype 1a (GT-1a) and L31 and Y93 for GT-1b, similar to the resistance substitutions observed with the in vitro replicon system. The primary difference in the resistance patterns observed in vitro and in vivo was the increased complexity of linked variant combinations observed in clinical specimens. Changes in the percentage of individual variants were observed during follow-up; however, the overall percentage of variants in the total population persisted up to 6 months. Our results suggest that during the 14-day monotherapy, most wild-type virus was eradicated by DCV. After the end of DCV treatment, viral fitness, rather than DCV resistance, probably determines which viral variants emerge as dominant in populations.

Hepatitis C viral kinetics: the past, present, and future

Mathematical modeling of hepatitis C viral kinetics has been an important tool in understanding hepatitis C virus (HCV) infection dynamics and in estimating crucial in vivo parameters characterizing the effectiveness of HCV therapy. Because of the introduction of direct-acting antiviral agents, there is a need to extend previous models so as to understand, characterize, and compare various new HCV treatment regimens. Here we review recent modeling efforts in this direction.

Preclinical evaluation of an anti-HCV miRNA cluster for treatment of HCV infection

We developed a strategy to treat hepatitis C virus (HCV) infection by replacing five endogenous microRNA (miRNA) sequences of a natural miRNA cluster (miR-17-92) with sequences that are complementary to the HCV genome. This miRNA cluster (HCV-miR-Cluster 5) is delivered to cells using adeno-associated virus (AAV) vectors and the miRNAs are expressed in the liver, the site of HCV replication and assembly. AAV-HCV-miR-Cluster 5 inhibited bona fide HCV replication in vitro by up to 95% within 2 days, and the spread of HCV to uninfected cells was prevented by continuous expression of the anti-HCV miRNAs. Furthermore, the number of cells harboring HCV RNA replicons decreased dramatically by sustained expression of the anti-HCV miRNAs, suggesting that the vector is capable of curing cells of HCV. Delivery of AAV-HCV-miR-Cluster 5 to mice resulted in efficient transfer of the miRNA gene cluster and expression of all five miRNAs in liver tissue, at levels up to 1,300 copies/cell. These levels achieved up to 98% gene silencing of cognate HCV sequences, and no liver toxicity was observed, supporting the safety of this approach. Therefore, AAV-HCV-miR-Cluster 5 represents a different paradigm for the treatment of HCV infection.

Mathematical modelling of HCV infection: what can it teach us in the era of direct-acting antiviral agents?

HCV infection is a major cause of chronic liver disease and affects nearly 170 million people worldwide. Whereas the previous standard of care with pegylated interferon and ribavirin had a modest effectiveness, the recent approval of two highly potent protease inhibitors and the ongoing development of dozens of direct-acting antiviral agents (DAAs) constitute a major milestone for HCV therapy. Mathematical modelling of viral kinetics under treatment has played an instrumental role in improving our understanding of virus pathogenesis and in guiding drug development. Here, we review the current state of HCV kinetic modelling, and challenges to the standard biphasic viral decline model that arise when fitting viral kinetic models to data obtained with DAAs.

Small molecule inhibitors of the hepatitis C virus-encoded NS5A protein

Hepatitis C virus (HCV) is a modern-day pandemic; 2-3% of the world's population are thought to be infected with the virus and are subsequently at risk of developing end-stage liver diseases. The traditional standard of care (SOC) for HCV-infected patients has been limited to a regimen of pegylated-interferon alpha (pegIFN) and ribavirin; displaying low cure rates in a majority of patients and severe side effects. However, in 2011 the first direct-acting antivirals (DAA) were licensed to treat HCV-infected patients in combination with SOC, which served to elevate treatment response rates. The HCV drug development pipeline is currently populated with many additional and improved DAAs; primarily molecules that target the virus-encoded protease or polymerase enzymes. These molecules are being evaluated both in combination with the traditional SOC and together with other DAAs as all-oral pegIFN-free regimens with the ultimate goal of developing multiple DAA-containing HCV therapies that do not rely on an pegIFN backbone. A recent addition to the arsenal of HCV inhibitors in development is represented by an entirely new DAA class; molecules that target the HCV-encoded non-enzymatic NS5A protein. NS5A is essential for HCV propagation and, although its actual functions are largely unknown, it is likely a key regulator of viral genome replication and virion assembly. The protein is exquisitely sensitive to small molecule-mediated inhibition; NS5A-targeting molecules are probably the most potent antiviral molecules ever discovered and exhibit a number of other attractive drug-like properties, including activity against many HCV genotypes/subtypes and once-daily dosing potential. Although their mechanism of action is unclear, NS5A-targeting molecules are already proving their utility in clinical evaluation; particularly as components of pegIFN-sparring DAA combination regimens. This review will aim to amalgamate our current understanding and knowledge of NS5A-targeting molecules; their discovery, properties, applications, and insight into their future impact as components of all-oral pegIFN-free DAA combination therapies to combat HCV infection.

Which of our modeling predictions are robust?

In theoretical ecology it is well known that the steady state expressions of the variables in a food chain crucially depend on the parity of the length of the chain. This poses a major problem for modeling real food webs because it is difficult to establish their true number of trophic levels, with sometimes rare predators and often rampant pathogens. Similar problems arise in the modeling of chronic viral infections. We review examples where seemingly general interpretations strongly depend on the number of levels in a model, and on its specific equations. This Perspective aims to open the discussion on this problem.

Abundant drug-resistant NS3 mutants detected by deep sequencing in hepatitis C virus-infected patients undergoing NS3 protease inhibitor monotherapy

The high genetic variation of hepatitis C virus (HCV) results in rapid selection of drug resistance mutations (DRMs) during monotherapy with direct-acting antivirals (DAAs). It has been proposed that each possible single mutant preexists in infected individuals; however, the levels of preexisting DRMs are too low to be directly quantified in most patients using current techniques. In this study, we evaluated the presence of DRMs in HCV-infected patients treated with the HCV protease inhibitors GS-9256 or GS-9451 as monotherapy using deep sequencing in 137 longitudinal samples from 45 patients. Software was developed to analyze deep-sequencing results with an assay cutoff of 0.25%. No NS3 DRMs that confer resistance to GS-9256 and GS-9451 (R155K, A156T, and D168V/E) were observed in 33 baseline samples at >0.25%. In contrast, these and other substitutions at NS3 positions 155, 156, and 168 were detected in 19/27 patients at day 2 (24 h) and 21/21 at day 4 (84 h) of monotherapy but not in placebo-treated patients. Based on the DRM growth kinetics during drug treatment, pretreated NS3 mutations at amino acids 155, 156, and 168 were estimated on average at 0.025% and 0.015% per genotype 1a and 1b HCV-infected patients, respectively. Relative fitness of the DRM viruses was shown to be significantly lower than the wild type. Deep-sequencing analyses of NS3 protease inhibitor-treated HCV-infected patients suggest a limit of HCV viral load suppression of 3.6 to 3.8 log(10) with NS3 protease inhibitor monotherapy that does not suppress the identified preexisting NS3 DRMs and thus a need for a combination therapy.

The impact of fibrosis and steatosis on early viral kinetics in HCV genotype 1-infected patients treated with Peg-IFN-alfa-2a and ribavirin

Hepatitis C viral (HCV) kinetics after initiation of interferon-based therapy provide valuable insights for understanding virus pathogenesis, evaluating treatment antiviral effectiveness and predicting treatment outcome. Adverse effects of liver fibrosis and steatosis on sustained virological response have been frequently reported, yet their impacts on the early viral kinetics remain unclear. In this study, associations between histology status and early viral kinetics were assessed in 149 HCV genotype 1-infected patients treated with pegylated interferon alfa-2a and ribavirin (DITTO trial). In multivariate analyses adjusted for critical factors such as IL28B genotype and baseline viral load, presence of significant fibrosis (Ishak stage > 2) was found to independently reduce the odds of achieving an initial reduction (calculated from day 0 to day 4) in HCV RNA of ≥2 logIU/mL (adjusted OR 0.03, P = 0.004) but was not associated with the second-phase slope of viral decline (calculated from day 8 to day 29). On the contrary, presence of liver steatosis was an independent risk factor for not having a rapid second-phase slope, that is, ≥0.3 logIU/mL/week (adjusted OR 0.22, P = 0.012) but was not associated with the first-phase decline. Viral kinetic modelling theory suggests that significant fibrosis primarily impairs the treatment antiviral effectiveness in blocking viral production by infected cells, whereas the presence of steatosis is associated with a lower net loss of infected cells. Further studies will be necessary to identify the biological mechanisms underlain by these findings.

Understanding silibinin's modes of action against HCV using viral kinetic modeling

BACKGROUND & AIMS

Legalon® SIL (SIL) is a chemically hydrophilized version of silibinin that has exhibited high antiviral effectiveness against hepatitis C virus (HCV). Its main mode of action (MOA) remains unclear, with contradicting in vitro studies supporting either suppression of entry and cell-to-cell spread or suppression of viral RNA synthesis as the main MOA. We sought to provide new insights into SIL's MOA in HCV genotype-1/4 patients receiving intravenous SIL monotherapy for 7 days via mathematical modeling.

METHODS

Changes in HCV RNA in 25 patients receiving 10, 15, or 20mg/kg/day of SIL were analyzed and modeled using viral kinetic methods.

RESULTS

In 15 patients, the virus declined in a biphasic manner, in which a sharp drop between days 0 and 2 was followed by a slower second phase of decline. In 10 patients, the initial decline was weaker and the virus declined in a single phase over the 7-day period. The blocking production effectiveness, ε, was dose-dependent with mean ε=0.49 and 0.89 in the 10 or 15 and 20mg/kg/day dosing groups, respectively (p=0.02). The effectiveness of blocking viral infection, η, was estimated as 0.60 with no significant differences across dosing groups. For all patients, the mean rate of viral load decline measured between days 2 and 7 was high (0.3 log(10)IU/ml/day), i.e., 4-fold higher than typically observed during the 2nd phase of (pegylated)-interferon-α±ribavirin treatment.

CONCLUSIONS

Modeling HCV kinetics in vivo suggests that SIL may block both viral infection and viral production/release with its main dose-dependent effect being blocking viral production/release.

Effect of IL28B genotype on early viral kinetics during interferon-free treatment of patients with chronic hepatitis C

BACKGROUND & AIMS

Although interleukin 28B (interferon, lambda 3) (IL28B) genotype affects the response of patients with chronic hepatitis C to peginterferon and ribavirin, little is known regarding its effect on response to direct-acting antivirals in interferon-free combinations. We analyzed the effects of IL28B genotype on the viral kinetic (VK) response to an interferon-free combination of the nucleoside polymerase inhibitor mericitabine (RG7128) and the hepatitis C virus (HCV) protease inhibitor danoprevir.

METHODS

We performed a double-blind, dose-escalation study of patients with chronic HCV genotype 1 infection who were interferon treatment naive or had not responded to previous therapy with peginterferon and ribavirin. Patients were sequentially assigned to 1 of 7 cohorts then randomly assigned to groups that received up to 13 days of treatment with mericitabine (500 or 1000 mg, twice daily) plus danoprevir (100 or 200 mg, every 8 hours, or 600 or 900 mg, twice daily) or placebo. Eighty-three of 87 patients were genotyped for the IL28B single-nucleotide polymorphism rs12979860. VKs were analyzed only in patients who received 13 days of treatment, at optimal doses, using a biphasic model to describe first- and second-phase slopes of viral decay during therapy.

RESULTS

At day 14 (the end of interferon-free treatment), the mean reduction in the serum level of HCV RNA was slightly greater in patients with the CC polymorphism (5.01 log(10) IU/mL) than those without (4.59 log(10) IU/mL). Modeling revealed that patients with the CC polymorphism had slightly better early VKs, most apparent in the β-phase of viral decay. A mixed effect on the α-phase was observed, which was reduced in magnitude but prolonged in patients with CC, who also had better on-treatment response to peginterferon and ribavirin during follow up.

CONCLUSIONS

IL28B genotype appears to affect early VKs in patients with chronic hepatitis C receiving interferon-free treatment.