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

Mathematical Models of HIV-1 Dynamics, Transcription, and Latency

HIV-1 latency is a major barrier to curing infections with antiretroviral therapy and, consequently, to eliminating the disease globally. The establishment, maintenance, and potential clearance of latent infection are complex dynamic processes and can be best described with the help of mathematical models followed by experimental validation. Here, we review the use of viral dynamics models for HIV-1, with a focus on applications to the latent reservoir. Such models have been used to explain the multi-phasic decay of viral load during antiretroviral therapy, the early seeding of the latent reservoir during acute infection and the limited inflow during treatment, the dynamics of viral blips, and the phenomenon of post-treatment control. Finally, we discuss that mathematical models have been used to predict the efficacy of potential HIV-1 cure strategies, such as latency-reversing agents, early treatment initiation, or gene therapies, and to provide guidance for designing trials of these novel interventions.

Lyapunov function and global asymptotic stability for a new multiscale viral dynamics model incorporating the immune system response: Implemented upon HCV

In this paper, a new mathematical model is formulated that describes the interaction between uninfected cells, infected cells, viruses, intracellular viral RNA, Cytotoxic T-lymphocytes (CTLs), and antibodies. Hence, the model contains certain biological relations that are thought to be key factors driving this interaction which allow us to obtain precise logical conclusions. Therefore, it improves our perception, that would otherwise not be possible, to comprehend the pathogenesis, to interpret clinical data, to control treatment, and to suggest new relations. This model can be used to study viral dynamics in patients for a wide range of infectious diseases like HIV, HPV, HBV, HCV, and Covid-19. Though, analysis of a new multiscale HCV model incorporating the immune system response is considered in detail, the analysis and results can be applied for all other viruses. The model utilizes a transformed multiscale model in the form of ordinary differential equations (ODE) and incorporates into it the interaction of the immune system. The role of CTLs and the role of antibody responses are investigated. The positivity of the solutions is proven, the basic reproduction number is obtained, and the equilibrium points are specified. The stability at the equilibrium points is analyzed based on the Lyapunov invariance principle. By using appropriate Lyapunov functions, the uninfected equilibrium point is proven to be globally asymptotically stable when the reproduction number is less than one and unstable otherwise. Global stability of the infected equilibrium points is considered, and it has been found that each equilibrium point has a specific domain of stability. Stability regions could be overlapped and a bistable equilibria could be found, which means the coexistence of two stable equilibrium points. Hence, the solution converges to one of them depending on the initial conditions.

Effect of DAA therapy in hepatitis C treatment - an impulsive control approach

In this article, we have presented a mathematical model to study the dynamics of hepatitis C virus (HCV) disease considering three populations namely the uninfected liver cells, infected liver cells, and HCV with the aim to control the disease. The model possesses two equilibria namely the disease-free steady state and the endemically infected state. There exists a threshold condition (basic reproduction number) that determines the stability of the disease-free equilibrium and the number of the endemic states. We have further introduced impulsive periodic therapy using DAA into the system and studied the efficacy of the DAA therapy for hepatitis C infected patients in terms of a threshold condition. Finally, impulse periodic dosing with varied rate and time interval is adopted for cost effective disease control for finding the proper dose and dosing interval for the control of HCV disease.

Mathematical modeling of hepatitis C RNA replication, exosome secretion and virus release

Hepatitis C virus (HCV) causes acute hepatitis C and can lead to life-threatening complications if it becomes chronic. The HCV genome is a single plus strand of RNA. Its intracellular replication is a spatiotemporally coordinated process of RNA translation upon cell infection, RNA synthesis within a replication compartment, and virus particle production. While HCV is mainly transmitted via mature infectious virus particles, it has also been suggested that HCV-infected cells can secrete HCV RNA carrying exosomes that can infect cells in a receptor independent manner. In order to gain insight into these two routes of transmission, we developed a series of intracellular HCV replication models that include HCV RNA secretion and/or virus assembly and release. Fitting our models to in vitro data, in which cells were infected with HCV, suggests that initially most secreted HCV RNA derives from intracellular cytosolic plus-strand RNA, but subsequently secreted HCV RNA derives equally from the cytoplasm and the replication compartments. Furthermore, our model fits to the data suggest that the rate of virus assembly and release is limited by host cell resources. Including the effects of direct acting antivirals in our models, we found that in spite of decreasing intracellular HCV RNA and extracellular virus concentration, low level HCV RNA secretion may continue as long as intracellular RNA is available. This may possibly explain the presence of detectable levels of plasma HCV RNA at the end of treatment even in patients that ultimately attain a sustained virologic response.

Approximately 70 million people are chronically infected with hepatitis C virus (HCV), which if left untreated may lead to cirrhosis and liver cancer. However, modern drug therapy is highly effective and hepatitis C is the first chronic virus infection that can be cured with short-term therapy in almost all infected individuals. The within-host transmission of HCV occurs mainly via infectious virus particles, but experimental studies suggest that there may be additional receptor-independent cell-to-cell transmission by exosomes that carry the HCV genome. In order to understand the intracellular HCV lifecycle and HCV RNA spread, we developed a series of mathematical models that take both exosomal secretion and viral secretion into account. By fitting these models to in vitro data, we found that secretion of both HCV RNA as well as virus probably occurs and that the rate of virus assembly is likely limited by cellular co-factors on which the virus strongly depends for its own replication. Furthermore, our modeling predicted that the parameters governing the processes in the viral lifecycle that are targeted by direct acting antivirals are the most sensitive to perturbations, which may help explain their ability to cure this infection.

Dynamical Analysis of a Multiscale Model of Hepatitis C Virus Infection Using a Transformed ODEs Model

A mathematically identical ordinary differential equations (ODEs) model was derived from a multiscale partial differential equations (PDEs) model of hepatitis c virus infection, which helps to overcome the limitations of the PDE model in clinical data analysis. We have discussed about basic properties of the system and found the basic reproduction number of the system. A condition for the local stability of the uninfected and the infected steady states is presented. The local stability analysis of the model shows that the system is asymptotically stable at the disease-free equilibrium point when the basic reproduction number is less than one. When the basic reproduction number is greater than one endemic equilibrium point exists, and the local stability analysis proves that this point is asymptotically stable. Numerical sensitivity analysis based on model parameters is performed and therefore the result describes the influence of each parameter on the basic reproduction number.

Peripheral Expression of CXCL10 Gene in Chronic Hepatitis C Patients Treated with Sofosbuvir, Daclatasvir, and Ribavirin

Hepatitis C virus (HCV) causes persistent infection and invades host's innate and adaptive immune systems. During the eradication of this pathogen, the components of immune system may cause bystander damage to host, which might be even worse than the viral pathogenesis. Thus, the therapy should not only eliminate primary virus infection but also improve the inflammatory immune responses. The breakthrough of interferon free direct acting antiviral (DAA) drugs has provided the opportunity to unravel the association of HCV with immune response. This study aimed to examine the expression level of C-X-C motif chemokine ligand 10 (CXCL10) in the Peripheral blood mononuclear cells (PBMCs) of HCV infected patients treated with DAAs + Ribavirin. In this study we analyzed the expression levels of CXCL10 mRNA in the 90 chronic HCV patients using quantitative PCR (qPCR) prior, after, and during therapy with sofosbuvir/ribavirin (SOF+RBV) and sofosbuvir/daclatasvir/ribavirin (SOF+DCV+RBV), and further, the results were analyzed relative to treatment response. Significantly elevated CXCL10 mRNA was seen in naive patients having higher viral load (P = 0.005) and those suffering from hepatocellular carcinoma (P = 0.006). HCV patients had remarkable decline in CXCL10 level after 4, 12, and 24 weeks of therapy with DAAs. An approximate one-fold decrease was observed in patients who attained sustained virological response compared to untreated patients (P < 0.0001). Comparing the 2 regimens, the reduction in peripheral CXCL10 expression was more pronounced in patients undergoing SOF+DCV+RBV therapy. The current study implicitly shows the role of CXCL10 as an indicator of disruption of host-virus equilibrium and consequent pathogenesis of HCV during successful antiviral therapy. Furthermore, the drop in CXCL10 level after HCV viral clearance might reflect the DAA-induced alleviation in the extrahepatic manifestation of this infection.

Modelling Degradation and Replication Kinetics of the Zika Virus In Vitro Infection

Mathematical models of in vitro viral kinetics help us understand and quantify the main determinants underlying the virus–host cell interactions. We aimed to provide a numerical characterization of the Zika virus (ZIKV) in vitro infection kinetics, an arthropod-borne emerging virus that has gained public recognition due to its association with microcephaly in newborns. The mathematical model of in vitro viral infection typically assumes that degradation of extracellular infectious virus proceeds in an exponential manner, that is, each viral particle has the same probability of losing infectivity at any given time. We incubated ZIKV stock in the cell culture media and sampled with high frequency for quantification over the course of 96 h. The data showed a delay in the virus degradation in the first 24 h followed by a decline, which could not be captured by the model with exponentially distributed decay time of infectious virus. Thus, we proposed a model, in which inactivation of infectious ZIKV is gamma distributed and fit the model to the temporal measurements of infectious virus remaining in the media. The model was able to reproduce the data well and yielded the decay time of infectious ZIKV to be 40 h. We studied the in vitro ZIKV infection kinetics by conducting cell infection at two distinct multiplicity of infection and measuring viral loads over time. We fit the mathematical model of in vitro viral infection with gamma distributed degradation time of infectious virus to the viral growth data and identified the timespans and rates involved within the ZIKV-host cell interplay. Our mathematical analysis combined with the data provides a well-described example of non-exponential viral decay dynamics and presents numerical characterization of in vitro infection with ZIKV.

Viral dynamics among HCV infected patients with different genotypes treated with genotypic specific or pan-genotypic direct-acting antiviral agent combinations

BACKGROUND

New hepatitis C virus (HCV) therapies have improved efficacy, allowed pangenotypic applications, increased barriers to drug resistance and shortened therapy duration.

METHODS

Patients infected with different HCV genotypes were divided into two groups: group 1 included 169 patients receiving genotypic specific regimens (GSR), while group 2 included 186 patients receiving pan-genotypic regimens (PGR). Patient's HCV RNA was quantified and sequenced.

RESULTS

Comparable sustained viral response (SVR) rates were observed in both GSR and PGR treated patients. Nevertheless, even if not significant, a greater proportion of non-detectable levels (NDL) of HCV RNA was observed in patients treated with PGR as compared with GSR. Overall, among patients in the GSR and PGR groups with residual viremia, 124/169 (73.4%) and 125/186 (67.2%) at four weeks, and 66/169 (39.1%) and 58/186 (31.2%) at eight weeks, achieved SVR. No difference was observed in the clinical outcome comparing patients in the GSR and PGR groups according to genotype. While, comparing patients between the two groups, the proportion of patients with NDL HCV RNA at four and eight weeks was higher in patients infected with genotype 1b treated with PGR (p=0.0015). A significantly higher number of patients infected with 1b had RASs at baseline (p=0.0001). In addition, the proportion of patients with treatment failure was higher in patients with RASs at baseline compared with those without (p=0.012). Overall, 2.5% patients failed to achieve SVR after DAA treatment.

CONCLUSION

A sharp HCV RNA decrease was observed in patients treated with both GSR and PGR. However, even if comparable, a slightly greater number of patients treated with PGR achieved NDL HCV RNA as compared with GSR. A significant difference was observed in patients with baseline RASs, both in relation to treatment failure and genotype. In conclusion, the use of new DAA combinations helps patients achieve a more rapid virologic response.

The Discovery and Early Clinical Evaluation of the HCV NS3/4A Protease Inhibitor Asunaprevir (BMS-650032)

The discovery of asunaprevir (1) began with the concept of engaging the small and well-defined S₁’ pocket of the hepatitis C virus (HCV) NS3/4A protease that was explored in the context of tripeptide carboxylic acid-based inhibitors. A cyclopropyl-acyl sulfonamide moiety was found to be the optimal element at the P₁-P₁’ interface enhancing the potency of carboxylic acid-based prototypes by 10- to >100-fold, dependent upon the specific background. Optimization for oral bioavailability identified a 1-substituted isoquinoline-based P₂* element that conferred a significant exposure advantage in rats compared to the matched 4-substituted quinoline isomer. BMS-605339 (30) was the first cyclopropyl-acyl sulfonamide derivative advanced into clinical trials that demonstrated dose-related reductions in plasma viral RNA in HCV-infected patients. However, 30 was associated with cardiac events observed in a normal healthy volunteer (NHV) and an HCV-infected patient that led to the suspension of the development program. Using a Langendorff rabbit heart model, a limited structure-cardiac liability relationship was quickly established that led to the discovery of 1. This compound, which differs from 30 only by changes in the substitution pattern of the P₂* isoquinoline heterocycle and the addition of a single chlorine atom to the molecular formula, gave a dose-dependent reduction in plasma viral RNA following oral administration to HCV-infected patients without the burden of the cardiac events that had been observed with 30. A small clinical trial of the combination of 1 with the HCV NS5A inhibitor daclatasvir (2) established for the first time that a chronic genotype 1 (GT-1) HCV infection could be cured by therapy with two direct-acting antiviral agents in the absence of exogenous immune-stimulating agents. Development of the combination of 1 and 2 was initially focused on Japan where the patient population is predominantly infected with GT-1b virus, culminating in marketing approval which was granted on July 4, 2014. In order to broaden therapy to include GT-1a infections, a fixed dose triple combination of 1, 2, and the allosteric NS5B inhibitor beclabuvir (3) was developed, approved by the Japanese health authorities for the treatment of HCV GT-1 infection on December 20, 2016 and marketed as Ximency^®.

Intracellular Hepatitis C Virus Modeling Predicts Infection Dynamics and Viral Protein Mechanisms

Hepatitis C virus (HCV) infection is a global health problem, with nearly 2 million new infections occurring every year and up to 85% of these infections becoming chronic infections that pose serious long-term health risks. To effectively reduce the prevalence of HCV infection and associated diseases, it is important to understand the intracellular dynamics of the viral life cycle. Here, we present a detailed mathematical model that represents the full hepatitis C virus life cycle. It is the first full HCV model to be fit to acute intracellular infection data and the first to explore the functions of distinct viral proteins, probing multiple hypotheses of cis- and trans-acting mechanisms to provide insights for drug targeting. Model parameters were derived from the literature, experiments, and fitting to experimental intracellular viral RNA, extracellular viral titer, and HCV core and NS3 protein kinetic data from viral inoculation to steady state. Our model predicts higher rates for protein translation and polyprotein cleavage than previous replicon models and demonstrates that the processes of translation and synthesis of viral RNA have the most influence on the levels of the species we tracked in experiments. Overall, our experimental data and the resulting mathematical infection model reveal information about the regulation of core protein during infection, produce specific insights into the roles of the viral core, NS5A, and NS5B proteins, and demonstrate the sensitivities of viral proteins and RNA to distinct reactions within the life cycle.IMPORTANCE We have designed a model for the full life cycle of hepatitis C virus. Past efforts have largely focused on modeling hepatitis C virus replicon systems, in which transfected subgenomic HCV RNA maintains autonomous replication in the absence of virion production or spread. We started with the general structure of these previous replicon models and expanded it to create a model that incorporates the full virus life cycle as well as additional intracellular mechanistic detail. We compared several different hypotheses that have been proposed for different parts of the life cycle and applied the corresponding model variations to infection data to determine which hypotheses are most consistent with the empirical kinetic data. Because the infection data we have collected for this study are a more physiologically relevant representation of a viral life cycle than data obtained from a replicon system, our model can make more accurate predictions about clinical hepatitis C virus infections.

Strategies to control HIV and HCV in methadone maintenance treatment in Guangdong Province, China: a system dynamic modeling study

Background

Human immunodeficiency virus (HIV) and hepatitis C virus (HCV) infections among methadone maintenance treatment (MMT) participants remain high. Optimized HIV and HCV prevention strategies for MMT clinics in resource-limited regions are urgently needed. This study aims to develop an MMT system dynamic model (SDM) to compare and optimize HIV and HCV control strategies in the MMT system.

Methods

We developed an MMT-SDM structure based on literature reviews. Model parameters were estimated from a cohort study, cross-sectional surveys and literature reviews. We further calibrated model outputs to historical data of HIV and HCV prevalence among MMT participants in 13 MMT clinics of Guangdong Province. Lastly, we simulated the impact of integrated interventions on HIV and HCV incidence among MMT participants using the MMT-SDM.

Results

The MMT-SDM comprises MMT clinics, MMT participants, detoxification centers, and HIV and HCV transmission, testing and treatment systems. We determined that condom promotion was the most effective way to reduce HIV infection (2013-2020: 2.86% to 1.76%) in MMT setting, followed by needle exchange program (2013-2020: 2.86% to 2.56%), psychological counseling (2013-2020: 2.86% to 2.71%) and contingency management (2013-2020: 2.86% to 2.72%). Health education had marginal impact on reducing HIV incidence among MMT participants (2013-2020:2.86% to 2.84%) from 2013 to 2020. By contrast, psychological counseling (2013-2020: 7.54% to 2.42%) and contingency management (2013-2020: 7.54% to 2.96%) had been shown to be the most effective interventions to reduce HCV incidence among MMT participants, followed by needle exchange program (2013-2020: 7.54% to 5.76%), health education (2013-2020: 7.54% to 6.35%), and condom promotion program (2013-2020: 7.54% to 6.40%). Notably, HCV treatment reduced HCV incidence by 0.32% (2013-2020: 7.54% to 7.22%).

Conclusions

In conclusion, we generated a valuable system dynamic model to analyze the Chinese MMT system and to guide the decision-making process to further improve this system. This study underscores the importance of promoting condom use in MMT clinics and integrating psychosocial interventions to reduce HIV and HCV infections in MMT clinics in China.

Electronic supplementary material

The online version of this article (10.1186/s13011-017-0140-3) contains supplementary material, which is available to authorized users.

Short article: Viral dynamics among hepatitis C virus chronic infected patients during direct-acting antiviral agents therapy: impact for monitoring and optimizing treatment duration

OBJECTIVES

Direct-acting antiviral agents (DAAs) have provided an ultimate treatment duration of 12 weeks for most hepatitis C virus (HCV)-infected patients. The opportunity to reduce treatment duration to 6 or 8 weeks is being evaluated. Here, the HCV viral dynamics at short times during HCV therapies and its implications for monitoring and optimizing treatment duration have been assessed.

PATIENTS AND METHODS

HCV chronic infected patients who began HCV therapy (March 2014 to June 2015) at a reference hospital of the Northwest of Spain were selected. HCV-RNA was quantified at different short time points during HCV therapy using Abbott RealTime HCV assay. Epidemiological, clinical, and virological data were recorded.

RESULTS

Eleven HCV-infected patients were included; 90.9% had cirrhosis (>12.5 kPa) and 72.7% were treatment-experienced. HCV genotype 1b was the most prevalent (72.7%). All of the combinations were pegylated interferon-free and all included ribavirin. The median HCV-RNA (log IU/ml) at baseline was 5.8 (5.4-6.1); the decline between baseline and day 3, weeks 4, 8, and 12 was 3.2, 4.8, 5.1, and 5.6, respectively. Fewer than 50% of patients achieved undetectable viral load at weeks 4 and 8; however, all patients achieved a sustained virologic response at 12 weeks.

CONCLUSION

Rapid and high HCV-RNA decline was observed among HCV-infected patients under DAA-based regimens, especially for those without cirrhosis. Despite low rates of patients with undetectable HCV-RNA at weeks 4 and 8, all achieved a sustained virologic response at 12 weeks. These findings suggest that the time points to monitor HCV-RNA during DAA therapies and the treatment duration need to be optimized.

Mathematical Models of HIV Latency

Viral latency is a major barrier to curing HIV infection with antiretroviral therapy, and consequently, for eliminating the disease globally. The establishment, maintenance, and potential clearance of latent infection are complex dynamic processes and can be best understood and described with the help of mathematical models. Here we review the use of viral dynamics models for HIV, with a focus on applications to the latent reservoir. Such models have been used to explain the multiphasic decay of viral load during antiretroviral therapy, the early seeding of the latent reservoir during acute infection and the limited inflow during treatment, the dynamics of viral blips, and the phenomenon of posttreatment control. In addition, mathematical models have been used to predict the efficacy of potential HIV cure strategies, such as latency-reversing agents, early treatment initiation, or gene therapies, and to provide guidance for designing trials of these novel interventions.

Modeling Viral Spread

The way in which a viral infection spreads within a host is a complex process that is not well understood. Different viruses, such as human immunodeficiency virus type 1 and hepatitis C virus, have evolved different strategies, including direct cell-to-cell transmission and cell-free transmission, to spread within a host. To what extent these two modes of transmission are exploited in vivo is still unknown. Mathematical modeling has been an essential tool to get a better systematic and quantitative understanding of viral processes that are difficult to discern through strictly experimental approaches. In this review, we discuss recent attempts that combine experimental data and mathematical modeling in order to determine and quantify viral transmission modes. We also discuss the current challenges for a systems-level understanding of viral spread, and we highlight the promises and challenges that novel experimental techniques and data will bring to the field.

2015 Philip S. Portoghese Medicinal Chemistry Lectureship. Curing Hepatitis C Virus Infection with Direct-Acting Antiviral Agents: The Arc of a Medicinal Chemistry Triumph

The development of direct-acting antiviral agents that can cure a chronic hepatitis C virus (HCV) infection after 8-12 weeks of daily, well-tolerated therapy has revolutionized the treatment of this insidious disease. In this article, three of Bristol-Myers Squibb's HCV programs are summarized, each of which produced a clinical candidate: the NS3 protease inhibitor asunaprevir (64), marketed as Sunvepra, the NS5A replication complex inhibitor daclatasvir (117), marketed as Daklinza, and the allosteric NS5B polymerase inhibitor beclabuvir (142), which is in late stage clinical studies. A clinical study with 64 and 117 established for the first time that a chronic HCV infection could be cured by treatment with direct-acting antiviral agents alone in the absence of interferon. The development of small molecule HCV therapeutics, designed by medicinal chemists, has been hailed as "the arc of a medical triumph" but may equally well be described as "the arc of a medicinal chemistry triumph".

A review of disease progression models of Parkinson's disease and applications in clinical trials

Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In Parkinson's disease (PD), several models have described longitudinal changes in the Unified Parkinson's Disease Rating Scale (UPDRS), one of the most utilized outcome measures for PD trials assessing disease progression. We conducted a literature review to examine the methods and applications of quantitative disease progression modeling for PD using a combination of key words including "Parkinson disease," "progression," and "model." For this review, we focused on models of PD progression quantifying changes in the total UPDRS scores against time. Four different models reporting equations and parameters have been published using linear and nonlinear functions. The reasons for constructing disease progression models of PD thus far have been to quantify disease trajectories of PD patients in active and inactive treatment arms of clinical trials, to quantify and discern symptomatic and disease-modifying treatment effects, and to demonstrate how model-based methods may be used to design clinical trials. The historical lack of efficiency of PD clinical trials begs for model-based simulations in planning for studies that result in more informative conclusions, particularly around disease modification. © 2016 International Parkinson and Movement Disorder Society.

Modelling the prevalence of hepatitis C virus amongst blood donors in Libya: An investigation of providing a preventive strategy

AIM: To determine hepatitis C virus (HCV) seroprevalence among the Libyan population using blood donors and applying the autoregressive integrated moving average (ARIMA) model to predict future trends and formulate plans to minimize the burden of HCV infection.

METHODS: HCV positive cases were collected from 1008214 healthy blood donors over a 6-year period from 2008 to 2013. Data were used to construct the ARIMA model to forecast HCV seroprevalence among blood donors. The validity of the model was assessed using the mean absolute percentage error between the observed and fitted seroprevalence. The fitted ARIMA model was used to forecast the incidence of HCV beyond the observed period for the year 2014 and further to 2055.

RESULTS: The overall prevalence of HCV among blood donors was 1.8%, varying over the study period from 1.7% to 2.5%, though no significant variation was found within each calendar year. The ARIMA model showed a non-significant auto-correlation of the residuals, and the prevalence was steady within the last 3 years as expressed by the goodness-of-fit test. The forecast incidence showed an increase in HCV seropositivity in 2014, ranging from 500 to 700 per 10000 population, with an overall prevalence of 2.3%-2.7%. This may be extended to 2055 with minimal periodical variation within each 6-year period.

CONCLUSION: The applied model was found to be valuable in evaluating the seroprevalence of HCV among blood donors, and highlighted the growing burden of such infection on the Libyan health care system. The model may help in formulating national policies to prevent increases in HCV infection and plan future strategies that target the consequences of the infection.

Temporal dynamics of inflammatory cytokines/chemokines during sofosbuvir and ribavirin therapy for genotype 2 and 3 hepatitis C infection

The analysis of inflammatory cytokines and chemokines produced during hepatitis C virus (HCV) infection has advanced our understanding of viral-host interactions and identified predictors of treatment response. Administration of interferons (IFNs) made it difficult to interpret biomarkers of immune activation during treatment. Direct-acting antiviral (DAA) regimens without IFN are now being used to treat HCV with excellent efficacy. To gain insight into HCV-host interactions occurring before, during, and after HCV treatment, we performed a case-control study that measured serial plasma levels of IFN-γ-inducible protein 10 (IP-10), monocyte chemoattractant protein 1 (MCP-1), macrophage inflammatory protein 1 beta (MIP-1β), and interleukin-18 (IL-18) in 131 patients with chronic HCV treated with sofosbuvir (SOF) plus ribavirin (RBV). A linear regression analysis using baseline factors identified strong positive associations between elevated alanine aminotransferase and pretreatment IP-10 and between the presence of cirrhosis and elevated pretreatment IL-18. Mean IP-10, MCP-1, MIP-1β, and IL-18 levels all decline on therapy, but display different dynamics late in treatment and after cessation of therapy. On treatment, IP-10 and MIP-1β levels were significantly higher in individuals who achieved sustained virological response (SVR). Logistic regression analyses examining treatment response in all patients demonstrated significant associations between higher baseline MIP-1β levels and smaller decreases in MIP-1β early in treatment and SVR. Higher early MIP-1β levels were also significantly associated with SVR in subsets of patients with cirrhosis and individuals with genotype 3 (GT3) infection, two factors associated with decreased responsiveness to treatment.

CONCLUSION

Changes in IP-10 levels mirror HCV RNA, suggesting that IP-10 is an indicator of innate immune viral recognition. MIP-1β levels remain elevated in GT2/3 patients who achieved SVR, suggesting differential immune activation in those who respond to SOF/RBV therapy and a potential role in predicting treatment responses.

Multi-scale model for hepatitis C viral load kinetics under treatment with direct acting antivirals

Hepatitis C virus (HCV) infections are a global health problem, and extensive research over the last decades has been targeted at understanding its molecular biology and developing effective antiviral treatments. Recently, a number of potent direct acting antiviral drugs have been developed targeting specific processes in the viral life cycle. Here, we developed a mathematical multi-scale model of the within-host dynamics of HCV infection by integrating a standard model for viral infection with a detailed model of the viral replication cycle inside infected cells. We use this model to study patient time courses of viral load under treatment with daclatasvir, an inhibitor of the viral non-structural protein NS5A. Model analysis predicts that treatment efficacy can be increased by combining daclatasvir with dedicated viral polymerase inhibitors, corresponding to promising current strategies in drug development. Hence, our model presents a predictive tool for in silico simulations, which can be used to study and optimize direct acting antiviral drug treatment.

Ebola virus dynamics in mice treated with favipiravir

The polymerase inhibitor favipiravir is a candidate for the treatment of Ebola virus disease. Here, we designed a mathematical model to characterize the viral dynamics in 20 mice experimentally infected with Ebola virus, which were either left untreated or treated with favipiravir at 6 or 8days post infection. This approach provided estimates of kinetic parameters of Ebola virus reproduction, such as the half-life of productively infected cells, of about 6h, and the basic reproductive number which indicates that virus produced by a single infected cell productively infects about 9 new cells. Furthermore, the model predicted that favipiravir efficiently blocks viral production, reaching an antiviral effectiveness of 95% and 99.6% at 2 and 6days after initiation of treatment, respectively. The model could be particularly helpful to guide future studies evaluating favipiravir in larger animals.

Modeling population heterogeneity in viral dynamics for chronic hepatitis C infection: Insights from Phase 3 telaprevir clinical studies

Viral dynamic modelling has proven useful for designing clinical studies and predicting treatment outcomes for patients infected with the hepatitis C virus. Generally these models aim to capture and predict the on-treatment viral load dynamics from a small study of individual patients. Here, we explored extending these models (1) to clinical studies with numerous patients and (2) by incorporating additional data types, including sequence data and prior response to interferon. Data from Phase 3 clinical studies of the direct-acting antiviral telaprevir (T; total daily dose of 2250 mg) combined with pegylated-interferon alfa and ribavirin (PR) were used for the analysis. The following data in the treatment-naïve population were reserved to verify the model: (1) a T/PR regimen where T was dosed every 8 h for 8 weeks (T8(q8h)/PR) and (2) a T/PR regimen where T was dosed twice daily for 12 weeks (T12(b.i.d.)/PR). The resulting model accurately predicted (1) sustained virologic response rates for both of these dosing regimens and (2) viral breakthrough characteristics of the T8(q8h)/PR regimen. Since the observed viral variants depend on the T exposure, the second verification suggested that the model was correctly sensitive to the different T regimen even though the model was developed using data from another T regimen. Furthermore, the model predicted that b.i.d. T dosing was comparable to q8h T dosing in the PR-experienced population, a comparison that has not been made in a controlled clinical study. The methods developed in this work to estimate the variability occurring below the limit of detection for the viral load were critical for making accurate predictions.

Kinetics of hepatitis C virus RNA decay, quasispecies evolution and risk of virological failure during telaprevir-based triple therapy in clinical practice

BACKGROUND

The used first generation protease inhibitors may be hampered by virological failure in partially interferon-sensitive patients.

AIM

To investigate early hepatitis C virus (HCV)-RNA decay and quasispecies modifications, and disclose viral dynamics underlying failure.

METHODS

Viraemia decay at early time-points during telaprevir treatment was modelled according to Neumann et al. (1998). NS3-sequences were obtained by population-sequencing and ultradeep-454-pyrosequencing.

RESULTS

13 treatment-experienced (8 non-responders, 5 relapsers), and two cirrhotic naïve patients, received telaprevir+pegylated-interferon-α+ribavirin. Viraemia decay was biphasic. In all patients, first-phase was rapid and consistent, with a median [interquartile-range] viraemia decay of 2.8 [2.6-3.2]logIU/ml within 48h. Second-phase decay was slower, especially in failing patients: 3/3 showed <1logIU/ml decay between 48h and 2 weeks, and HCV-RNA >100IU/ml at week 2. Only one patient experiencing sustained viral response showed similar kinetics. By pyrosequencing, mutational freeze was observed in all 15 patients within the first 24h, but only in patients with sustained response afterwards. Indeed, 2/2 failing patients showed early resistance, as minor (V36A-T54A: prevalence <26% at 48h) or major (V36M/A-R155K: prevalence, 99.8% at week 2) variants.

CONCLUSIONS

Following telaprevir administration, first-phase HCV-RNA decay is consistent with mutational freeze and limited/no viral replication, while second-phase is significantly slower in failing patients (with appearance of resistance), suggesting the usefulness of early HCV-RNA monitoring.

Hepatitis C virus RNA levels at week-2 of telaprevir/boceprevir administration are predictive of virological outcome

BACKGROUND

Triple therapy with telaprevir/boceprevir + pegylated-interferon+ribavirin can achieve excellent antiviral efficacy, but it can be burdened with resistance development at failure.

AIMS

To evaluate kinetics of hepatitis C virus (HCV) RNA decay and early resistance development, in order to promptly identify patients at highest risk of failure to first generation protease inhibitors.

METHODS

HCV-RNA was prospectively quantified in 158 patients receiving pegylated-interferon+ribavirin+telaprevir (N = 114) or+boceprevir (N = 44), at early time-points and during per protocol follow-up. Drug resistance was contextually evaluated by population sequencing.

RESULTS

HCV-RNA at week-2 was significantly higher in patients experiencing virological failure to triple-therapy than in patients with sustained viral response (2.3 [1.9-2.8] versus 1.2 [0.3-1.7]log IU/mL, p < 0.001). A 100 IU/mL cut-off value for week-2 HCV-RNA had the highest sensitivity (86%) in predicting virological success. Indeed, 23/23 (100%) patients with undetectable HCV-RNA reached success, versus 26/34 (76.5%) patients with HCV-RNA<100 IU/mL, and only 11/31 (35.5%) with HCV-RNA > 100 IU/mL (p < 0.001). Furthermore, differently from failing patients, none of the patient with undetectable HCV-RNA at week-2 had baseline/early resistance.

CONCLUSIONS

With triple therapy based on first generation protease inhibitors, suboptimal HCV-RNA decay at week-2 combined with early detection of resistance can help identifying patients with higher risk of virological failure, thus requiring a closer monitoring during therapy.

Understanding early serum hepatitis D virus and hepatitis B surface antigen kinetics during pegylated interferon-alpha therapy via mathematical modeling

There is little information on the early kinetics of hepatitis delta virus (HDV) and hepatitis B surface antigen (HBsAg) during interferon-α therapy. Here a mathematical model was developed and fitted to frequent HDV and HBsAg kinetic data from 10 patients during the first 28 weeks of pegylated-interferon-α2a (peg-IFN) therapy. Three patients achieved a complete virological response (CVR), defined as undetectable HDV 6 months after treatment stopped with loss of HBsAg and anti-HBsAg seroconversion. After initiation of therapy, a median delay of 9 days (interquartile range [IQR]: 5-15) was observed with no significant changes in HDV level. Thereafter, HDV declined in a biphasic manner, where a rapid first phase lasting for 25 days (IQR: 23-58) was followed by a slower or plateau second phase. The model predicts that the main effect of peg-IFN is to reduce HDV production/release with a median effectiveness of 96% (IQR: 93-99.8). Median serum HDV half-life (t1/2 ) was estimated as 2.9 days (IQR: 1.5-5.3) corresponding to a pretreatment production and clearance of about 10(10) (IQR: 10(9.7) -10(10.7) ) virions/day. None of the patients with flat second phase in HDV achieved CVR. HBsAg kinetics of decline paralleled the second phase of HDV decline consistent with HBsAg-productive-infected cells being the main source of production of HDV, with a median t1/2 of 135 days (IQR: 20-460). The interferon lambda-3 polymorphism (rs12979860) was not associated with kinetic parameters.

CONCLUSION

Modeling results provide insights into HDV-host dynamics, the relationship between serum HBsAg levels and HBsAg-infected cells, IFN's mode of action, and its effectiveness. The observation that a flat second phase in HDV and HBsAg kinetics was associated with failure to achieve CVR provides the basis to develop early stopping rules during peg-IFN treatment in HDV-infected patients.

In vitro and in vivo antiviral activity and resistance profile of the hepatitis C virus NS3/4A protease inhibitor ABT-450

The development of direct-acting antiviral agents is a promising therapeutic advance in the treatment of hepatitis C virus (HCV) infection. However, rapid emergence of drug resistance can limit efficacy and lead to cross-resistance among members of the same drug class. ABT-450 is an efficacious inhibitor of HCV NS3/4A protease, with 50% effective concentration values of 1.0, 0.21, 5.3, 19, 0.09, and 0.69 nM against stable HCV replicons with NS3 protease from genotypes 1a, 1b, 2a, 3a, 4a, and 6a, respectively. In vitro, the most common amino acid variants selected by ABT-450 in genotype 1 were located in NS3 at positions 155, 156, and 168, with the D168Y variant conferring the highest level of resistance to ABT-450 in both genotype 1a and 1b replicons (219- and 337-fold, respectively). In a 3-day monotherapy study with HCV genotype 1-infected patients, ABT-450 was coadministered with ritonavir, a cytochrome P450 3A4 inhibitor shown previously to markedly increase peak, trough, and overall drug exposures of ABT-450. A mean maximum HCV RNA decline of 4.02 log10 was observed at the end of the 3-day dosing period across all doses. The most common variants selected in these patients were R155K and D168V in genotype 1a and D168V in genotype 1b. However, selection of resistant variants was significantly reduced at the highest ABT-450 dose compared to lower doses. These findings were informative for the subsequent evaluation of ABT-450 in combination with additional drug classes in clinical trials in HCV-infected patients. (Study M11-602 is registered at ClinicalTrials.gov under registration no. NCT01074008.).

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.

A pharmacokinetic/viral kinetic model to evaluate the treatment effectiveness of danoprevir against chronic HCV

BACKGROUND

Viral kinetic models have proven useful to characterize treatment effectiveness during HCV therapy with interferon (IFN) or with direct-acting antivirals.

METHODS

We use a pharmacokinetic/viral kinetic (PK/VK) model to describe HCV RNA kinetics during treatment with danoprevir, a protease inhibitor. In a Phase I study, danoprevir monotherapy was administered for 14 days in ascending doses ranging from 200 to 600 mg per day to 40 patients of whom 32 were treatment-naive and 8 were non-responders to prior pegylated IFN-α/ribavirin treatment.

RESULTS

In all patients, a biphasic decline of HCV RNA during therapy was observed. A two-compartment PK model and a VK model that considered treatment effectiveness to vary with the predicted danoprevir concentration inside the second compartment provided a good fit to the viral load data. A time-varying effectiveness model was also used to fit the viral load data. The antiviral effectiveness increased in a dose-dependent manner, with a 14-day time-averaged effectiveness of 0.95 at the lowest dose (100 mg twice daily) and 0.99 at the highest dose (200 mg three times daily). Prior IFN non-responders exhibited a 14-day time-averaged effectiveness of 0.98 (300 mg twice daily). The second phase decline showed two different behaviours, with 30% of patients exhibiting a rapid decline of HCV RNA, comparable to that seen with other protease inhibitors (>0.3 day(-1)), whereas the viral decline was slower in the other patients.

CONCLUSIONS

Our results are consistent with the modest SVR rates from the INFORM-SVR study where patients were treated with a combination of mericitabine and ritonavir-boosted danoprevir.

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.

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.

Interferon γ-induced protein 10 kinetics in treatment-naive versus treatment-experienced patients receiving interferon-free therapy for hepatitis C virus infection: implications for the innate immune response

We measured interferon γ-induced protein 10 (IP-10) levels in 428 patients at baseline, week 1, and week 2 of all-oral treatment for hepatitis C virus (HCV) infection. An increased baseline IP-10 level was associated with a T allele in the IL28B gene, an increased alanine aminotransferase level in treatment-naive but not experienced patients, and an increased body mass index. At week 1, the mean decline in plasma IP-10 levels was the same in treatment-naive and treatment-experienced patients (-49%), whereas during week 2 the mean decline in IP-10 levels in treatment-naive patients (-14%) was significantly larger than in treatment-experienced patients (-2%; P = .0176). IP-10 thus may be a surrogate marker of the rate of intracellular viral replication complex decay.

Modeling viral kinetics and treatment outcome during alisporivir interferon-free treatment in hepatitis C virus genotype 2 and 3 patients

Alisporivir (ALV) is a cyclophilin inhibitor with pan-genotypic activity against hepatitis C virus (HCV). Here, we characterize the viral kinetics observed in 249 patients infected with HCV genotypes 2 or 3 and treated for 6 weeks with different doses of ALV with or without ribavirin (RBV). We use this model to predict the effects of treatment duration and different doses of ALV plus RBV on sustained virologic response (SVR). Continuous viral decline was observed in 214 (86%) patients that could be well described by the model. All doses led to a high level of antiviral effectiveness equal to 0.98, 0.96, and 0.90 in patients treated with 1,000, 800, and 600 mg of ALV once-daily, respectively. Patients that received RBV had a significantly faster rate of viral decline, which was attributed to an enhanced loss rate of infected cells, δ (mean δ = 0.35 d(-1) vs. 0.21 d(-1) in patients ± RBV, respectively; P = 0.0001). The remaining 35 patients (14%) had a suboptimal response with flat or increasing levels of HCV RNA after 1 week of treatment, which was associated with ALV monotherapy, high body weight, and low RBV levels in patients that received ALV plus RBV. Assuming full compliance and the same proportion of suboptimal responders, the model predicted 71% and 79% SVR after ALV 400 mg with RBV 400 mg twice-daily for 24 and 36 weeks, respectively. The model predicted that response-guided treatment could allow a reduction in mean treatment duration to 25.3 weeks and attain a 78.6% SVR rate.

CONCLUSION

ALV plus RBV may represent an effective IFN-free treatment that is predicted to achieve high SVR rates in patients with HCV genotype 2 or 3 infection.

Discovery of daclatasvir, a pan-genotypic hepatitis C virus NS5A replication complex inhibitor with potent clinical effect

The discovery and development of the first-in-class hepatitis C virus (HCV) NS5A replication complex inhibitor daclatasvir (6) provides a compelling example of the power of phenotypic screening to identify leads engaging novel targets in mechanistically unique ways. HCV NS5A replication complex inhibitors are pan-genotypic in spectrum, and this mechanistic class provides the most potent HCV inhibitors in vitro that have been described to date. Clinical trials with 6 demonstrated a potent effect on reducing plasma viral load and, in combination with mechanistically orthogonal HCV inhibitors, established the ability to cure even the most difficult infections without the need for immune stimulation. In this Drug Annotation, we describe the discovery of the original high-throughput screening lead 7 and the chemical conundrum and challenges resolved in optimizing to 6 as a clinical candidate and finally we summarize the results of select clinical studies.

Identification of weak points of hepatitis C virus NS3 protease inhibitors using surface plasmon resonance biosensor-based interaction kinetic analysis and genetic variants

To aid the design of next generation hepatitis C virus (HCV) drugs, the kinetics of the interactions between NS3 protease inhibitors and enzyme from genotypes 1a, 1b, and 3a have been characterized. The linear mechanism-based inhibitors VX-950 (telaprevir) and SCH 503034 (boceprevir) benefited from covalent adduct formation. However, the apparent affinities were rather weak (VX-950, K(D)* of 340, 8.5, and 1000 nM for genotypes 1a, 1b and 3a, respectively; SCH 503034, K(D)* of 90 and 3.9 nM for 1b and 3a, respectively). The non-mechanism-based macrocyclic inhibitors BILN-2016 (ciluprevir) and ITMN-191 (danoprevir) had faster association and slower dissociation kinetics, indicating that rigidification is kinetically favorable. ITMN-191 had nanomolar affinities for all genotypes (K(D)* of 0.13, 1.6, and 0.52 nM), suggesting that a broad spectrum drug is conceivable. The data show that macrocyclic scaffolds and mechanism-based inhibition are advantageous but that there is considerable room for improvement of the kinetics of HCV protease targeted drugs.

Discovery and development of hepatitis C virus NS5A replication complex inhibitors

Lead inhibitors that target the function of the hepatitis C virus (HCV) nonstructural 5A (NS5A) protein have been identified by phenotypic screening campaigns using HCV subgenomic replicons. The demonstration of antiviral activity in HCV-infected subjects by the HCV NS5A replication complex inhibitor (RCI) daclatasvir (1) spawned considerable interest in this mechanistic approach. In this Perspective, we summarize the medicinal chemistry studies that led to the discovery of 1 and other chemotypes for which resistance maps to the NS5A protein and provide synopses of the profiles of many of the compounds currently in clinical trials. We also summarize what is currently known about the NS5A protein and the studies using NS5A RCIs and labeled analogues that are helping to illuminate aspects of both protein function and inhibitor interaction. We conclude with a synopsis of the results of notable clinical trials with HCV NS5A RCIs.

Analysis of hepatitis C viral kinetics during administration of two nucleotide analogues: sofosbuvir (GS-7977) and GS-0938

BACKGROUND

Sofosbuvir (GS-7977) and GS-0938 are nucleotide analogue HCV polymerase inhibitors, with sofosbuvir being a pyrimidine and GS-0938 being a purine. Mathematical modelling has provided important insights for characterizing HCV RNA decline and for estimating the in vivo effectiveness of single direct-acting antiviral agents (DAAs); however it has not been used to characterize viral kinetics with combination DAA therapy.

METHODS

We evaluated the antiviral activity of sofosbuvir and GS-0938 given alone and in combination for 14 days in 32 HCV genotype 1 treatment-naive patients (P2938-0212; NUCLEAR study).

RESULTS

Viral load declined rapidly in a biphasic manner in all subjects and could be well fitted by assuming that both drugs had a similar and additive level of effectiveness in reducing viral production equal to 99.96%, on average. The model predicted that this level of effectiveness was not reached until 0.6 and 2 days for GS-0938 and sofosbuvir, respectively, and likely represents the time needed to accumulate intracellular triphosphates. Subsequently, both drugs led to a rapid second phase of viral decline with a mean rate of 0.35 d(-1). No effect of IL28B-polymorphism was found on viral kinetic parameters.

CONCLUSIONS

Both sofosbuvir and GS-0938 are highly effective at blocking viral production from HCV-infected cells. Both drugs led to a rapid and consistent second phase viral decline and exhibited no breakthroughs or other signs of resistance. From a kinetics perspective, because both drugs were of the same class there was little benefit in combining them, suggesting that future DAA combinations should consider utilizing drugs with different modes of action.

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.

Influence of a priori Information, Designs, and Undetectable Data on Individual Parameters Estimation and Prediction of Hepatitis C Treatment Outcome

Hepatitis C viral kinetic analysis based on nonlinear mixed effect models can be used to individualize treatment. For that purpose, it is necessary to obtain precise estimation of individual parameters. Here, we evaluated by simulation the influence on Bayesian individual parameter estimation and outcome prediction of a priori information on population parameters, viral load sampling designs, and methods for handling data below detection limit (BDL). We found that a precise estimation of both individual parameters and treatment outcome could be obtained using as few as six measurements in the first month of therapy. This result remained valid even when incorrect a priori information on population parameters was set as long as the parameters were identifiable and BDL data were properly handled. However, setting wrong values for a priori population parameters could lead to severe estimation/prediction errors if BDL data were ignored and not properly accounted in the likelihood function.

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.

Clinical trial simulation to evaluate power to compare the antiviral effectiveness of two hepatitis C protease inhibitors using nonlinear mixed effect models: a viral kinetic approach

BACKGROUND

Models of hepatitis C virus (HCV) kinetics are increasingly used to estimate and to compare in vivo drug's antiviral effectiveness of new potent anti-HCV agents. Viral kinetic parameters can be estimated using non-linear mixed effect models (NLMEM). Here we aimed to evaluate the performance of this approach to precisely estimate the parameters and to evaluate the type I errors and the power of the Wald test to compare the antiviral effectiveness between two treatment groups when data are sparse and/or a large proportion of viral load (VL) are below the limit of detection (BLD).

METHODS

We performed a clinical trial simulation assuming two treatment groups with different levels of antiviral effectiveness. We evaluated the precision and the accuracy of parameter estimates obtained on 500 replication of this trial using the stochastic approximation expectation-approximation algorithm which appropriately handles BLD data. Next we evaluated the type I error and the power of the Wald test to assess a difference of antiviral effectiveness between the two groups. Standard error of the parameters and Wald test property were evaluated according to the number of patients, the number of samples per patient and the expected difference in antiviral effectiveness.

RESULTS

NLMEM provided precise and accurate estimates for both the fixed effects and the inter-individual variance parameters even with sparse data and large proportion of BLD data. However Wald test with small number of patients and lack of information due to BLD resulted in an inflation of the type I error as compared to the results obtained when no limit of detection of VL was considered. The corrected power of the test was very high and largely outperformed what can be obtained with empirical comparison of the mean VL decline using Wilcoxon test.

CONCLUSION

This simulation study shows the benefit of viral kinetic models analyzed with NLMEM over empirical approaches used in most clinical studies. When designing a viral kinetic study, our results indicate that the enrollment of a large number of patients is to be preferred to small population sample with frequent assessments of VL.