Modelling the kinetics of hepatitis C virus RNA decline over 4 weeks of treatment with pegylated interferon alpha-2b

A New Age-Structured Multiscale Model of the Hepatitis C Virus Life-Cycle During Infection and Therapy With Direct-Acting Antiviral Agents

The dynamics of hepatitis C virus (HCV) RNA during translation and replication within infected cells were added to a previous age-structured multiscale mathematical model of HCV infection and treatment. The model allows the study of the dynamics of HCV RNA inside infected cells as well as the release of virus from infected cells and the dynamics of subsequent new cell infections. The model was used to fit in vitro data and estimate parameters characterizing HCV replication. This is the first model to our knowledge to consider both positive and negative strands of HCV RNA with an age-structured multiscale modeling approach. Using this model we also studied the effects of direct-acting antiviral agents (DAAs) in blocking HCV RNA intracellular replication and the release of new virions and fit the model to in vivo data obtained from HCV-infected subjects under therapy.

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.

A hepatitis C virus infection model with time-varying drug effectiveness: solution and analysis

Simple models of therapy for viral diseases such as hepatitis C virus (HCV) or human immunodeficiency virus assume that, once therapy is started, the drug has a constant effectiveness. More realistic models have assumed either that the drug effectiveness depends on the drug concentration or that the effectiveness varies over time. Here a previously introduced varying-effectiveness (VE) model is studied mathematically in the context of HCV infection. We show that while the model is linear, it has no closed-form solution due to the time-varying nature of the effectiveness. We then show that the model can be transformed into a Bessel equation and derive an analytic solution in terms of modified Bessel functions, which are defined as infinite series, with time-varying arguments. Fitting the solution to data from HCV infected patients under therapy has yielded values for the parameters in the model. We show that for biologically realistic parameters, the predicted viral decay on therapy is generally biphasic and resembles that predicted by constant-effectiveness (CE) models. We introduce a general method for determining the time at which the transition between decay phases occurs based on calculating the point of maximum curvature of the viral decay curve. For the parameter regimes of interest, we also find approximate solutions for the VE model and establish the asymptotic behavior of the system. We show that the rate of second phase decay is determined by the death rate of infected cells multiplied by the maximum effectiveness of therapy, whereas the rate of first phase decline depends on multiple parameters including the rate of increase of drug effectiveness with time.

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.

Treatment of hepatitis C: how will we use viral kinetics, response-guided therapy?

Hepatitis C virus (HCV) RNA level monitoring is currently used to guide the duration of interferon-containing treatment regimens. Nowadays, HCV RNA level quantification is based on real-time polymerase chain reaction assays that are both sensitive and accurate. Assessing the virological response to therapy is used to shorten treatment duration in early responders, in order to reduce the cost and burden of adverse events of therapy without impacting the chance of success. Whether response-guided therapy will still be useful in the era of all-oral, interferon-free regimens remains uncertain.

Hepatitis C virus viral kinetics during α-2a or α-2b pegylated interferon plus ribavirin therapy in liver transplant recipients with different immunosuppression regimes

BACKGROUND

Predictors of sustained virological response (SVR) to antiviral therapy post-liver transplantation (LT) for chronic hepatitis C are needed. In non-transplanted patients, viral kinetics can predict SVR.

OBJECTIVES

To determine the early viral kinetics in LT recipients with different immunosuppression (tacrolimus - Tac- vs. cyclosporine - CsA-) during treatment with peg-IFN+RBV.

STUDY DESIGN

Prospective pilot study in HCV-1b infected patients: (LT CsA n=8; Tac n=8; non-LT n=4), treated with IFN α-2a vs. α-2b (180 μg or 1.5 μg/kg, respectively) once weekly plus weight-based RBV. Median CsA or Tac baseline trough levels were 141 and 7.70 ng/mL, respectively. HCV-RNA was quantified before treatment and after 3, 6, 12h; days 1-6; and weeks 4, 12, 24, 48 and 78 (follow-up).

RESULTS

Different kinetics were observed: early viral load declines with shoulder phase (n=12), delayed monophasic without first phase (n=5, all CsA), and biphasic (n=1) or flat (n=1), without influence of IL28B rs12979860 donor/recipient alleles. In LT, median declines (log(10)UI/mL) at week 4 were -3.62 and -1.49 for Tac vs. CsA; and -2.10 vs.-1.50 for IFN α-2a vs. α-2b (NS), with a trend for faster declines in Tac patients. Generalized additive models suggested a cut-off for predicting response in LT patients of 30 days for Tac, but beyond day 40 for CsA.

CONCLUSION

In LT, the viral kinetics during peg-IFN+RBV treatment is delayed. HCV-RNA at 48 h. may not be predictive of response, and CsA-immunosupressed patients with delayed monophasic declines may potentially achieve ETVR and SVR despite unfavourable or absent early viral load declines.

Association of IL28B gene variations with mathematical modeling of viral kinetics in chronic hepatitis C patients with IFN plus ribavirin therapy

Asian patients with chronic hepatitis C (CHC) are known to have better virological responses to pegylated (Peg) IFN-based therapy than Western patients. Although IL28B gene polymorphisms may contribute to this difference, whether favorable hepatitis C virus (HCV) kinetics during treatment plays a role remains unclear. We enrolled 145 consecutive Taiwanese patients with CHC receiving Peg-IFN α-2a plus ribavirin for the study. Blood samples were taken more frequently at defined intervals in the first 3 d. Peg-IFN was administered at week 1. It was then administered weekly in combination with daily ribavirin for 24 or 48 wk. A mathematical model fitted to the observed HCV kinetics was constructed, which could interpret the transient HCV titer elevation after Peg-IFN treatment. The results demonstrated a comparable viral clearance rate (c = 3.45 ± 3.73) (day(-1), mean ± SD) but lower daily viral production rate (P = 10(6)-10(12)) in our patients than those reported previously in Western patients. Of 110 patients with a sustained virological response (SVR), 47 (43%) had a transient elevation of viral titer within 12 h (proportion of 12 h/3 d: 44% in non-SVR vs. 70% in SVR; P = 0.029). Among 91 patients with available rs8099917 data, patients with the TT genotype had an early surge of viral titer after therapy and a higher SVR and viral clearance rate than those with the GT genotype. In conclusion, Taiwanese patients with CHC receiving Peg-IFN plus ribavirin therapy have a lower daily viral production rate than Western patients, and the rs8099917 TT genotype may contribute to the increased viral clearance rate and better virological responses in these patients.

Modeling HCV kinetics under therapy using PK and PD information

BACKGROUND

Mathematical models have proven helpful in analyzing the virological response to antiviral therapy in hepatitis C virus (HCV) infected subjects.

OBJECTIVE

To summarize the uses and limitations of different models for analyzing HCV kinetic data under pegylated IFN therapy.

METHODS

We formulate mathematical models and fit them by nonlinear least square regression to patient data to estimate model parameters. We compare the goodness of fit and parameter values estimated by different models statistically.

RESULTS/CONCLUSION

The best model for parameter estimation depends on the availability and the quality of data as well as the therapy used. We also discuss the mathematical models that will be needed to analyze HCV kinetic data from clinical trials with new antiviral drugs.

Avoiding therapeutic pitfalls: the rational use of specifically targeted agents against hepatitis C infection

The development of specifically targeted antiviral agents against hepatitis C is a major therapeutic advance that promises to markedly improve treatment response rates in patients with chronic infection. However, rapid emergence of drug resistance has already been described, the consequences of which are not yet understood. Although there are important differences between hepatitis C (HCV) and human immunodeficiency virus (HIV) infection, the judicious use of candidate agents against HCV should be guided by principles that have been established in the HIV therapeutic arena. In this review, we attempt to draw useful parallels between the development of antiretroviral therapy for HIV and preliminary data on antiviral agents for hepatitis C virus infection. Applying concepts learned in HIV therapeutics will hopefully lead to a prudent and cautious path in HCV treatment paradigms, particularly with respect to drug resistance.

A Hepatitis C Viral Kinetic Model that Allows for Time-Varying Drug Effectiveness

Background

The standard model of hepatitis C virus (HCV) dynamics under high-dose daily interferon (IFN) therapy assumed that the drug effectiveness remains constant. However, for treatment with pegylated (PEG)-IFN-α2b dosed weekly, drug levels fall substantially and viral load rebounds have been observed toward the end of the weekly dosing interval, implying non-constant drug efficacy.

Methods

In this paper, we developed the decreasing effectiveness (DE) model, a new mathematical model that allows the drug effectiveness to change with time.

Results

The DE model can describe viral load rebounds as well as other viral kinetic patterns observed in clinical practice, such as biphasic viral declines. We applied the DE model to the HCV RNA kinetic data under PEG-IFN-α2b therapy. The average drug effectiveness during the first week of therapy estimated in the DE model agreed with the one estimated from HCV RNA kinetic data plus pharmacokinetic data.

Conclusions

We illustrated the usefulness of the DE model by analysing HCV RNA data from patients who received PEG-IFN-α2b once weekly plus daily ribavirin.

Modelling hepatitis C virus kinetics during treatment with pegylated interferon alpha-2b: errors in the estimation of viral kinetic parameters

Neumann et al. [1] developed a widely used model for the analysis of hepatitis C virus (HCV) dynamics after the initiation of interferon therapy that assumes the effectiveness of therapy in blocking virion production, epsilon, is constant. However, with pegylated interferon alpha-2b (PEG-IFN) given weekly, there are significant changes in drug concentration between doses, leading to changes in drug effectiveness and viral rebounds. To investigate the appropriateness of the constant effectiveness (CE) model [1] for studies involving PEG-IFN, we simulated PEG-IFN treatment, using 294 sets of pharmacokinetic/pharmacodynamic (PK/PD) parameters that span observed ranges and fit the simulated data to the CE model. For most combinations of PK/PD parameters, the fits resulted in an infected cell loss rate, delta, that underestimates the true value used in the simulations and yielded over-estimates of the average effectiveness of PEG-IFN. In the setting of PEG-IFN therapy, the use of the CE model of HCV kinetics has to be reevaluated and the validity of its use depends on the amount of HCV RNA rebound observed between doses.