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

Integrated pharmacokinetic/viral dynamic model for daclatasvir/asunaprevir in treatment of patients with genotype 1 chronic hepatitis C

In order to develop an integrated pharmacokinetic/viral dynamic (PK/VD) model to predict long-term virological response rates to daclatasvir (DCV) and asunaprevir (ASV) combination therapy in patients infected with genotype 1 (GT1) chronic hepatitis C virus (HCV), a systematic publication search was conducted for DCV and ASV administered alone and/or in combination in healthy subjects or patients with GT1 HCV infection. On the basis of a constructed meta-database, an integrated PK/VD model was developed, which adequately described both DCV and ASV PK profiles and viral load time curves. The IC₅₀ values of DCV and ASV were estimated to be 0.041 and 2.45 μg/L, respectively, in GT1A patients. A sigmoid E_max function was applied to describe the antiviral effects of DCV and ASV, depending on the drug concentrations in the effect compartment. An empirical exponential function revealed that IC₅₀ changing over time described drug resistance in HCV GT1A patients during DCV or ASV monotherapy. Finally, the PK/VD model was evaluated externally by comparing the expected and observed virological response rates during and post-treatment with DCV and ASV combination therapy in HCV GT1B patients. Both the rates were in general agreement. Our PK/VD model provides a useful platform for the characterization of pharmacokinetic/pharmacodynamic relationships and the prediction of long-term virological response rates to aid future development of direct acting antiviral drugs.

Alisporivir Has Limited Antiviral Effects Against Ebola Virus Strains Makona and Mayinga

Antiviral therapeutics with existing clinical safety profiles would be highly desirable in an outbreak situation, such as the 2013-2016 emergence of Ebola virus (EBOV) in West Africa. Although, the World Health Organization declared the end of the outbreak early 2016, sporadic cases of EBOV infection have since been reported. Alisporivir is the most clinically advanced broad-spectrum antiviral that functions by targeting a host protein, cyclophilin A (CypA). A modest antiviral effect of alisporivir against contemporary (Makona) but not historical (Mayinga) EBOV strains was observed in tissue culture. However, this effect was not comparable to observations for an alisporivir-susceptible virus, the flavivirus tick-borne encephalitis virus. Thus, EBOV does not depend on (CypA) for replication, in contrast to many other viruses pathogenic to humans.

The cyclophilin-inhibitor alisporivir stimulates antigen presentation thereby promoting antigen-specific CD8(+) T cell activation

BACKGROUND & AIMS

Cyclophilin-inhibitors have potent antiviral activity against Hepatitis C virus (HCV) and are promising candidates for broad-spectrum antiviral therapy. Cyclosporine A (CsA) acts immunosuppressive by blocking T cell activation and antigen presentation. Alisporivir, a non-immunosuppressive CsA analog in clinical development, does not inhibit T cell activation. In this study we explored the impact of alisporivir on antigen presentation.

METHODS

Hepatoma cells endogenously expressing the epitope-restricting major histocompatibility complex-class I (MHC-I) allele HLA-A2 and constitutively expressing a viral antigen were established to study the impact of cyclophilin-inhibitors on antigen presentation. Antigen-specific CD8(+) T cell activation and MHC-I surface expression were measured to quantify antigen presentation.

RESULTS

Our work establishes a novel cell culture model to study antigen presentation in liver-derived cells. Authentic regulation of antigen presentation was ensured by the action of pro- and anti-inflammatory cytokines. Alisporivir pretreatment stimulated antigen presentation by hepatoma target cells, leading to enhancement of antigen-specific CD8(+) T cell activation by 40%. Alisporivir, as well as a panel of other cyclophilin-inhibitors, induced an increase of MHC-I and beta-2 microglobulin on the surface of several cell lines. The drug neither enhanced MHC-I transcript or protein levels nor affected surface expression of other proteins or protein trafficking in general. Proteasome-inhibitors completely blocked the alisporivir-directed enhancement of surface MHC-I, suggesting an influence of the drug on peptide-availability.

CONCLUSIONS

Alisporivir stimulates antigen presentation by inducing enhanced MHC-I surface expression, thereby promoting antigen-specific CD8(+) T cell activation. This immunostimulatory function might further contribute to the antiviral activity of non-immunosuppressive cyclophilin-inhibitors.

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.

Modelling hepatitis C therapy--predicting effects of treatment

Mathematically modelling changes in HCV RNA levels measured in patients who receive antiviral therapy has yielded many insights into the pathogenesis and effects of treatment on the virus. By determining how rapidly HCV is cleared when viral replication is interrupted by a therapy, one can deduce how rapidly the virus is produced in patients before treatment. This knowledge, coupled with estimates of the HCV mutation rate, enables one to estimate the frequency with which drug resistant variants arise. Modelling HCV also permits the deduction of the effectiveness of an antiviral agent at blocking HCV replication from the magnitude of the initial viral decline. One can also estimate the lifespan of an HCV-infected cell from the slope of the subsequent viral decline and determine the duration of therapy needed to cure infection. The original understanding of HCV RNA decline under interferon-based therapies obtained by modelling needed to be revised in order to interpret the HCV RNA decline kinetics seen when using direct-acting antiviral agents (DAAs). There also exist unresolved issues involving understanding therapies with combinations of DAAs, such as the presence of detectable HCV RNA at the end of therapy in patients who nonetheless have a sustained virologic response.

HCV Kinetic Models and Their Implications in Drug Development

Chronic infection with hepatitis C virus (HCV) affects about 170 million people worldwide and is a major cause of liver complications. Mathematical modeling of viral kinetics under treatment has provided insight into the viral life cycle, treatment effectiveness, and drugs' mechanisms of action. Here we review the implications of viral kinetic models at the different stages of development of anti-HCV agents.

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.