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

Comparative effectiveness of seven interventions for chronic hepatitis D: a systematic review and network meta-analysis of randomized controlled trials

OBJECTIVE

To compare the effectiveness of seven major interventions [Bulevirtide (BLV), Interferon (IFN), Nucleoside analogs (NAs), BLV + IFN, BLV + NAs, IFN + NAs, and Placebo] to treat chronic hepatitis D.

METHODS

We followed PRISMA-NMA guidelines, searched databases (Cochrane Library, PubMed, EMBASE, and Web Of Science) for eligible randomized controlled trials (RCTs), and applied STATA17.0 software to execute the meta-analysis.

RESULTS

We included 14 randomized controlled trials (814 patients) comparing seven different interventions. The results of the network meta-analysis showed that: ① Sustained virological response (after 24 weeks of follow-up): Four intervention groups (BLV + IFN, IFN alone, IFN + NAs, and NAs alone) were effective (relative risk (RR) = 13.30, 95% confidence interval (Cl) [1.68,105.32], RR = 12.13, 95% Cl [1.46,101.04], RR = 5.05, 95% Cl [1.68,15.19], RR = 5.03, 95% Cl [1.66,15.20]), with no statistically significant differences between the four groups. The top three in probability rankings were: BLV + NAs, BLV + IFN, and BLV alone (surface under the cumulative ranking curve (SUCRA) = 86.8%, 80.3%, and 48.4%; ② Sustained biochemical response (after 24 weeks of follow-up): BLV + IFN and IFN were superior to BLV (RR = 14.71, 95% Cl [1.14,189.07], RR = 16.67, 95% Cl [1.39,199.52]). The top three were BLV alone, BLV + NAs, and BLV + IFN (SUCRA = 86.9%,81.2%, and 64.3%). ③ Histological response: NAs were superior to BLV (RR = 2.08, 95% Cl [1.10,3.93]), whereas the difference between other treatment regimens was not statistically significant, and the top three in the probability ranking were BLV alone, BLV + NAs, and BLV + IFN (SUCRA = 75.6%, 75.6%, and 61.8%).

CONCLUSIONS

IFN, IFN + BLV, and IFN + NAs were effective in clearing HDV RNA and normalizing alanine aminotransferase levels; however, IFN and IFN + NAs had a high rate of viral relapse at 24 weeks post-treatment follow-up. There was no additional benefit of adding NAs to IFN therapy for chronic hepatitis D; however, the combination of IFN + BLV significantly improved short-term HDV RNA clearance, which showed strong synergistic effects. The seven regimens included in the study did not contribute significantly to liver histological improvement. Therefore, the IFN + BLV combination has the most potential as a treatment option to improve the long-term prognosis or even cure chronic hepatitis D.

TRIAL REGISTRATION

This systematic evaluation and meta-analysis was registered with PROSPERO under the registration number: CRD42022314544.).

Towards a Mathematical Model for the Viral Progression in the Pharynx

In this work, a comprehensive model for the viral progression in the pharynx has been developed. This one-dimension model considers both Fickian diffusion and convective flow coupled with chemical reactions, such as virus population growth, infected and uninfected cell accumulation as well as virus clearance. The effect of a sterilizing agent such as an alcoholic solution on the viral progression in the pharynx was taken into account and a parametric analysis for the effect of kinetic rate parameters on virus propagation was made. Moreover, different conditions caused by further medical treatment, such as a decrease in virus yield per infected cell, were examined. It is shown that the infection fails to establish by decreasing the virus yield per infected cell. It is believed that this work could be used to further investigate the medical treatment of viral progression in the pharynx.

Facilitating Antiviral Drug Discovery Using Genetic and Evolutionary Knowledge

Over the course of human history, billions of people worldwide have been infected by various viruses. Despite rapid progress in the development of biomedical techniques, it is still a significant challenge to find promising new antiviral targets and drugs. In the past, antiviral drugs mainly targeted viral proteins when they were used as part of treatment strategies. Since the virus mutation rate is much faster than that of the host, such drugs feature drug resistance and narrow-spectrum antiviral problems. Therefore, the targeting of host molecules has gradually become an important area of research for the development of antiviral drugs. In recent years, rapid advances in high-throughput sequencing techniques have enabled numerous genetic studies (such as genome-wide association studies (GWAS), clustered regularly interspersed short palindromic repeats (CRISPR) screening, etc.) for human diseases, providing valuable genetic and evolutionary resources. Furthermore, it has been revealed that successful drug targets exhibit similar genetic and evolutionary features, which are of great value in identifying promising drug targets and discovering new drugs. Considering these developments, in this article the authors propose a host-targeted antiviral drug discovery strategy based on knowledge of genetics and evolution. We first comprehensively summarized the genetic, subcellular location, and evolutionary features of the human genes that have been successfully used as antiviral targets. Next, the summarized features were used to screen novel druggable antiviral targets and to find potential antiviral drugs, in an attempt to promote the discovery of new antiviral drugs.

Mechanistic Modeling of SARS-CoV-2 and Other Infectious Diseases and the Effects of Therapeutics

Modern viral kinetic modeling and its application to therapeutics is a field that attracted the attention of the medical, pharmaceutical, and modeling communities during the early days of the AIDS epidemic. Its successes led to applications of modeling methods not only to HIV but a plethora of other viruses, such as hepatitis C virus (HCV), hepatitis B virus and cytomegalovirus, which along with HIV cause chronic diseases, and viruses such as influenza, respiratory syncytial virus, West Nile virus, Zika virus, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which generally cause acute infections. Here we first review the historical development of mathematical models to understand HIV and HCV infections and the effects of treatment by fitting the models to clinical data. We then focus on recent efforts and contributions of applying these models towards understanding SARS-CoV-2 infection and highlight outstanding questions where modeling can provide crucial insights and help to optimize nonpharmaceutical and pharmaceutical interventions of the coronavirus disease 2019 (COVID-19) pandemic. The review is written from our personal perspective emphasizing the power of simple target cell limited models that provided important insights and then their evolution into more complex models that captured more of the virology and immunology. To quote Albert Einstein, "Everything should be made as simple as possible, but not simpler," and this idea underlies the modeling we describe below.

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.

Zika plasma viral dynamics in nonhuman primates provides insights into early infection and antiviral strategies

The recent outbreak of Zika virus (ZIKV) has been associated with fetal abnormalities and neurological complications, prompting global concern. Here we present a mathematical analysis of the within-host dynamics of plasma ZIKV burden in a nonhuman primate model, allowing for characterization of the growth and clearance of ZIKV within individual macaques. We estimate that the eclipse phase for ZIKV, the time between cell infection and viral production, is most likely short (∼4 h), the median within-host basic reproductive number R₀ is 10.7, the rate of viral production is rapid (>25,000 virions d^-1), and the lifetime of an infected cell while producing virus is ∼5 h. We also estimate that the minimum number of virions produced by an infected cell over its lifetime is ∼5,500. We assess the potential effect of an antiviral treatment that blocks viral replication, showing that the median time to undetectable plasma viral load (VL) can be reduced from ∼5 d to ∼3 d with a drug concentration ∼15 times the drug's EC₅₀ when treatment is given prophylactically starting at the time of infection. In the case of favipiravir, a polymerase inhibitor with activity against ZIKV, we predict a dose of 150 mg/kg given twice a day initiated at the time of infection can reduce the peak median VL by ∼3 logs and shorten the time to undetectable median VL by ∼2 d, whereas treatment given 2 d postinfection is mostly ineffective in accelerating plasma VL loss in macaques.

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.

HCV1b genome evolution under selective pressure of the cyclophilin inhibitor alisporivir during the DEB-025-HCV-203 phase II clinical trial

Major advances have revolutionized the HCV antiviral treatment field, with interferon-free combinations of direct-acting antivirals (DAAs) resulting into success rates of >90% for all HCV genotypes. Nevertheless, viral eradication at a global level stills remains challenging, stimulating the continued search for new affordable pan-genotypic drugs. To overcome selection of drug resistant variants, targeting host proteins can be an attractive mechanism of action. Alisporivir (Debio 025) is a potent pan-genotypic host-targeting antiviral agent, acting on cyclophilin A, which is necessary for HCV replication. The efficacy and safety of three different oral doses of alisporivir in combination with pegylated interferon-α2a given over a period of four weeks, was investigated in a randomized, double-blind and placebo-controlled phase IIa clinical trial, in 90 treatment-naïve subjects infected with chronic hepatitis C, wherefrom 58 HCV1b samples were selected for genetic sequencing purposes. Sequencing results were used to study the HCV genome for amino acid changes potentially related with selective pressure and resistance to alisporivir. By comparing baseline and on-treatment sequences, a large variation in proportion of amino acid changes was detected in all treatment arms. The NS5A variant D320E, which was previously identified during in vitro resistance selection and resulted in 3.6-fold reduced alisporivir susceptibility, emerged in two subjects in the alisporivir monotherapy arm. However, emergence of D320E appeared to be associated only with concurrent viral load rebound in one subject with 0.8log10IU/ml increase in HCV RNA. In general, for all datasets, low numbers of positions under positive selective pressure were observed, with no significant differences between naïve and treated sequences. Additionally, incomplete sequence information for some of the 22 patients and the low number of individuals per treatment arm, is limiting the power to assess the association of alisporivir or interferon treatment with the observed amino acid changes.

New perspectives for preventing hepatitis C virus liver graft infection

Hepatitis C virus (HCV) infection is a leading cause of end-stage liver disease that necessitates liver transplantation. The incidence of virus-induced cirrhosis and hepatocellular carcinoma continues to increase, making liver transplantation increasingly common. Infection of the engrafted liver is universal and accelerates progression to advanced liver disease, with 20-30% of patients having cirrhosis within 5 years of transplantation. Treatments of chronic HCV infection have improved dramatically, albeit with remaining challenges of failure and access, and therapeutic options to prevent graft infection during liver transplantation are emerging. Developments in directed use of new direct-acting antiviral agents (DAAs) to eliminate circulating HCV before or after transplantation in the past 5 years provide renewed hope for prevention and treatment of liver graft infection. Identification of the ideal regimen and use of DAAs reveals new ways to treat this specific population of patients. Complementing DAAs, viral entry inhibitors have been shown to prevent liver graft infection in animal models and delay graft infection in clinical trials, which shows their potential for use concomitant to transplantation. We review the challenges and pathology associated with HCV liver graft infection, highlight current and future strategies of DAA treatment timing, and discuss the potential role of entry inhibitors that might be used synergistically with DAAs to prevent or treat graft infection.

Alisporivir plus ribavirin, interferon free or in combination with pegylated interferon, for hepatitis C virus genotype 2 or 3 infection

Alisporivir is a cyclophilin inhibitor with pan-genotypic anti-hepatitis C virus (HCV) activity and a high barrier to viral resistance. The VITAL-1 study assessed alisporivir as interferon (IFN)-free therapy in treatment-naïve patients infected with HCV genotype 2 or 3. Three hundred forty patients without cirrhosis were randomized to: arm 1, alisporivir (ALV) 1,000 mg once-daily (QD); arm 2, ALV 600 mg QD and ribavirin (RBV); arm 3, ALV 800 mg QD and RBV; arm 4, ALV 600 mg QD and pegylated IFN (Peg-IFN); or arm 5, Peg-IFN and RBV. Patients receiving IFN-free ALV regimens who achieved rapid virological response (RVR) continued the same treatment throughout, whereas those with detectable HCV RNA at week 4 received ALV, RBV, and Peg-IFN from weeks 6 to 24. Overall, 300 patients received ALV-based regimens. In arm 1 to arm 4, the intent-to-treat rates of sustained virological response (SVR) 24 weeks after treatment (SVR24) were from 80% to 85%, compared with 58% (n = 23 of 40) with Peg-IFN/RBV. Per-protocol analysis showed higher SVR24 rates in patients who received ALV/RBV, IFN-free after RVR (92%; n = 56 of 61) than with ALV alone after RVR (72%; n = 13 of 18) or with Peg-IFN/RBV (70%; n = 23 of 33). Both RVRs and SVRs to ALV IFN-free regimens were numerically higher in genotype 3- than in genotype 2-infected patients. Viral breakthrough was infrequent (3%; n = 7 of 258). IFN-free ALV treatment showed markedly better safety/tolerability than IFN-containing regimens.

CONCLUSIONS

ALV plus RBV represents an effective IFN-free option for a proportion of patients with HCV genotype 2 or 3 infections, with high SVR rates for patients with early viral clearance. Further investigations of ALV in IFN-free combination regimens with direct-acting antiviral drugs deserve exploration in future trials.

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.

Liver-targeted cyclosporine A-encapsulated poly (lactic-co-glycolic) acid nanoparticles inhibit hepatitis C virus replication

Therapeutic options for hepatitis C virus (HCV) infection have been limited by drug resistance and adverse side effects. Targeting the host factor cyclophilin A (CypA), which is essential for HCV replication, offers a promising strategy for antiviral therapy. However, due to its immunosuppressive activity and severe side effects, clinical application of cyclosporine A (CsA) has been limited as an antiviral agent. To overcome these drawbacks, we have successfully developed a liver-specific, sustained drug delivery system by conjugating the liver-targeting peptide (LTP) to PEGylated CsA-encapsulated poly (lactic-co-glycolic) acid (PLGA) nanoparticles. Furthermore, our delivery system exhibited high specificity to liver, thus contributing to the reduced immunosuppressive effect and toxicity profile of CsA. Finally, targeted nanoparticles were able to effectively inhibit viral replication in vitro and in an HCV mouse model. As a proof of principle, we herein show that our delivery system is able to negate the adverse effects of CsA and produce therapeutic effects in an HCV mouse model.

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.

Hepatitis C NS5A protein: two drug targets within the same protein with different mechanisms of resistance

The era of interferon-free antiviral treatments for hepatitis C virus infection has arrived. With increasing numbers of approved antivirals, evaluating all parameters that may influence response is necessary to choose optimal combinations for treatment success. Targeting NS5A has become integral in antiviral combinations in clinical development. Daclatasvir and ledipasvir belong to the NS5A inhibitor class, which directly target the NS5A protein. Alisporivir, a host-targeting antiviral, is a cyclophilin inhibitor that indirectly targets NS5A by blocking NS5A/cyclophilin A interaction. Resistance to daclatasvir and ledipasvir differs from alisporivir, with mutations arising in NS5A domains I and II, respectively. Combining these two classes acting on distinct NS5A domains represents an attractive strategy for potentially effective interferon-free treatments for chronic hepatitis C infection.

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.

Natural product and natural product derived drugs in clinical trials

The 25 Natural Product (NP)-derived drugs launched since 2008 and the 100 NP-derived compounds and 33 Antibody Drug Conjugates (ADCs) in clinical trials or in registration at the end of 2013 are reviewed.