Assessing antiviral potency of anti-HIV therapies in vivo by comparing viral decay rates in viral dynamic models

A virologic marker, the number of HIV RNA copies or viral load, is currently used to evaluate anti-HIV therapies in AIDS clinical trials. This marker can be used to assess the antiviral potency of therapies, but is easily affected by noncompliance, drug resistance, toxicities, and other factors during the long-term treatment evaluation process. Recently it has been suggested to use viral dynamics to assess the potency of antiviral drugs and therapies, since viral decay rates in viral dynamic models have been shown to be related to the antiviral drug potency directly, and they need a shorter evaluation time. In this paper we first review the two statistical approaches for characterizing HIV dynamics and estimating viral decay rates: the individual nonlinear least squares regression (INLS) method and the population nonlinear mixed-effect model (PMEM) approach. To compare the viral decay rates between two treatment arms, parametric and nonparametric tests, based on the estimates of viral decay rates (the derived variables) from both the INLS and PMEM methods, are proposed and studied. We show, using the concept of exchangeability, that the test based on the empirical Bayes' estimates from the PMEM is valid, powerful and robust. This proposed method is very useful in most practical cases where the INLS-based tests and the general likelihood ratio test may not apply. We validate and compare various tests for finite samples using Monte Carlo simulations. Finally, we apply the proposed tests to an AIDS clinical trial to compare the antiviral potency between a 3-drug combination regimen and a 4-drug combination regimen. The proposed tests provide some significant evidence that the 4-drug regimen is more potent than the 3-drug regimen, while the naive methods fail to give a significant result.*To whom correspondence should be addressed.     

Potential Benefits of Sequential Inhibitor-Mutagen Treatments of RNA Virus Infections

Lethal mutagenesis is an antiviral strategy consisting of virus extinction associated with enhanced mutagenesis. The use of non-mutagenic antiviral inhibitors has faced the problem of selection of inhibitor-resistant virus mutants. Quasispecies dynamics predicts, and clinical results have confirmed, that combination therapy has an advantage over monotherapy to delay or prevent selection of inhibitor-escape mutants. Using ribavirin-mediated mutagenesis of foot-and-mouth disease virus (FMDV), here we show that, contrary to expectations, sequential administration of the antiviral inhibitor guanidine (GU) first, followed by ribavirin, is more effective than combination therapy with the two drugs, or than either drug used individually. Coelectroporation experiments suggest that limited inhibition of replication of interfering mutants by GU may contribute to the benefits of the sequential treatment. In lethal mutagenesis, a sequential inhibitor-mutagen treatment can be more effective than the corresponding combination treatment to drive a virus towards extinction. Such an advantage is also supported by a theoretical model for the evolution of a viral population under the action of increased mutagenesis in the presence of an inhibitor of viral replication. The model suggests that benefits of the sequential treatment are due to the involvement of a mutagenic agent, and to competition for susceptible cells exerted by the mutant spectrum. The results may impact lethal mutagenesis-based protocols, as well as current antiviral therapies involving ribavirin.     

Comparison of Linear,Nonlinear and Semiparametric Mixed‐effects Models for Estimating HIV Dynamic Parameters

The potency of antiretroviral agents in AIDS clinical trials can be assessed on the basis of an early viral response such as viral decay rate or change in viral load (number of copies of HIV RNA) of the plasma. Linear, parametric nonlinear, and semiparametric nonlinear mixed‐effects models have been proposed to estimate viral decay rates in viral dynamic models. However, before applying these models to clinical data, a critical question that remains to be addressed is whether these models produce coherent estimates of viral decay rates, and if not, which model is appropriate and should be used in practice. In this paper, we applied these models to data from an AIDS clinical trial of potent antiviral treatments and found significant incongruity in the estimated rates of reduction in viral load. Simulation studies indicated that reliable estimates of viral decay rate were obtained by using the parametric and semiparametric nonlinear mixed‐effects models. Our analysis also indicated that the decay rates estimated by using linear mixed‐effects models should be interpreted differently from those estimated by using nonlinear mixed‐effects models. The semiparametric nonlinear mixed‐effects model is preferred to other models because arbitrary data truncation is not needed. Based on real data analysis and simulation studies, we provide guidelines for estimating viral decay rates from clinical data. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Development of novel antiviral therapies for hepatitis C virus

Over 170 million people worldwide are infected with hepatitis C virus (HCV), a major cause of liver diseases. Current interferon-based therapy is of limited efficacy and has significant side effects and more effective and better tolerated therapies are urgently needed. HCV is a positive, single-stranded RNA virus with a 9.6 kb genome that encodes ten viral proteins. Among them, the NS3 protease and the NSSB polymerase are essential for viral replication and have been the main focus of drug discovery efforts. Aided by structure-based drug design,potent and specific inhibitors of NS3 and NSSB have been identified, some of which are in late stage clinical trials and may significantly improve current HCV treatment. Inhibitors of other viral targets such as NSSA are also being pursued. However, HCV is an RNA virus characterized by high replication and mutation rates and consequently, resistance emerges quickly in patients treated with specific antivirals as monotherapy. A complementary approach is to target host factors such as cyclophilins that are also essential for viral replication and may present a higher genetic barrier to resistance. Combinations of these inhibitors of different mechanism are likely to become the essential components of future HCV therapies in order to maximize antiviral efficacy and prevent the emergence of resistance.     

Targeting host cofactors to inhibit viral infection

The majority of FDA-approved drugs indicated for the treatment of viral infections are inhibitors of viral proteins, of which the emergence of resistant strains is a major concern. This issue is exacerbated as most developed antiviral therapies are indicated for the treatment of viruses with error-prone replication. These problems may be addressed by the development of drugs that modulate the function of host factors involved in various aspects of a viral life cycle. Targeting host factors uncouples the mutation of a druggable protein gene from the replication and survival selection pressure exerted on a virus. Currently, a host-targeting antiviral (HTA), maraviroc, is approved for the treatment of human immunodeficiency virus (HIV) infection. In addition, several HTAs indicated for the treatment of hepatitis C virus (HCV) or HIV infection are at various stages of clinical evaluation. Targeting host factors is an attractive complement to therapies directly targeting a viral protein because of the expected higher genetic barrier for resistance and an overall increase in the diversity of treatment options. We examine how the integrated roles of emerging host cofactor screening approaches and drug development strategies may advance current treatment options.     

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study

BackgroundDevelopment of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials.Methods and findingsA modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d⁻¹ (95% CI: 1.06 to 1.27 d⁻¹), 0.777 d⁻¹ (0.716 to 0.838 d⁻¹), and 0.450 d⁻¹ (0.378 to 0.522 d⁻¹) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies).Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome.We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation.ConclusionsIn this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

Using a viral dynamics model, Shingo Iwami and colleagues investigate the sample sizes required to detect significant antiviral drug effects on COVID-19 in randomized controlled trials.     

Modeling hepatitis C virus dynamics: liver regeneration and critical drug efficacy

Mathematical models for hepatitis C viral (HCV) RNA kinetics have provided a means of evaluating the antiviral effectiveness of therapy, of estimating parameters such as the rate of HCV RNA clearance, and they have suggested mechanism of action against HCV for both interferon and ribavirin. Nevertheless, the model that was originally formulated by Neumann et al. [1998. Hepatitis C viral dynamics in vivo and the antiviral efficacy of interferon-alpha therapy. Science 282 (5386), 103-107] is unable to explain all of the observed HCV RNA profiles under treatment e.g., a triphasic viral decay and a viral rebound to baseline values after the cessation of therapy. Further, the half-life of productively HCV-infected cells, estimated from the second phase HCV RNA decline slope, is very variable and sometimes zero with no clear understanding of why. We show that extending the original model by including hepatocyte proliferation yields a more realistic model without any of these deficiencies. Further, we define and characterize a critical drug efficacy, such that for efficacies above the critical value HCV is ultimately cleared, while for efficacies below it, a new chronically infected viral steady-state level is reached.     

Induction of long-term protective antiviral endogenous immune response by short neutralizing monoclonal antibody treatment

Long-term immune control of viral replication still remains a major challenge in retroviral diseases. Several monoclonal antibodies (MAbs) have already shown antiviral activities in vivo, including in the clinic but their effects on the immune system of treated individuals are essentially unknown. Using the lethal neurodegeneration induced in mice upon infection of neonates by the FrCas(E) retrovirus as a model, we report here that transient treatment by a neutralizing MAb shortly after infection can, after an immediate antiviral effect, favor the development of a strong protective host immune response containing viral propagation long after the MAb has disappeared. In vitro virus neutralization- and complement-mediated cell lysis assays, as well as in vivo viral challenges and serum transfer experiments, indicate a clear and essential contribution of the humoral response to antiviral protection. Our observation may have important therapeutic consequences as it suggests that short antibody-based therapies early after infection should be considered, at least in the case of maternally infected infants, as adjunctive treatment strategies against human immunodeficiency virus, not only for a direct effect on the viral load but also for favoring the emergence of an endogenous antiviral immune response.     

The Molecular Basis of Drug Resistance against Hepatitis C Virus NS3/4A Protease Inhibitors

Hepatitis C virus (HCV) infects over 170 million people worldwide and is the leading cause of chronic liver diseases, including cirrhosis, liver failure, and liver cancer. Available antiviral therapies cause severe side effects and are effective only for a subset of patients, though treatment outcomes have recently been improved by the combination therapy now including boceprevir and telaprevir, which inhibit the viral NS3/4A protease. Despite extensive efforts to develop more potent next-generation protease inhibitors, however, the long-term efficacy of this drug class is challenged by the rapid emergence of resistance. Single-site mutations at protease residues R155, A156 and D168 confer resistance to nearly all inhibitors in clinical development. Thus, developing the next-generation of drugs that retain activity against a broader spectrum of resistant viral variants requires a comprehensive understanding of the molecular basis of drug resistance. In this study, 16 high-resolution crystal structures of four representative protease inhibitors – telaprevir, danoprevir, vaniprevir and MK-5172 – in complex with the wild-type protease and three major drug-resistant variants R155K, A156T and D168A, reveal unique molecular underpinnings of resistance to each drug. The drugs exhibit differential susceptibilities to these protease variants in both enzymatic and antiviral assays. Telaprevir, danoprevir and vaniprevir interact directly with sites that confer resistance upon mutation, while MK-5172 interacts in a unique conformation with the catalytic triad. This novel mode of MK-5172 binding explains its retained potency against two multi-drug-resistant variants, R155K and D168A. These findings define the molecular basis of HCV N3/4A protease inhibitor resistance and provide potential strategies for designing robust therapies against this rapidly evolving virus.     

Bacterial Neuraminidase Rescues Influenza Virus Replication from Inhibition by a Neuraminidase Inhibitor

Influenza virus neuraminidase (NA) cleaves terminal sialic acid residues on oligosaccharide chains that are receptors for virus binding, thus playing an important role in the release of virions from infected cells to promote the spread of cell-to-cell infection. In addition, NA plays a role at the initial stage of viral infection in the respiratory tract by degrading hemagglutination inhibitors in body fluid which competitively inhibit receptor binding of the virus. Current first line anti-influenza drugs are viral NA-specific inhibitors, which do not inhibit bacterial neuraminidases. Since neuraminidase producing bacteria have been isolated from oral and upper respiratory commensal bacterial flora, we posited that bacterial neuraminidases could decrease the antiviral effectiveness of NA inhibitor drugs in respiratory organs when viral NA is inhibited. Using in vitro models of infection, we aimed to clarify the effects of bacterial neuraminidases on influenza virus infection in the presence of the NA inhibitor drug zanamivir. We found that zanamivir reduced progeny virus yield to less than 2% of that in its absence, however the yield was restored almost entirely by the exogenous addition of bacterial neuraminidase from Streptococcus pneumoniae. Furthermore, cell-to-cell infection was severely inhibited by zanamivir but restored by the addition of bacterial neuraminidase. Next we examined the effects of bacterial neuraminidase on hemagglutination inhibition and infectivity neutralization activities of human saliva in the presence of zanamivir. We found that the drug enhanced both inhibitory activities of saliva, while the addition of bacterial neuraminidase diminished this enhancement. Altogether, our results showed that bacterial neuraminidases functioned as the predominant NA when viral NA was inhibited to promote the spread of infection and to inactivate the neutralization activity of saliva. We propose that neuraminidase from bacterial flora in patients may reduce the efficacy of NA inhibitor drugs during influenza virus infection. (295 words).     

Cell Type Mediated Resistance of Vesicular Stomatitis Virus and Sendai Virus to Ribavirin

Ribavirin (RBV) is a synthetic nucleoside analog with broad spectrum antiviral activity. Although RBV is approved for the treatment of hepatitis C virus, respiratory syncytial virus, and Lassa fever virus infections, its mechanism of action and therapeutic efficacy remains highly controversial. Recent reports show that the development of cell-based resistance after continuous RBV treatment via decreased RBV uptake can greatly limit its efficacy. Here, we examined whether certain cell types are naturally resistant to RBV even without prior drug exposure. Seven different cell lines from various host species were compared for RBV antiviral activity against two nonsegmented negative-strand RNA viruses, vesicular stomatitis virus (VSV, a rhabdovirus) and Sendai virus (SeV, a paramyxovirus). Our results show striking differences between cell types in their response to RBV, ranging from virtually no antiviral effect to very effective inhibition of viral replication. Despite differences in viral replication kinetics for VSV and SeV in the seven cell lines, the observed pattern of RBV resistance was very similar for both viruses, suggesting that cellular rather than viral determinants play a major role in this resistance. While none of the tested cell lines was defective in RBV uptake, dramatic variations were observed in the long-term accumulation of RBV in different cell types, and it correlated with the antiviral efficacy of RBV. While addition of guanosine neutralized RBV only in cells already highly resistant to RBV, actinomycin D almost completely reversed the RBV effect (but not uptake) in all cell lines. Together, our data suggest that RBV may inhibit the same virus via different mechanisms in different cell types depending on the intracellular RBV metabolism. Our results strongly point out the importance of using multiple cell lines of different origin when antiviral efficacy and potency are examined for new as well as established drugs in vitro.     

Success of prophylactic antiviral therapy for SARS-CoV-2: Predicted critical efficacies and impact of different drug-specific mechanisms of action

Repurposed drugs that are safe and immediately available constitute a first line of defense against new viral infections. Despite limited antiviral activity against SARS-CoV-2, several drugs are being tested as medication or as prophylaxis to prevent infection. Using a stochastic model of early phase infection, we evaluate the success of prophylactic treatment with different drug types to prevent viral infection. We find that there exists a critical efficacy that a treatment must reach in order to block viral establishment. Treatment by a combination of drugs reduces the critical efficacy, most effectively by the combination of a drug blocking viral entry into cells and a drug increasing viral clearance. Below the critical efficacy, the risk of infection can nonetheless be reduced. Drugs blocking viral entry into cells or enhancing viral clearance reduce the risk of infection more than drugs that reduce viral production in infected cells. The larger the initial inoculum of infectious virus, the less likely is prevention of an infection. In our model, we find that as long as the viral inoculum is smaller than 10 infectious virus particles, viral infection can be prevented almost certainly with drugs of 90% efficacy (or more). Even when a viral infection cannot be prevented, antivirals delay the time to detectable viral loads. The largest delay of viral infection is achieved by drugs reducing viral production in infected cells. A delay of virus infection flattens the within-host viral dynamic curve, possibly reducing transmission and symptom severity. Thus, antiviral prophylaxis, even with reduced efficacy, could be efficiently used to prevent or alleviate infection in people at high risk.     

Reversal of the Progression of Fatal Coronavirus Infection in Cats by a Broad-Spectrum Coronavirus Protease Inhibitor

Coronaviruses infect animals and humans causing a wide range of diseases. The diversity of coronaviruses in many mammalian species is contributed by relatively high mutation and recombination rates during replication. This dynamic nature of coronaviruses may facilitate cross-species transmission and shifts in tissue or cell tropism in a host, resulting in substantial change in virulence. Feline enteric coronavirus (FECV) causes inapparent or mild enteritis in cats, but a highly fatal disease, called feline infectious peritonitis (FIP), can arise through mutation of FECV to FIP virus (FIPV). The pathogenesis of FIP is intimately associated with immune responses and involves depletion of T cells, features shared by some other coronaviruses like Severe Acute Respiratory Syndrome Coronavirus. The increasing risks of highly virulent coronavirus infections in humans or animals call for effective antiviral drugs, but no such measures are yet available. Previously, we have reported the inhibitors that target 3C-like protease (3CLpro) with broad-spectrum activity against important human and animal coronaviruses. Here, we evaluated the therapeutic efficacy of our 3CLpro inhibitor in laboratory cats with FIP. Experimental FIP is 100% fatal once certain clinical and laboratory signs become apparent. We found that antiviral treatment led to full recovery of cats when treatment was started at a stage of disease that would be otherwise fatal if left untreated. Antiviral treatment was associated with a rapid improvement in fever, ascites, lymphopenia and gross signs of illness and cats returned to normal health within 20 days or less of treatment. Significant reduction in viral titers was also observed in cats. These results indicate that continuous virus replication is required for progression of immune-mediated inflammatory disease of FIP. These findings may provide important insights into devising therapeutic strategies and selection of antiviral compounds for further development for important coronaviruses in animals and humans.     

Self-Interest versus Group-Interest in Antiviral Control

Antiviral agents have been hailed to hold considerable promise for the treatment and prevention of emerging viral diseases like H5N1 avian influenza and SARS. However, antiviral drugs are not completely harmless, and the conditions under which individuals are willing to participate in a large-scale antiviral drug treatment program are as yet unknown. We provide population dynamical and game theoretical analyses of large-scale prophylactic antiviral treatment programs. Throughout we compare the antiviral control strategy that is optimal from the public health perspective with the control strategy that would evolve if individuals make their own, rational decisions. To this end we investigate the conditions under which a large-scale antiviral control program can prevent an epidemic, and we analyze at what point in an unfolding epidemic the risk of infection starts to outweigh the cost of antiviral treatment. This enables investigation of how the optimal control strategy is moulded by the efficacy of antiviral drugs, the risk of mortality by antiviral prophylaxis, and the transmissibility of the pathogen. Our analyses show that there can be a strong incentive for an individual to take less antiviral drugs than is optimal from the public health perspective. In particular, when public health asks for early and aggressive control to prevent or curb an emerging pathogen, for the individual antiviral drug treatment is attractive only when the risk of infection has become non-negligible. It is even possible that from a public health perspective a situation in which everybody takes antiviral drugs is optimal, while the process of individual choice leads to a situation where nobody is willing to take antiviral drugs.     

Antiviral effects of statins

Introducing statins as possible widely-available drugs for the treatment of viral infections requires an in depth review of their antiviral properties. Despite some inconsistency, a large body of literature data from experimental and clinical studies suggest that statins may have a role in the treatment of viral infections due to their immunomodulatory properties as well as their ability to inhibit viral replication. In the present review, the role that statins may play while interacting with the immune system during viral infections and the possible inhibitory effects of statins on different stages of virus cell cycle (i.e., from fusion with host cell membranes to extracellular release) and subsequent virus transmission are described. Specifically, cholesterol-dependent and cholesterol-independent mechanisms of the antiviral effects of statins are reported.     

Hsp90 Inhibitor 17-DMAG Decreases Expression of Conserved Herpesvirus Protein Kinases and Reduces Virus Production in Epstein-Barr Virus-Infected Cells

All eight human herpesviruses have a conserved herpesvirus protein kinase (CHPK) that is important for the lytic phase of the viral life cycle. In this study, we show that heat shock protein 90 (Hsp90) interacts directly with each of the eight CHPKs, and we demonstrate that an Hsp90 inhibitor drug, 17-dimethylaminoethylamino-17-demethoxygeldanamycin (17-DMAG), decreases expression of all eight CHPKs in transfected HeLa cells. 17-DMAG also decreases expression the of the endogenous Epstein-Barr virus protein kinase (EBV PK, encoded by the BGLF4 gene) in lytically infected EBV-positive cells and inhibits phosphorylation of several different known EBV PK target proteins. Furthermore, 17-DMAG treatment abrogates expression of the human cytomegalovirus (HCMV) kinase UL97 in HCMV-infected human fibroblasts. Importantly, 17-DMAG treatment decreased the EBV titer approximately 100-fold in lytically infected AGS-Akata cells without causing significant cellular toxicity during the same time frame. Increased EBV PK expression in 17-DMAG-treated AGS-Akata cells did not restore EBV titers, suggesting that 17-DMAG simultaneously targets multiple viral and/or cellular proteins required for efficient viral replication. These results suggest that Hsp90 inhibitors, including 17-DMAG, may be a promising group of drugs that could have profound antiviral effects on herpesviruses.