Quantifying antiviral activity optimizes drug combinations against hepatitis C virus infection

Broad-spectrum antiviral strategy: Host-targeting antivirals against emerging and re-emerging viruses

Viral infections are amongst the most prevalent diseases that pose a significant threat to human health. Targeting viral proteins or host factors represents two primary strategies for the development of antiviral drugs. In contrast to virus-targeting antivirals (VTAs), host-targeting antivirals (HTAs) offer advantages in terms of overcoming drug resistance and effectively combating a wide range of viruses, including newly emerging ones. Therefore, targeting host factors emerges as an extremely promising strategy with the potential to address critical challenges faced by VTAs. In recent years, extensive research has been conducted on the discovery and development of HTAs, leading to the approval of maraviroc, a chemokine receptor type 5 (CCR5) antagonist used for the treatment of HIV-1 infected individuals, with several other potential treatments in various stages of development for different viral infections. This review systematically summarizes advancements made in medicinal chemistry regarding various host targets and classifies them into four distinct catagories based on their involvement in the viral life cycle: virus attachment and entry, biosynthesis, nuclear import and export, and viral release.

Mathematical Modeling of Virus-Mediated Syncytia Formation: Past Successes and Future Directions

Many viruses have the ability to cause cells to fuse into large multi-nucleated cells, known as syncytia. While the existence of syncytia has long been known and its importance in helping spread viral infection within a host has been understood, few mathematical models have incorporated syncytia formation or examined its role in viral dynamics. This review examines mathematical models that have incorporated virus-mediated cell fusion and the insights they have provided on how syncytia can change the time course of an infection. While the modeling efforts are limited, they show promise in helping us understand the consequences of syncytia formation if future modeling efforts can be coupled with appropriate experimental efforts to help validate the models.

A viral RNA-dependent RNA polymerase inhibitor VV116 broadly inhibits human coronaviruses and has synergistic potency with 3CLpro inhibitor nirmatrelvir

During the ongoing pandemic, providing treatment consisting of effective, low-cost oral antiviral drugs at an early stage of SARS-CoV-2 infection has been a priority for controlling COVID-19. Although Paxlovid and molnupiravir have received emergency approval from the FDA, some side effect concerns have emerged, and the possible oral agents are still limited, resulting in optimized drug development becoming an urgent requirement. An oral remdesivir derivative, VV116, has been reported to have promising antiviral effects against SARS-CoV-2 and positive therapeutic outcomes in clinical trials. However, whether VV116 has broad-spectrum anti-coronavirus activity and potential synergy with other drugs is not clear. Here, we uncovered the broad-spectrum antiviral potency of VV116 against SARS-CoV-2 variants of concern (VOCs), HCoV-OC43, and HCoV-229E in various cell lines. In vitro drug combination screening targeted RdRp and proteinase, highlighting the synergistic effect of VV116 and nirmatrelvir on HCoV-OC43 and SARS-CoV-2. When co-administrated with ritonavir, the combination of VV116 and nirmatrelvir showed significantly enhanced antiviral potency with noninteracting pharmacokinetic properties in mice. Our findings will facilitate clinical treatment with VV116 or VV116+nirmatrelvir combination to fight coronavirus infection.

Modelling how increased Cathepsin B/L and decreased TMPRSS2 usage for cell entry by the SARS-CoV-2 Omicron variant may affect the efficacy and synergy of TMPRSS2 and Cathepsin B/L inhibitors

The SARS-CoV-2 Omicron variant harbours many mutations in its spike protein compared to the original SARS-CoV-2 strain, which may alter its ability to enter cells, cell tropism, and response to interventions blocking virus entry. To elucidate these effects, we developed a mathematical model of SARS-CoV-2 entry into target cells and applied it to analyse recent in vitro data. SARS-CoV-2 can enter cells via two pathways, one using the host proteases Cathepsin B/L and the other using the host protease TMPRSS2. We found enhanced entry efficiency of the Omicron variant in cells where the original strain preferentially used Cathepsin B/L and reduced efficiency where it used TMPRSS2. The Omicron variant thus appears to have evolved to use the Cathepsin B/L pathway better but at the expense of its ability to use the TMPRSS2 pathway compared to the original strain. We estimated >4-fold enhanced efficiency of the Omicron variant in entry via the Cathepsin B/L pathway and >3-fold reduced efficiency via the TMPRSS2 pathway compared to the original or other strains in a cell type-dependent manner. Our model predicted that Cathepsin B/L inhibitors would be more efficacious and TMPRSS2 inhibitors less efficacious in blocking Omicron variant entry into cells than the original strain. Furthermore, model predictions suggested that drugs simultaneously targeting the two pathways would exhibit synergy. The maximum synergy and drug concentrations yielding it would differ for the Omicron variant compared to the original strain. Our findings provide insights into the cell entry mechanisms of the Omicron variant and have implications for intervention targeting these mechanisms.

Potential Anti-Mpox Virus Activity of Atovaquone, Mefloquine, and Molnupiravir, and Their Potential Use as Treatments

BACKGROUND

Mpox virus (MPXV) is a zoonotic orthopoxvirus and caused an outbreak in 2022. Although tecovirimat and brincidofovir are approved as anti-smallpox drugs, their effects in mpox patients have not been well documented. In this study, by a drug repurposing approach, we identified potential drug candidates for treating mpox and predicted their clinical impacts by mathematical modeling.

METHODS

We screened 132 approved drugs using an MPXV infection cell system. We quantified antiviral activities of potential drug candidates by measuring intracellular viral DNA and analyzed the modes of action by time-of-addition assay and electron microscopic analysis. We further predicted the efficacy of drugs under clinical concentrations by mathematical simulation and examined combination treatment.

RESULTS

Atovaquone, mefloquine, and molnupiravir exhibited anti-MPXV activity, with 50% inhibitory concentrations of 0.51-5.2 μM, which was more potent than cidofovir. Whereas mefloquine was suggested to inhibit viral entry, atovaquone and molnupiravir targeted postentry processes. Atovaquone was suggested to exert its activity through inhibiting dihydroorotate dehydrogenase. Combining atovaquone with tecovirimat enhanced the anti-MPXV effect of tecovirimat. Quantitative mathematical simulations predicted that atovaquone can promote viral clearance in patients by 7 days at clinically relevant drug concentrations.

CONCLUSIONS

These data suggest that atovaquone would be a potential candidate for treating mpox.

The synergy between nucleotide biosynthesis inhibitors and antiviral nucleosides: New opportunities against viral infections?

5'-Phosphorylated nucleoside derivatives are molecules that can be found in all living organisms and viruses. Over the last century, the development of structural analogs that could disrupt the transcription and translation of genetic information culminated in the development of clinically relevant anticancer and antiviral drugs. However, clinically effective broad-spectrum antiviral compounds or treatments are lacking. This viewpoint proposes that molecules that inhibit nucleotide biosynthesis may sensitize virus-infected cells toward direct-acting antiviral nucleosides. Such potentially synergistic combinations might allow the repurposing of drugs, leading to the development of new combination therapies.

Comparative highlights on MERS-CoV, SARS-CoV-1, SARS-CoV-2, and NEO-CoV

The severe acute respiratory syndrome (SARS-CoV, now SARS-CoV-1), middle east respiratory syndrome (MERS-CoV), Neo-CoV, and 2019 novel coronavirus (SARS-CoV-2/COVID-19) are the most notable coronaviruses, infecting the number of people worldwide by targeting the respiratory system. All these viruses are of zoonotic origin, predominantly from bats which are one of the natural reservoir hosts for coronaviruses. Thus, the major goal of our review article is to compare and contrast the characteristics and attributes of these coronaviruses. The SARS-CoV-1, MERS-CoV, and COVID-19 have many viral similarities due to their classification, they are not genetically related. COVID-19 shares approximately 79 % of its genome with SARS-CoV-1 and about 50 % with MERS-CoV. The shared receptor protein, ACE2 exhibit the most striking genetic similarities between SARS-CoV-1 and SARS-CoV-2. SARS-CoV primarily replicates in the epithelial cells of the respiratory system, but it may also affect macrophages, monocytes, activated T cells, and dendritic cells. MERS-CoV not only infects and replicates inside the epithelial and immune cells, but it may lyse them too, which is one of the common reasons for MERS's higher mortality rate. The details of infections caused by SARS-CoV-2 and lytic replication mechanisms in host cells are currently mysterious. In this review article, we will discuss the comparative highlights of SARS-CoV-1, MERS-CoV, SARS-CoV-2, and Neo-CoV, concerning their structural features, morphological characteristics, sources of virus origin and their evolutionary transitions, infection mechanism, computational study approaches, pathogenesis and their severity towards several diseases, possible therapeutic approaches, and preventive measures.

Different efficacies of neutralizing antibodies and antiviral drugs on SARS-CoV-2 Omicron subvariants, BA.1 and BA.2

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron subvariant BA.2 has spread in many countries, replacing the earlier Omicron subvariant BA.1 and other variants. Here, using a cell culture infection assay, we quantified the intrinsic sensitivity of BA.2 and BA.1 compared with other variants of concern, Alpha, Gamma, and Delta, to five approved-neutralizing antibodies and antiviral drugs. Our assay revealed the diverse sensitivities of these variants to antibodies, including the loss of response of both BA.1 and BA.2 to casirivimab and of BA.1 to imdevimab. In contrast, EIDD-1931 and nirmatrelvir showed a more conserved activities to these variants. The viral response profile combined with mathematical analysis estimated differences in antiviral effects among variants in the clinical concentrations. These analyses provide essential evidence that gives insight into variant emergence's impact on choosing optimal drug treatment.

Treatment of Respiratory Viral Coinfections

With the advent of rapid multiplex PCR, physicians have been able to test for multiple viral pathogens when a patient presents with influenza-like illness. This has led to the discovery that many respiratory infections are caused by more than one virus. Antiviral treatment of viral coinfections can be complex because treatment of one virus will affect the time course of the other virus. Since effective antivirals are only available for some respiratory viruses, careful consideration needs to be given on the effect treating one virus will have on the dynamics of the other virus, which might not have available antiviral treatment. In this study, we use mathematical models of viral coinfections to assess the effect of antiviral treatment on coinfections. We examine the effect of the mechanism of action, relative growth rates of the viruses, and the assumptions underlying the interaction of the viruses. We find that high antiviral efficacy is needed to suppress both infections. If high doses of both antivirals are not achieved, then we run the risk of lengthening the duration of coinfection or even of allowing a suppressed virus to replicate to higher viral titers.

Preclinical characterization of an intravenous coronavirus 3CL protease inhibitor for the potential treatment of COVID19

COVID-19 caused by the SARS-CoV-2 virus has become a global pandemic. 3CL protease is a virally encoded protein that is essential across a broad spectrum of coronaviruses with no close human analogs. PF-00835231, a 3CL protease inhibitor, has exhibited potent in vitro antiviral activity against SARS-CoV-2 as a single agent. Here we report, the design and characterization of a phosphate prodrug PF-07304814 to enable the delivery and projected sustained systemic exposure in human of PF-00835231 to inhibit coronavirus family 3CL protease activity with selectivity over human host protease targets. Furthermore, we show that PF-00835231 has additive/synergistic activity in combination with remdesivir. We present the ADME, safety, in vitro, and in vivo antiviral activity data that supports the clinical evaluation of PF-07304814 as a potential COVID-19 treatment.

Low Inducibility of Latent Human Immunodeficiency Virus Type 1 Proviruses as a Major Barrier to Cure

The latent reservoir for human immunodeficiency virus type 1 (HIV-1) in resting CD4+ T cells is a major barrier to cure. The dimensions of the reservoir problem can be defined with 2 assays. A definitive minimal estimate of the frequency of latently infected cells is provided by the quantitative viral outgrowth assay (QVOA), which detects cells that can be induced by T-cell activation to release infectious virus. In contrast, the intact proviral DNA assay (IPDA) detects all genetically intact proviruses and provides a more accurate upper limit on reservoir size than standard single-amplicon polymerase chain reaction assays which mainly detect defective proviruses. The frequency of cells capable of initiating viral rebound on interruption of antiretroviral therapy lies between the values produced by the QVOA and the IPDA. We argue here that the 1-2-log difference between QVOA and IPDA values in part reflects that the fact that many replication-competent proviruses are not readily induced by T-cell activation. Findings of earlier studies suggest that latently infected cells can be activated to proliferate in vivo without expressing viral genes. The proliferating cells nevertheless retain the ability to produce virus on subsequent stimulation. The low inducibility of latent proviruses is a major problem for the shock-and-kill strategy for curing HIV-1 infection, which uses latency-reversing agents to induce viral gene expression and render infected cells susceptible to immune clearance. The latency-reversing agents developed to date are much less effective at reversing latency than T-cell activation. Taken together, these results indicate that HIV-1 eradication will require the discovery of much more effective ways to induce viral gene expression.

The optimization of combinatorial drug therapies: Strategies and laboratorial platforms

Designing optimal combinatorial drug therapies is challenging, because the drug interactions depend not only on the drugs involved, but also on their doses. With recent advances, combinatorial drug therapy is closer than ever to clinical application. Herein, we summarize approaches and advances over the past decade for identifying and optimizing drug combination therapies, with innovations across research fields, covering physical laboratory platforms for combination screening to computational models and algorithms designed for synergism prediction and optimization. By comparing different types of approach, we detail a three-step workflow that could maximize the overall optimization efficiency, thus enabling the application of personalized optimization of combinatorial drug therapy.

Drugs repurposed for COVID-19 by virtual screening of 6,218 drugs and cell-based assay

Recent spread of SARS-CoV-2 has sparked significant health concerns of emerging infectious viruses. Drug repurposing is a tangible strategy for developing antiviral agents within a short period. In general, drug repurposing starts with virtual screening of approved drugs employing docking simulations. However, the actual hit rate is low, and most of the predicted compounds are false positives. To tackle the challenges, we report advanced virtual screening with pre- and postdocking pharmacophore filtering of 6,218 drugs for COVID-19. Notably, 7 out of 38 compounds showed efficacies in inhibiting SARS-CoV-2 in Vero cells. Three of these were also found to inhibit SARS-CoV-2 in human Calu-3 cells. Furthermore, three drug combinations showed strong synergistic effects in SARS-CoV-2 inhibition at their clinically achievable concentrations.

The COVID-19 pandemic caused by SARS-CoV-2 is an unprecedentedly significant health threat, prompting the need for rapidly developing antiviral drugs for the treatment. Drug repurposing is currently one of the most tangible options for rapidly developing drugs for emerging and reemerging viruses. In general, drug repurposing starts with virtual screening of approved drugs employing various computational methods. However, the actual hit rate of virtual screening is very low, and most of the predicted compounds are false positives. Here, we developed a strategy for virtual screening with much reduced false positives through incorporating predocking filtering based on shape similarity and postdocking filtering based on interaction similarity. We applied this advanced virtual screening approach to repurpose 6,218 approved and clinical trial drugs for COVID-19. All 6,218 compounds were screened against main protease and RNA-dependent RNA polymerase of SARS-CoV-2, resulting in 15 and 23 potential repurposed drugs, respectively. Among them, seven compounds can inhibit SARS-CoV-2 replication in Vero cells. Three of these drugs, emodin, omipalisib, and tipifarnib, show anti-SARS-CoV-2 activities in human lung cells, Calu-3. Notably, the activity of omipalisib is 200-fold higher than that of remdesivir in Calu-3. Furthermore, three drug combinations, omipalisib/remdesivir, tipifarnib/omipalisib, and tipifarnib/remdesivir, show strong synergistic effects in inhibiting SARS-CoV-2. Such drug combination therapy improves antiviral efficacy in SARS-CoV-2 infection and reduces the risk of each drug’s toxicity. The drug repurposing strategy reported here will be useful for rapidly developing drugs for treating COVID-19 and other viruses.

Strategy, Progress, and Challenges of Drug Repurposing for Efficient Antiviral Discovery

Emerging or re-emerging viruses are still major threats to public health. Prophylactic vaccines represent the most effective way to prevent virus infection; however, antivirals are more promising for those viruses against which vaccines are not effective enough or contemporarily unavailable. Because of the slow pace of novel antiviral discovery, the high disuse rates, and the substantial cost, repurposing of the well-characterized therapeutics, either approved or under investigation, is becoming an attractive strategy to identify the new directions to treat virus infections. In this review, we described recent progress in identifying broad-spectrum antivirals through drug repurposing. We defined the two major categories of the repurposed antivirals, direct-acting repurposed antivirals (DARA) and host-targeting repurposed antivirals (HTRA). Under each category, we summarized repurposed antivirals with potential broad-spectrum activity against a variety of viruses and discussed the possible mechanisms of action. Finally, we proposed the potential investigative directions of drug repurposing.

Mefloquine, a Potent Anti-severe Acute Respiratory Syndrome-Related Coronavirus 2 (SARS-CoV-2) Drug as an Entry Inhibitor in vitro

Coronavirus disease 2019 (COVID-19) has caused serious public health, social, and economic damage worldwide and effective drugs that prevent or cure COVID-19 are urgently needed. Approved drugs including Hydroxychloroquine, Remdesivir or Interferon were reported to inhibit the infection or propagation of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2), however, their clinical efficacies have not yet been well demonstrated. To identify drugs with higher antiviral potency, we screened approved anti-parasitic/anti-protozoal drugs and identified an anti-malarial drug, Mefloquine, which showed the highest anti-SARS-CoV-2 activity among the tested compounds. Mefloquine showed higher anti-SARS-CoV-2 activity than Hydroxychloroquine in VeroE6/TMPRSS2 and Calu-3 cells, with IC₅₀ = 1.28 μM, IC₉₀ = 2.31 μM, and IC₉₉ = 4.39 μM in VeroE6/TMPRSS2 cells. Mefloquine inhibited viral entry after viral attachment to the target cell. Combined treatment with Mefloquine and Nelfinavir, a replication inhibitor, showed synergistic antiviral activity. Our mathematical modeling based on the drug concentration in the lung predicted that Mefloquine administration at a standard treatment dosage could decline viral dynamics in patients, reduce cumulative viral load to 7% and shorten the time until virus elimination by 6.1 days. These data cumulatively underscore Mefloquine as an anti-SARS-CoV-2 entry inhibitor.

Potential anti-COVID-19 agents, cepharanthine and nelfinavir, and their usage for combination treatment

Antiviral treatments targeting the coronavirus disease 2019 are urgently required. We screened a panel of already approved drugs in a cell culture model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and identified two new agents having higher antiviral potentials than the drug candidates such as remdesivir and chroloquine in VeroE6/TMPRSS2 cells: the anti-inflammatory drug cepharanthine and human immunodeficiency virus protease inhibitor nelfinavir. Cepharanthine inhibited SARS-CoV-2 entry through the blocking of viral binding to target cells, while nelfinavir suppressed viral replication partly by protease inhibition. Consistent with their different modes of action, synergistic effect of this combined treatment to limit SARS-CoV-2 proliferation was highlighted. Mathematical modeling in vitro antiviral activity coupled with the calculated total drug concentrations in the lung predicts that nelfinavir will shorten the period until viral clearance by 4.9 days and the combining cepharanthine/nelfinavir enhanced their predicted efficacy. These results warrant further evaluation of the potential anti-SARS-CoV-2 activity of cepharanthine and nelfinavir.

A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2

The scientific community is focused on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease 2019 (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination with published viral load data, we compare within-host viral dynamics of SARS-CoV-2 with analogous dynamics of MERS-CoV and SARS-CoV. Our quantitative analyses using a mathematical model revealed that the within-host reproduction number at symptom onset of SARS-CoV-2 was statistically significantly larger than that of MERS-CoV and similar to that of SARS-CoV. In addition, the time from symptom onset to the viral load peak for SARS-CoV-2 infection was shorter than those of MERS-CoV and SARS-CoV. These findings suggest the difficulty of controlling SARS-CoV-2 infection by antivirals. We further used the viral dynamics model to predict the efficacy of potential antiviral drugs that have different modes of action. The efficacy was measured by the reduction in the viral load area under the curve (AUC). Our results indicate that therapies that block de novo infection or virus production are likely to be effective if and only if initiated before the viral load peak (which appears 2-3 days after symptom onset), but therapies that promote cytotoxicity of infected cells are likely to have effects with less sensitivity to the timing of treatment initiation. Furthermore, combining a therapy that promotes cytotoxicity and one that blocks de novo infection or virus production synergistically reduces the AUC with early treatment. Our unique modeling approach provides insights into the pathogenesis of SARS-CoV-2 and may be useful for development of antiviral therapies.

Discovery of a Novel Inhibitor of Coronavirus 3CL Protease for the Potential Treatment of COVID-19

COVID-19 caused by the SARS-CoV-2 virus has become a global pandemic. 3CL protease is a virally encoded protein that is essential across a broad spectrum of coronaviruses with no close human analogs. The designed phosphate prodrug PF-07304814 is metabolized to PF-00835321 which is a potent inhibitor in vitro of the coronavirus family 3CL pro, with selectivity over human host protease targets. Furthermore, PF-00835231 exhibits potent in vitro antiviral activity against SARS-CoV-2 as a single agent and it is additive/synergistic in combination with remdesivir. We present the ADME, safety, in vitro , and in vivo antiviral activity data that supports the clinical evaluation of this compound as a potential COVID-19 treatment.

Required concentration index quantifies effective drug combinations against hepatitis C virus infection

Successful clinical drug development requires rational design of combination treatments based on preclinical data. Anti-hepatitis C virus (HCV) drugs exhibit significant diversity in antiviral effect. Dose-response assessments can be used to determine parameters profiling the diverse antiviral effect during combination treatment. In the current study, a combined experimental and mathematical approaches were used to compare and score different combinations of anti-HCV treatments. A “required concentration index” was generated and used to rank the antiviral profile of possible double- and triple-drug combinations against HCV genotype 1b and 2a. Rankings varied based on target HCV genotype. Interestingly, multidrug (double and triple) treatment not only augmented antiviral activity, but also reduced genotype-specific efficacy, suggesting another advantage of multidrug treatment. The current study provides a quantitative method for profiling drug combinations against viral genotypes, to better inform clinical drug development.

Janus Dendrimers to Assess the Anti-HCV Activity of Molecules in Cell-Assays

The use of nanocarriers has been revealed as a valid strategy to facilitate drug bioavailability, and this allows for expanding the drug libraries for the treatment of certain diseases such as viral diseases. In the case of Hepatitis C, the compounds iopanoic acid and 3,3',5-triiodothyroacetic acid (or tiratricol) were identified in a primary screening as bioactive allosteric inhibitors of viral NS3 protease, but they did not exhibit accurate activity inhibiting viral replication in cell-based assays. In this work, dendritic nanocarriers are proposed due to their unique properties as drug delivery systems to rescue the bioactivity of these two drugs. Specifically, four different amphiphilic Janus dendrimers synthesized by combining 2,2'-bis(hydroxymethyl)propionic acid (bis-MPA) and 2,2'-bis(glyciloxy)propionic acid (bis-GMPA) functionalized with either hydrophilic or lipophilic moieties at their periphery were used to entrap iopanoic acid and tiratricol. Interestingly, differences were found in the loading efficiencies depending on the dendrimer design, which also led to morphological changes of the resulting dendrimer aggregates. The most remarkable results consist of the increased water solubility of the bioactive compounds within the dendrimers and the improved antiviral activity of some of the dendrimer/drug aggregates, considerably improving antiviral activity in comparison to the free drugs. Moreover, imaging studies have been developed in order to elucidate the mechanism of cellular internalization.

Quantifying the effect of remdesivir in rhesus macaques infected with SARS-CoV-2

The world is in the midst of a pandemic caused by a novel coronavirus and is desperately searching for possible treatments. The antiviral remdesivir has shown some effectiveness against SARS-CoV-2 in vitro and in a recent animal study. We use data from a study of remdesivir in rhesus macaques to fit a viral kinetics model in an effort to determine the most appropriate mathematical descripton of the effect of remdesivir. We find statistically significant differences in the viral decay rate and use this to inform a possible mathematical formulation of the effect of remdesivir. Unfortunately, this model formulation suggests that the application of remdesivir will lengthen SARS-CoV-2 infections, putting into question its potential clinical benefit.

Danoprevir for the Treatment of Hepatitis C Virus Infection: Design, Development, and Place in Therapy

On June 8, 2018, an NS3/4A protease inhibitor called danoprevir was approved in China to treat the infections of HCV genotype (GT) 1b – the most common HCV genotype worldwide. Based on phase 2 and 3 clinical trials, the 12-week regimen of ritonavir-boosted danoprevir (danoprevir/r) plus peginterferon alpha-2a and ribavirin offered 97.1% (200/206) of sustained virologic response at post-treatment week 12 (SVR12) in treatment-naïve non-cirrhotic patients infected with HCV genotype 1b. Adverse events such as anemia, fatigue, fever, and headache were associated with the inclusion of peginterferon alpha-2a and ribavirin in the danoprevir-based regimen. Moreover, drug resistance to danoprevir could be traced to amino acid substitutions (Q80K/R, R155K, D168A/E/H/N/T/V) near the drug-binding pocket of HCV NS3 protease. Despite its approval, the clinical use of danoprevir is currently limited to its combination with peginterferon alpha-2a and ribavirin, thereby driving its development towards interferon-free, ribavirin-free regimens with improved tolerability and adherence. In the foreseeable future, pan-genotypic direct-acting antivirals with better clinical efficacy and less adverse events will be available to treat HCV infections worldwide.

Modeling Favipiravir Antiviral Efficacy Against Emerging Viruses: From Animal Studies to Clinical Trials

In 2014, our research network was involved in the evaluation of favipiravir, an anti-influenza polymerase inhibitor, against Ebola virus. In this review, we discuss how mathematical modeling was used, first to propose a relevant dosing regimen in humans, and then to optimize its antiviral efficacy in a nonhuman primate (NHP) model. The data collected in NHPs were finally used to develop a model of Ebola pathogenesis integrating the interactions among the virus, the innate and adaptive immune response, and the action of favipiravir. We conclude the review of this work by discussing how these results are of relevance for future human studies in the context of Ebola virus, but also for other emerging viral diseases for which no therapeutics are available.

You Cannot Have Your Synergy and Efficacy Too

Synergistic drugs are preferred in combination therapies for many diseases, including viral infections and cancers. Maximizing synergy, however, may come at the cost of efficacy. This synergy-efficacy trade-off appears to be widely prevalent and independent of the specific drug interactions yielding synergy. We present examples of the trade-off in drug combinations used in hepatitis C, HIV, and cancer therapies and believe that screens for optimal drug combinations that presently seek to maximize synergy may be improved by considering the trade-off.

Interferon at the cellular, individual, and population level in hepatitis C virus infection: Its role in the interferon-free treatment era

The advent of powerful direct-acting antiviral agents (DAAs) has revolutionized the treatment of hepatitis C. DAAs cure nearly all patients with short duration, oral treatments. Significant efforts are now underway to optimize DAA-based treatments. We discuss the potential role of interferon in this optimization. Clinical studies present compelling evidence that DAAs perform better in treatment-naive individuals than in individuals who previously failed treatment with interferon, a surprising correlation because interferon and DAAs are thought to act independently. Recent mathematical models explore a mechanistic hypothesis underlying this correlation. The hypothesis invokes the action of interferon at the cellular, individual, and population levels. Strong interferon responses prevent the productive infection of cells, reduce viral replication, and impede the development of resistance to DAAs in infected individuals and improve cure rates elicited by DAAs in treated populations. The models develop descriptions of these processes, integrate them into a comprehensive framework, and capture clinical data quantitatively, providing a successful test of the hypothesis. Individuals with strong endogenous interferon responses thus present a promising subpopulation for reducing DAA treatment durations. This review discusses the conceptual advances made by the models, highlights the new insights they unravel, and examines their applicability to optimize DAA-based treatments.

A liquid chromatography-tandem mass spectrometry method for simultaneous determination of simeprevir, daclatasvir, sofosbuvir, and GS-331007 applied to a retrospective clinical pharmacological study

A highly sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated for simultaneous determination of daclatasvir (DCV), simeprevir (SMV), sofosbuvir (SOF), and its major metabolite GS-331007 in human plasma using stable-isotope-labeled (SIL) analogs as internal standards (IS) to minimize a possible matrix effect. Liquid-liquid extraction (LLE) of the analytes and IS from human plasma was performed using a commercial extraction kit requiring low sample volume (50 μL). The analytes were eluted under a gradient program with mobile phase A (water + 0.1% formic acid) and mobile phase B (methanol + 0.1% formic acid) at a flow-rate of 0.6 mL/min for 10 min. The detection was performed on a Qtrap 5500 triple quadrupole tandem-mass spectrometer using multiple reaction monitoring (MRM) mode via the positive electrospray ionization interface. The method was validated according to the European Medicine Agency (EMA) guidelines over the clinically relevant concentration range of 15.6-2000 ng/mL. The high reproducibility, the low matrix effect associated with the use of SIL-IS, and the need of small sample amounts make this method particularly suited for high-throughput routine analysis. The proposed method was successfully applied to a retrospective clinical pharmacology study involving 67 HIV/HCV co-infected patients treated with a SOF-based therapy. DCV, SMV, SOF, and GS-331007 plasma levels were measured at week 4 of treatment and compared with the patients' clinical and laboratory characteristics. Higher GS-331007 plasma concentrations were observed in female patients compared to males, which can be explained by different anthropometric characteristics between genders. Importantly, patients with high plasma levels of GS-331007 also showed enhanced concentration of DCV and SMV probably due to a specific metabolic/pathological condition. Altogether, our findings indicate that the proposed method is a reliable and accurate new tool for high-throughput screening of large patient cohorts that could be readily used to optimize treatment modalities and reduce drug-related toxicities.

Mutational pathway maps and founder effects define the within-host spectrum of hepatitis C virus mutants resistant to drugs

Knowledge of the within-host frequencies of resistance-associated amino acid variants (RAVs) is important to the identification of optimal drug combinations for the treatment of hepatitis C virus (HCV) infection. Multiple RAVs may exist in infected individuals, often below detection limits, at any resistance locus, defining the diversity of accessible resistance pathways. We developed a multiscale mathematical model to estimate the pre-treatment frequencies of the entire spectrum of mutants at chosen loci. Using a codon-level description of amino acids, we performed stochastic simulations of intracellular dynamics with every possible nucleotide variant as the infecting strain and estimated the relative infectivity of each variant and the resulting distribution of variants produced. We employed these quantities in a deterministic multi-strain model of extracellular dynamics and estimated mutant frequencies. Our predictions captured database frequencies of the RAV R155K, resistant to NS3/4A protease inhibitors, presenting a successful test of our formalism. We found that mutational pathway maps, interconnecting all viable mutants, and strong founder effects determined the mutant spectrum. The spectra were vastly different for HCV genotypes 1a and 1b, underlying their differential responses to drugs. Using a fitness landscape determined recently, we estimated that 13 amino acid variants, encoded by 44 codons, exist at the residue 93 of the NS5A protein, illustrating the massive diversity of accessible resistance pathways at specific loci. Accounting for this diversity, which our model enables, would help optimize drug combinations. Our model may be applied to describe the within-host evolution of other flaviviruses and inform vaccine design strategies.

Insight into treatment of HIV infection from viral dynamics models

The odds of living a long and healthy life with HIV infection have dramatically improved with the advent of combination antiretroviral therapy. Along with the early development and clinical trials of these drugs, and new field of research emerged called viral dynamics, which uses mathematical models to interpret and predict the time-course of viral levels during infection and how they are altered by treatment. In this review, we summarize the contributions that virus dynamics models have made to understanding the pathophysiology of infection and to designing effective therapies. This includes studies of the multiphasic decay of viral load when antiretroviral therapy is given, the evolution of drug resistance, the long-term persistence latently infected cells, and the rebound of viremia when drugs are stopped. We additionally discuss new work applying viral dynamics models to new classes of investigational treatment for HIV, including latency-reversing agents and immunotherapy.

HA1077 displays synergistic activity with daclatasvir against hepatitis C virus and suppresses the emergence of NS5A resistance-associated substitutions in mice

The kinase C-related kinase 2 (PRK2), which phosphorylates hepatitis C virus (HCV) RNA polymerase, is a proviral factor enhancing HCV replication. Here, we report on the in vivo anti-HCV efficacy of HA1077, which inhibits viral genome replication by targeting PRK2 and displays viral entry inhibitory activity by targeting Rho-associated kinase. HA1077 showed synergistic antiviral activity selectively with nonstructural protein 5 A (NS5A) inhibitors including daclatasvir (DCV). HA1077 oral administration substantially reduced serum viral loads in mice bearing HCV genotype 2a-replicating Huh7 xenografts. When administered with DCV, HA1077 potentiated the antiviral efficacy of DCV and suppressed the generation of DCV resistance-associated variants (RAVs). By deep-sequencing analysis, we uncovered an unprecedented DCV-induced polymorphism at the poly-proline motif (PxxPxxP) of NS5A. Coadministration of HA1077 reduced such a polymorphism. Overall, our results demonstrate the potential therapeutic benefit of combination therapy with HA1077 plus DCV for HCV patients carrying emerging or pre-existing RAVs toward NS5A inhibitors.

Modelling how responsiveness to interferon improves interferon-free treatment of hepatitis C virus infection

Direct-acting antiviral agents (DAAs) for hepatitis C treatment tend to fare better in individuals who are also likely to respond well to interferon-alpha (IFN), a surprising correlation given that DAAs target specific viral proteins whereas IFN triggers a generic antiviral immune response. Here, we posit a causal relationship between IFN-responsiveness and DAA treatment outcome. IFN-responsiveness restricts viral replication, which would prevent the growth of viral variants resistant to DAAs and improve treatment outcome. To test this hypothesis, we developed a multiscale mathematical model integrating IFN-responsiveness at the cellular level, viral kinetics and evolution leading to drug resistance at the individual level, and treatment outcome at the population level. Model predictions quantitatively captured data from over 50 clinical trials demonstrating poorer response to DAAs in previous non-responders to IFN than treatment-naïve individuals, presenting strong evidence supporting the hypothesis. Model predictions additionally described several unexplained clinical observations, viz., the percentages of infected individuals who 1) spontaneously clear HCV, 2) get chronically infected but respond to IFN-based therapy, and 3) fail IFN-based therapy but respond to DAA-based therapy, resulting in a comprehensive understanding of HCV infection and treatment. An implication of the causal relationship is that failure of DAA-based treatments may be averted by adding IFN, a strategy of potential use in settings with limited access to DAAs. A second, wider implication is that individuals with greater IFN-responsiveness would require shorter DAA-based treatment durations, presenting a basis and a promising population for response-guided therapy.

Targeting the Latent Reservoir for HIV-1

Antiretroviral therapy can effectively block HIV-1 replication and prevent or reverse immunodeficiency in HIV-1-infected individuals. However, viral replication resumes within weeks of treatment interruption. The major barrier to a cure is a small pool of resting memory CD4+ T cells that harbor latent HIV-1 proviruses. This latent reservoir is now the focus of an intense international research effort. We describe how the reservoir is established, challenges involved in eliminating it, and pharmacologic and immunologic strategies for targeting this reservoir. The development of a successful cure strategy will most likely require understanding the mechanisms that maintain HIV-1 proviruses in a latent state and pathways that drive the proliferation of infected cells, which slows reservoir decay. In addition, a cure will require the development of effective immunologic approaches to eliminating infected cells. There is renewed optimism about the prospect of a cure, and the interventions discussed here could pave the way.

A PDE multiscale model of hepatitis C virus infection can be transformed to a system of ODEs

Direct-acting antivirals (DAAs) treat hepatitis C virus (HCV) by targeting its intracellular viral replication. DAAs are effective and deliver high clinical performance against HCV infection, but optimization of the DAA treatment regimen is ongoing. Different classes of DAAs are currently under development, and HCV treatments that combine two or three DAAs with different action mechanisms are being improved. To accurately quantify the antiviral effect of these DAA treatments and optimize multi-drug combinations, we must describe the intracellular viral replication processes corresponding to the action mechanisms by multiscale mathematical models. Previous multiscale models of HCV treatment have been formulated by partial differential equations (PDEs). However, estimating the parameters from clinical datasets requires comprehensive numerical PDE computations that are time consuming and often converge poorly. Here, we propose a user-friendly approach that transforms a standard PDE multiscale model of HCV infection (Guedj J et al., Proc. Natl. Acad. Sci. USA 2013; 110(10):3991-6) to mathematically identical ordinary differential equations (ODEs) without any assumptions. We also confirm consistency between the numerical solutions of our transformed ODE model and the original PDE model. This relationship between a detailed structured model and a simple model is called ``model aggregation problem'' and a fundamental important in theoretical biology. In particular, as the parameters of ODEs can be estimated by already established methods, our transformed ODE model and its modified version avoid the time-consuming computations and are broadly available for further data analysis.

[Revealing the characteristics of antiviral agents]

Rapid development of novel anti-hepatitis C virus (HCV) agents in recent years has greatly improved treatment outcomes. However, such rapid progress in anti-HCV treatment has not allowed us to fully argue the different characteristics of each anti-HCV agent, optimal multidrug combinations, and the selection of treatment enabling to efficiently eliminate drug resistant viruses. We here quantified the intrinsic antiviral effect of 15 anti-HCV agents either clinically available or under developmental phase using a cell culture system, and identified the parameters that represent the antiviral profile of drugs through mathematical analysis. A computer simulation that calculated the antiviral activity and the frequency of mutation rate under dual- and triple-multidrug treatment presented the argument for the advantage of multidrug treatments. In this review, we summarize the novel approaches to evaluate intrinsic antiviral efficacy of drugs by combining the virological and mathematical analyses.

Resistance to hepatitis C virus. Implications and therapeutic options

We are currently living in an unprecedented era of hepatitis C treatment with the availability of highly effective drugs yielding minimal side effects. The problem we currently face is the retreatment of patients refractory to these drugs. Although several factors can influence treatment failure, this review focuses on antiviral resistance. Resistance-associated substitutions may be identified at baseline or be treatment-emergent. The latter seem to be more clinically relevant and must be studied in the event of treatment failure (no virological response). In this article, we present the latest data from clinical trials and studies in real-life clinical practice. Finally, based on this current evidence, we propose some recommendations for the management and retreatment of these patients.