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Background: The efficacy of a single dose of pegylated interferon lambda in preventing clinical events among outpatients with acute symptomatic coronavirus disease 2019 (Covid-19) is unclear. Methods: We conducted a randomized, controlled, adaptive platform trial involving predominantly vaccinated adults with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Brazil and Canada. Outpatients who presented with an acute clinical condition consistent with Covid-19 within 7 days after the onset of symptoms received either pegylated interferon lambda (single subcutaneous injection, 180 μg) or placebo (single injection or oral). The primary composite outcome was hospitalization (or transfer to a tertiary hospital) or an emergency department visit (observation for >6 hours) due to Covid-19 within 28 days after randomization. Results: A total of 933 patients were assigned to receive pegylated interferon lambda (2 were subsequently excluded owing to protocol deviations) and 1018 were assigned to receive placebo. Overall, 83% of the patients had been vaccinated, and during the trial, multiple SARS-CoV-2 variants had emerged. A total of 25 of 931 patients (2.7%) in the interferon group had a primary-outcome event, as compared with 57 of 1018 (5.6%) in the placebo group, a difference of 51% (relative risk, 0.49; 95% Bayesian credible interval, 0.30 to 0.76; posterior probability of superiority to placebo, >99.9%). Results: were generally consistent in analyses of secondary outcomes, including time to hospitalization for Covid-19 (hazard ratio, 0.57; 95% Bayesian credible interval, 0.33 to 0.95) and Covid-19-related hospitalization or death (hazard ratio, 0.59; 95% Bayesian credible interval, 0.35 to 0.97). The effects were consistent across dominant variants and independent of vaccination status. Among patients with a high viral load at baseline, those who received pegylated interferon lambda had lower viral loads by day 7 than those who received placebo. The incidence of adverse events was similar in the two groups. Conclusions: Among predominantly vaccinated outpatients with Covid-19, the incidence of hospitalization or an emergency department visit (observation for >6 hours) was significantly lower among those who received a single dose of pegylated interferon lambda than among those who received placebo.

Model-informed drug development (MIDD) has a long and rich history in infectious diseases. This review describes foundational principles of translational anti-infective pharmacology, including choice of appropriate measures of exposure and pharmacodynamic (PD) measures, patient subpopulations, and drug-drug interactions. Examples are presented for state-of-the-art, empiric, mechanistic, interdisciplinary, and real-world evidence MIDD applications in the development of antibacterials (review of minimum inhibitory concentration-based models, mechanism-based pharmacokinetic/PD (PK/PD) models, PK/PD models of resistance, and immune response), antifungals, antivirals, drugs for the treatment of global health infectious diseases, and medical countermeasures. The degree of adoption of MIDD practices across the infectious diseases field is also summarized. The future application of MIDD in infectious diseases will progress along two planes; "depth" and "breadth" of MIDD methods. "MIDD depth" refers to deeper incorporation of the specific pathogen biology and intrinsic and acquired-resistance mechanisms; host factors, such as immunologic response and infection site, to enable deeper interrogation of pharmacological impact on pathogen clearance; clinical outcome and emergence of resistance from a pathogen; and patient and population perspective. In particular, improved early assessment of the emergence of resistance potential will become a greater focus in MIDD, as this is poorly mitigated by current development approaches. "MIDD breadth" refers to greater adoption of model-centered approaches to anti-infective development. Specifically, this means how various MIDD approaches and translational tools can be integrated or connected in a systematic way that supports decision making by key stakeholders (sponsors, regulators, and payers) across the entire development pathway.

The efficacy and safety of hydroxychloroquine (HCQ) for the prevention and treatment of COVID-19 has received great attention, and most notably, the enthusiasm for HCQ has been one of politicization rather than science. Laboratory studies and case series published early in the pandemic supported its efficacy. The scientific community raced to conduct observational and randomized evaluations of the drug in all stages of the disease, including prophylaxis, early treatment, and advanced disease. Yet a divisive media response affected recruitment, funding, and subsequent enthusiasm for continuing scientific investigations. Of the more than 300 HCQ trials registered, fewer than 50% report having recruited any patients, and most trials might fail to achieve any useful portions of their intended sample size. Multiple observational studies and two large randomized trials have demonstrated HCQ does not offer efficacy against COVID-19 in hospitalized patients. Prophylaxis studies and early treatment studies provided heterogeneous results and are plagued by low event rates and poor study outcome monitoring. Emerging high-quality evaluations of prophylaxis and early treatment do not support a role for HCQ in these populations. The story of HCQ for COVID-19 has followed a pattern of initial enthusiasm supported by poor quality evidence, followed by disappointment based on more rigorous evaluations. The experience of HCQ in the COVID-19 era calls for the depoliticization of science away from media glare.

Alison Dillman,1 Michael J Zoratti,2 Jay JH Park,3 Grace Hsu,2 Louis Dron,2 Gerald Smith,2 Ofir Harari,2 Craig R Rayner,4 Noor-E Zannat,2 Alind Gupta,2 Eric Mackay,5 Paul Arora,6 Zelyn Lee,7 Edward J Mills2 1School of Public Health, Faculty of Medicine, Imperial College London, London, England; 2Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada; 3Department of Experimental Medicine, University of British Columbia, Vancouver, British Columbia, Canada; 4Monash Institute of Pharmaceutical Sciences, Monash University, Melbourne, Australia; 5Department of Statistical Sciences, University of Toronto, Toronto, Canada; 6Dalla Lana School of Public Health, University of Toronto, Toronto, Canada; 7Department of Physiology & Department of Neuroscience, University of Toronto, Toronto, CanadaCorrespondence: Jay JH Park Tel +1 604 294-3823Email jayhpark1@alumni.ubc.caPurpose: A multitude of randomized controlled trials (RCTs) have emerged in response to the novel coronavirus disease (COVID-19) pandemic. Understanding the distribution of trials among various settings is important to guide future research priorities and efforts. The purpose of this review was to describe the emerging evidence base of COVID-19 RCTs by stages of disease progression, from pre-exposure to hospitalization.Methods: We collated trial data across international registries: ClinicalTrials.gov; International Standard Randomised Controlled Trial Number Registry; Chinese Clinical Trial Registry; Clinical Research Information Service; EU Clinical Trials Register; Iranian Registry of Clinical Trials; Japan Primary Registries Network; German Clinical Trials Register (up to 7 October 2020). Active COVID-19 RCTs in international registries were eligible for inclusion. We extracted trial status, intervention(s), control, sample size, and clinical context to generate descriptive frequencies, network diagram illustrations, and statistical analyses including odds ratios and the Mann–Whitney U-test.Results: Our search identified 11503 clinical trials registered for COVID-19 and identified 2388 RCTs. After excluding 45 suspended RCTs and 480 trials with unclear or unreported disease stages, 1863 active RCTs were included and categorized into four broad disease stages: pre-exposure (n=107); post-exposure (n=208); outpatient treatment (n=266); hospitalization, including the intensive care unit (n=1376). Across all disease stages, most trials had two arms (n=1500/1863, 80.52%), most often included (hydroxy)chloroquine (n=271/1863, 14.55%) and were US-based (n=408/1863, 21.90%). US-based trials had lower odds of including (hydroxy)chloroquine than trials in other countries (OR: 0.63, 95% CI: 0.45– 0.90) and similar odds of having two arms compared to other geographic regions (OR: 1.05, 95% CI: 0.80– 1.38).Conclusion: There is a marked difference in the number of trials across settings, with limited studies on non-hospitalized persons. Focus on pre- and post-exposure, and outpatients, is worthwhile as a means of reducing infections and lessening the health, social, and economic burden of COVID-19.Keywords: COVID-19, novel coronavirus 2019, systematic review, randomized controlled trials

The efficacy of ivermectin in preventing hospitalization or extended observation in an emergency setting among outpatients with acutely symptomatic coronavirus disease 2019 (Covid-19), the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is unclear.We conducted a double-blind, randomized, placebo-controlled, adaptive platform trial involving symptomatic SARS-CoV-2-positive adults recruited from 12 public health clinics in Brazil. Patients who had had symptoms of Covid-19 for up to 7 days and had at least one risk factor for disease progression were randomly assigned to receive ivermectin (400 μg per kilogram of body weight) once daily for 3 days or placebo. (The trial also involved other interventions that are not reported here.) The primary composite outcome was hospitalization due to Covid-19 within 28 days after randomization or an emergency department visit due to clinical worsening of Covid-19 (defined as the participant remaining under observation for6 hours) within 28 days after randomization.A total of 3515 patients were randomly assigned to receive ivermectin (679 patients), placebo (679), or another intervention (2157). Overall, 100 patients (14.7%) in the ivermectin group had a primary-outcome event, as compared with 111 (16.3%) in the placebo group (relative risk, 0.90; 95% Bayesian credible interval, 0.70 to 1.16). Of the 211 primary-outcome events, 171 (81.0%) were hospital admissions. Findings were similar to the primary analysis in a modified intention-to-treat analysis that included only patients who received at least one dose of ivermectin or placebo (relative risk, 0.89; 95% Bayesian credible interval, 0.69 to 1.15) and in a per-protocol analysis that included only patients who reported 100% adherence to the assigned regimen (relative risk, 0.94; 95% Bayesian credible interval, 0.67 to 1.35). There were no significant effects of ivermectin use on secondary outcomes or adverse events.Treatment with ivermectin did not result in a lower incidence of medical admission to a hospital due to progression of Covid-19 or of prolonged emergency department observation among outpatients with an early diagnosis of Covid-19. (Funded by FastGrants and the Rainwater Charitable Foundation; TOGETHER ClinicalTrials.gov number, NCT04727424.).

Summary Background Recent evidence indicates a potential therapeutic role of fluvoxamine for COVID-19. In the TOGETHER trial for acutely symptomatic patients with COVID-19, we aimed to assess the efficacy of fluvoxamine versus placebo in preventing hospitalisation defined as either retention in a COVID-19 emergency setting or transfer to a tertiary hospital due to COVID-19. Methods This placebo-controlled, randomised, adaptive platform trial done among high-risk symptomatic Brazilian adults confirmed positive for SARS-CoV-2 included eligible patients from 11 clinical sites in Brazil with a known risk factor for progression to severe disease. Patients were randomly assigned (1:1) to either fluvoxamine (100 mg twice daily for 10 days) or placebo (or other treatment groups not reported here). The trial team, site staff, and patients were masked to treatment allocation. Our primary outcome was a composite endpoint of hospitalisation defined as either retention in a COVID-19 emergency setting or transfer to tertiary hospital due to COVID-19 up to 28 days post-random assignment on the basis of intention to treat. Modified intention to treat explored patients receiving at least 24 h of treatment before a primary outcome event and per-protocol analysis explored patients with a high level adherence (>80%). We used a Bayesian analytic framework to establish the effects along with probability of success of intervention compared with placebo. The trial is registered at ClinicalTrials.gov (NCT04727424) and is ongoing. Findings The study team screened 9803 potential participants for this trial. The trial was initiated on June 2, 2020, with the current protocol reporting randomisation to fluvoxamine from Jan 20 to Aug 5, 2021, when the trial arms were stopped for superiority. 741 patients were allocated to fluvoxamine and 756 to placebo. The average age of participants was 50 years (range 18–102 years); 58% were female. The proportion of patients observed in a COVID-19 emergency setting for more than 6 h or transferred to a teritary hospital due to COVID-19 was lower for the fluvoxamine group compared with placebo (79 [11%] of 741 vs 119 [16%] of 756); relative risk [RR] 0·68; 95% Bayesian credible interval [95% BCI]: 0·52–0·88), with a probability of superiority of 99·8% surpassing the prespecified superiority threshold of 97·6% (risk difference 5·0%). Of the composite primary outcome events, 87% were hospitalisations. Findings for the primary outcome were similar for the modified intention-to-treat analysis (RR 0·69, 95% BCI 0·53–0·90) and larger in the per-protocol analysis (RR 0·34, 95% BCI, 0·21–0·54). There were 17 deaths in the fluvoxamine group and 25 deaths in the placebo group in the primary intention-to-treat analysis (odds ratio [OR] 0·68, 95% CI: 0·36–1·27). There was one death in the fluvoxamine group and 12 in the placebo group for the per-protocol population (OR 0·09; 95% CI 0·01–0·47). We found no significant differences in number of treatment emergent adverse events among patients in the fluvoxamine and placebo groups. Interpretation Treatment with fluvoxamine (100 mg twice daily for 10 days) among high-risk outpatients with early diagnosed COVID-19 reduced the need for hospitalisation defined as retention in a COVID-19 emergency setting or transfer to a tertiary hospital. Funding FastGrants and The Rainwater Charitable Foundation. Translation For the Portuguese translation of the abstract see Supplementary Materials section.

The global response to finding therapeutics for coronavirus disease 2019 (COVID-19) is chaotic even if well intentioned. There is an opportunity, but more importantly, an obligation for the global clinical and quantitative pharmacology community to come together and use our state-of-the-art tools and expertise to help society accelerate therapeutics to fight COVID-19. This brief commentary is a call to action and highlights how the global pharmacology community should contribute to the COVID-19 pandemic and prepare for future pandemics.

Summary COVID-19 has had negative repercussions on the entire global population. Despite there being a common goal that should have unified resources and efforts, there have been an overwhelmingly large number of clinical trials that have been registered that are of questionable methodological quality. As the final paper of this Series, we discuss how the medical research community has responded to COVID-19. We recognise the incredible pressure that this pandemic has put on researchers, regulators, and policy makers, all of whom were doing their best to move quickly but safely in a time of tremendous uncertainty. However, the research community's response to the COVID-19 pandemic has prominently highlighted many fundamental issues that exist in clinical trial research under the current system and its incentive structures. The COVID-19 pandemic has not only re-emphasised the importance of well designed randomised clinical trials but also highlighted the need for large-scale clinical trials structured according to a master protocol in a coordinated and collaborative manner. There is also a need for structures and incentives to enable faster data sharing of anonymised datasets, and a need to provide similar opportunities to those in high-income countries for clinical trial research in low-resource regions where clinical trial research receives considerably less research funding.

During a pandemic caused by a novel pathogen (NP), drug repurposing offers the potential of a rapid treatment response via a repurposed drug (RD) while more targeted treatments are developed. Five steps of model-informed drug repurposing (MIDR) are discussed: (i) utilize RD product label and in vitro NP data to determine initial proof of potential, (ii) optimize potential posology using clinical pharmacokinetics (PK) considering both efficacy and safety, (iii) link events in the viral life cycle to RD PK, (iv) link RD PK to clinical and virologic outcomes, and optimize clinical trial design, and (v) assess RD treatment effects from trials using model-based meta-analysis. Activities which fall under these five steps are categorized into three stages: what can be accomplished prior to an NP emergence (preparatory stage), during the NP pandemic (responsive stage) and once the crisis has subsided (retrospective stage). MIDR allows for extraction of a greater amount of information from emerging data and integration of disparate data into actionable insight.

Antivirals have demonstrated efficacy in treating other infectious diseases in early stages of disease, reducing morbidity, mortality, and the likelihood of onward transmission. At the time of writing, more than 1900 clinical trials are registered globally to assess the efficacy and safety of candidate therapeutics for COVID-19. The majority of these trials are designed to evaluate the comparative efficacy and safety of candidate therapeutics for the treatment of COVID-19 to prevent death among populations of hospitalized patients with advanced disease. Yet, emerging epidemiological evidence now indicates that the majority of those infected with the SARS-CoV-2, while still infectious, experience minimal or mild disease symptomology. Like HIV and hepatitis C that pioneered treatment as prevention, there is a missed opportunity for trials of early pharmaceutical intervention for COVID-19 disease evaluating not only reductions in morbidity and mortality but also transmissibility. We discuss this clinical research gap within an historical context of viral treatment as prevention for HIV and hepatitis C, and comment on the challenges and opportunities for clinical research of candidate therapeutics for early COVID-19 disease.

As the global COVID-19 pandemic continues, unabated and clinical trials demonstrate limited effective pharmaceutical interventions, there is a pressing need to accelerate treatment evaluations. Among options for accelerated development is the evaluation of drug combinations in the absence of prior monotherapy data. This approach is appealing for a number of reasons. First, combining two or more drugs with related or complementary therapeutic effects permits a multipronged approach addressing the variable pathways of the disease. Second, if an individual component of a combination offers a therapeutic effect, then in the absence of antagonism, a trial of combination therapy should still detect individual efficacy. Third, this strategy is time saving. Rather than taking a stepwise approach to evaluating monotherapies, this strategy begins with testing all relevant therapeutic options. Finally, given the severity of the current pandemic and the absence of treatment options, the likelihood of detecting a treatment effect with combination therapy maintains scientific enthusiasm for evaluating repurposed treatments. Antiviral combination selection can be facilitated by insights regarding SARS-CoV-2 pathophysiology and cell cycle dynamics, supported by infectious disease and clinical pharmacology expert advice. We describe a clinical evaluation strategy using adaptive combination platform trials to rapidly test combination therapies to treat COVID-19.

Tafenoquine [TQ] exhibited EC50/90s of ~ 2.6/5.1 μM against SARS-CoV-2 in VERO E6 cells and was 4-fold more potent than hydroxychloroquine [HCQ]. Time-of-addition experiments were consistent with a different mechanism for TQ v HCQ. Physiologically based pharmacokinetic (PBPK) modeling suggested that lung unbound concentrations of TQ in COVID-19 patients may exceed the EC90 for at least 8 weeks after administration. The therapeutic potential for TQ in management of COVID-19 should be further evaluated.

Aim: We hypothesize that the efficacy of COVID-19 therapeutic candidates will be better predicted by understanding their effects at various points on a viral cell cycle, in particular, the specific rate constants, and that drugs acting independently of these specific discrete sites may not yield expected efficacy. We hypothesize that drugs, or combinations of drugs that act at specific multiple sites on the viral life cycle have the highest probability of success in the treatment of early infection phase in COVID-19 patients. Methods: Using a target cell limited model structure that had been used to characterize viral load dynamics from COVID-19 patients, we performed simulations to show that combinations of therapeutics targeting specific rate constants have greater probability of efficacy and supportive rationale for clinical trial evaluation. Results: Based on the known kinetics of the SARS-CoV-2 life cycle, we rank ordered potential targeted approaches involving repurposed, low-potency agents. We suggest that targeting multiple points central to viral replication within infected host cells or release from those cells is a viable strategy for reducing both viral load and host cell infection. In addition, we observed that the time-window opportunity for a therapeutic intervention to effect duration of viral shedding exceeds the effect on sparing epithelial cells from infection or impact on viral load AUC. Furthermore, the impact on reduction on duration of shedding may extend further in patients who exhibit a prolonged shedder phenotype. Conclusions: Our work highlights the use of model-informed tools to better rationalize effective treatments for COVID-19.

Summary: Background: Observational studies have postulated a therapeutic role of metformin in treating COVID-19. We conducted an adaptive platform clinical trial to determine whether metformin is an effective treatment for high-risk patients with early COVID-19 in an outpatient setting. Methods: The TOGETHER Trial is a placebo-controled, randomized, platform clinical trial conducted in Brazil. Eligible participants were symptomatic adults with a positive antigen test for SARS-CoV-2. We enroled eligible patients over the age of 50 years or with a known risk factor for disease severity. Patients were randomly assigned to receive either placebo or metformin (750 mg twice daily for 10 days or placebo, twice daily for 10 days). The primary outcome was hospitalization defined as either retention in a COVID-19 emergency setting for > 6 h or transfer to tertiary hospital due to COVID-19 at 28 days post randomization. Secondary outcomes included viral clearance at day 7, time to hospitalization, mortality, and adverse drug reactions. We used a Bayesian framework to determine probability of success of the intervention compared to placebo. Findings: The TOGETHER Trial was initiated June 2, 2020. We randomized patients to metformin starting January 15, 2021. On April 3, 2021, the Data and Safety Monitoring Committee recommended stopping enrollment into the metformin arm due to futility. We recruited 418 participants, 215 were randomized to the metformin arm and 203 to the placebo arm. More than half of participants (56.0%) were over the age of 50 years and 57.2% were female. Median age was 52 years. The proportion of patients with the primary outcome at 28 days was not different between the metformin and placebo group (relative risk [RR] 1.14[95% Credible Interval 0.73; 1.81]), probability of superiority 0.28. We found no significant differences between the metformin and placebo group on viral clearance through to day 7 (Odds ratio [OR], 0.99, 95% Confidence Intervals 0.88–1.11) or other secondary outcomes. Interpretation: In this randomized trial, metformin did not provide any clinical benefit to ambulatory patients with COVID-19 compared to placebo, with respect to reducing the need for retention in an emergency setting or hospitalization due to worsening COVID-19. There were also no differences between metformin and placebo observed for other secondary clinical outcomes.

Model-informed precision dosing (MIPD) is biosimulation in healthcare to predict the drug dose for a given patient based on their individual characteristics that is most likely to improve efficacy and/or lower toxicity compared with traditional dosing. Despite widespread use of biosimulation in drug development, MIPD has not been adopted beyond academic-hospital centers. A reason for this is that MIPD requires more supporting evidence in the language that everyday doctors understand-evidence-based medicine. In this commentary, codevelopment of companion MIPD tools during drug development is advocated as a way to accelerate the generation of the evidence required for broader clinical implementation of MIPD. Such tools have the potential to evolve into "dynamic" prescribing information that could guide dose selection for complex patients.

Potential effects on cardiac repolarization of single doses of moxidectin, a potent long-acting macrocyclic lactone endectocide, were assessed in a concentration-QT (c-QT; exposure-response) study. This double-blind, placebo-controlled, parallel-group study in healthy male volunteers (n = 60) randomized subjects to a single oral dose of moxidectin (4 mg, 8 mg, 16 mg, 24 mg, or 36 mg) or matching placebo. Serial plasma samples for pharmacokinetic (PK) analysis and concurrent triplicate electrocardiogram measurements were taken at baseline and 14 prespecified time points over 72 hours, yielding 900 QT interval-plasma concentration time-matched pairs. Moxidectin had no statistically significant or clinically relevant impact on QT interval at any dose level. The primary mixed effects model analysis revealed no treatment-related impact on the Fridericia-corrected QT interval-plasma concentration gradient (-0.0077, 90% confidence interval (CI) -0.0255 to +0.0101).

Background: There remains a need for an effective and affordable outpatient treatment for early COVID-19. Multiple repurposed drugs have shown promise in treating COVID-19. We describe a master protocol that will assess the efficacy of different repurposed drugs as treatments for early COVID-19 among outpatients at a high risk for severe complications. Methods: The TOGETHER Trial is a multi-center platform adaptive randomized, placebo-controlled, clinical trial. Patients are included if they are at least 18 years of age, have a positive antigen test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and have an indication for high risk of disease severity, including co-morbidities, older age, or high body mass index. Eligible patients are randomized with equal chance to an investigational product (IP) or to placebo.The primary endpoint is hospitalization defined as either retention in a COVID-19 emergency setting for greater than 6 hours or transfer to tertiary hospital due to COVID-19. Secondary outcomes include mortality, adverse events, adherence, and viral clearance. Scheduled interim analyses are conducted and reviewed by the Data and Safety Monitoring Committee (DSMC), who make recommendations on continuing or stopping each IP. The platform adaptive design go-no-go decision rules are extended to dynamically incorporate external evidence on COVID-19 interventions from ongoing independent randomized clinical trials. Discussion: Results from this trial will assist in the identification of therapeutics for the treatment of early diagnosed COVID-19. The novel methodological extension of the platform adaptive design to dynamically incorporate external evidence is one of the first of its kind and may provide highly valuable information for all COVID-19 trials going forward. Clinicaltrials.gov registration: NCT04727424 (27/01/2021)

Background: Although vaccines are currently available for coronavirus disease 2019 (COVID-19), there remains a need for an effective and affordable outpatient treatment for early COVID-19. Multiple repurposed drugs have shown promise in treating COVID-19. We describe a master protocol that will assess the efficacy of different repurposed drugs as treatments for early COVID-19 among outpatients at a high risk for severe complications. Methods: The TOGETHER Trial is an international (currently in Brazil and Africa), multi-center platform adaptive randomized, placebo-controlled, clinical trial. Patients are included if they are at least 18 years of age, have a positive antigen test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and have an indication for high risk of disease severity, including co-morbidities, older age, or high body mass index. Eligible patients are randomized with equal chance to an investigational product (IP) or to placebo. The primary endpoint is hospitalization due to clinical worsening of COVID-19 or emergency room required observation for more than 6 hours up to 28 days after randomization. Key secondary endpoints include viral clearance, clinical improvement, hospitalization for any cause, mortality for any cause, and safety and tolerability of each IP. Scheduled interim analyses are conducted and reviewed by the Data and Safety Monitoring Committee (DSMC), who make recommendations on continuing or stopping each IP. The platform adaptive design go-no-go decision rules are extended to dynamically incorporate external evidence on COVID-19 interventions from ongoing independent randomized clinical trials. Discussion: Results from this trial will assist in the identification of therapeutics for COVID-19 that can easily be scaled in low- and middle-income settings. The novel methodological extension of the platform adaptive design to dynamically incorporate external evidence is one of the first of its kind and may provide highly valuable information for all COVID-19 trials going forward. Clinicaltrials.gov registration: NCT04727424 (27/01/2021)

Aims A modular interdisciplinary platform was developed to investigate the economic impact of oseltamivir treatment by dosage regimen under simulated influenza pandemic scenarios. Methods The pharmacology module consisted of a pharmacokinetic distribution of oseltamivir carboxylate daily area under the concentration–time curve at steady state (simulated for 75 mg and 150 mg twice daily regimens for 5 days) and a pharmacodynamic distribution of viral shedding duration obtained from phase II influenza inoculation data. The epidemiological module comprised a susceptible, exposed, infected, recovered (SEIR) model to which drug effect on the basic reproductive number (R0), a measure of transmissibility, was linked by reduction of viral shedding duration. The number of infected patients per population of 100 000 susceptible individuals was simulated for a series of pandemic scenarios, varying oseltamivir dose, R0 (1.9 vs. 2.7), and drug uptake (25%, 50%, and 80%). The number of infected patients for each scenario was entered into the health economics module, a decision analytic model populated with branch probabilities, disease utility, costs of hospitalized patients developing complications, and case-fatality rates. Change in quality-adjusted life years was determined relative to base case. Results Oseltamivir 75 mg relative to no treatment reduced the median number of infected patients, increased change in quality-adjusted life years by deaths averted, and was cost-saving under all scenarios; 150 mg relative to 75 mg was not cost effective in low transmissibility scenarios but was cost saving in high transmissibility scenarios. Conclusion This methodological study demonstrates proof of concept that the disciplines of pharmacology, disease epidemiology and health economics can be linked in a single quantitative framework.

CITATION: Park, J. J. H. et al. 2020. Clinical trials of disease stages in COVID 19 : complicated and often misinterpreted. Lancet Global Health, 8(10):e1249-e1250, doi:10.1016/S2214-109X(20)30365-X.

In the Original Publication of the article, Copyright license type was erroneously published.

Simulation models are used widely in pharmacology, epidemiology and health economics (HEs). However, there have been no attempts to incorporate models from these disciplines into a single integrated model. Accordingly, we explored this linkage to evaluate the epidemiological and economic impact of oseltamivir dose optimisation in supporting pandemic influenza planning in the USA. An HE decision analytic model was linked to a pharmacokinetic/pharmacodynamics (PK/PD) – dynamic transmission model simulating the impact of pandemic influenza with low virulence and low transmissibility and, high virulence and high transmissibility. The cost-utility analysis was from the payer and societal perspectives, comparing oseltamivir 75 and 150 mg twice daily (BID) to no treatment over a 1-year time horizon. Model parameters were derived from published studies. Outcomes were measured as cost per quality-adjusted life year (QALY) gained. Sensitivity analyses were performed to examine the integrated model's robustness. Under both pandemic scenarios, compared to no treatment, the use of oseltamivir 75 or 150 mg BID led to a significant reduction of influenza episodes and influenza-related deaths, translating to substantial savings of QALYs. Overall drug costs were offset by the reduction of both direct and indirect costs, making these two interventions cost-saving from both perspectives. The results were sensitive to the proportion of inpatient presentation at the emergency visit and patients’ quality of life. Integrating PK/PD–EPI/HE models is achievable. Whilst further refinement of this novel linkage model to more closely mimic the reality is needed, the current study has generated useful insights to support influenza pandemic planning.

End-stage renal disease (ESRD) patients receiving hemodialysis (HD) are at heightened risk for influenza, but the optimal oseltamivir dosage regimen for treating or preventing influenza in this high-risk population is still uncertain. Pharmacokinetic data for 24 adults with ESRD were pooled from a single-dose and a multiple-dose study to develop a population pharmacokinetic model using nonlinear mixed-effects modeling. The final model comprised five compartments, two each to describe the systemic pharmacokinetics of oseltamivir phosphate and its metabolite, oseltamivir carboxylate (OC), and a delay compartment to describe oseltamivir metabolism. Estimated OC clearance in the model was markedly faster during HD sessions (7.43 liters/min) than at other times (0.19 liter/min). Model simulations showed that 30 mg oseltamivir given after every HD session is the most suitable regimen for influenza treatment, producing trough OC concentrations above the median value achieved with the 75-mg twice-daily regimen in patients with normal renal function and peak concentrations below the highest oseltamivir exposures known to be well tolerated (median exposures after twice-daily dosing of 450 mg). Administration of the first dose following diagnosis of influenza need not wait until after the next HD session: addition of a single 30-mg dose during the 12 h before the next HD session raises OC exposures quickly without posing any safety risk. Further simulation showed that 30 mg oseltamivir given after every other HD session is the most suitable regimen for influenza prophylaxis.

Availability of lower-dose oseltamivir capsules, an increased pharmacokinetic database, and a desire to align drug exposure across the spectrum of renal function prompted reassessment of oral dosing in patients with renal impairment. The data set comprised 128 subjects (71 with varying degrees of renal impairment) from 8 studies, which included single and multiple doses of 20-1000 mg. Pharmacokinetic profiles of oseltamivir phosphate (OP) and oseltamivir carboxylate (OC) were modeled simultaneously in NONMEM. Exposure metrics of OP and OC (AUC48 h , Cmax , Cmin ) after administration of various dosing regimens were simulated for renal impairment subgroups and compared with exposures in patients with normal renal function receiving approved regimens. For influenza treatment, 30 mg once-daily and twice-daily regimens were selected for severe and moderate impairment, respectively. These regimens provided OC exposures similar or above those of the approved 75-mg twice-daily treatment regimen in subjects with normal renal function. For influenza prophylaxis, 30 mg once every other day and once-daily regimens were selected for severe and moderate impairment, respectively. No dosing adjustments were required for mild impairment. This analysis supported revised labeling in the United States and Europe for oral oseltamivir dosing in patients with moderate and severe renal impairment.

This work characterizes the pharmacokinetics (PK) of oseltamivir phosphate (OP) and its active metabolite, oseltamivir carboxylate (OC), and investigates oseltamivir i.v. dosing regimens for treatment of influenza in patients with normal renal function and with various degrees of renal impairment. Initially, data collected from 149 subjects with normal renal function and mild to severe renal impairment who were administered 40-200 mg oseltamivir i.v. were described by a four-compartment model. Two compartments described OP, one compartment described OC and one compartment described OP to OC metabolism. Then, data of 128 subjects administered 20-1,000 mg oseltamivir orally were added. The absorp- tion model included three first-order processes with direct (via first-pass) input in the OC compartment and two (di- rect and delayed) inputs in the OP compartment. Simula- tions and PK bridging were used to recommend i.v. dosing regimens. The analysis demonstrated that renal function had a major effect on OC clearance (CLM) and exposure. CLM for subjects with mild, moderate and severe renal impairment was 18, 50, and 84 % lower than for subjects with normal renal function. Simulations were used to select i.v. dosing regimens that provide OC Cmin coverage and exposures comparable to those achieved in subjects with normal renal function administered 75 mg b.i.d. orally. The oseltamivir dose depended on the degree of renal impair- ment and was independent of route of administration. Specifically, 75 mg b.i.d. is recommended for subjects with normal renal function or mild renal impairment, 30 mg b.i.d. for subjects with moderate renal impairment, and 30 mg q.d. for subjects with severe renal impairment. Recommended i.v. doses were the same as those recom- mended for oral administration in corresponding renal impairment groups.

AIMS Patients with end-stage renal disease (ESRD) are at increased risk of developing complications associated with influenza infection. Oseltamivir is indicated for influenza treatment in ESRD patients, but the disposition is poorly understood in this patient population. This study aimed to characterize the pharmacokinetics and tolerability of oseltamivir in automated peritoneal dialysis (APD) and construct a pharmacokinetic model to assist with optimized dosing.

OBJECTIVES Hypermutable bacteria are causing a drastic problem via their enhanced ability to become resistant. Our objectives were to compare bacterial killing and resistance emergence between differently shaped tobramycin concentration-time profiles at a given fAUC/MIC, and determine the tobramycin exposure durations that prevent resistance. METHODS Static concentration time-kill studies over 24 h used Pseudomonas aeruginosa WT strains (ATCC 27853 and PAO1) and hypermutable PAOΔmutS. fAUC/MIC values of 36, 72 and 168 were assessed at initial inocula of 106 and 104 cfu/mL (all strains) and 101.2 cfu/mL (PAOΔmutS only) in duplicate. Tobramycin was added at 0 h and removed at 1, 4, 10 or 24 h. Proportions of resistant bacteria and MICs were determined at 24 h. Mechanism-based modelling was conducted. RESULTS For all strains, high tobramycin concentrations over 1 and 4 h resulted in more rapid and extensive initial killing compared with 10 and 24 h exposures at a given fAUC/MIC. No resistance emerged for 1 and 4 h durations of exposure, although extensive regrowth of susceptible bacteria occurred. The 24 h duration of exposure revealed less regrowth, but tobramycin-resistant populations had completely replaced susceptible bacteria by 24 h for the 106 cfu/mL inoculum. The hypermutable PAOΔmutS showed the highest numbers of resistant bacteria. Total and resistant bacterial counts were described well by novel mechanism-based modelling. CONCLUSIONS Extensive resistance emerged for 10 and 24 h durations of exposure, but not for shorter durations. The tobramycin concentration-time profile shape is vital for resistance prevention and should aid the introduction of optimized combination regimens.

A modular interdisciplinary platform was developed to investigate the economic impact of oseltamivir treatment by dosage regimen under simulated influenza pandemic scenarios.The pharmacology module consisted of a pharmacokinetic distribution of oseltamivir carboxylate daily area under the concentration-time curve at steady state (simulated for 75 mg and 150 mg twice daily regimens for 5 days) and a pharmacodynamic distribution of viral shedding duration obtained from phase II influenza inoculation data. The epidemiological module comprised a susceptible, exposed, infected, recovered (SEIR) model to which drug effect on the basic reproductive number (ROseltamivir 75 mg relative to no treatment reduced the median number of infected patients, increased change in quality-adjusted life years by deaths averted, and was cost-saving under all scenarios; 150 mg relative to 75 mg was not cost effective in low transmissibility scenarios but was cost saving in high transmissibility scenarios.This methodological study demonstrates proof of concept that the disciplines of pharmacology, disease epidemiology and health economics can be linked in a single quantitative framework.

A population drug-disease model was developed to describe the time course of influenza virus with and without oseltamivir treatment and to investigate opportunities for antiviral combination therapy. Data included viral titers from 208 subjects, across 4 studies, receiving placebo and oseltamivir at 20 to 200 mg twice daily for 5 days. A 3-compartment mathematical model, comprising target cells infected at rate β, free virus produced at rate p and cleared at rate c , and infected cells cleared at rate δ, was implemented in NONMEM with an inhibitory Hill function on virus production ( p ), accounting for the oseltamivir effect. In congruence with clinical data, the model predicts that the standard 75-mg regimen initiated 2 days after infection decreased viral shedding duration by 1.5 days versus placebo; the 150-mg regimen decreased shedding by an additional average 0.25 day. The model also predicts that initiation of oseltamivir sooner postinfection, specifically at day 0.5 or 1, results in proportionally greater decreases in viral shedding duration of 5 and 3.5 days, respectively. Furthermore, the model suggests that combining oseltamivir (acting to subdue virus production rate) with an antiviral whose activity decreases viral infectivity (β) results in a moderate additive effect dependent on therapy initiation time. In contrast, the combination of oseltamivir with an antiviral whose activity increases viral clearance ( c ) shows significant additive effects independent of therapy initiation time. The utility of the model for investigating the pharmacodynamic effects of novel antivirals alone or in combination on emergent influenza virus strains warrants further investigation.

Volume 59, no. 9, p. [5388–5395][1], 2015. Page 5391, Table 2: It was brought to our attention that there was an inadvertent error in reporting the residual error term (σerror, Table 2) in our model. The minor error is isolated and has no impact on the stated objectives of the paper, the

The ferret is a suitable small animal model for preclinical evaluation of efficacy of antiviral drugs against various influenza strains, including highly pathogenic H5N1 viruses. Rigorous pharmacokinetics/pharmacodynamics (PK/PD) assessment of ferret data has not been conducted, perhaps due to insufficient information on oseltamivir PK. Here, based on PK data from several studies on both uninfected and influenza-infected groups (i.e., with influenza A viruses of H5N1 and H3N2 subtypes and an influenza B virus) and several types of anesthesia we developed a population PK model for the active compound oseltamivir carboxylate (OC) in the ferret. The ferret OC population PK model incorporated delayed first-order input, two-compartment distribution, and first-order elimination to successfully describe OC PK. Influenza infection did not affect model parameters, but anesthesia did. The conclusion that OC PK was not influenced by influenza infection must be viewed with caution because the influenza infections in the studies included here resulted in mild clinical symptoms in terms of temperature, body weight, and activity scores. Monte Carlo simulations were used to determine that administration of a 5.08 mg/kg dose of oseltamivir phosphate to ferret every 12 h for 5 days results in the same median OC area under the plasma concentration-time curve 0-12 h (i.e., 3220 mg h/mL) as that observed in humans during steady state at the approved dose of 75 mg twice daily for 5 days. Modeling indicated that PK variability for OC in the ferret model is high, and can be affected by anesthesia. Therefore, for proper interpretation of PK/PD data, sparse PK sampling to allow the OC PK determination in individual animals is important. Another consideration in appropriate design of PK/PD studies is achieving an influenza infection with pronounced clinical symptoms and efficient virus replication, which will allow adequate evaluation of drug effects.