Favipiravir, lopinavir-ritonavir, or combination therapy (FLARE): A randomised, double-blind, 2 × 2 factorial placebo-controlled trial of early antiviral therapy in COVID-19.

BACKGROUND: Early antiviral treatment is effective for Coronavirus Disease 2019 (COVID-19) but currently available agents are expensive. Favipiravir is routinely used in many countries, but efficacy is unproven. Antiviral combinations have not been systematically studied. We aimed to evaluate the effect of favipiravir, lopinavir-ritonavir or the combination of both agents on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) viral load trajectory when administered early. METHODS AND FINDINGS: We conducted a Phase 2, proof of principle, randomised, placebo-controlled, 2 × 2 factorial, double-blind trial of ambulatory outpatients with early COVID-19 (within 7 days of symptom onset) at 2 sites in the United Kingdom. Participants were randomised using a centralised online process to receive: favipiravir (1,800 mg twice daily on Day 1 followed by 400 mg 4 times daily on Days 2 to 7) plus lopinavir-ritonavir (400 mg/100 mg twice daily on Day 1, followed by 200 mg/50 mg 4 times daily on Days 2 to 7), favipiravir plus lopinavir-ritonavir placebo, lopinavir-ritonavir plus favipiravir placebo, or both placebos. The primary outcome was SARS-CoV-2 viral load at Day 5, accounting for baseline viral load. Between 6 October 2020 and 4 November 2021, we recruited 240 participants. For the favipiravir+lopinavir-ritonavir, favipiravir+placebo, lopinavir-ritonavir+placebo, and placebo-only arms, we recruited 61, 59, 60, and 60 participants and analysed 55, 56, 55, and 58 participants, respectively, who provided viral load measures at Day 1 and Day 5. In the primary analysis, the mean viral load in the favipiravir+placebo arm had changed by -0.57 log10 (95% CI -1.21 to 0.07, p = 0.08) and in the lopinavir-ritonavir+placebo arm by -0.18 log10 (95% CI -0.82 to 0.46, p = 0.58) compared to the placebo arm at Day 5. There was no significant interaction between favipiravir and lopinavir-ritonavir (interaction coefficient term: 0.59 log10, 95% CI -0.32 to 1.50, p = 0.20). More participants had undetectable virus at Day 5 in the favipiravir+placebo arm compared to placebo only (46.3% versus 26.9%, odds ratio (OR): 2.47, 95% CI 1.08 to 5.65; p = 0.03). Adverse events were observed more frequently with lopinavir-ritonavir, mainly gastrointestinal disturbance. Favipiravir drug levels were lower in the combination arm than the favipiravir monotherapy arm, possibly due to poor absorption. The major limitation was that the study population was relatively young and healthy compared to those most affected by the COVID-19 pandemic. CONCLUSIONS: At the current doses, no treatment significantly reduced viral load in the primary analysis. Favipiravir requires further evaluation with consideration of dose escalation. Lopinavir-ritonavir administration was associated with lower plasma favipiravir concentrations. TRIAL REGISTRATION: Clinicaltrials.gov NCT04499677 EudraCT: 2020-002106-68.

Comparative assessment of viral dynamic models for SARS-CoV-2 for pharmacodynamic assessment in early treatment trials.

Pharmacometric analyses of time series viral load data may detect drug effects with greater power than approaches using single time points. Because SARS-CoV-2 viral load rapidly rises and then falls, viral dynamic models have been used. We compared different modelling approaches when analysing Phase II-type viral dynamic data. Using two SARS-CoV-2 datasets of viral load starting within 7 days of symptoms, we fitted the slope-intercept exponential decay (SI), reduced target cell limited (rTCL), target cell limited (TCL) and TCL with eclipse phase (TCLE) models using nlmixr. Model performance was assessed via Bayesian information criterion (BIC), visual predictive checks (VPCs), goodness-of-fit plots, and parameter precision. The most complex (TCLE) model had the highest BIC for both datasets. The estimated viral decline rate was similar for all models except the TCL model for dataset A with a higher rate (median [range] day-1 : dataset A; 0.63 [0.56-1.84]; dataset B: 0.81 [0.74-0.85]). Our findings suggest simple models should be considered during pharmacodynamic model development.

Randomized controlled trial of molnupiravir SARS-CoV-2 viral and antibody response in at-risk adult outpatients.

Viral clearance, antibody response and the mutagenic effect of molnupiravir has not been elucidated in at-risk populations. Non-hospitalised participants within 5 days of SARS-CoV-2 symptoms randomised to receive molnupiravir (n = 253) or Usual Care (n = 324) were recruited to study viral and antibody dynamics and the effect of molnupiravir on viral whole genome sequence from 1437 viral genomes. Molnupiravir accelerates viral load decline, but virus is detectable by Day 5 in most cases. At Day 14 (9 days post-treatment), molnupiravir is associated with significantly higher viral persistence and significantly lower anti-SARS-CoV-2 spike antibody titres compared to Usual Care. Serial sequencing reveals increased mutagenesis with molnupiravir treatment. Persistence of detectable viral RNA at Day 14 in the molnupiravir group is associated with higher transition mutations following treatment cessation. Viral viability at Day 14 is similar in both groups with post-molnupiravir treated samples cultured up to 9 days post cessation of treatment. The current 5-day molnupiravir course is too short. Longer courses should be tested to reduce the risk of potentially transmissible molnupiravir-mutated variants being generated. Trial registration: ISRCTN30448031.

SARS-CoV-2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapy.

Mathematical models of viral dynamics have been reported to describe adequately the dynamic changes of severe acute respiratory syndrome-coronavirus 2 viral load within an individual host. In this study, eight published viral dynamic models were assessed, and model selection was performed. Viral load data were collected from a community surveillance study, including 2155 measurements from 162 patients (124 household and 38 non-household contacts). An extended version of the target-cell limited model that includes an eclipse phase and an immune response component that enhances viral clearance described best the data. In general, the parameter estimates showed good precision (relative standard error <10), apart from the death rate of infected cells. The parameter estimates were used to simulate the outcomes of a clinical trial of the antiviral tixagevimab-cilgavimab, a monoclonal antibody combination which blocks infection of the target cells by neutralizing the virus. The simulated outcome of the effectiveness of the antiviral therapy in controlling viral replication was in a good agreement with the clinical trial data. Early treatment with high antiviral efficacy is important for desired therapeutic outcome.

Ceftolozane/tazobactam plus tobramycin against free-floating and biofilm bacteria of hypermutable Pseudomonas aeruginosa epidemic strains: Resistance mechanisms and synergistic activity.

OBJECTIVE: Acute exacerbations of biofilm-associated Pseudomonas aeruginosa infections in cystic fibrosis (CF) have limited treatment options. Ceftolozane/tazobactam (alone and with a second antibiotic) has not yet been investigated against hypermutable clinical P. aeruginosa isolates in biofilm growth. This study aimed to evaluate, using an in vitro dynamic biofilm model, ceftolozane/tazobactam alone and in combination with tobramycin at simulated representative lung fluid pharmacokinetics against free-floating (planktonic) and biofilm states of two hypermutable P. aeruginosa epidemic strains (LES-1 and CC274) from adolescents with CF. METHODS: Regimens were intravenous ceftolozane/tazobactam 4.5 g/day continuous infusion, inhaled tobramycin 300 mg 12-hourly, intravenous tobramycin 10 mg/kg 24-hourly, and both ceftolozane/tazobactam-tobramycin combinations. The isolates were susceptible to both antibiotics. Total and less-susceptible free-floating and biofilm bacteria were quantified over 120-168 h. Ceftolozane/tazobactam resistance mechanisms were investigated by whole-genome sequencing. Mechanism-based modelling of bacterial viable counts was performed. RESULTS: Monotherapies of ceftolozane/tazobactam and tobramycin did not sufficiently suppress emergence of less-susceptible subpopulations, although inhaled tobramycin was more effective than intravenous tobramycin. Ceftolozane/tazobactam resistance development was associated with classical (AmpC overexpression plus structural modification) and novel (CpxR mutations) mechanisms depending on the strain. Against both isolates, combination regimens demonstrated synergy and completely suppressed the emergence of ceftolozane/tazobactam and tobramycin less-susceptible free-floating and biofilm bacterial subpopulations. CONCLUSION: Mechanism-based modelling incorporating subpopulation and mechanistic synergy well described the antibacterial effects of all regimens against free-floating and biofilm bacterial states. These findings support further investigation of ceftolozane/tazobactam in combination with tobramycin against biofilm-associated P. aeruginosa infections in adolescents with CF.

Evaluation of Meropenem-Ciprofloxacin Combination Dosage Regimens for the Pharmacokinetics of Critically Ill Patients With Augmented Renal Clearance.

Augmented renal clearance (ARC, creatinine clearance > 130 mL/minute) makes difficult achievement of effective concentrations of renally cleared antibiotics in critically ill patients. This study examined the synergistic killing and resistance suppression for meropenem-ciprofloxacin combination dosage regimens against Pseudomonas aeruginosa isolates within the context of ARC. Clinically relevant meropenem and ciprofloxacin concentrations, alone and in combinations, were studied against three clinical isolates with a range of susceptibilities to each of the antibiotics. Isolate Pa1280 was susceptible to both meropenem and ciprofloxacin, Pa1284 had intermediate susceptibility to meropenem and was susceptible to ciprofloxacin, and CR380 was resistant to meropenem and had intermediate susceptibility to ciprofloxacin. Initially, isolates were studied in 72-hour static-concentration time-kill (SCTK) studies. Subsequently, the pharmacokinetic profiles expected in patients with ARC receiving dosage regimens, including at the highest approved daily doses (meropenem 6 g daily divided and administered as 0.5-hour infusions every 8 hours, or as a continuous infusion; ciprofloxacin 0.4 g as 1-hour infusions every 8 hours), were examined in a dynamic hollow-fiber infection model (HFIM) over 7-10 days. In both SCTK and HFIM, combination regimens were generally synergistic and suppressed growth of less-susceptible subpopulations, these effects being smaller for isolate CR380. The time-courses of total and less-susceptible bacterial populations in the HFIM were well-described by mechanism-based models, which enabled conduct of Monte Carlo simulations to predict likely effectiveness of approved dosage regimens at different creatinine clearances. Optimized meropenem-ciprofloxacin combination dosage regimens may be a viable consideration for P. aeruginosa infections in critically ill patients with ARC.

A systematic review and meta-analysis of treatment outcomes following antibiotic therapy among patients with carbapenem-resistant Klebsiella pneumoniae infections.

INTRODUCTION: Carbapenem-resistant Klebsiella pneumoniae (CRKP) infections are a major global public health challenge. This study aimed to systematically review the evidence on treatment outcomes (mortality, clinical and microbiological response) following antibiotic therapy administered for CRKP infections. METHODS: Medline, EMBASE, the Cochrane Central Register of Controlled Trials, and the International Pharmaceutical Abstracts databases were searched from inception to 26 December 2018. Data were analysed via meta-analysis techniques using random-effects (DerSimonian and Laird) modelling. RESULTS: Fifty-four observational studies involving 3195 CRKP-infected patients who received antibiotic treatment were included. The pooled mortality, clinical and microbiological response rates were 37.2% (95% confidence interval [CI] 33.1-41.4%), 69.0% (95% CI 60.1-78.2%) and 63.7% (95% CI 53.7-74.1%), respectively. Compared with combination therapy, monotherapy was associated with a higher likelihood of mortality (odds ratio [OR] 1.45, 95% CI 1.18-1.78%), but there were no statistically significant differences in the likelihood of achieving clinical and microbiological responses. There were no statistically significant differences in the pooled likelihood of mortality, clinical or microbiological responses between two-drug and three-or-more-drug combination therapies or combination-containing and combination-sparing regimens of polymyxins, tigecycline, aminoglycosides and carbapenems. Moreover, clinical outcomes did not significantly differ among the various monotherapies. CONCLUSIONS: These data highlight the need for systematic studies and well-designed randomised clinical trials to identify and evaluate the most appropriate antibiotic therapies for CRKP infections towards informing clinical decision-making. Furthermore, continuous surveillance of antimicrobial susceptibility patterns at local, regional, and national/international levels are important to support empirically-based therapy until susceptibility results for the isolate from the patient are available.

Mortality, clinical and microbiological response following antibiotic therapy among patients with carbapenem-resistant Klebsiella pneumoniae infections (a meta-analysis dataset).

This meta-analysis was conducted to assess mortality, clinical and microbiological response following antibiotic therapy among patients with carbapenem-resistant Klebsiella pneumoniae (CRKP) infections. Fifty-four observational studies involving 3195 CRKP-infected patients who received antibiotic treatment were included. We found combination therapy to be associated with lower mortality than monotherapy, but no differences in clinical and microbiological response. Among the various combination therapies, no significant differences in mortality, clinical and microbiological response were found. Moreover, clinical outcomes did not differ significantly among various monotherapies. This report describes the data related to the article entitled: "A systematic review and meta-analysis of treatment outcomes following antibiotic therapy among patients with carbapenem-resistant Klebsiella pneumoniae infections".