Totality of evidence of the effectiveness of repurposed therapies for COVID-19: Can we use real-world studies alongside randomized controlled trials?

Rapid and robust strategies to evaluate the efficacy and effectiveness of novel and existing pharmacotherapeutic interventions (repurposed treatments) in future pandemics are required. Observational "real-world studies" (RWS) can report more quickly than randomized controlled trials (RCTs) and would have value were they to yield reliable results. Both RCTs and RWS were deployed during the coronavirus disease 2019 (COVID-19) pandemic. Comparing results between them offers a unique opportunity to determine the potential value and contribution of each. A learning review of these parallel evidence channels in COVID-19, based on quantitative modeling, can help improve speed and reliability in the evaluation of repurposed therapeutics in a future pandemic. Analysis of all-cause mortality data from 249 observational RWS and RCTs across eight treatment regimens for COVID-19 showed that RWS yield more heterogeneous results, and generally overestimate the effect size subsequently seen in RCTs. This is explained in part by a few study factors: the presence of RWS that are imbalanced for age, gender, and disease severity, and those reporting mortality at 2 weeks or less. Smaller studies of either type contributed negligibly. Analysis of evidence generated sequentially during the pandemic indicated that larger RCTs drive our ability to make conclusive decisions regarding clinical benefit of each treatment, with limited inference drawn from RWS. These results suggest that when evaluating therapies in future pandemics, (1) large RCTs, especially platform studies, be deployed early; (2) any RWS should be large and should have adequate matching of known confounders and long follow-up; (3) reporting standards and data standards for primary endpoints, explanatory factors, and key subgroups should be improved; in addition, (4) appropriate incentives should be in place to enable access to patient-level data; and (5) an overall aggregate view of all available results should be available at any given time.

Peak plasma concentration of total and free bupivacaine after erector spinae plane and pectointercostal fascial plane blocks

PURPOSE

Erector spinae plane blocks (ESPB) and pectointercostal fascial (PIFB) plane blocks are novel interfascial blocks for which local anesthetic (LA) doses and concentrations necessary to achieve safe and effective analgesia are unknown. The goal of this prospective observational study was to provide the timing (Tmax) and concentration (Cmax) of maximum total and free plasma bupivacaine after ESPB in breast surgery and after PIFB in cardiac surgery patients.

METHODS

Erector spinae plane blocks or PIFBs (18 patients per block; total, 36 patients) were performed with 2 mg⋅kg-1 of bupivacaine with epinephrine 5 μg⋅mL-1. Our principal outcomes were the mean or median Cmax of total and free plasma bupivacaine measured 10, 20, 30, 45, 60, 90, 180, and 240 min after LA injection using liquid chromatography with tandem mass spectrometry.

RESULTS

For ESPB, the mean (standard deviation [SD]) total bupivacaine Cmax was 0.37 (0.12) μg⋅mL-1 (range, 0.19 to 0.64), and the median [interquartile range (IQR)] Tmax was 30 [50] min (range, 10-180). For ESPB, the mean (SD) free bupivacaine Cmax was 0.015 (0.017) μg⋅mL-1 (range, 0.003-0.067), and the median [IQR] Tmax was 30 [20] min (range, 10-120). After PIFB, mean plasma concentrations plateaued at 60-240 min. For PIFB, the mean (SD) total bupivacaine Cmax was 0.32 (0.21) μg⋅mL-1 (range, 0.14-0.95), with a median [IQR] Tmax of 120 [150] min (range, 30-240). For PIFB, the mean (SD) free bupivacaine Cmax was 0.019 (0.010) μg⋅mL-1 (range, 0.005-0.048), and the median [IQR] Tmax was 180 [120] min (range, 30-240). For both ESPB and PIFB, we observed no correlations between pharmacokinetic and demographic parameters.

CONCLUSION

Total and free bupivacaine Cmax observed after ESPB and PIFB with 2 mg⋅kg-1 of bupivacaine with epinephrine 5 μg⋅mL-1 were five to twenty times lower than levels considered toxic in the literature.

Model-informed drug repurposing: A pharmacometric approach to novel pathogen preparedness, response and retrospection

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.

Modeling and Simulation Analysis of Aprepitant Pharmacokinetics in Pediatric Patients With Postoperative or Chemotherapy-Induced Nausea and Vomiting

OBJECTIVES

Aprepitant is effective for the prevention of chemotherapy-induced or postoperative nausea and vomiting (CINV/PONV). The aim of this study was to develop a population pharmacokinetic (PK) model of aprepitant in pediatric patients and to support dosing recommendations for oral aprepitant in pediatric patients at risk of CINV.

METHODS

A population PK model was constructed based on data from 3 clinical studies in which children (6 months to 12 years) and adolescents (12–19 years) were treated with a 3-day regimen of oral aprepitant (capsules or suspension), with or without intravenous fosaprepitant on day 1 (CINV), or a single dose of oral aprepitant (capsules or suspension; PONV). Nonlinear mixed-effects modeling was used for model development, and a stepwise covariate search determined factors influencing PK parameters. Simulations were performed to guide final dosing strategies of aprepitant in pediatric patients.

RESULTS

The analysis included 1326 aprepitant plasma concentrations from 147 patients. Aprepitant PK was described by a 2-compartment model with linear elimination and first-order absorption, with allometric scaling for central and peripheral clearance and volume using body weight, and a cytochrome P450 3A4 maturation component for the effect of ontogeny on systemic clearance. Simulations established that application of a weight-based (for those <12 years) and fixed-dose (for those 12–17 years) dosing regimen results in comparable exposures to those observed in adults.

CONCLUSIONS

The developed population PK model adequately described aprepitant PK across a broad pediatric population, justifying fixed (adult) dosing for adolescents and weight-based dosing of oral aprepitant for children.

Phxnlme: An R package that facilitates pharmacometric workflow of Phoenix NLME analyses

BACKGROUND AND OBJECTIVE

Pharmacometric analyses are integral components of the drug development process, and Phoenix NLME is one of the popular software used to conduct such analyses. To address current limitations with model diagnostic graphics and efficiency of the workflow for this software, we developed an R package, Phxnlme, to facilitate its workflow and provide improved graphical diagnostics.

METHODS

Phxnlme was designed to provide functionality for the major tasks that are usually performed in pharmacometric analyses (i.e. nonlinear mixed effects modeling, basic model diagnostics, visual predictive checks and bootstrap). Various estimation methods for modeling using the R package are made available through the Phoenix NLME engine. The Phxnlme R package utilizes other packages such as ggplot2 and lattice to produce the graphical output, and various features were included to allow customizability of the output. Interactive features for some plots were also added using the manipulate R package.

RESULTS

Phxnlme provides enhanced capabilities for nonlinear mixed effects modeling that can be accessed using the phxnlme() command. Output from the model can be graphed to assess the adequacy of model fits and further explore relationships in the data using various functions included in this R package, such as phxplot() and phxvpc.plot(). Bootstraps, stratified up to three variables, can also be performed to obtain confidence intervals around the model estimates. With the use of an R interface, different R projects can be created to allow multi-tasking, which addresses the current limitation of the Phoenix NLME desktop software. In addition, there is a wide selection of diagnostic and exploratory plots in the Phxnlme package, with improvements in the customizability of plots, compared to Phoenix NLME.

CONCLUSIONS

The Phxnlme package is a flexible tool that allows implementation of the analytical workflow of Phoenix NLME with R, with features for greater overall efficiency and improved customizable graphics. Phxnlme is freely available for download on the CRAN repository (https://cran.r-project.org/web/packages/Phxnlme/).

Meropenem in children receiving continuous renal replacement therapy: clinical trial simulations using realistic covariates

Meropenem is frequently prescribed in children receiving continuous renal replacement therapy (CRRT). Fluid overload is often present in critically ill children and affects drug disposition. The purpose of this study was to develop a pharmacokinetic model to (1) evaluate target attainment of meropenem dosing regimens against P. aeruginosa in children receiving CRRT and (2) estimate the effect of fluid overload on target attainment. Clinical trial simulations were employed to evaluate target attainment of meropenem in various age groups and degrees of fluid overload in children receiving CRRT. Pharmacokinetic parameters were extracted from published literature, and 287 patients from the prospective pediatric CRRT registry database provided realistic clinical covariates including patient weight, fluid overload, and CRRT prescription characteristics. Target attainment at 40% and 75% time above the minimum inhibitory concentration was evaluated. Clinical trial simulations demonstrated that children greater than 5 years of age achieved acceptable target attainment with a dosing regimen of 20 mg/kg every 12 hours. In children less than 5, however, increased dosing of 20 mg/kg every 8 hours was needed to optimize target attainment. Fluid overload did not affect target attainment. These in silico model predictions will need to be verified in vivo in children receiving meropenem and CRRT.

Safety and population pharmacokinetic analysis of intravenous acetaminophen in neonates, infants, children, and adolescents with pain or Fever

OBJECTIVES

The administration of acetaminophen via the oral and rectal routes may be contraindicated in specific clinical settings. Intravenous administration provides an alternative route for fever reduction and analgesia. This phase 1 study of intravenous acetaminophen (Ofirmev, Cadence Pharmaceuticals, Inc., San Diego, CA) in inpatient pediatric patients with pain or fever requiring intravenous therapy was designed to assess the safety and pharmacokinetics of repeated doses over 48 hours.

METHODS

Neonates (full-term to 28 days) received either 12.5 mg/kg every 6 hours or 15 mg/kg every 8 hours. Infants (29 days to <2 years), children (2 to <12 years) and adolescents (≥12 years) received either 12.5 mg/kg every 4 hours or 15 mg/kg every 6 hours. Both noncompartmental and population nonlinear mixed-effects modeling approaches were used. Urinary metabolite data were analyzed, and safety and tolerability were assessed.

RESULTS

Pharmacokinetic parameters of acetaminophen were estimated using a two-compartment disposition model with weight allometrically expressed on clearances and central and peripheral volumes of distribution (Vds). Postnatal age, with a maturation function, was a significant covariate on clearance. Total systemic normalized clearance was 18.4 L/hr per 70 kg, with a plateau reached at approximately 2 years. Total central and peripheral Vds of acetaminophen were 16 and 59.5 L/70 kg, respectively. The drug was well tolerated based on the incidence of adverse events. The primary and minor pathways of elimination were acetaminophen glucuronidation, sulfation, and glutathione conjugate metabolites across all age groups.

CONCLUSIONS

Intravenous acetaminophen in infants, children, and adolescents was well tolerated and achieved plasma concentrations similar to those achieved with labeled 15 mg/kg body weight doses by oral or rectal administration.