Abstract
Background
High-dose daptomycin is increasingly used in patients with bone and joint infection (BJI). This raises concerns about a higher risk of adverse events (AEs), including ...daptomycin-induced eosinophilic pneumonia (DIEP) and myotoxicity. We aimed to examine pharmacokinetic and other potential determinants of DIEP and myotoxicity in patients with BJI receiving daptomycin.
Methods
All patients receiving daptomycin for BJI were identified in a prospective cohort study. Cases were matched at a 1:3 ratio, with controls randomly selected from the same cohort. Bayesian estimation of the daptomycin daily area under the concentration-time curve over 24 hours (AUC24h) was performed with the Monolix software based on therapeutic drug monitoring (TDM) data. Demographic and biological data were also collected. Risk factors of AEs were analyzed using Cox proportional hazards model.
Results
From 1130 patients followed over 7 years, 9 with DIEP, 26 with myotoxicity, and 106 controls were included in the final analysis. Daptomycin AUC24h, C-reactive protein, and serum protein levels were associated with the risk of AEs. The adjusted hazard ratio of DIEP or myotoxicity was 3.1 (95% confidence interval CI, 1.48–6.5; P < .001) for daptomycin AUC24h > 939 mg/h/L, 9.8 (95% CI, 3.94–24.5; P < .001) for C-reactive protein > 21.6 mg/L, and 2.4 (95% CI, 1.02–5.65; P = .04) for serum protein <72 g/L.
Conclusions
We identified common determinants of DIEP and myotoxicity in patients with BJI. Because the risk of AEs was associated with daptomycin exposure, daptomycin TDM and model-informed precision dosing may help optimize the efficacy and safety of daptomycin treatment in this setting. A target AUC24h range of 666 to 939 mg/h/L is suggested.
Initial dosing and dose adjustment of intravenous tobramycin in children with cystic fibrosis (CF) is challenging. The objectives of this study were to develop nonparametric population ...pharmacokinetic (PK) models of tobramycin in children with CF to be used for dosage design and model-guided therapeutic drug monitoring. We performed a retrospective analysis of tobramycin PK data in our children's CF center. The Pmetrics package was used for nonparametric population PK analysis and dosing simulations. Both the ratios of maximal concentration to the MIC (
/MIC) and daily area under the concentration-time curve to the MIC (AUC
/MIC) were considered efficacy targets. Trough concentration (
) was considered the safety target. A total of 2,884 tobramycin concentrations collected in 195 patients over 9 years were analyzed. A two-compartment model including total body weight, body surface area, and creatinine clearance as covariates best described the data. A simpler model was also derived for implementation in the BestDose software to perform Bayesian dose adjustment. Both models were externally validated. PK/pharmacodynamics (PD) simulations with the final model suggest that an initial dose of tobramycin of 15 to 17.5 mg/kg/day was necessary to achieve
/MICs of ≥10 for MICs up to 2 mg/liter in most patients. The AUC
/MIC target was associated with higher dosage requirements and higher
. A daily dose of 12.5 mg/kg would optimize both efficacy and safety target attainment. We recommend performing tobramycin therapeutic drug monitoring (TDM), model-based dose adjustment, and MIC determination to individualize intravenous tobramycin therapy in children with CF.
The Hill equation was first introduced by A.V. Hill to describe the equilibrium relationship between oxygen tension and the saturation of haemoglobin. In pharmacology, the Hill equation has been ...extensively used to analyse quantitative drug–receptor relationships. Many pharmacokinetic–pharmacodynamic models have used the Hill equation to describe nonlinear drug dose–response relationships. Although the Hill equation is widely used, its many properties are not all well known. This article aims at reviewing the various properties of the Hill equation. The descriptive aspects of the Hill equation, in particular mathematical and graphical properties, are examined, and related to Hill’s original work. The mechanistic aspect of the Hill equation, involving a strong connection with the Guldberg and Waage law of mass action, is also described. Finally, a probabilistic view of the Hill equation is examined. Here, we provide some new calculation results, such as Fisher information and Shannon entropy, and we introduce multivariate probabilistic Hill equations. The main features and potential applications of this probabilistic approach are also discussed. Thus, within the same formalism, the Hill equation has many different properties which can be of great interest for those interested in mathematical modelling in pharmacology and biosciences.
Population pharmacokinetics consists of analyzing pharmacokinetic (PK) data collected in groups of individuals. Population PK is widely used to guide drug development and to inform dose adjustment ...via therapeutic drug monitoring and model-informed precision dosing. There are 2 main types of population PK methods: parametric (P) and nonparametric (NP). The characteristics of P and NP population methods have been previously reviewed. The aim of this article is to answer some frequently asked questions that are often raised by scholars, clinicians, and researchers about P and NP population PK methods. The strengths and limitations of both approaches are explained, and the characteristics of the main software programs are presented. We also review the results of studies that compared the results of both approaches in the analysis of real data. This opinion article may be informative for potential users of population methods in PK and guide them in the selection and use of those tools. It also provides insights on future research in this area.
Amikacin is commonly used for probabilistic antimicrobial therapy in critically ill patients with sepsis. Its narrow therapeutic margin makes it challenging to determine the right individual dose ...that ensures the highest efficacy target attainment rate (TAR) in this setting. This study aims to develop a new initial dosing approach for amikacin by optimizing the
TAR in this population. A population pharmacokinetic model was built with a learning data set from critically ill patients who received amikacin. It was then used to design an initial dosing approach maximizing
TAR for a target ratio of ≥8 for the peak concentration to the MIC (
/MIC) or of ≥75 for the ratio of the area under the concentration-time curve from 0 to 24 h to the MIC (AUC
/MIC). In the 166 patients included, 53% had amikacin
of ≥64 mg/liter with a median dose of 23.4 mg/kg. A two-compartment model with creatinine clearance and body surface area as covariates best described the data and showed good predictive performance. Our dosing approach was successful in optimizing TAR for
/MIC, with a rate of 92.9% versus 67.9% using a 30-mg/kg regimen, based on an external subset of data and assuming a MIC of 8 mg/liter. Mean optimal doses were higher (3.5 ± 0.5 g) than with the 30-mg/kg regimen (2.1 ± 0.3 g). Suggested doses varied with the MIC, the target index, and desired TAR threshold. A dosing algorithm based on the method is proposed for a large range of patient covariates. Clinical studies are necessary to confirm efficacy and safety of this optimized dosing approach.
Since the 1950s, vancomycin has remained a reference treatment for severe infections caused by Gram-positive bacteria, including methicillin-resistant Staphylococcus aureus Vancomycin is a ...nephrotoxic and ototoxic drug mainly eliminated through the kidneys. It has a large interindividual pharmacokinetic variability, which justifies monitoring its plasma concentrations in patients. This is especially important in patients aged over 80 years, who frequently have renal impairment. However, the pharmacokinetics of vancomycin in this population is very poorly described in the literature. The objective of this work was to propose a model able to predict the pharmacokinetics of vancomycin in very elderly people. First, a population pharmacokinetic model was carried out using the algorithm NPAG (nonparametric adaptive grid) on a database of 70 hospitalized patients aged over 80 years and treated with vancomycin. An external validation then was performed on 41 patients, and the predictive capabilities of the model were assessed. The model had two compartments and six parameters. Body weight and creatinine clearance significantly influenced vancomycin volume of distribution and body clearance, respectively. The means (± standard deviations) of vancomycin volume of distribution and clearance were 36.3 ± 15.2 liter and 2.0 ± 0.9 liter/h, respectively. In the validation group, the bias and precision were -0.75 mg/liter and 8.76 mg/liter for population predictions and -0.39 mg/liter and 2.68 mg/liter for individual predictions. In conclusion, a pharmacokinetic model of vancomycin in a very elderly population has been created and validated for predicting plasma concentrations of vancomycin.
The emergency contraceptive drugs (EC), levonorgestrel (LNG) and ulipristal acetate (UPA), are sensitive substrates of cytochrome P450 3A4 (CYP3A4). In 2016, the label of LNG was updated based on a ...drug–drug interaction (DDI) study showing a significant decrease in LNG exposure when co‐administered with efavirenz, a known CYP3A4 inducer. DDI between UPA and CYP3A4 inducers are poorly characterized. The aims of this study were to review quantitative data from the literature on DDI with EC, to provide quantitative predictions of DDI between UPA and CYP3A4 inducers, and to identify moderate and severe DDI that may require a dose adjustment. A literature search was performed on pharmacokinetic DDI of LNG and UPA. Quantitative prediction of DDI with UPA was carried out by using the in vivo mechanistic static model (IMSM). Limited information was available on DDI with emergency contraception drugs. For LNG, data from eleven studies were retrieved, including five known CYP3A4 inducers that confirmed a risk of underexposure to LNG when co‐administered with inducers. For UPA, only three studies were identified, including only one CYP3A4 inducer. The IMSM approach indicated that UPA is a sensitive substrate of CYP3A4, with an estimated contribution of 86% of CYP3A4 to oral clearance. Moderate to severe DDI were predicted in 17 cases with CYP3A4 inducers, and dosage adjustments were suggested. This study illustrates the ability of the IMSM approach to inform about the DDI profile of old and new drugs.
PDF
