Optimizing Amikacin Dosage in Pediatrics Based on Population Pharmacokinetic/Pharmacodynamic Modeling

Predictive Performance of Population Pharmacokinetic Models for Amikacin in Term Neonates

BACKGROUND AND OBJECTIVE

Amikacin is preferred in treating Gram-negative infections in neonates and it has a narrow therapeutic window. The population pharmacokinetic modeling approach can aid in designing optimal dosage regimens for amikacin in neonates. In this study, we attempted to identify the suitable population pharmacokinetic model from the published reports for the study population from an Indian setting.

METHODS

Published population pharmacokinetic studies for amikacin in neonates were identified. Data on structural models and typical pharmacokinetic parameters were extracted from the studies. For the clinical study, neonates who met the inclusion criteria were enrolled in the study from the NICU, Kasturba Medical College, Manipal, during Jan 2020 to March 2022. Drug concentrations were estimated, and demographic and clinical data were collected. Identified population pharmacokinetic models were used to predict the amikacin concentrations in neonates. Predicted concentrations were compared against the observed concentrations. Differences between predicted and observed concentrations were quantified using statistical measures. The population pharmacokinetic model, which was able to predict the data well, is considered a suitable model for the study population. Dosing regimens were suggested for neonates using the pharmacometric simulation approach generated by the selected model.

RESULTS

A total of 43 plasma samples were collected from 31 neonates. Twelve population pharmacokinetic models were found for amikacin in neonates. The predictive performance of the 12 studies was performed using clinical data. A two-compartment model reported by Illamola et al. predicted the amikacin concentrations better than other models. Illamola et al. reported creatinine clearance and body weight as the significant covariates impacting the pharmacokinetic parameters of amikacin. This model was able to predict the clinical data with 29.97% and 0.686 of relative median absolute prediction error and relative root mean square error, respectively, which is the best among the published models. The Illamola et al. model was selected as the final model to perform pharmacometric simulations for the subjects with different combinations of creatinine clearance and body weight. Dosage regimens were designed to attain target therapeutic concentrations for the virtual subjects and a nomogram was developed.

CONCLUSIONS

The population pharmacokinetic model reported by the Illamola et al. model was selected as the final model to explain the clinical data with the lowest relative median absolute prediction error and relative root mean square error when compared with other models. An amikacin nomogram was developed for the neonates whose creatinine clearance and body weight ranged between 10 and 90 mL/min and between 2 and 4 kg, respectively. A developed nomogram can assist clinicians to design an optimal dosage regimen of amikacin for term neonates.

Amikacin initial dosage in patients with hypoalbuminaemia: an interactive tool based on a population pharmacokinetic approach

OBJECTIVES

To characterize amikacin population pharmacokinetics in patients with hypoalbuminaemia and to develop a model-based interactive application for amikacin initial dosage.

METHODS

A population pharmacokinetic model was developed using a non-linear mixed-effects modelling approach (NONMEM) with amikacin concentration-time data collected from clinical practice (75% hypoalbuminaemic patients). Goodness-of-fit plots, minimum objective function value, prediction-corrected visual predictive check, bootstrapping, precision and bias of parameter estimates were used for model evaluation. An interactive model-based simulation tool was developed in R (Shiny and R Markdown). Cmax/MIC ratio, time above MIC and AUC/MIC were used for optimizing amikacin initial dose recommendation. Probabilities of reaching targets were calculated for the dosage proposed.

RESULTS

A one-compartment model with first-order linear elimination best described the 873 amikacin plasma concentrations available from 294 subjects (model development and external validation groups). Estimated amikacin population pharmacokinetic parameters were CL (L/h) = 0.525 + 4.78 × (CKD-EPI/98) × (0.77 × vancomycin) and V (L) = 26.3 × (albumin/2.9)-0.51 × [1 + 0.006 × (weight - 70)], where CKD-EPI is calculated with the Chronic Kidney Disease Epidemiology Collaboration equation. AMKdose is a useful interactive model-based application for a priori optimization of amikacin dosage, using individual patient and microbiological information together with predefined pharmacokinetic/pharmacodynamic (PKPD) targets.

CONCLUSIONS

Serum albumin, total bodyweight, estimated glomerular filtration rate (using the CKD-EPI equation) and co-medication with vancomycin showed a significant impact on amikacin pharmacokinetics. A powerful interactive initial dose-finding tool has been developed and is freely available online. AMKdose could be useful for guiding initial amikacin dose selection before any individual pharmacokinetic information is available.

Population Pharmacokinetics Analysis of Amikacin Initial Dosing Regimen in Elderly Patients

There are limited data of amikacin pharmacokinetics (PK) in the elderly population. Hence, we aimed to describe the population PK of amikacin in elderly patients (>70 years old) and to establish optimized initial dosing regimens. We simulated individual maximum concentrations in plasma (Cmax) and minimal concentrations (Cmin) for several dosing regimens (200–2000 mg every 24, 48, and 72 h) for patients with creatinine clearance (CCr) of 10–90 mL/min and analyzed efficacy (Cmax/minimal inhibitory concentration (MIC) ≥ 8) for MICs of 4, 8, and 16 mg/L and safety (Cmin < 4 mg/L). A one-compartment model best described the data. CCr was the only covariate associated with amikacin clearance. The population PK parameter estimates were 2.25 L/h for clearance and 18.0 L for volume of distribution. Dosing simulations recommended the dosing regimens (1800 mg) with dosing intervals ranging 48–72 h for patients with CCr of 40–90 mL/min based on achievement of both efficacy for the MIC of 8 mg/L and safety. None of the dosing regimens achieved the targets for an MIC of 16 mg/L. We recommend the initial dosing regimen using a nomogram based on CCr for an MIC of ≤8 mg/L in elderly patients with CCr of 40–90 mL/min.

Molecular Characterization of Extended-Spectrum β-Lactamase-Producing Escherichia coli and Klebsiella pneumoniae Among the Pediatric Population in Qatar

INTRODUCTION

Although extended-spectrum β-lactamase (ESBL)-producing Enterobacterales are a public health problem in the Arabian Peninsula, data on the molecular characteristic of their antimicrobial resistance determinants in children is limited.

AIM

To determine the molecular characteristics of ESBL-producing Escherichia coli and Klebsiella pneumoniae in the pediatric population of Qatar.

METHODS

Whole-genome sequencing was performed on ESBL-producing E. coli and K. pneumoniae isolates recovered from screening and clinical specimens from pediatric patients at Sidra Medicine in Doha from January to December 2018.

RESULTS

A total of 327 ESBL producers were sequenced: 254 E. coli and 73 K. pneumoniae. Non-susceptibility rates to non-β-lactam antibiotics for both species were 18.1 and 30.1% for gentamicin, 0.8 and 4.1% for amikacin, 41.3 and 41.1% for ciprofloxacin, and 65.8 and 76.1% for cotrimoxazole. The most common sequence types (STs) were ST131 (16.9%), ST38 and ST10 (8.2% each) in E. coli and ST307 (9.7%), and ST45 and ST268 (6.9% each) in K. pneumoniae. CTX-M type ESBLs were found in all but one isolate, with CTX-M-15 accounting for 87.8%. Among other β-lactamases, TEM-1B and OXA-1 were coproduced in 41 and 19.6% of isolates. The most common plasmid-mediated quinolone resistance genes cocarried were qnr A/B/E/S (45.3%). Ninety percent of gentamicin non-susceptible isolates harbored genes encoding AAC(3) enzymes, mainly aac(3)-IIa. Only two of 57 isolates harboring aac(6')-Ib-cr were non-susceptible to amikacin. Chromosomal mutations in genes encoding DNA gyrase and topoisomerase IV enzymes were detected in 96.2% fluoroquinolone-non-susceptible E. coli and 26.7% fluoroquinolone-non-susceptible K. pneumoniae.

CONCLUSION

Our data show that CTX-M enzymes are largely the most prevalent ESBLs in children in Qatar with a predominance of CTX-M-15. Carbapenem-sparing options to treat ESBL infections are limited, given the frequent coproduction of OXA-1 and TEM-1B enzymes and coresistance to antibiotic classes other than β-lactams.

Optimal Management of Complicated Infections in the Pediatric Patient: The Role and Utility of Ceftazidime/Avibactam

Antimicrobial resistance poses a substantial threat to global public health. The pursuit of new antibiotics has decreased and very few options have been investigated for the treatment of complicated multidrug-resistant Gram-negative (MDR-GN) infections in adult population and even less in pediatric patients. Ceftazidime-avibactam (CAZ-AVI) is novel cephalosporin/β-lactamase inhibitor (BL-BLI) combination with broad antibacterial spectrum. The aim of this review is to describe the current and future role CAZ-AVI in the pediatric population with suspected or confirmed MDR-GN infections.

Population pharmacokinetic/pharmacodynamic modelling of nifekalant in healthy Chinese volunteers

Nifekalant is a class III antiarrhythmic drug, and its major adverse effect is prolongation of the QT interval. This study analysed data generated from a pharmacokinetic (PK) study to develop a population PK/pharmacodynamics (PD) model for describing the relationship between plasma concentrations and prolongation of the QT interval over time following intravenous administration of nifekalant. This open-labelled, phase I clinical study comprised two dose level groups of eight healthy Chinese volunteers. Concentrations of nifekalant in plasma samples collected at set time-points were determined using a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. A PK/PD model was constructed using a non-linear mixed-effects approach (Phoenix NLME 8.1). Furthermore, demographic covariates of the model were investigated and a concentration factor (Conc^Ɵ) was introduced as the only covariate which improved the performance of the model. The final population PK model exhibited one-order elimination with two-compartment distribution and adequately described nifekalant plasma concentrations over time. The QT interval prolongation was best described by an indirect effect model with an inhibition build-up effect, representing the relationship between plasma concentrations and effect. The final population PK/PD model may facilitate more accurate predictions of the drug profile in clinical settings in the future.

IR, Raman and SERS analysis of amikacin combined with DFT-based calculations

Amikacin, a molecule formed by two glucosamine rings linked by α-linkages through a central deoxystreptamine, is an antibiotic often used in clinical treatments, with a special attention in the pediatric cases, due to the physiological activity of their renal system. In spite of its extensive use, no detailed information about the vibrational features of the molecule is available in the literature. Thus, in this study we performed a comprehensive vibrational investigation of amikacin from both an experimental and theoretical point of view. Raman and IR spectroscopy combined with DFT calculations conducted to a complete vibrational characterization of the molecule, with the assignment of the vibrational modes. Moreover, SERS spectrum was recorded and analyzed and provided information about the adsorption behavior of the amikacin on the silver nanoparticles surface.