Evaluating renal function and age as predictors of amikacin clearance in neonates: model-based analysis and optimal dosing strategies

Dose optimization of cefazolin in South African children undergoing cardiac surgery with cardiopulmonary bypass

Cefazolin is an antibiotic used to prevent surgical site infections. During cardiac surgery with cardiopulmonary bypass (CPB), its efficacy target could be underachieved. We aimed to develop a population pharmacokinetic model for cefazolin in children and optimize the prophylactic dosing regimen. Children under 25 kg undergoing cardiac surgery with CPB and receiving cefazolin at standard doses (50 mg/kg IV every 4-6 h) were included in this analysis. A population pharmacokinetic model and Monte Carlo simulations were used to evaluate the probability of target attainment (PTA) for efficacy and toxicity with the standard regimen and an alternative regimen of continuous infusion, where loading and maintenance doses were calculated from model-derived individual parameters. Twenty-two patients were included, with median (range) age, body weight, and eGFR of 19.5 (1-94) months, 8.7 (2-21) kg, and 116 (48-159) mL/min, respectively. Six patients received an additional dose in the CPB circuit. A two-compartment disposition model with an additional compartment for the CPB was developed, including weight-based allometric scaling and eGFR. For a 10 kg patient with eGFR of 120 mL/min/1.73 m2, clearance was estimated as 0.856 L/h. Simulations indicated that the standard dosing regimen fell short of achieving the efficacy target >40% of the time within a dosing duration and in patients with good renal function, PTA ranged from <20% to 70% for the smallest to the largest patients, respectively, at high MICs. In contrast, the alternative regimen consistently maintained target concentrations throughout the procedure for all patients while using a lower overall dose.

Virtual Patient Simulation Using Copula Modeling

Virtual patient simulation is increasingly performed to support model-based optimization of clinical trial designs or individualized dosing strategies. Quantitative pharmacological models typically incorporate individual-level patient characteristics, or covariates, which enable the generation of virtual patient cohorts. The individual-level patient characteristics, or covariates, used as input for such simulations should accurately reflect the values seen in real patient populations. Current methods often make unrealistic assumptions about the correlation between patient's covariates or require direct access to actual data sets with individual-level patient data, which may often be limited by data sharing limitations. We propose and evaluate the use of copulas to address current shortcomings in simulation of patient-associated covariates for virtual patient simulations for model-based dose and trial optimization in clinical pharmacology. Copulas are multivariate distribution functions that can capture joint distributions, including the correlation, of covariate sets. We compare the performance of copulas to alternative simulation strategies, and we demonstrate their utility in several case studies. Our work demonstrates that copulas can reproduce realistic patient characteristics, both in terms of individual covariates and the dependence structure between different covariates, outperforming alternative methods, in particular when aiming to reproduce high-dimensional covariate sets. In conclusion, copulas represent a versatile and generalizable approach for virtual patient simulation which preserve relationships between covariates, and offer an open science strategy to facilitate re-use of patient data sets.

Therapeutic drug monitoring of amikacin in preterm and term neonates with late-onset sepsis. Can saliva samples replace plasma samples?

Amikacin is an aminoglycoside antibiotic that is frequently used for the treatment of neonatal late-onset sepsis, for which therapeutic drug monitoring (TDM) is advised. In order to decrease the TDM associated burden of plasma sampling, a noninvasive TDM method using saliva samples was investigated.

METHODS

This was a prospective single-centre, observational feasibility study with 23 premature and term neonates from whom up to 8 saliva samples were collected, together with residual plasma from clinical routine. Amikacin concentrations in saliva and plasma were quantified with liquid chromatography-tandem mass spectrometry. A population pharmacokinetic analysis was performed to develop an integrated pharmacokinetic model of amikacin in plasma and saliva and for the identification of covariates. TDM performance of different sampling regimens was evaluated using Monte Carlo simulations in a fictional cohort of representative neonates (n = 10 000).

RESULTS

Amikacin could be detected in saliva and a saliva compartment was appended to a 2-compartment plasma model. First-order absorption (k13 ) of the saliva compartment was 0.0345 h-1 with an interindividual variability of 45.3%. The rate of first-order elimination (k30 ) was 0.176 h-1 . Postmenstrual age had a significant negative covariate effect on k13 , with an exponent of -4.3. Target attainment increased from 77.6 to 79.2% and from 79.9 to 83.2% using 1-to 5 saliva samples or 1-5 plasma samples, respectively.

CONCLUSION

TDM of amikacin using saliva samples results in target attainment comparable to plasma samples and may be beneficial for (premature) neonates with late-onset sepsis.

Fructose-enabled killing of antibiotic-resistant Salmonella enteritidis by gentamicin: Insight from reprogramming metabolomics

Salmonella enterica is a food-borne pathogen that poses a severe threat to both poultry production and human health. Antibiotics are critical for the initial treatment of bacterial infections. However, the overuse and misuse of antibiotics results in the rapid evolution of antibiotic-resistant bacteria, and the discovery and development of new antibiotics are declining. Therefore, understanding antibiotic resistance mechanisms and developing novel control measures are essential. In the present study, GC-MS-based metabolomics analysis was performed to determine the metabolic profile of gentamicin sensitive (SE-S) and resistant (SE-R) S. enterica. Fructose was identified as a crucial biomarker. Further analysis demonstrated a global depressed central carbon metabolism and energy metabolism in SE-R. The decrease in the pyruvate cycle reduces the production of NADH and ATP, causing a decrease in membrane potential, which contributes to gentamicin resistance. Exogenous fructose potentiated the effectiveness of gentamicin in killing SE-R by promoting the pyruvate cycle, NADH, ATP and membrane potential, thereby increasing gentamicin intake. Further, fructose plus gentamicin improved the survival rate of chicken infected with gentamicin-resistant Salmonella in vivo. Given that metabolite structures are conserved across species, fructose identified from bacteria could be used as a biomarker for breeding disease-resistant phenotypes in chicken. Therefore, a novel strategy is proposed for fighting against antibiotic-resistant S. enterica, including exploring molecules suppressed by antibiotics and providing a new approach to find pathogen targets for disease resistance in chicken breeding.

Population pharmacokinetics of amikacin in suspected cases of neonatal sepsis

AIMS

This study aimed to characterize the population pharmacokinetic parameters of intravenously administered amikacin in newborns and assess the effect of sepsis in amikacin exposure.

METHODS

Newborns aged ≥3 days who received at least 1 dose of amikacin during their hospitalization period were eligible for the study. Amikacin was administered intravenously during a 60-min infusion period. Three venous blood samples were taken from each patient during the first 48 h. Population pharmacokinetic parameter estimates were obtained using a population approach with the programme NONMEM.

RESULTS

Data from 329 drug assay samples were obtained from 116 newborn patients (postmenstrual age [PMA] 38.3, range 32-42.4 weeks; weight 2.8, range 1.6-3.8 kg). Measured amikacin concentrations ranged from 0.8 to 56.4 mg/L. A 2-compartment model with linear elimination produced a good fit of the data. Estimated parameters for a typical subject (2.8 kg, 38.3 weeks) were clearance (Cl = 0.16 L/h), intercompartmental clearance (Q = 0.15 L/h), volume of distribution of the central compartment (Vc = 0.98 L) and peripheral volume of distribution (Vp = 1.23 L). Total bodyweight, PMA and the presence of sepsis positively influenced Cl. Plasma creatinine concentration and circulatory instability (shock) negatively influenced Cl.

CONCLUSION

Our main results confirm previous findings showing that weight, PMA and renal function are relevant factors influencing newborn amikacin pharmacokinetics. In addition, current results showed that pathophysiological states of critically ill neonates, such as sepsis and shock, were associated with opposite effects in amikacin clearance and should be considered in dose adjustments.

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 Combined with Fosfomycin for Treatment of Neonatal Sepsis in the Setting of Highly Prevalent Antimicrobial Resistance

Antimicrobial resistance (particularly through extended-spectrum β-lactamase and aminoglycoside-modifying enzyme production) in neonatal sepsis is a global problem, particularly in low- and middle-income countries, with significant mortality rates. High rates of resistance are reported for the current WHO-recommended first-line antibiotic regimen for neonatal sepsis, i.e., ampicillin and gentamicin. We assessed the utility of fosfomycin and amikacin as a potential alternative regimen to be used in settings of increasingly prevalent antimicrobial resistance. The combination was studied in a 16-arm dose-ranged hollow-fiber infection model (HFIM) experiment. The combination of amikacin and fosfomycin enhanced bactericidal activity and prevented the emergence of resistance, compared to monotherapy with either antibiotic. Modeling of the experimental quantitative outputs and data from checkerboard assays indicated synergy. We further assessed the combination regimen at clinically relevant doses in the HFIM with nine Enterobacterales strains with high fosfomycin and amikacin MICs and demonstrated successful kill to sterilization for 6/9 strains. From these data, we propose a novel combination breakpoint threshold for microbiological success for this antimicrobial combination against Enterobacterales strains, i.e., MIC_F × MIC_A < 256 (where MIC_F and MIC_A are the fosfomycin and amikacin MICs, respectively). Monte Carlo simulations predict that a standard fosfomycin-amikacin neonatal regimen would achieve >99% probability of pharmacodynamic success for strains with MICs below this threshold. We conclude that the combination of fosfomycin with amikacin is a viable regimen for the empirical treatment of neonatal sepsis and is suitable for further clinical assessment in a randomized controlled trial.

Comparison of Amikacin Pharmacokinetics in Neonates With and Without Congenital Heart Disease

OBJECTIVES

The primary objective was to compare the volume of distribution (Vd), clearance (CL), elimination rate (K_e), and half-life (t½) of amikacin in neonates with cyanotic defects, acyanotic defects, and controls, adjusted for gestational and postnatal age. Secondary objectives were to compare the incidence of acute kidney injury (AKI) between controls and the congenital heart disease (CHD) group and to identify potential risk factors.

METHODS

This retrospective cohort study included neonates receiving amikacin from January 1, 2013 to August 31, 2016. Patients were excluded if concentrations were not appropriately obtained or if AKI or renal anomalies were identified prior to amikacin initiation. Congenital heart disease was classified as acyanotic or cyanotic. Patients with CHD were matched 1:1 with non-CHD controls according to postmenstrual age. Bivariate analyses were performed using Wilcoxon-Mann-Whitney test, Pearson χ² tests, or Fisher exact as appropriate with a p value <0.05. Regression analyses included logistic and analysis of covariance.

RESULTS

Fifty-four patients with CHD were matched with 54 controls. Median (IQR) postnatal age (days) at amikacin initiation significantly differed between CHD and controls, 3.0 (1.0-16.0) versus 1.0 (1.0-3.0), p = 0.016. After adjusting for gestational and postnatal age, there was no difference in the mean (95% CI) Vd (L/kg) and CL (L/kg/hr) between CHD and controls, 0.47 (0.44-0.50) versus 0.46 (0.43-0.49), p = 0.548 and 0.05 (0.05-0.05) versus 0.05 (0.05-0.05), p = 0.481, respectively. There was no difference in K_e or t½ between groups. There was no difference in AKI between the CHD and controls, 18.5% versus 9.3%, p = 0.16.

CONCLUSIONS

Clinicians should consider using standard amikacin dosing for neonates with CHD and monitor renal function, since they may have greater AKI risk factors.

Population Pharmacokinetics of Amikacin in Adult Patients with Cystic Fibrosis

Practitioners commonly use amikacin in patients with cystic fibrosis. Establishment of the pharmacokinetics of amikacin in adults with cystic fibrosis may increase the efficacy and safety of therapy. This study was aimed to establish the population pharmacokinetics of amikacin in adults with cystic fibrosis. We used serum concentration data obtained during routine therapeutic drug monitoring and explored the influence of patient covariates on drug disposition. We performed a retrospective chart review to collect the amikacin dosing regimens, serum amikacin concentrations, blood sampling times, and patient characteristics for adults with cystic fibrosis admitted for treatment of acute pulmonary exacerbations. Amikacin concentrations were retrospectively collected for 49 adults with cystic fibrosis, and 192 serum concentrations were available for analysis. A population pharmacokinetic model was developed using nonlinear mixed-effects modeling with the first-order conditional estimation method. A two-compartment model with first-order elimination best described amikacin pharmacokinetics. Creatinine clearance and weight were identified as significant covariates for clearance and the volume of distribution, respectively, in the final model. Residual variability was modeled using a proportional error model. Typical estimates for clearance, central and peripheral volumes of distribution, and intercompartmental clearance were 3.06 liters/h, 14.4 liters, 17.1 liters, and 0.925 liters/h, respectively. The pharmacokinetics of amikacin in individuals with cystic fibrosis seems to differ from those in individuals without cystic fibrosis. However, further investigations are needed to confirm these results and, thus, the need for variations in amikacin dosing. Future pharmacodynamic studies will potentially establish the optimal amikacin dosing regimens for the treatment of acute pulmonary exacerbations in adult patients with CF.

Evaluating renal function and age as predictors of amikacin clearance in neonates: model-based analysis and optimal dosing strategies

AIMS

We aimed to compare the performance of renal function and age as predictors of inter-individual variability (IIV) in clearance of amikacin in neonates through parallel development of population pharmacokinetic (PK) models and their associated impact on optimal dosing regimens.

METHODS

Amikacin concentrations were retrospectively collected for 149 neonates receiving amikacin (post-natal age (PNA) between 4-89 days). Two population PK models were developed in parallel, considering at least as predictors current body weight (WT), in combination with either creatinine clearance (CLcr ) or age descriptors. Using stochastic simulations for both renal function or age-based dosing, we identified optimal dosing strategies that were based on attainment of optimal peak- (PCC) and trough target concentration coverage (TCC) windows associated with efficacy and toxicity.

RESULTS

The CLcr and age-based population PK models both included current body weight (WT) on CL, central distribution volume and intercompartmental clearance, in combination with either CLcr or PNA as predictors for IIV of clearance (CL). The WT-CLcr model explained 6.9% more IIV in CL compared with the WT-PNA model. Both models successfully described an external dataset (n = 53) of amikacin PK. The simulation analysis of optimal dose regimens suggested similar performance of either CLcr or PNA based dosing.

CONCLUSION

CLcr predicted more IIV in CL, but did not translate into clinically relevant improvements of target concentrations. Our optimized dose regimens can be considered for further evaluation to optimize initial treatment with amikacin.