Background: Our objectives were to (1) determine the pharmacokinetic indices of vancomycin in pediatric patients; and (2) compare attainment of 2 target exposures: area under curve (AUC) / minimum inhibitory concentration (MIC) ≥400 and trough concentration ≥15 mcg/mL. Methods: The population-based pharmacokinetic modeling was performed using NONMEM 7.2 for children ≥3 months old who received vancomycin for ≥48 hours from 2003 to 2011. A 1-compartment model with first-order kinetics was used to estimate clearance, volume of distribution and AUC. Empiric Bayesian post hoc individual parameters and Monte Carlo simulations (N = 11,000) were performed. Results: Analysis included 702 patients with 1660 vancomycin serum concentrations. Median age was 6.6 (interquartile range 2.2–13.4) years, weight 22.7 (12.6–46) kg and baseline serum creatinine 0.40 (0.30–0.60) mg/dL. Final model pharmacokinetic indices were clearance (L/h) = 0.248 * Wt^0.75 * (0.48/serum creatinine)^0.361 * (ln(age)/7.8)^0.995 and volume of distribution (L) = 0.636 * Wt. Using these parameters and the observed MIC distribution, Monte Carlo simulation indicated that the initial median dose of 44 (39–52) mg/kg/day was inadequate in most subjects. Regimens of 60 mg/kg/day for subjects ≥12 years old and 70 mg/kg/day for those <12 years old achieved target AUC/MIC in ~75% and trough concentrations ≥15 in ~45% of virtual subjects. An AUC/MIC ~400 corresponded to trough concentration ~8 to 9 mcg/mL. Conclusions: Targeted exposure using vancomycin AUC/MIC, compared with trough concentrations, is a more realistic target in children. Depending on age, serum creatinine and MIC distribution, vancomycin in a dosage of 60 to 70 mg/kg/day was necessary to achieve AUC/MIC ≥ 400 in 75% of patients.

Limited studies incorporating population-based pharmacokinetic modeling have been conducted to determine pharmacodynamic indices associated with nephrotoxicity during vancomycin exposure in children. A retrospective cohort analysis was conducted from September 2003 to December 2011 at 2 hospitals. Nephrotoxicity was defined as an increase in serum creatinine concentration (SCr) by ≥0.5 mg/dL, or ≥50% increase in baseline SCr, either persisting for ≥2 consecutive days. A 1-compartment model with first-order kinetics was used in NONMEM 7.2 to estimate trough concentrations ( C_min ) and area under the curve over 24 hours (AUC). Univariate, classification and regression tree (CART), and multivariate analyses were conducted to identify factors contributing to nephrotoxicity. The analyses included 680 pediatric subjects with 1576 vancomycin serum concentrations. Based on univariate analysis, median C_min (14.2 [interquartile range, IQR, 7.1–25.4] vs 8.4 [IQR, 5.5–12.4] mcg/mL; P = .001) and AUC (544 [IQR, 359–801] vs 378 [IQR, 304–494]; P < .001) were significantly higher in the nephrotoxic group compared with the non-nephrotoxic group. Using CART, we discovered that subjects with doses ≥60 mg/kg per day and AUC >1063 mg-h/L had a significantly higher occurrence of nephrotoxicity ( P = .005). Adjusting for intensive care unit stay and concomitant nephrotoxic drugs, steady-state vancomycin C_min ≥15 mcg/mL (adjusted odds ratio [aOR], 2.5; 95% confidence interval [CI], 1.1–5.8; P = .028) and AUC ≥800 mg-h/L (aOR, 3.7; 95% CI, 1.2–11.0; P = .018) were associated with increased risk of nephrotoxicity. Our study describes the pediatric exposure-nephrotoxicity relationships for vancomycin. Vancomycin C_min ≥15 mcg/mL and AUC ≥800 mg-h/L in children are independently associated with a > 2.5-fold increased risk of nephrotoxicity and may provide justification for use of alternative antibiotics in selected situations.

Background: Optimal monitoring of vancomycin in children needs evaluation using the exposure target with area under the curve (AUC) of the serum concentrations versus time over 24 hours. Our study objectives were to: (1) compare the accuracy and precision of vancomycin AUC estimations using 2 sampling strategies—1 serum concentration sample (1S, near trough) versus 2 samples (2S, near peak and trough) against the rich sample (RS) method; and (2) determine the performance of these strategies in predicting future AUC against an internal validation sample (VS). Methods: This was a retrospective cohort study using population-based pharmacokinetic modeling with Bayesian post hoc individual estimations in nonlinear mixed effects modeling (version 7.2). Pediatric subjects 3 months–21 years of age who received vancomycin ≥48 hours and had more than 3 drug samples within the first ≤96 hours of therapy were enrolled. Outcome measures were the accuracy, precision, and internal predictive performance of AUC estimations using 2 monitoring strategies (ie, 1S versus 2S) against the RS (which was derived from modeling all serum vancomycin concentrations obtained anytime during therapy) and VS (from serum concentrations obtained after 96 hours of therapy). Results: Analysis included 138 subjects with 712 vancomycin serum concentrations. Median age was 6.1 (interquartile range, 2.2–12.2) years, weight 22 (13–38) kg, and baseline serum creatinine 0.37 (0.30–0.50) mg/dL. Both accuracy and precision were improved with the 2S, compared with 1S, for AUC estimations (−2.0% versus −7.6% and 10.3% versus 12.8%, respectively) against the RS. Improved accuracy and precision were also observed for 2S when evaluated against VS in predicting future AUC. Conclusions: Compared with 1S, the 2S sampling strategy for vancomycin monitoring improved accuracy and precision in estimating and predicting future AUC. Evaluating 2 drug concentrations in children may be prudent to ensure adequate drug exposure.

The selection of the right antibiotic and right dose necessitates clinicians understand the contribution of pharmacokinetic variability stemming from age‐related physiologic maturation and the pharmacodynamics to optimize drug exposure for clinical response. The complexity of selecting the right dose arises from the multiplicity of pediatric age groups, from premature neonates to adolescents. Body size and age (which relate to organ function) must be incorporated to optimize antibiotic dosing in this vulnerable population. In the effort to optimize and individualize drug dosing regimens, clinical pharmacometrics that incorporate population‐based pharmacokinetic modeling, Bayesian estimation, and Monte Carlo simulations are utilized as a quantitative approach to understanding and predicting the pharmacology and clinical and microbiologic efficacy of antibiotics. In addition, opportunistic study designs and alternative blood sampling strategies can serve as practical approaches to ensure successful conduct of pediatric studies. This review article examines relevant literature on optimization of antibiotic pharmacotherapy in pediatric populations published within the last decade. Specific pediatric antibiotic data, including beta‐lactam antibiotics, aminoglycosides, and vancomycin, are critically evaluated.