Therapeutic drug monitoring of meropenem and pharmacokinetic-pharmacodynamic target assessment in critically ill pediatric patients from a prospective observational study.

OBJECTIVES: To compare the unbound plasma meropenem concentrations at mid-dosing intervals (Cmid, 50%fT), end-dosing intervals (Ctrough, 100%fT), and proportions of patients achieving 50%fT and 100%fT above minimum inhibitory concentration (MIC) (50%fT>MIC and 100%fT>MIC) between extended infusion (EI) and intermittent bolus (IB) administration in a therapeutic drug monitoring (TDM) program in children. METHODS: A prospective observational study was conducted in children aged 1 month to 18 years receiving meropenem every 8 hours by either EI or IB. Meropenem Cmid, Ctrough, and proportions of patients achieving 50%fT>MIC and 100%fT>MIC were compared. RESULTS: TDM data from 72 patients with a median age (interquartile range [IQR]) of 12 months (3-37) were used. Meropenem dose was 120 and 60 mg/kg/day in EI and IB groups, respectively. Geometric mean (95% confidence interval [CI]) Cmid of EI versus IB was 17.3 mg/L (13.7-21.8) versus 3.4 mg/L (1.7-6.7) (P <0.001). Geometric mean (95% CI) Ctrough of EI versus IB was 2.3 mg/L (1.6-3.4) versus 0.8 mg/L (0.4-1.5) (P=0.005). Greater proportions of patients achieving 50%fT>MIC and 100%fT>MIC were observed in the EI group. CONCLUSIONS: A meropenem dose of 20 mg/kg/dose given by IB should not be used in critically ill children, even if they are not suspected of having a central nervous system infection. A dose of 40 mg/kg/dose given by EI resulted in higher Cmid, Ctrough, and proportions of patients achieving 50%fT>MIC and 100%fT>MIC.

Population pharmacokinetics of meropenem in critically ill infant patients.

BACKGROUND: Population pharmacokinetic analysis in critically ill infants remains a challenge for lack of information. OBJECTIVES: To determine the population pharmacokinetic parameters of meropenem and evaluate the covariates affecting population pharmacokinetic parameters. METHODS: A prospective study was conducted on 35 patients. A total of 160 blood samples were collected and determined free of drug concentrations of meropenem. Population pharmacokinetic data were analyzed using NONMEM software. Internal validation methods, including bootstrapping and prediction-corrected visual predictive checks, were applied to evaluate the robustness and predictive power of the final model. RESULTS: A one-compartment model with first-order elimination showed the best fit to the data. The typical clearance (CL) values and volume of distribution (Vd) were 1.33 L/h and 2.27 L, respectively. Weight and creatinine clearance were influential covariates for CL, while weight was a significant covariate for Vd of meropenem. The model evaluation results suggested robustness and good predictability of the final model. The standard dosage regimens of meropenem achieved 40% f T>MIC but not enough if a more aggressive target of 80% f T>MIC at MIC value of ≥ 16 µg/mL is desired. CONCLUSIONS: This population pharmacokinetic model could be used for suggesting individualized meropenem dosage regimens in critically ill infants.

Pharmacokinetic/pharmacodynamic modeling of in vitro activity of azithromycin against four different bacterial strains.

The bacterial time-kill curves of azithromycin against four bacterial strains (Streptococcus pneumoniae/penicillin-intermediate, S. pneumoniae/penicillin-sensitive, Haemophilus influenzae and Moraxella catarrhalis) were determined by in vitro infection models. Eighteen different pharmacokinetic/pharmacodynamic models were fitted to the time-kill data using non-linear regression and compared for best fit. A simple, widely used E(max) model was not sufficient to describe the pharmacodynamic effects for the four bacterial strains. Appropriate models that gave good curve fits included additional terms for saturation of the number of bacteria (N(max)), delay in the initial bacterial growth phase and/or the onset of anti-infective activity (1-exp(-zt)) as well as a Hill factor (h) that captures the steepness of the concentration-response profile. Azithromycin was highly effective against S. pneumoniae strains and M. catarrhalis while the efficacy against H. influenzae was poor. Applications of these pharmacokinetic/pharmacodynamic models will eventually provide a tool for rational antibiotic dosing regimen decisions.