A pharmacometric approach to define target site-specific breakpoints for bacterial killing and resistance suppression integrating microdialysis, time-kill curves and heteroresistance data: a case study with moxifloxacin.

OBJECTIVES: Pharmacokinetic-pharmacodynamic (PK-PD) considerations are at the heart of defining susceptibility breakpoints for antibiotic therapy. However, current approaches follow a fragmented workflow. The aim of this study was to develop an integrative pharmacometric approach to define MIC-based breakpoints for killing and suppression of resistance development for plasma and tissue sites, integrating clinical microdialysis data as well as in vitro time-kill curves and heteroresistance information, exemplified by moxifloxacin against Staphylococcus aureus and Escherichia coli. METHODS: Plasma and target site samples were collected from ten patients receiving 400 mg moxifloxacin/day. In vitro time-kill studies with three S. aureus and two E. coli strains were performed and resistant subpopulations were quantified. Using these data, a hybrid physiologically based (PB) PK model and a PK-PD model were developed, and utilized to predict site-specific breakpoints. RESULTS: For both bacterial species, the predicted MIC breakpoint for stasis at 400 mg/day was 0.25 mg/L. Less reliable killing was predicted for E. coli in subcutaneous tissues where the breakpoint was 0.125 mg/L. The breakpoint for resistance suppression was 0.06 mg/L. Notably, amplification of resistant subpopulations was highest at the clinical breakpoint of 0.25 mg/L. High-dose moxifloxacin (800 mg/day) increased all breakpoints by one MIC tier. CONCLUSIONS: An efficient pharmacometric approach to define susceptibility breakpoints was developed; this has the potential to streamline the process of breakpoint determination. Thereby, the approach provided additional insight into target site PK-PD and resistance development for moxifloxacin. Application of the approach to further drugs is warranted.

Towards precision dosing of vancomycin: a systematic evaluation of pharmacometric models for Bayesian forecasting.

OBJECTIVES: Vancomycin is a vital treatment option for patients suffering from critical infections, and therapeutic drug monitoring is recommended. Bayesian forecasting is reported to improve trough concentration monitoring for dose adjustment. However, the predictive performance of pharmacokinetic models that are utilized for Bayesian forecasting has not been systematically evaluated. METHOD: Thirty-one published population pharmacokinetic models for vancomycin were encoded in NONMEM®7.4. Data from 292 hospitalized patients were used to evaluate the predictive performance (forecasting bias and precision, visual predictive checks) of the models to forecast vancomycin concentrations and area under the curve (AUC) by (a) a priori prediction, i.e., solely by patient characteristics, and (b) also including measured vancomycin concentrations from previous dosing occasions using Bayesian forecasting. RESULTS: A priori prediction varied substantially-relative bias (rBias): -122.7-67.96%, relative root mean squared error (rRMSE) 44.3-136.8%, respectively-and was best for models which included body weight and creatinine clearance as covariates. The model by Goti et al. displayed the best predictive performance with an rBias of -4.41% and an rRMSE of 44.3%, as well as the most accurate visual predictive checks and AUC predictions. Models with less accurate predictive performance provided distorted AUC predictions which may lead to inappropriate dosing decisions. CONCLUSION: There is a diverse landscape of population pharmacokinetic models for vancomycin with varied predictive performance in Bayesian forecasting. Our study revealed the Goti model as suitable for improving precision dosing in hospitalized patients. Therefore, it should be used to drive vancomycin dosing decisions, and studies to link this finding to clinical outcomes are warranted.

Tigecycline in critically ill patients on continuous renal replacement therapy: a population pharmacokinetic study.

BACKGROUND: Tigecycline is a vital antibiotic treatment option for infections caused by multiresistant bacteria in the intensive care unit (ICU). Acute kidney injury (AKI) is a common complication in the ICU requiring continuous renal replacement therapy (CRRT), but pharmacokinetic data for tigecycline in patients receiving CRRT are lacking. METHODS: Eleven patients mainly with intra-abdominal infections receiving either continuous veno-venous hemodialysis (CVVHD, n = 8) or hemodiafiltration (CVVHDF, n = 3) were enrolled, and plasma as well as effluent samples were collected according to a rich sampling schedule. Total and free tigecycline was determined by ultrafiltration and high-performance liquid chromatography (HPLC)-UV. Population pharmacokinetic modeling using NONMEM® 7.4 was used to determine the pharmacokinetic parameters as well as the clearance of CVVHD and CVVHDF. Pharmacokinetic/pharmacodynamic target attainment analyses were performed to explore the potential need for dose adjustments of tigecycline in CRRT. RESULTS: A two-compartment population pharmacokinetic (PK) model was suitable to simultaneously describe the plasma PK and effluent measurements of tigecycline. Tigecycline dialysability was high, as indicated by the high mean saturation coefficients of 0.79 and 0.90 for CVVHD and CVVHDF, respectively, and in range of the concentration-dependent unbound fraction of tigecycline (45-94%). However, the contribution of CRRT to tigecycline clearance (CL) was only moderate (CLCVVHD: 1.69 L/h, CLCVVHDF: 2.71 L/h) in comparison with CLbody (physiological part of the total clearance) of 18.3 L/h. Bilirubin was identified as a covariate on CLbody in our collective, reducing the observed interindividual variability on CLbody from 58.6% to 43.6%. The probability of target attainment under CRRT for abdominal infections was ≥ 0.88 for minimal inhibitory concentration (MIC) values ≤ 0.5 mg/L and similar to patients without AKI. CONCLUSIONS: Despite high dialysability, dialysis clearance displayed only a minor contribution to tigecycline elimination, being in the range of renal elimination in patients without AKI. No dose adjustment of tigecycline seems necessary in CRRT. TRIAL REGISTRATION: EudraCT, 2012-005617-39 . Registered on 7 August 2013.