A pharmacokinetic-pharmacodynamic (PKPD) model-based analysis of tedizolid against enterococci using the hollow-fibre infection model.

BACKGROUND: Tedizolid is a novel oxazolidinone antibiotic. Considering the higher antibacterial effect in immunocompetent compared with immunosuppressed animals, it is not recommended in immunocompromised patients. OBJECTIVES: In this study, we assessed the 'pure' pharmacokinetic-pharmacodynamic (PKPD) relationship for tedizolid against Enterococcus in the hollow-fibre infection model (HFIM). METHODS: Unbound plasma concentration time profiles (200-5000 mg/day IV) were simulated in the HFIM over 120 h against an Enterococcus faecalis strain and two clinical isolates of Enterococcus faecium (VRE-vanB and VRE-vanA). Next, a PKPD model describing tedizolid efficacy against bacterial isolates was developed. A population PK model was linked to the developed PKPD model and utilized to predict the bacterial kinetics in plasma and in target tissues [adipose, muscle, epithelial lining fluid (ELF) and sputum] over 120 h of therapy. RESULTS: The PKPD model adequately described the bacterial kill kinetics for all bacterial populations. At the human recommended dose of 200 mg/day, bacterial growth was predicted in plasma and all tissues, except for ELF. Bacteriostasis was observed only at a higher dose of 1200 mg/day over 120 h. An fAUC/MIC of 80 related to stasis over 120 h. Subpopulations resistant to 3 × MIC were amplified in plasma and target tissues, except for ELF, at doses of 200-800 mg/day. CONCLUSIONS: The human dose of 200 mg/day was insufficient to suppress bacterial growth in the HFIM, indicating that further components contribute to the clinical effect of tedizolid. This study supports the warning/precaution for tedizolid to limit its use in immunocompromised patients.

In vivo / in vitro Correlation of Pharmacokinetics of Gentamicin, Vancomycin, Teicoplanin and Doripenem in a Bovine Blood Hemodialysis Model.

Background: Elimination of a drug during renal replacement therapy is not only dependent on flow rates, molecular size and protein binding, but is often influenced by difficult to predict drug membrane interactions. In vitro models allow for extensive profiling of drug clearance using a wide array of hemofilters and flow rates. We present a bovine blood based in vitro pharmacokinetic model for intermittent renal replacement therapy. Methods: Four different drugs were analyzed: gentamicin, doripenem, vancomicin and teicoplanin. The investigated drug was added to a bovine blood reservoir connected to a hemodialysis circuit. In total seven hemofilter models were analyzed using commonly employed flow rates. Pre-filter, post-filter and dialysate samples were drawn, plasmaseparated and analyzed using turbidimetric assays or HPLC. Protein binding of doripenem and vancomycin was measured in bovine plasma and compared to previously published values for human plasma. Results: Clearance values were heavily impacted by choice of membrane material and surface as well as by dialysis parameters such as blood flow rate. Gentamicin clearance ranged from a minimum of 90.12 ml/min in a Baxter CAHP-170 diacetate hemofilter up to a maximum of 187.90 ml/min in a Fresenius medical company Fx80 polysulfone model (blood flow rate 400 ml/min, dialysate flow rate 800 ml/min). Clearance of Gentamicin vs Vancomicin over the F80s hemofilter model using the same flow rates was 137.62 mL vs 103.25 ml/min. Doripenem clearance with the Fx80 was 141.25 ml/min. Conclusion: Clearance values corresponded very well to previously published data from clinical pharmacokinetic trials. In conjunction with in silico pharmacometric models. This model will allow precise dosing recommendations without the need of large scale clinical trials.

Towards precision dosing of vancomycin in critically ill patients: an evaluation of the predictive performance of pharmacometric models in ICU patients.

OBJECTIVES: Vancomycin dose recommendations depend on population pharmacokinetic models. These models have not been adequately assessed in critically ill patients, who exhibit large pharmacokinetic variability. This study evaluated model predictive performance in intensive care unit (ICU) patients and identified factors influencing model performance. METHODS: Retrospective data from ICU adult patients administered vancomycin were used to evaluate model performance to predict serum concentrations a priori (no observed concentrations included) or with Bayesian forecasting (using concentration data). Predictive performance was determined using relative bias (rBias, bias) and relative root mean squared error (rRMSE, precision). Models were considered clinically acceptable if rBias was between ±20% and 95% confidence intervals included zero. Models were compared with rRMSE; no threshold was used. The influence of clinical factors on model performance was assessed with multiple linear regression. RESULTS: Data from 82 patients were used to evaluate 12 vancomycin models. The Goti model was the only clinically acceptable model with both a priori (rBias 3.4%) and Bayesian forecasting (rBias 1.5%) approaches. Bayesian forecasting was superior to a priori prediction, improving with the use of more recent concentrations. Four models were clinically acceptable with Bayesian forecasting. Renal replacement therapy status (p < 0.001) and sex (p = 0.007) significantly influenced the performance of the Goti model. CONCLUSIONS: The Goti, Llopis and Roberts models are clinically appropriate to inform vancomycin dosing in critically ill patients. Implementing the Goti model in dose prediction software could streamline dosing across both ICU and non-ICU patients, considering it is also the most accurate model in non-ICU patients.

How to design a study to evaluate therapeutic drug monitoring in infectious diseases?

BACKGROUND: Therapeutic drug monitoring (TDM) is a tool to personalize and optimize dosing by measuring the drug concentration and subsequently adjusting the dose to reach a target concentration or exposure. The evidence to support TDM is however often ranked as expert opinion. Limitations in study design and sample size have hampered definitive conclusions of the potential added value of TDM. OBJECTIVES: We aim to give expert opinion and discuss the main points and limitations of available data from antibiotic TDM trials and emphasize key elements for consideration in design of future clinical studies to quantify the benefits of TDM. SOURCES: The sources were peer-reviewed publications, guidelines and expert opinions from the field of TDM. CONTENT: This review focuses on key aspects of antimicrobial TDM study design: describing the rationale for a TDM study, assessing the exposure of a drug, assessing susceptibility of pathogens and selecting appropriate clinical endpoints. Moreover we provide guidance on appropriate study design. IMPLICATIONS: This is an overview of different aspects relevant for the conduct of a TDM study. We believe that this paper will help researchers and clinicians to design and conduct high-quality TDM studies.

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.

Translational Pharmacometric Evaluation of Typical Antibiotic Broad-Spectrum Combination Therapies Against Staphylococcus Aureus Exploiting In Vitro Information.

Broad-spectrum antibiotic combination therapy is frequently applied due to increasing resistance development of infective pathogens. The objective of the present study was to evaluate two common empiric broad-spectrum combination therapies consisting of either linezolid (LZD) or vancomycin (VAN) combined with meropenem (MER) against Staphylococcus aureus (S. aureus) as the most frequent causative pathogen of severe infections. A semimechanistic pharmacokinetic-pharmacodynamic (PK-PD) model mimicking a simplified bacterial life-cycle of S. aureus was developed upon time-kill curve data to describe the effects of LZD, VAN, and MER alone and in dual combinations. The PK-PD model was successfully (i) evaluated with external data from two clinical S. aureus isolates and further drug combinations and (ii) challenged to predict common clinical PK-PD indices and breakpoints. Finally, clinical trial simulations were performed that revealed that the combination of VAN-MER might be favorable over LZD-MER due to an unfavorable antagonistic interaction between LZD and MER.

[Pharmacokinetics and pharmacodynamics of antibiotic therapy]. / Pharmakokinetik und Pharmakodynamik der Antibiotikatherapie.

Antibiotic agents are crucial pillars in intensive care medicine and must be used rationally and sensibly. In the case of critically ill patients optimal dosing with respect to pharmacokinetic and pharmacodynamic principles (PK/PD) can be vital. Preclinical results demonstrated important differences between antibiotic classes and gave rise to differing clinical dosing strategies, e.g. high dose once daily regimens for aminoglycosides or extended/continuous infusion of betalactams. Critically ill patients with altered pharmacokinetic parameters and infections by pathogens with low susceptibility are most likely to benefit from PK/PD-guided therapy.