Pharmacokinetic-Pharmacodynamic Target Attainment Analyses To Determine Optimal Dosing of Ceftazidime-Avibactam for the Treatment of Acute Pulmonary Exacerbations in Patients with Cystic Fibrosis

Abstract

Acute pulmonary exacerbations (APE) involving Pseudomonas aeruginosa are associated with increased morbidity and mortality in cystic fibrosis (CF) patients. Drug resistance is a significant challenge to treatment. Ceftazidime-avibactam (CZA) demonstrates excellent in vitro activity against isolates recovered from CF patients, including drug-resistant strains. Altered pharmacokinetics (PK) of several beta-lactam antibiotics have been reported in CF patients. Therefore, this study sought to characterize the PK of CZA and perform target attainment analyses to determine the optimal treatment regimen. The PK of CZA in 12 adult CF patients administered 3 intravenous doses of 2.5 g every 8 h infused over 2 h were determined. Population modeling utilized the maximum likelihood expectation method. Monte Carlo simulations determined the probability of target attainment (PTA). An exposure target consisting of the cumulative percentage of a 24-h period that the free drug concentration exceeds the MIC under steady-state pharmacokinetic conditions (fT>MIC) was evaluated for ceftazidime (CAZ), and an exposure target consisting of the cumulative percentage of a 24-h period that the free drug concentration exceeds a 1-mg/liter threshold concentration (fT>1 mg/liter) was evaluated for avibactam (AVI). Published CAZ and CZA MIC distributions were incorporated to evaluate cumulative response probabilities. CAZ and AVI were best described by one-compartment models. The values of total body clearance (CL; CAZ CL, 7.53 ± 1.28 liters/h; AVI CL, 12.30 ± 1.96 liters/h) and volume of distribution (V; CAZ V, 18.80 ± 6.54 liters; AVI V, 25.30 ± 4.43 liters) were broadly similar to published values for healthy adults. CZA achieved a PTA (fT>MIC, 50%) of >0.9 for MICs of ≤16 mg/liter. The overall likelihood of a treatment response was 0.82 for CZA, whereas it was 0.42 for CAZ. These data demonstrate improved pharmacodynamics of CZA in comparison with those of CAZ and provide guidance on the optimal dosing of CZA for future studies. (This study has been registered at ClinicalTrials.gov under registration no. NCT02504827.).

Keywords: antipseudomonal; avibactam; ceftazidime; cystic fibrosis; pharmacodynamics; pharmacokinetics.

Copyright © 2017 American Society for Microbiology.

Figures

FIG 1

Observed CAZ plasma concentrations, model-predicted CAZ plasma concentrations, and goodness-of-fit of CAZ plasma concentrations after multiple administrations of CZA i.v. via a 2-h infusion in adults with CF. (A) Spaghetti plot of CAZ concentrations. (B) Summary of observed CAZ concentration-time profiles after the 3rd dose overlaid with the mean of the individual model predictions (Model Pred). (C to F) Goodness-of-fit plots of final population PK model: individual measured CAZ concentrations versus population prediction (C) or individual prediction (D), conditional standardized residuals (Cond. Std. Resid.) versus time after dose (E), and conditional standardized residuals versus individual prediction (F). Drug concentrations are plotted on a log10 scale. Summarized observed data are presented as the mean ± SD (n = 12).

FIG 2

Observed AVI plasma concentrations, model-predicted AVI plasma concentrations, and goodness-of-fit of AVI plasma concentrations after multiple administrations of CZA i.v. with a 2-h infusion in adults with CF. (A) Spaghetti plot of AVI concentrations. (B) Summary of observed AVI concentration-time profiles after the 3rd dose overlaid with the mean of the individual model predictions (Model Pred). (C to F) Goodness-of-fit plots of final population PK model: individual measured AVI concentrations versus population prediction (C) or individual prediction (D), conditional standardized residuals (Cond. Std. Resid.) versus time after dose (E), and conditional standardized residuals versus individual prediction (F). Drug concentrations are plotted on a log10 scale. Summarized observed data are represented as the mean ± SD (n = 12).

FIG 3

Probability of target attainment for discrete CZA MICs for Pseudomonas aeruginosa isolates recovered from CF patients under steady-state conditions. (A) Probability of target attainment and cumulative response of P. aeruginosa to CZA over the MIC distribution for CZA at 2.5 g infused over 2 h every 8 h. (B) Probability of target attainment dependent on infusion time for discrete MICs of 8, 16, and 32 mg/liter using a 1,000-patient Monte Carlo simulation trial incorporating PK variability from a one-compartment base model derived from data for 12 adult CF patients. The target was defined as an fT>MIC of 50% for CAZ and an fT>1 mg/liter of 50% for AVI. The distribution of the CZA MICs for P. aeruginosa isolates from patients with CF was digitized from previously published data (10).

FIG 4

Relationship between infusion time and probability of target attainment by CZA MICs for Pseudomonas aeruginosa recovered from patients with CF under steady-state conditions. The fraction achieving exposure targets of fT>MICs of 40, 50, 65, and 100% by various infusion times for MICs of 8 mg/liter (A), 16 mg/liter (B), and 32 mg/liter (C) using a 1,000-patient Monte Carlo simulation trial incorporating PK variability from a one-compartment base model derived from 12 adult CF patients is shown.