Development of a population pharmacokinetic model and optimal sampling strategies for intravenous ciprofloxacin

Abstract

Data obtained from 74 acutely ill patients treated in two clinical efficacy trials were used to develop a population model of the pharmacokinetics of intravenous (i.v.) ciprofloxacin. Dosage regimens ranged between 200 mg every 12 h and 400 mg every 8 h. Plasma samples (2 to 19 per patient; mean +/- standard deviation = 7 +/- 5) were obtained and assayed (by high-performance liquid chromatography) for ciprofloxacin. These data and patient covariates were modelled by iterative two-stage analysis, an approach which generates pharmacokinetic parameter values for both the population and each individual patient. The final model was used to implement a maximum a posteriori-Bayesian pharmacokinetic parameter value estimator. Optimal sampling theory was used to determine the best (maximally informative) two-, three-, four-, five-, and six-sample study designs (e.g., optimal sampling strategy 2 [OSS2] was the two-sample strategy) for identifying a patient's pharmacokinetic parameter values. These OSSs and the population model were evaluated by selecting the relatively rich data sets, those with 7 to 10 samples obtained in a single dose interval (n = 29), and comparing the parameter estimates (obtained by the maximum a posteriori-Bayesian estimator) based on each of the OSSs with those obtained by fitting all of the available data from each patient. Distributional clearance and apparent volumes were significantly related to body size (e.g., weight in kilograms or body surface area in meters squared); plasma clearance (CLT in liters per hour) was related to body size and renal function (creatinine clearance [CLCR] in milliliters per minute per 1.73 m2) by the equation CLT = (0.00145.CLCR + 0.167).weight. However, only 30% of the variance in CLT was explained by this relationship, and no other patient covariates were significant. Compared with previously published data, this target population had smaller distribution volumes (by 30%; P < 0.01) and CLT (by 44%; P < 0.001) than weight- and CLCR- matched stable volunteers. OSSs provided parameter estimates that showed good to excellent estimates of CLT (or area under the concentrations-time curve [AUC]) were unbiased and precise (e.g., r2 for AUC for all data versus AUC for OSS2 was > 0.99) and concentration-time profiles were accurately reconstructed. These results will be used to model the pharmacodynamic relationships between ciprofloxacin exposure and response and to aid in developing algorithms for individual optimization of ciprofloxacin dosage regimens.