Pharmacokinetic variability and exposures of fluconazole, anidulafungin, and caspofungin in intensive care unit patients: Data from multinational Defining Antibiotic Levels in Intensive care unit (DALI) patients Study.

INTRODUCTION: The objective of the study was to describe the pharmacokinetics (PK) of fluconazole, anidulafungin, and caspofungin in critically ill patients and to compare with previously published data. We also sought to determine whether contemporary fluconazole doses achieved PK/pharmacodynamic (PD; PK/PD) targets in this cohort of intensive care unit patients. METHODS: The Defining Antibiotic Levels in Intensive care unit patients (DALI) study was a prospective, multicenter point-prevalence PK study. Sixty-eight intensive care units across Europe participated. Inclusion criteria were met by critically ill patients administered fluconazole (n = 15), anidulafungin (n = 9), and caspofungin (n = 7). Three blood samples (peak, mid-dose, and trough) were collected for PK/PD analysis. PK analysis was performed by using a noncompartmental approach. RESULTS: The mean age, weight, and Acute Physiology and Chronic Health Evaluation (APACHE) II scores of the included patients were 58 years, 84 kg, and 22, respectively. Fluconazole, caspofungin, and anidulafungin showed large interindividual variability in this study. In patients receiving fluconazole, 33% did not attain the PK/PD target, ratio of free drug area under the concentration-time curve from 0 to 24 hours to minimum inhibitory concentration (fAUC(0-24)/MIC) ≥100. The fluconazole dose, described in milligrams per kilogram, was found to be significantly associated with achievement of fAUC(0-24)/MIC ≥100 (P = 0.0003). CONCLUSIONS: Considerable interindividual variability was observed for fluconazole, anidulafungin, and caspofungin. A large proportion of the patients (33%) receiving fluconazole did not attain the PK/PD target, which might be related to inadequate dosing. For anidulafungin and caspofungin, dose optimization also appears necessary to minimize variability.