Pharmacokinetic/Pharmacodynamic Target Attainment of Different Antifungal Agents in De-escalation Treatment in Critically Ill Patients: a Step toward Dose Optimization Using Monte Carlo Simulation.

Differences in pharmacokinetics/pharmacodynamics (PK/PD) target attainment are rarely considered when antifungals are switched in critically ill patients. This study intends to explore whether the antifungal de-escalation treatment strategy and the new intermittent dosing strategy of echinocandins in critically ill patients are able to achieve the corresponding PK/PD targets. The published population PK models of antifungals in critically ill patients and a public data set from the MIMIC-III database (n = 662) were employed to evaluate PK/PD target attainment of different dosing regimens of antifungals. Cumulative fraction of response (CFR) was calculated for each dosing regimen. Most guideline-recommended dosing regimens of fluconazole and voriconazole could achieve target exposure as de-escalation treatment in critically ill patients. For initial echinocandin treatment, achievement of the target exposure decreased as body weight increased, and the intermittent dosing strategy had a slightly higher CFR value in most simulations compared to conventional dosing strategy. For Candida albicans and Candida glabrata infection, caspofungin at the lowest dose achieved a CFR of >90%, while micafungin or anidulafungin required almost the highest doses simulated in this study to achieve the same effect. None of the echinocandins other than 150 mg every 24 h (q24h) or 200 mg q48h of caspofungin achieved the target CFR for Candida parapsilosis infection. These findings support the guideline-recommended dose of triazoles for antifungal de-escalation treatment and confirm the insufficient dosage of echinocandins in critically ill patients, indicating that a dosing regimen based on body weight or intermittent dosing of echinocandins may be required.

A strategy for designing voriconazole dosage regimens to prevent invasive pulmonary aspergillosis based on a cellular pharmacokinetics/pharmacodynamics model.

BACKGROUND: Invasive pulmonary aspergillosis (IPA) is a life-threatening disease in immunosuppressed patients. Voriconazole is commonly used to prevent and treat IPA in the clinic, but the optimal prophylactic antifungal regimen is unknown. The objective of this study was to clarify the mechanism underlying how voriconazole prevents IPA based on a target cellular pharmacokinetics/pharmacodynamics model, with the aim of identifying a way to design an optimal prophylactic antifungal regimen. METHODS: A nystatin assay was used to establish a target-cells model for A. fumigatus infection. An inhibitory effect sigmoid Emax model was developed to explore the cellular PK/PD breakpoint, and Monte Carlo simulation was used to design the prophylactic antifungal regimen. RESULTS: The intracellular activity of voriconazole in the target cells varied with its concentration, with the minimum inhibitory concentration (MIC) being an important determinant. For A. fumigatus strains AF293 and AF26, voriconazole decreased the intracellular inoculum by 0.79 and 0.84 lg cfu, respectively. The inhibitory effect sigmoid Emax model showed that 84.01% of the intracellular inoculum was suppressed by voriconazole within 24 h, and that a PK/PD value of 35.53 for the extracellular voriconazole concentration divided by MIC was associated with a 50% suppression of intracellular A. fumigatus. The Monte Carlo simulation results showed that the oral administration of at least 200 mg of voriconazole twice daily was yielded estimated the cumulative fraction of response value of 91.48%. Concentration of voriconazole in the pulmonary epithelial lining fluid and the plasma of > 17.77 and > 1.55 mg/L, respectively, would ensure the PK/PD > 35.53 for voriconazole against most isolates of A. fumigatus and may will be benefit to prevent IPA in clinical applications. CONCLUSIONS: This study used a target cellular pharmacokinetics/pharmacodynamics model to reveal a potential mechanism underlying how voriconazole prevents IPA and has provided a method for designing voriconazole prophylactic antifungal regimen in immunosuppressed patients.

Population Pharmacokinetics of Tigecycline in Critically Ill Patients with Severe Infections.

We sought to describe the population pharmacokinetics of tigecycline in critically ill patients and to determine optimized dosing regimens of tigecycline for different bacterial infections. This prospective study included 10 critically ill patients given a standard dose of tigecycline. Blood samples were collected during one dosing interval and were analyzed using validated chromatography. Population pharmacokinetics and Monte Carlo dosing simulations were undertaken using Pmetrics. Three target exposures, expressed as ratios of the 24-h area under the curve to MICs (AUC0-24/MIC), were evaluated (≥17.9 for skin infections, ≥6.96 for intra-abdominal infections, ≥4.5 for hospital-acquired pneumonia). The median age, total body weight, and body mass index (BMI) were 67 years, 69.1 kg, and 24.7 kg/m2, respectively. A two-compartment linear model best described the time course of tigecycline concentrations. The parameter estimates (expressed as means ± standard deviations [SD]) from the final model were as follows: clearance (CL), 7.50 ± 1.11 liters/h; volume in the central compartment, 72.50 ± 21.18 liters; rate constant for tigecycline distribution from the central to the peripheral compartment, 0.31 ± 0.16 h-1; and rate constant for tigecycline distribution from the peripheral to the central compartment, 0.29 ± 0.30 h-1 A larger BMI was associated with increased CL of tigecycline. Licensed doses were found to be sufficient for Enterobacter cloacae, Escherichia coli, Klebsiella pneumoniae, and methicillin-resistant Staphylococcus aureus for an AUC0-24/MIC target of 4.5 or 6.96. For a therapeutic target of 17.9, an increased tigecycline dose is required, especially for patients with higher BMI. The dosing requirements of tigecycline differ with the indication, with pathogen susceptibility, and potentially with patient BMI.