Nine static models (seven basic and two mechanistic) and their respective cutoff values used for predicting cytochrome P450 3A (CYP3A) inhibition, as recommended by the US Food and Drug Administration and the European Medicines Agency, were evaluated using data from 119 clinical studies with orally administered midazolam as a substrate. Positive predictive error (PPE) and negative predictive error (NPE) rates were used to assess model performance, based on a cutoff of 1.25-fold change in midazolam area under the curve (AUC) by inhibitor. For reversible inhibition, basic models using total or unbound systemic inhibitor concentration [I] had high NPE rates (46-47%), whereas those using intestinal luminal ([I]gut) values had no NPE but a higher PPE. All basic models for time-dependent inhibition had no NPE and reasonable PPE rates (15-18%). Mechanistic static models that incorporate all interaction mechanisms and organ specific [I] values (enterocyte and hepatic inlet) provided a higher predictive precision, a slightly increased NPE, and a reasonable PPE. Various cutoffs for predicting the likelihood of CYP3A inhibition were evaluated for mechanistic models, and a cutoff of 1.25-fold change in midazolam AUC appears appropriate.
What is already known about this subject • Itraconazole is a triazole antifungal used in the treatment of allergic bronchopulmonary aspergillosis in patients with cystic fibrosis (CF). • The pharmacokinetic (PK) properties of this drug and its active metabolite have been described before, mostly in healthy volunteers. • However, only sparse information from case reports were available of the PK properties of this drug in CF patients at the start of our study. What this study adds • This study reports for the first time the population pharmacokinetic properties of itraconazole and a known active metabolite, hydroxy‐itraconazole in adult patients with CF. • As a result, this study offers new dosing approaches and their pharmacoeconomic impact as well as a PK model for therapeutic drug monitoring of this drug in this patient group. • Furthermore, it is an example of a successful d‐optimal design application in a clinical setting. Aim The primary objective of the study was to estimate the population pharmacokinetic parameters for itraconazole and hydroxy‐itraconazole, in particular, the relative oral bioavailability of the capsule compared with solution in adult cystic fibrosis patients, in order to develop new dosing guidelines. A secondary objective was to evaluate the performance of a population optimal design. Methods The blood sampling times for the population study were optimized previously using POPT v.2.0. The design was based on the administration of solution and capsules to 30 patients in a cross‐over study. Prior information suggested that itraconazole is generally well described by a two‐compartment disposition model with either linear or saturable elimination. The pharmacokinetics of itraconazole and the metabolite were modelled simultaneously using NONMEM. Dosing schedules were simulated to assess their ability to achieve a trough target concentration of 0.5 mg ml−1. Results Out of 241 blood samples, 94% were taken within the defined optimal sampling windows. A two‐compartment model with first order absorption and elimination best described itraconazole kinetics, with first order metabolism to the hydroxy‐metabolite. For itraconazole the absorption rate constants (between‐subject variability) for capsule and solution were 0.0315 h−1 (91.9%) and 0.125 h−1 (106.3%), respectively, and the relative bioavailability of the capsule was 0.82 (62.3%) (confidence interval 0.36, 1.97), compared with the solution. There was no evidence of nonlinearity. Simulations from the final model showed that a dosing schedule of 500 mg twice daily for both formulations provided the highest chance of target success. Conclusion The optimal design performed well and the pharmacokinetics of itraconazole and hydroxy‐itraconazole were described adequately by the model. The relative bioavailability for itraconazole capsules was 82% compared with the solution.
Optimal sampling times are found for a study in which one of the primary purposes is to develop a model of the pharmacokinetics of itraconazole in patients with cystic fibrosis for both capsule and solution doses. The optimal design is expected to produce reliable estimates of population parameters for two different structural PK models. Data collected at these sampling times are also expected to provide the researchers with sufficient information to reasonably discriminate between the two competing structural models.
Evacetrapib is a novel cholesteryl ester transfer protein (CETP) inhibitor currently being evaluated in a late-stage cardiovascular outcome trial. Using population-based models, we analyzed evacetrapib concentration data along with high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) data from a 12-week study in dyslipidemic patients treated with evacetrapib alone or in combination with atorvastatin, simvastatin, or rosuvastatin. Evacetrapib pharmacokinetics were characterized using a two-compartment model with first-order absorption. Evacetrapib exposure increased in a less than dose-proportional manner, similar to other CETP inhibitors. No patient factors had a clinically relevant impact on evacetrapib pharmacokinetics. The relationships between evacetrapib exposure and HDL-C and LDL-C were characterized using Emax models. The theoretical maximal mean HDL-C increase and LDL-C decrease relative to baseline were 177 and 44.1%, respectively. HDL-C change from baseline was found to be negatively correlated with baseline HDL-C. A pharmacologically independent LDL-C reduction was found when evacetrapib was coadministered with statins.
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