Effect of Food on the Pharmacokinetics of the Investigational Aurora A Kinase Inhibitor Alisertib (MLN8237) in Patients with Advanced Solid Tumors.

ObjectiveThis study was conducted to characterize the effects of food on single-dose pharmacokinetics (PK) of the investigational Aurora A kinase inhibitor alisertib (MLN8237) in patients with advanced solid tumors.MethodsFollowing overnight fasting for 10 h, a single 50 mg enteric-coated tablet (ECT) of alisertib was administered under either fasted (alisertib with 240 mL of water) or fed (high-fat meal consumed 30 min before receiving alisertib with 240 mL of water) conditions using a two-cycle, two-way crossover design. Patients on both arms were not allowed food for 4 h post-dose. Water was allowed as desired, except for 1 h before and after alisertib administration.ResultsTwenty-four patients were enrolled and 14 patients were PK-evaluable (ten patients were not PK-evaluable due to insufficient data). Following a single oral dose of alisertib, median t max was 6 h and 3 h under fed and fasted conditions, respectively. The geometric mean ratio of AUCinf (fed- vs. fasted-state dosing) was 0.94 [90% confidence interval (CI) 0.68-1.32]. The geometric mean C max under fed conditions was 84% of that under fasted conditions (90% CI 66-106). Alisertib was generally well-tolerated; most common drug-related grade 3/4 adverse events included neutropenia (50%), leukopenia (38%), and thrombocytopenia (21%).ConclusionsSystemic exposures achieved following a single 50 mg dose of alisertib administered as an ECT formulation after a high-fat meal are similar to those observed in the fasted state. Alisertib 50 mg ECT can be administered without regard for food. CLINICALTRIALS.Gov identifierNCT00962091

Drug–Drug Interaction Potential of Marketed Oncology Drugs: In Vitro Assessment of Time-Dependent Cytochrome P450 Inhibition, Reactive Metabolite Formation and Drug–Drug Interaction Prediction

Purpose: To evaluate 26 marketed oncology drugs for time-dependent inhibition (TDI) of cytochrome P450 (CYP) enzymes. Evaluate TDI-positive drugs for potential to generate reactive intermediates. Assess clinical drug-drug interaction (DDI) risk using static mechanistic models. Methods: Human liver microsomes and CYP-specific probes were used to assess TDI in a dilution shift assay followed by generation of K I and k inact. Reactive metabolite trapping studies were performed with stable label probes. Static mechanistic model was used to predict DDI risk using a 1.25-fold AUC increase as a cut-off for positive DDI. Results: Negative TDI across CYPs was observed for 13/26 drugs; the rest were time-dependent inhibitors of, predominantly, CYP3A. The k inact/K I ratios for 11 kinase inhibitors ranged from 0.7 to 42.2 ml/min/μmol. Stable label trapping agent-drug conjugates were observed for ten kinase inhibitors. DDI predictions gave no false negatives, one true negative, four false positives and three true positives. The magnitude of DDI was overestimated irrespective of the inhibitor concentration selected. Conclusions: 13/26 oncology drugs investigated showed TDI potential towards CYP3A, formation of reactive metabolites was also observed. An industry standard static mechanistic model gave no false negative predictions but did not capture the modest clinical DDI potential of kinase inhibitors. © 2012 Springer Science+Business Media, LLC