Drug metabolism and disposition : the biological fate of chemicals
-
Drug Metab. Dispos. · Apr 2017
Randomized Controlled TrialA Physiologically-Based Pharmacokinetic Modeling Approach To Predict Drug-Drug Interactions of Sonidegib (LDE225) with Perpetrators of CYP3A in Cancer Patients.
Sonidegib (Odomzo) is an orally available Smoothened inhibitor for the treatment of advanced basal cell carcinoma. Sonidegib was found to be metabolized primarily by cytochrome P450 (CYP)3A in vitro. The effect of multiple doses of the strong CYP3A perpetrators, ketoconazole (KTZ) and rifampin (RIF), on sonidegib pharmacokinetics (PK) after a single 800 mg dose in healthy subjects was therefore assessed. ⋯ The effect of KTZ and RIF on sonidegib in healthy subjects was also simulated well, and the predicted DDI in patients was slightly less and independent of sonidegib dose. At steady state, sonidegib was predicted to have a higher DDI magnitude with strong or moderate CYP3A perpetrators compared with a single dose. Different dosing regimens of sondigeb with the perpetrators were also simulated and provided guidance to the current dosing recommendations incorporated in the product label.
-
Drug Metab. Dispos. · Apr 2017
Application of Physiologically Based Pharmacokinetic Modeling to the Understanding of Bosutinib Pharmacokinetics: Prediction of Drug-Drug and Drug-Disease Interactions.
Bosutinib is an orally available Src/Abl tyrosine kinase inhibitor indicated for the treatment of patients with Philadelphia chromosome-positive chronic myelogenous leukemia. Bosutinib is predominantly metabolized by CYP3A4 as the primary clearance mechanism. The main objectives of this study were to 1) develop physiologically based pharmacokinetic (PBPK) models of bosutinib; 2) verify and refine the PBPK models based on clinical study results of bosutinib single-dose drug-drug interaction (DDI) with ketoconazole and rifampin, as well as single-dose drug-disease interaction (DDZI) in patients with renal and hepatic impairment; 3) apply the PBPK models to predict DDI outcomes in patients with weak and moderate CYP3A inhibitors; and 4) apply the PBPK models to predict DDZI outcomes in renally and hepatically impaired patients after multiple-dose administration. ⋯ The PBPK models also reasonably predicted changes in bosutinib exposures in the single-dose DDI and DDZI results, suggesting that the PBPK models were sufficiently developed and verified based on the currently available data. Finally, the PBPK models predicted 2- to 4-fold increases in bosutinib exposures by moderate CYP3A inhibitors, as well as comparable increases in bosutinib exposures in renally and hepatically impaired patients between single- and multiple-dose administrations. Given the challenges in conducting numerous DDI and DDZI studies of anticancer drugs in patients, we believe that the PBPK models verified in our study would be valuable to reasonably predict bosutinib exposures under various scenarios that have not been tested clinically.