BACKGROUND: Oncology therapy typically involves drug combinations since monotherapy seldom provides the desired outcome. But combination therapy presents the potential for drug-drug interactions (DDIs). Due to the narrow window between therapeutic concentrations and onset of toxicity often observed with oncology therapeutics, managing DDIs with combination therapy in cancer is critical. Physiologically based pharmacokinetic (PBPK) modeling can be effectively used for predicting DDIs and guiding dose-selection, but requires development of PBPK models of cancer drugs. Among various types of cancer, metastatic prostate cancer is an area of high unmet medical need with minimal therapeutic options. Recently, enzalutamide was approved for treatment of metastatic prostate cancer and is often dosed as a combination in clinical practice. Enzalutamide is a potent CYP3A inducer and a model-based approach to guide dose-selection for enzalutamide combinations that are CYP3A substrates is needed. OBJECTIVE: A "fit for purpose" PBPK model of enzalutamide was developed to illustrate the CYP3A4 induction potential, understand the kinetics of de-induction of CYP3A4 following cessation of enzalutamide dosing and guide dose-selection of a co-administered CYP3A substrate. METHOD: The population-based simulator, Simcyp, was used for model building purposes. Model input parameters were obtained from public information, primarily from the FDA summaries. RESULTS: The simulated concentration time profiles of enzalutamide in healthy male subjects were comparable to observed profiles in male patients. Model predicted enzalutamide pharmacokinetic (PK) parameters, i.e. AUC, Cmax and half-life were within 1.5-fold of observed results obtained from two reported studies, supporting verification of the PBPK model. Model application was demonstrated by simulating a drug-drug interaction between enzalutamide and midazolam, a sensitive CYP3A4 substrate. Based on simulations, the midazolam AUC ratio ranged from 0.06 to 0.16 and was comparable to the observed ratio of 0.14. Based on modeling, upon cessation of enzalutamide dosing, it is predicted that at least 8 weeks are needed to re-attain baseline CYP3A4 activity. Based on PBPK modeling, dose adjustment of up to 3-fold for a co-administered CYP3A substrate was shown to re-attain baseline exposure. CONCLUSION: A "fit for purpose" PBPK model of enzalutamide was successfully developed using public information that recapitulated it's observed pharmacokinetics, CYP3A4 induction potential and the potential need for dose-adjustment of co-administered CYP3A substrates.
BACKGROUND: Oncology therapy typically involves drug combinations since monotherapy seldom provides the desired outcome. But combination therapy presents the potential for drug-drug interactions (DDIs). Due to the narrow window between therapeutic concentrations and onset of toxicity often observed with oncology therapeutics, managing DDIs with combination therapy in cancer is critical. Physiologically based pharmacokinetic (PBPK) modeling can be effectively used for predicting DDIs and guiding dose-selection, but requires development of PBPK models of cancer drugs. Among various types of cancer, metastatic prostate cancer is an area of high unmet medical need with minimal therapeutic options. Recently, enzalutamide was approved for treatment of metastatic prostate cancer and is often dosed as a combination in clinical practice. Enzalutamide is a potent CYP3A inducer and a model-based approach to guide dose-selection for enzalutamide combinations that are CYP3A substrates is needed. OBJECTIVE: A "fit for purpose" PBPK model of enzalutamide was developed to illustrate the CYP3A4 induction potential, understand the kinetics of de-induction of CYP3A4 following cessation of enzalutamide dosing and guide dose-selection of a co-administered CYP3A substrate. METHOD: The population-based simulator, Simcyp, was used for model building purposes. Model input parameters were obtained from public information, primarily from the FDA summaries. RESULTS: The simulated concentration time profiles of enzalutamide in healthy male subjects were comparable to observed profiles in male patients. Model predicted enzalutamide pharmacokinetic (PK) parameters, i.e. AUC, Cmax and half-life were within 1.5-fold of observed results obtained from two reported studies, supporting verification of the PBPK model. Model application was demonstrated by simulating a drug-drug interaction between enzalutamide and midazolam, a sensitive CYP3A4 substrate. Based on simulations, the midazolam AUC ratio ranged from 0.06 to 0.16 and was comparable to the observed ratio of 0.14. Based on modeling, upon cessation of enzalutamide dosing, it is predicted that at least 8 weeks are needed to re-attain baseline CYP3A4 activity. Based on PBPK modeling, dose adjustment of up to 3-fold for a co-administered CYP3A substrate was shown to re-attain baseline exposure. CONCLUSION: A "fit for purpose" PBPK model of enzalutamide was successfully developed using public information that recapitulated it's observed pharmacokinetics, CYP3A4 induction potential and the potential need for dose-adjustment of co-administered CYP3A substrates.
Authors: Eleni Efstathiou; Mark Titus; Sijin Wen; Patricia Troncoso; Anh Hoang; Paul Corn; Ina Prokhorova; John Araujo; Carl Dmuchowski; Amal Melhem-Bertrandt; Shiva Patil; Christopher J Logothetis Journal: Eur Urol Oncol Date: 2019-04-20
Authors: Riikka Huhtaniemi; Petra Sipilä; Arttu Junnila; Riikka Oksala; Matias Knuuttila; Arfa Mehmood; Eija Aho; Teemu D Laajala; Tero Aittokallio; Asta Laiho; Laura Elo; Claes Ohlsson; Malin Hagberg Thulin; Pekka Kallio; Sari Mäkelä; Mika V J Mustonen; Matti Poutanen Journal: iScience Date: 2022-04-25