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.