Prediction of Drug-Drug-Gene Interaction Scenarios of (<i>E</i>)-Clomiphene and Its Metabolites Using Physiologically Based Pharmacokinetic Modeling

• Main Authors: Christina Kovar (Author), Lukas Kovar (Author), Simeon Rüdesheim (Author), Dominik Selzer (Author), Boian Ganchev (Author), Patrick Kröner (Author), Svitlana Igel (Author), Reinhold Kerb (Author), Elke Schaeffeler (Author), Thomas E. Mürdter (Author), Matthias Schwab (Author), Thorsten Lehr (Author)
• Format: Book
• Published: MDPI AG, 2022-11-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Summary

Clomiphene, a selective estrogen receptor modulator (SERM), has been used for the treatment of anovulation for more than 50 years. However, since (<i>E</i>)-clomiphene ((<i>E</i>)-Clom) and its metabolites are eliminated primarily via Cytochrome P450 (CYP) 2D6 and CYP3A4, exposure can be affected by CYP2D6 polymorphisms and concomitant use with CYP inhibitors. Thus, clomiphene therapy may be susceptible to drug-gene interactions (DGIs), drug-drug interactions (DDIs) and drug-drug-gene interactions (DDGIs). Physiologically based pharmacokinetic (PBPK) modeling is a tool to quantify such DGI and DD(G)I scenarios. This study aimed to develop a whole-body PBPK model of (<i>E</i>)-Clom including three important metabolites to describe and predict DGI and DD(G)I effects. Model performance was evaluated both graphically and by calculating quantitative measures. Here, 90% of predicted C_max and 80% of AUC_last values were within two-fold of the corresponding observed value for DGIs and DD(G)Is with clarithromycin and paroxetine. The model also revealed quantitative contributions of different CYP enzymes to the involved metabolic pathways of (<i>E</i>)-Clom and its metabolites. The developed PBPK model can be employed to assess the exposure of (<i>E</i>)-Clom and its active metabolites in as-yet unexplored DD(G)I scenarios in future studies.

Item Description

10.3390/pharmaceutics14122604
1999-4923