Physiologically Based Pharmacokinetic Modelling of Hyperforin to Predict Drug Interactions with St John’s Wort

Background and Objectives: Herb–drug interactions with St John’s wort (SJW) have been widely studied in numerous clinical studies. The objective of this study was to develop and evaluate a physiologically based pharmacokinetic (PBPK) model for hyperforin (the constituent of SJW responsible for interactions), which has the potential to provide unique insights into SJW interactions and allow prediction of the likely extent of interactions with SJW compared to published interaction reports. Methods: A PBPK model of hyperforin accounting for the induction of cytochrome P450 (CYP) 3A, CYP2C9 and CYP2C19 was developed in the Simcyp Simulator (version 17) and verified using published, clinically observed pharmacokinetic data. The predictive performance of this model based on the prediction fold-difference (expressed as the ratio of predicted and clinically observed change in systemic exposure of drug) was evaluated across a range of CYP substrates. Results: The verified PBPK model predicted the change in victim drug exposure due to the induction by SJW (expressed as area under the plasma concentration–time curve (AUC) ratio) within 1.25-fold (0.80–1.25) of that reported in clinical studies. The PBPK simulation indicated that the unbound concentration of hyperforin in the liver was far lower than in the gut (enterocytes). Simulations revealed that induction of intestinal CYP enzymes by hyperforin was found to be more pronounced than the corresponding increase in liver CYP activity (15.5- vs. 1.1-fold, respectively, at a hyperforin dose of 45 mg/day). Conclusion: In the current study, a PBPK model for hyperforin was successfully developed, with a predictive capability for the interactions of SJW with different CYP3A, CYP2C9 and CYP2C19 substrates. This PBPK model is valuable to predict the extent of herb–drug interactions with SJW and help design the clinical interaction studies, particularly for new drugs and previously unstudied clinical scenarios.