4ß-OH Cholesterol as endogenous biomarker for CYP3A4 inducer DDI studies – a PBPK-QSP platform for in silico compound testing
Pavel Balazki (1), Ghazal Montaseri (2), Stephan Schaller (1), José David Gómez Mantilla (2)
(1) esqLABS GmbH, Saterland, Germany, (2) Boehringer Ingelheim Pharma GmbH & Co. KG Transl. Medicine + Clin. Pharmacology, Germany
Objectives:
Drug-drug interactions (DDIs) occur when one drug alters the pharmacokinetics (PK) or pharmacodynamics (PD) of another drug, potentially leading to adverse effects or therapeutic failure. DDIs are a major concern in drug development and clinical practice, particularly with drugs that are metabolized by cytochrome P450 (CYP) enzymes. Preclinical in vitro data often overpredict the ability of small molecules to DDI through the induction of CYP3A4. Therefore, in vivo human data are required. Traditionally, the potency of new drug candidates to induce CYP-mediated metabolism and, by that, to be involved in DDIs with CYP-cleared drugs is assessed in clinical studies by co-administration of sensitive index substrates such as midazolam. This approach is time- and cost-intensive and involves additional exposure of test subjects to medications. 4β-OH cholesterol (4bOH) has been suggested as an alternative endogenous biomarker for CYP3A4 induction (1).
The objective of this study is to develop a PBPK model for cholesterol and its metabolite 4bOH and qualify it for evaluation and prediction of CYP3A4 induction potential. The model should be then used in an automated R-framework for assessment of CYP3A4 induction potency of a drug candidate from in vitro or in vivo data.
Methods:
PBPK models of cholesterol and its metabolite 4bOH were developed with the Open Systems Pharmacology (OSP) Suite (2) and coupled with published inducer and victim models from the OSP CYP3A4-DDI network (3). The model was calibrated with published 4bOH data from perturbation scenarios with efavirenz and carbamazepine as CYP3A4 inducers. 23 DDI scenarios from the qualified database have been simulated, and area under the curve (AUC) ratios (AUCR) reported for index substrates were compared with predicted 4bOH AUCR and concentration ratios.
Results:
The developed model includes endogenous production of cholesterol in the gut and liver, cholesterol conversion to 4bOH by CYP3A4, and liver plasma clearance. 4bOH is eliminated through liver plasma clearance.
The model accurately describes the observed increase in 4bOH concentrations after the administration of CYP3A4 inducers. The predicted median 4bOH AUCR is 2.7, 1.87, 1.53, and 1.12 for observed midazolam AUCR <0.2, 0.2-0.5, 0.5-0.8, and >0.8, respectively.
Conclusions:
The developed PBPK-QSP model of 4bOH supports the idea of using 4bOH as a sensitive endogenous marker for CYP3A4 induction. Based on simulation results, 4bOH has a sensitivity comparable with oral administration of midazolam and is superior to intravenous midazolam administration. The model can be used to a) predict induction potency of a drug candidate from in vitro data or b) to estimate induction parameters from clinically measured 4bOH data. A future regulatory acceptance of 4bOH as an important biomarker could bridge the gap between overpredicting CYP3A4 induction from in vitro data and the need for clinical DDI studies with midazolam. This could save unnecessary DDI trials particularly in oncology or other fields, where exposure to the drug candidate should be kept to the minimum required.
References:
- Björkhem-Bergman L, Bäckström T, Nylén H, Rönquist-Nii Y, Bredberg E, Andersson TB, et al. Comparison of Endogenous 4β-Hydroxycholesterol with Midazolam as Markers for CYP3A4 Induction by Rifampicin. Drug Metab Dispos. 2013 Aug 1;41(8):1488–93.
- Open Systems Pharmacology Community. Open Systems Pharmacology [Internet]. 2018 [cited 2018 Feb 4]. Available from: www.open-systems-pharmacology.org
- Frechen S, Solodenko J, Wendl T, Dallmann A, Ince I, Lehr T, et al. A generic framework for the physiologically-based pharmacokinetic platform qualification of PK-Sim and its application to predicting cytochrome P450 3A4–mediated drug–drug interactions. CPT Pharmacomet Syst Pharmacol. 2021;10(6):633–44.
