Fatima Zahra Marok (1), Jan-Georg Wojtyniak (1), Laura Maria Fuhr (1), Matthias Schwab (2,3,4), Johanna Weiss (4,5), Walter Emil Haefeli (4,5), Thorsten Lehr (1)
(1) Department of Clinical Pharmacy, Saarland University, Saarbrücken, Germany (2) Dr. Margarete Fischer-Bosch-Institut of Clinical Pharmacology, Stuttgart, Germany (3) Departments of Clinical Pharmacology, Pharmacy and Biochemistry, University Hospital Tübingen, Tübingen, Germany (4) Cluster of excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University Tübingen, Tübingen, Germany (4) Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Germany (5) German Center for Infection Research (DZIF), Heidelberg Partner Site, Germany
Introduction: The antimycotic drug ketoconazole is well known for its strong drug-drug interaction (DDI) potential [1]. As a substrate and potent inhibitor of cytochrome P450 (CYP) 3A4, among other proteins, co-administration of ketoconazole with victim compounds can lead to tremendous increases in drug exposure. For example, administration of 400 mg ketoconazole over 4 days can lead to a 15-fold increase in the area under the plasma concentration-time curve of midazolam [2]. However, since ketoconazole inhibits CYP3A4 reversibly and has a mean half-life of 160 min (after a 400 mg dose) [3], long-term inhibitory effects cannot be explained solely by involvement of ketoconazole [4]. Weiss et al. successfully investigated the inhibitory effect of N-deacetyl ketoconazole, a metabolite formed by the arylacetamide deacetylase (AADAC) [1]. It was reported that N-deacetyl ketoconazole inhibited the same enzymes and transporters as ketoconazole itself, including CYP3A4 or P-glycoprotein (P-gp) [1]. Based on the structural similarities between ketoconazole and N-deacetyl ketoconazole, it can be assumed that N-deacetyl ketoconazole may be responsible for long-term inhibitory effects of ketoconazole [5].
Objectives:
- To build a physiologically-based pharmacokinetic (PBPK) model for ketoconazole and its metabolite N-deacetyl ketoconazole
- To predict DDIs of ketoconazole and its metabolite as perpetrator drugs with the victim drugs midazolam, alprazolam, triazolam (CYP3A4 victim drugs), and digoxin (P‑gp victim drug)
Methods: The PBPK models were developed with PK-Sim® and MoBi® (version 9.1) as part of the Open Systems Pharmacology Suite (www.open-systems-pharmacology.org) [6]. Data for model development were extracted from the literature, including physicochemical parameters and plasma concentration-time profiles for all compounds. Data were split in a training and test dataset for model development and evaluation, respectively. Additionally, previously published victim drug models were used for prediction of DDIs. Here, midazolam, alprazolam, and triazolam were used to evaluate CYP3A4 DDIs, and digoxin was used to evaluate P-gp DDIs. DDIs were simulated with the involvement of both ketoconazole and its metabolite N-deacetyl ketoconazole as combined parent-metabolite CYP3A4 and P-gp perpetrator.
Results: Whole-body PBPK models for ketoconazole and its metabolite N-deacetyl ketoconazole were developed. The compiled data consists of 54 studies with a dosing range 100–2000 mg as tablets or solutions in 526 patients. The models precisely predict the pharmacokinetics of ketoconazole for fed and fasted patients. The geometric mean fold error (GMFE) was 1.36 for predicted compared to observed AUC values and 1.25 for predicted compared to observed Cmax values. Additionally, mean predicted to observed DDI AUC values for CYP3A4 and P-gp DDIs showed ratios of 0.70 and 0.88 (range 0.24–1.47).
Conclusion: A comprehensive parent-metabolite PBPK model was successfully developed for ketoconazole and its metabolite N-deacetyl ketoconazole. The models capture the important impact on DDIs regarding ketoconazole application. Furthermore, they underline the importance of parent and metabolites regarding a possible combined DDI potential of ketoconazole.
Funding: The project has received support from the project “Open-source modeling framework for automated quality control and management of complex life science systems models” (OSMOSES), which is funded by the German Federal Ministry of Education and Research (BMBF, grant ID: 031L0161C).
References:
[1] J. Weiss et al., “Does the circulating ketoconazole metabolite N-deacetyl ketoconazole contribute to the drug-drug interaction potential of the parent compound?,” Eur. J. Pharm. Sci., vol. 169, p. 106076, 2022.
[2] K. T. Olkkola, J. T. Backman, and P. J. Neuvonen, “Midazolam should be avoided in patients receiving the systemic antimycotics ketoconazole or itraconazole.,” Clin. Pharmacol. Ther., vol. 55, no. 5, pp. 481–5, May 1994.
[3] T. K. Daneshmend, D. W. Warnock, A. Turner, and C. J. C. Roberts, “Pharmacokinetics of ketoconazole in normal subjects,” J. Antimicrob. Chemother., vol. 8, no. 4, pp. 299–304, 1981.
[4] E. D. Kharasch et al., “Concurrent assessment of hepatic and intestinal cytochrome P450 3A activities using deuterated alfentanil.,” Clin. Pharmacol. Ther., vol. 89, no. 4, pp. 562–70, Apr. 2011.
[5] T. Fukami, A. Iida, K. Konishi, and M. Nakajima, “Human arylacetamide deacetylase hydrolyzes ketoconazole to trigger hepatocellular toxicity,” Biochem. Pharmacol., vol. 116, pp. 153–161, 2016.
[6] J. Lippert et al., “Open Systems Pharmacology Community—An Open Access, Open Source, Open Science Approach to Modeling and Simulation in Pharmaceutical Sciences,” CPT Pharmacometrics Syst. Pharmacol., vol. 8, no. 12, pp. 878–882, Dec. 2019.
Reference: PAGE 30 (2022) Abstr 9986 [www.page-meeting.org/?abstract=9986]
Poster: Drug/Disease Modelling - Absorption & PBPK