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Development of a Physiologically Based Pharmacokinetic Model for Itraconazole Pharmacokinetics and Drug–Drug Interaction Prediction

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Abstract

Background and Objectives

Physiologically based pharmacokinetic (PBPK) modeling for itraconazole has been challenging due to highly variable in vitro d ata used for ‘bottom-up’ model building. Under-prediction of pharmacokinetics and drug–drug interactions (DDIs) following multiple doses of itraconazole has limited the use of PBPK model simulation to aid an itraconazole clinical DDI study design. The aim of this work is to develop an itraconazole PBPK model predominantly using a ‘top-down’ approach to enable a more accurate pharmacokinetic and DDI prediction.

Methods

An itraconazole PBPK model describing itraconazole and hydroxyl-itraconazole (OH-ITZ) was constructed in Simcyp®. The key parameters that govern the pharmacokinetic profile, including non-linear clearance (i.e., maximum rate of reaction [V max] and the Michaelis-Menten constant [K m]) and volume of distribution for both itraconazole and OH-ITZ, were redefined by leveraging existing in vivo data. Model verification was performed by comparing the simulated itraconazole and OH-ITZ pharmacokinetic profiles with the observed clinical data. Finally, the model was used to simulate clinical DDIs between itraconazole and midazolam.

Results

The developed PBPK model well-described the pharmacokinetics of itraconazole and OH-ITZ, and particularly captured their accumulation after repeated doses of itraconazole. This was verified with the observed data from 29 clinical studies where itraconazole solution or capsule was given as a single or multiple dose. The predicted DDI between itraconazole and midazolam was within 1.25-fold of the observed data for seven of ten studies and within 1.5-fold for nine of ten studies.

Conclusion

The improvement of the itraconazole PBPK model increased our confidence in using PBPK model simulations to optimize clinical itraconazole DDI study design.

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Author contributions

Participated in model design: YC and FM. Collected data and ran simulations: YC, FM, and TL. Performed data analysis and wrote the manuscript: YC, FM, TL, HW, and JM. Reviewed the manuscript and approved for submission: YC, FM, TL, NB, JYJ, JRK, HW, CH, and JM.

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Author notes

  1. Fang Ma

    Present address: Alios BioPharma, Inc., South San Francisco, CA, 94080, USA

  2. Harvey Wong

    Present address: Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, BC, Canada

Authors and Affiliations

  1. Drug Metabolism and Pharmacokinetics, Genentech Inc., 1 DNA Way, South San Francisco, CA, 94080, USA

    Yuan Chen, Fang Ma, Jane R. Kenny, Harvey Wong, Cornelis E. C. A. Hop & Jialin Mao

  2. Clinical Pharmacology, Genentech Inc., South San Francisco, CA, 94080, USA

    Tong Lu, Nageshwar Budha & Jin Yan Jin

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  1. Yuan Chen
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Corresponding author

Correspondence to Yuan Chen.

Ethics declarations

This study was funded by Genentech (a member of the Roche group). All authors (YC, FM, TL, NB, JYJ, JRK, HW, CH, JM) were employees of Genentech when this work was carried out. They have no other conflicts of interest to declare. We would like to thank Tao Ji for participating in the discussions. We especially thank Karen R. Yeo from Simcyp (a Certara company) for sharing her experience related to the itraconazole model assessment during scientific discussion at Simcyp consortium meetings.

Electronic supplementary material

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40262_2015_352_MOESM1_ESM.pdf

Supplementary material 1 (PDF 650 kb) Fig. 1S—best fit parameter estimation (PE) curve generated by Simcyp model using data from IV administration of ITZ (Mouton et al., 2006): i—50 mg ITZ PK; ii—100 mg ITZ PK, iii—200 mg ITZ PK; iv—300 mg ITZ PK. For observed 100mg PK data (a) Mouton et al., 2006 (b) Heykants, et al., 1989. Fig. 2S—Simulated and observed plasma concentration-time profiles of OH-ITZ formed from IV administration of ITZ at 50 (i), 100 (ii), 200 (iii), and 300 mg (iv). Simulated mean is the mean of 100 individuals (10 trials of 10 subjects per trial); simulated trial is the mean of 10 subjects in each trial; 5th–95th percentile for 100 individuals simulated represents the 5th and 95th highest concentrations from the ranked concentrations

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Chen, Y., Ma, F., Lu, T. et al. Development of a Physiologically Based Pharmacokinetic Model for Itraconazole Pharmacokinetics and Drug–Drug Interaction Prediction. Clin Pharmacokinet 55, 735–749 (2016). https://doi.org/10.1007/s40262-015-0352-5

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