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Clarithromycin, Midazolam, and Digoxin: Application of PBPK Modeling to Gain New Insights into Drug–Drug Interactions and Co-medication Regimens

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Abstract

Clarithromycin is a substrate and mechanism-based inhibitor of cytochrome P450 (CYP) 3A4 as well as a substrate and competitive inhibitor of P-glycoprotein (P-gp) and organic anion-transporting polypeptides (OATP) 1B1 and 1B3. Administered concomitantly, clarithromycin causes drug–drug interactions (DDI) with the victim drugs midazolam (CYP3A4 substrate) and digoxin (P-gp substrate). The objective of the presented study was to build a physiologically based pharmacokinetic (PBPK) DDI model for clarithromycin, midazolam, and digoxin and to exemplify dosing adjustments under clarithromycin co-treatment. The PBPK model development included an extensive literature search for representative PK studies and for compound characteristics of clarithromycin, midazolam, and digoxin. Published concentration-time profiles were used for model development (training dataset), and published and unpublished individual profiles were used for model evaluation (evaluation dataset). The developed single-compound PBPK models were linked for DDI predictions. The full clarithromycin DDI model successfully predicted the metabolic (midazolam) and transporter (digoxin) DDI, the acceptance criterion (0.5 ≤ AUCratio,predicted/AUCratio,observed ≤ 2) was met by all predictions. During co-treatment with 250 or 500 mg clarithromycin (bid), the midazolam and digoxin doses should be reduced by 74 to 88% and by 21 to 22%, respectively, to ensure constant midazolam and digoxin exposures (AUC). With these models, we provide highly mechanistic tools to help researchers understand and characterize the DDI potential of new molecular entities and inform the design of DDI studies with potential CYP3A4 and P-gp substrates.

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Authors and Affiliations

  1. Department of Pharmacy, Clinical Pharmacy, Saarland University, Campus C2 2, 66123, Saarbruecken, Germany

    Daniel Moj, Nina Hanke, Hannah Britz & Thorsten Lehr

  2. Computational Systems Biology, Bayer Technology Services GmbH, Leverkusen, Germany

    Sebastian Frechen, Tobias Kanacher & Thomas Wendl

  3. Department of Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Heidelberg, Germany

    Walter Emil Haefeli

Authors
  1. Daniel Moj
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  2. Nina Hanke
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  3. Hannah Britz
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  4. Sebastian Frechen
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  5. Tobias Kanacher
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  6. Thomas Wendl
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  7. Walter Emil Haefeli
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  8. Thorsten Lehr
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Correspondence to Thorsten Lehr.

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ESM 1

Predicted concentration-time profiles of clarithromycin after intravenous application of clarithromycin (A,B: ref. (23), C,D: ref. (24)) in comparison with observed mean data. Solid line: predicted mean, dash-dotted line: predicted median, gray shaded area: predicted SD, dashed line: predicted minimum/maximum, gray circles: observed mean data. (GIF 98 kb)

High resolution images (TIF 784 kb)

ESM 2

Predicted concentration-time profiles of clarithromycin after oral rising doses of clarithromycin (13) in comparison with observed mean data (± standard deviation (SD)). Solid line: predicted mean, dash-dotted line: predicted median, gray shaded area: predicted SD, dashed line: predicted minimum/maximum, gray circles: observed mean data (± SD). (GIF 205 kb)

High resolution images (TIF 1747 kb)

ESM 3

Predicted CYP3A4 activity after multiple doses of clarithromycin in comparison with observed data. Left: CYP3A4 activity in the liver, right: CYP3A4 activity in the duodenum. Solid line: predicted median, gray shaded area: predicted 5th–95th percentile, dashed line: predicted minimum/maximum, boxplots/point estimates: observed data (94). (GIF 136 kb)

High resolution images (TIF 852 kb)

ESM 4

Predicted concentration-time profiles of midazolam after single intravenous doses of midazolam in comparison with observed mean/individual data. Training dataset A,B: ref. (30,34) and evaluation dataset C–E: ref. (32,33,35). Solid line: predicted mean, dash-dotted line: predicted median, gray shaded area: predicted SD, dashed line: predicted minimum/maximum, gray circles: observed mean and individual data. (GIF 137 kb)

High resolution images (TIF 1478 kb)

ESM 5

Predicted concentration-time profiles of midazolam after single oral doses of midazolam in comparison with observed mean data. Training dataset A–C: ref. (35,38) and evaluation dataset D-F: ref. (33,38). Solid line: predicted mean, dash-dotted line: predicted median, gray shaded area: predicted SD, dashed line: predicted minimum/maximum, gray circles: observed mean data. (GIF 150 kb)

High resolution images (TIF 1525 kb)

ESM 6

Predicted concentration-time profiles of digoxin after single intravenous doses of digoxin in comparison with observed mean data. Training dataset A–F: ref. (41,46) and evaluation dataset G–J: ref. (20,42–44). Solid line: predicted mean, dash-dotted line: predicted median, gray shaded area: predicted SD, dashed line: predicted minimum/maximum, gray circles: observed mean data (± SD). (GIF 154 kb)

High resolution images (TIF 1478 kb)

ESM 7

Predicted concentration-time profiles of digoxin after single oral doses of digoxin in comparison with observed mean data. Training dataset A–C: ref. (44,47,49) and evaluation dataset D,E: ref. (41,50). Solid line: predicted mean, dash-dotted line: predicted median, gray shaded area: predicted SD, dashed line: predicted minimum/maximum, gray circles: observed mean data (± SD). (GIF 144 kb)

High resolution images (TIF 1452 kb)

ESM 8

Predicted concentration-time profiles of digoxin after multiple oral doses of digoxin in comparison with observed mean data. Training dataset A,B: ref. (52,53) and evaluation dataset C: ref. (54). Solid line: predicted mean, dash-dotted line: predicted median, gray shaded area: predicted SD, dashed line: predicted minimum/maximum, gray circles: observed mean data (± SD). (GIF 120 kb)

High resolution images (TIF 1042 kb)

ESM 9

Predicted concentration-time profiles of digoxin after single intravenous doses of digoxin (A,B: (26), C,D: (45)) with and without prior clarithromycin regimens in comparison with observed mean data. Solid line: predicted digoxin mean without prior clarithromycin, dashed line: predicted digoxin mean with prior clarithromycin, gray circles: observed mean digoxin without prior clarithromycin, gray triangles: observed mean digoxin with prior clarithromycin. Clarithromycin was administered orally (bid) with 250 mg (A,B) and 200 mg (C,D). (GIF 75 kb)

High resolution images (TIF 915 kb)

ESM 10

Parameter sensitivity analysis. The x-axis represents the logarithm of the factor by which the parameters are multiplied in order to vary them over a range of 0.1 to 10-fold. (GIF 80 kb)

High resolution images (TIF 693 kb)

ESM 11

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Moj, D., Hanke, N., Britz, H. et al. Clarithromycin, Midazolam, and Digoxin: Application of PBPK Modeling to Gain New Insights into Drug–Drug Interactions and Co-medication Regimens. AAPS J 19, 298–312 (2017). https://doi.org/10.1208/s12248-016-0009-9

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