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Pharmaceutical Research

, Volume 29, Issue 7, pp 1960–1976 | Cite as

Drug–Drug Interaction Potential of Marketed Oncology Drugs: In Vitro Assessment of Time-Dependent Cytochrome P450 Inhibition, Reactive Metabolite Formation and Drug–Drug Interaction Prediction

  • Jane R. KennyEmail author
  • Sophie Mukadam
  • Chenghong Zhang
  • Suzanne Tay
  • Carol Collins
  • Aleksandra Galetin
  • S. Cyrus Khojasteh
Research Paper

ABSTRACT

Purpose

To evaluate 26 marketed oncology drugs for time-dependent inhibition (TDI) of cytochrome P450 (CYP) enzymes. Evaluate TDI-positive drugs for potential to generate reactive intermediates. Assess clinical drug–drug interaction (DDI) risk using static mechanistic models.

Methods

Human liver microsomes and CYP-specific probes were used to assess TDI in a dilution shift assay followed by generation of KI and kinact. Reactive metabolite trapping studies were performed with stable label probes. Static mechanistic model was used to predict DDI risk using a 1.25-fold AUC increase as a cut-off for positive DDI.

Results

Negative TDI across CYPs was observed for 13/26 drugs; the rest were time-dependent inhibitors of, predominantly, CYP3A. The kinact/KI ratios for 11 kinase inhibitors ranged from 0.7 to 42.2 ml/min/μmol. Stable label trapping agent–drug conjugates were observed for ten kinase inhibitors. DDI predictions gave no false negatives, one true negative, four false positives and three true positives. The magnitude of DDI was overestimated irrespective of the inhibitor concentration selected.

Conclusions

13/26 oncology drugs investigated showed TDI potential towards CYP3A, formation of reactive metabolites was also observed. An industry standard static mechanistic model gave no false negative predictions but did not capture the modest clinical DDI potential of kinase inhibitors.

KEY WORDS

drug-drug interaction kinase inhibitors prediction reactive metabolites time-dependent CYP inhibition 

ABBREVIATIONS

AUC

area under the curve

Cav

average plasma concentration

Cmax

maximum plasma concentration

CYP

cytochrome P450

DDI

drug–drug interaction

HLM

human liver microsomes

LC

liquid chromatography

MS/MS

tandem mass spectrometry

NME

new molecular entity

PBPK

physiologically based pharmacokinetic modeling

TDI

time-dependent inhibition

Notes

ACKNOWLEDGMENTS & DISCLOSURES

We thank Dr Cornelis ECA Hop for encouragement to investigate these oncology drugs and members of Genentech DMPK for valuable discussions.

Supplementary material

11095_2012_724_MOESM1_ESM.doc (66 kb)
ESM 1 (DOC 66 kb)

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Jane R. Kenny
    • 1
    Email author
  • Sophie Mukadam
    • 1
  • Chenghong Zhang
    • 1
  • Suzanne Tay
    • 1
  • Carol Collins
    • 2
  • Aleksandra Galetin
    • 3
  • S. Cyrus Khojasteh
    • 1
  1. 1.Department of Drug Metabolism and PharmacokineticsGenentech Inc.South San FranciscoUSA
  2. 2.Department of PharmaceuticsUniversity of WashingtonSeattleUSA
  3. 3.Center for Applied Pharmacokinetic Research School of Pharmacy and Pharmaceutical SciencesThe University of ManchesterManchesterUK

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