Development of in vitro methods to predict induction of CYP1A2 and CYP3A4 in humans

G Scott Grover1, Timothy G Brayman, Richard L Voorman

  • 1Pharmacokinetics, Dynamics & Metabolism, Pfizer Global Research and Development, Ann Arbor, MI, USA. scott.grover@pfizer.com

Insights

The aryl hydrocarbon receptor (AHR) and pregnane X receptor (PXR) are key drivers of drug-drug interactions. This study presents in vitro methods to detect AHR- and PXR-mediated induction of CYP1A2 and CYP3A4 enzymes.

Area of Science:

  • Pharmacology and Toxicology
  • Drug Metabolism and Pharmacokinetics (DMPK)

Background:

  • Cytochrome P450 (CYP) drug-metabolizing enzymes play a crucial role in drug efficacy and safety.
  • Enzyme induction by drugs can lead to significant drug-drug interactions (DDIs).
  • The aryl hydrocarbon receptor (AHR) and pregnane X receptor (PXR) are increasingly recognized as primary mediators of clinically relevant DDIs.

Purpose of the Study:

  • To investigate the role of AHR and PXR in drug-metabolizing enzyme induction.
  • To present in vitro methods for detecting AHR- and PXR-mediated induction of key drug-metabolizing enzymes.
  • To identify reliable biomarkers for assessing potential drug induction liabilities.

Main Methods:

  • Utilized several in vitro assays to detect AHR- and PXR-mediated induction.
  • Employed fresh and cryopreserved primary human hepatocytes for testing.
  • Included stable transfectants and transiently transfected immortalized cell lines.

Main Results:

  • CYP1A2 and CYP3A4 were identified as reliable biomarkers for AHR and PXR induction, respectively.
  • Demonstrated the capability of the presented in vitro methods to detect induction liabilities.
  • Validated the role of AHR and PXR in modulating drug-metabolizing enzyme activity.

Conclusions:

  • AHR and PXR are critical regulators of drug-metabolizing enzymes and transporters.
  • CYP1A2 and CYP3A4 serve as effective biomarkers for AHR and PXR activation.
  • The developed in vitro methods are valuable tools for predicting drug-induced DDIs.

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