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How Science Is Driving Regulatory Guidances.

Xinning Yang1, Jianghong Fan2, Lei Zhang3

  • 1Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA. Xinning.Yang@fda.hhs.gov.

Methods in Molecular Biology (Clifton, N.J.)
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Summary

This chapter explains how to use in vitro drug metabolism data to predict in vivo drug-drug interactions (DDIs). It details regulatory guidance from the FDA for evaluating cytochrome P450 and UDP-glucuronosyltransferase inhibition.

Keywords:
CYPDDIEnzymeGuidanceIVIVEInhibitionMetaboliteRegulatoryUGT

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Area of Science:

  • Pharmacology
  • Drug Metabolism and Pharmacokinetics
  • Regulatory Science

Background:

  • Drug-drug interactions (DDIs) are a significant concern in drug development.
  • Predicting in vivo DDI potential from in vitro data is crucial for regulatory decision-making.
  • Existing FDA guidances provide frameworks for assessing DDI risks.

Purpose of the Study:

  • To provide regulatory perspectives on translating in vitro drug metabolism findings into in vivo DDI predictions.
  • To delineate the rationale behind FDA DDI guidance recommendations for cytochrome P450 (CYP) and UDP-glucuronosyltransferase (UGT) inhibition.
  • To discuss the framework and considerations for assessing UGT inhibition-mediated DDI potential.

Main Methods:

  • In vitro-in vivo extrapolation (IVIVE) of drug metabolism data.
  • Analysis of FDA DDI guidances.
  • Evaluation of decision criteria for DDI assessment.
  • Case examples illustrating the application of decision criteria.

Main Results:

  • The chapter outlines methods for predicting CYP inhibition-mediated DDI potential for new drugs and their metabolites.
  • It details a framework for assessing UGT inhibition-mediated DDI potential.
  • Case examples demonstrate the practical application of these regulatory approaches.

Conclusions:

  • Translating in vitro data to in vivo DDI predictions is essential for efficient drug development.
  • The FDA's guidance provides a structured approach to evaluating DDI potential.
  • Further improvements in decision criteria and assessment frameworks are needed.