Literature DB >> 32452536

Interpretation of Cytochrome P-450 Inhibition and Induction Effects From Clinical Data: Current Standards and Recommendations for Implementation.

Stephen M Stout1, Carrie W Nemerovski1, Daniel S Streetman1, Melody Berg1, Jamie Hoffman1, Kayann Burke1, Nina M Bemben1, Stephen J Sklar1.   

Abstract

Agents that modify cytochrome P-450 (CYP) enzyme activity are characterized as strong, moderate, or weak inhibitors or inducers based on the magnitude of their impact on substrate exposure in clinical studies. Criteria for these classifications are simple and semiquantitative. However, assignment of a given agent to a CYP inhibitor or inducer category is often complicated by limitations of the published data, inconsistent study findings, and other factors. CYP inhibitor and inducer categories are commonly used as a basis for differentiating drug interaction management recommendations. For example, product labeling for a CYP substrate may recommend avoidance in combination with strong inhibitors and dose reduction in combination with moderate inhibitors. When such recommendations exist, ambiguity or variability in placement of inhibitors or inducers into categories can introduce potentially harmful variations in clinical drug interaction management. Failure to adequately reflect the drug interaction potential of an agent by under-categorizing it (e.g., calling it weak when data point to moderate effects), for example, may lead clinicians to respond inadequately to real risks, or to ignore potential interactions altogether. Over-categorization may lead to actions such as over-adjustment of substrate doses or unnecessary avoidance of optimal treatments. This review describes the current criteria for assignment of CYP inhibitor and inducer categories, summarizes common circumstances leading to ambiguous or variable CYP inhibitor and inducer categorizations, and proposes an approach to data interpretation and application of current criteria under uncertainty. When applied to > 1,000 CYP reviews, the approach described has identified a clear categorization in almost all cases.
© 2020 The Authors Clinical Pharmacology & Therapeutics © 2020 American Society for Clinical Pharmacology and Therapeutics.

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Year:  2020        PMID: 32452536     DOI: 10.1002/cpt.1918

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.875


  3 in total

Review 1.  Contribution of Humanized Liver Chimeric Mice to the Study of Human Hepatic Drug Transporters: State of the Art and Perspectives.

Authors:  Anna Zerdoug; Marc Le Vée; Shotaro Uehara; Béatrice Lopez; Christophe Chesné; Hiroshi Suemizu; Olivier Fardel
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2022-07-06       Impact factor: 2.569

Review 2.  How to Integrate CYP2D6 Phenoconversion Into Clinical Pharmacogenetics: A Tutorial.

Authors:  Emily J Cicali; Amanda L Elchynski; Kelsey J Cook; John T Houder; Cameron D Thomas; D Max Smith; Amanda Elsey; Julie A Johnson; Larisa H Cavallari; Kristin Wiisanen
Journal:  Clin Pharmacol Ther       Date:  2021-07-28       Impact factor: 6.903

3.  Model-Based Comparative Analysis of Rifampicin and Rifabutin Drug-Drug Interaction Profile.

Authors:  Vianney Tuloup; Mathilde France; Romain Garreau; Nathalie Bleyzac; Laurent Bourguignon; Michel Tod; Sylvain Goutelle
Journal:  Antimicrob Agents Chemother       Date:  2021-08-17       Impact factor: 5.191

  3 in total

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