Literature DB >> 24939654

A numerical method for analysis of in vitro time-dependent inhibition data. Part 1. Theoretical considerations.

Swati Nagar1, Jeffrey P Jones1, Ken Korzekwa2.   

Abstract

Inhibition of cytochromes P450 by time-dependent inhibitors (TDI) is a major cause of clinical drug-drug interactions. It is often difficult to predict in vivo drug interactions based on in vitro TDI data. In part 1 of these manuscripts, we describe a numerical method that can directly estimate TDI parameters for a number of kinetic schemes. Datasets were simulated for Michaelis-Menten (MM) and several atypical kinetic schemes. Ordinary differential equations were solved directly to parameterize kinetic constants. For MM kinetics, much better estimates of KI can be obtained with the numerical method, and even IC50 shift data can provide meaningful estimates of TDI kinetic parameters. The standard replot method can be modified to fit non-MM data, but normal experimental error precludes this approach. Non-MM kinetic schemes can be easily incorporated into the numerical method, and the numerical method consistently predicts the correct model at errors of 10% or less. Quasi-irreversible inactivation and partial inactivation can be modeled easily with the numerical method. The utility of the numerical method for the analyses of experimental TDI data is provided in our companion manuscript in this issue of Drug Metabolism and Disposition (Korzekwa et al., 2014b).
Copyright © 2014 by The American Society for Pharmacology and Experimental Therapeutics.

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Year:  2014        PMID: 24939654      PMCID: PMC4152869          DOI: 10.1124/dmd.114.058289

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


  38 in total

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  11 in total

1.  A numerical method for analysis of in vitro time-dependent inhibition data. Part 2. Application to experimental data.

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Journal:  Drug Metab Dispos       Date:  2014-06-17       Impact factor: 3.922

2.  Numerical Methods for Modeling Enzyme Kinetics.

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3.  Multienzyme Kinetics and Sequential Metabolism.

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4.  Numerical Analysis of Time-Dependent Inhibition by MDMA.

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5.  Impact of Lipid Partitioning on the Design, Analysis, and Interpretation of Microsomal Time-Dependent Inactivation.

Authors:  Jaydeep Yadav; Ken Korzekwa; Swati Nagar
Journal:  Drug Metab Dispos       Date:  2019-05-01       Impact factor: 3.922

6.  Numerical analysis of time dependent inhibition kinetics: comparison between rat liver microsomes and rat hepatocyte data for mechanistic model fitting.

Authors:  Chuong Pham; Swati Nagar; Ken Korzekwa
Journal:  Xenobiotica       Date:  2017-06-23       Impact factor: 1.908

7.  Mechanism-Based Inhibition of CYP3A4 by Podophyllotoxin: Aging of an Intermediate Is Important for in Vitro/in Vivo Correlations.

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8.  Improved Predictions of Drug-Drug Interactions Mediated by Time-Dependent Inhibition of CYP3A.

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Review 9.  Time-dependent enzyme inactivation: Numerical analyses of in vitro data and prediction of drug-drug interactions.

Authors:  Jaydeep Yadav; Erickson Paragas; Ken Korzekwa; Swati Nagar
Journal:  Pharmacol Ther       Date:  2019-12-11       Impact factor: 12.310

10.  Mechanisms of Herb-Drug Interactions Involving Cinnamon and CYP2A6: Focus on Time-Dependent Inhibition by Cinnamaldehyde and 2-Methoxycinnamaldehyde.

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Journal:  Drug Metab Dispos       Date:  2020-08-12       Impact factor: 3.922

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