Literature DB >> 28336578

Quantitative Prediction of CYP3A4 Induction: Impact of Measured, Free, and Intracellular Perpetrator Concentrations from Human Hepatocyte Induction Studies on Drug-Drug Interaction Predictions.

Yongkai Sun1, Paresh P Chothe1, Jennifer E Sager1, Hong Tsao1, Amanda Moore1, Leena Laitinen1, Niresh Hariparsad2.   

Abstract

Typically, concentration-response curves are based upon nominal inducer concentrations for in-vitro-to-in-vivo extrapolation of CYP3A4 induction. The limitation of this practice is that it assumes the hepatocyte culture model is a static system. We assessed whether correcting for: 1) changes in perpetrator concentration in the induction medium during the incubation period, 2) perpetrator binding to proteins in the induction medium, and 3) nonspecific binding of perpetrator can improve the accuracy of CYP3A4 induction predictions. Of the seven compounds used in this evaluation, significant parent loss and nonspecific binding were observed for rifampicin (29.3-38.3%), pioglitazone (64.3-78.6%), and rosiglitazone (57.1-75.5%). As a result, the free measured EC50 values (EC50u) of pioglitazone, rosiglitazone, and rifampicin were significantly lower than the nominal EC50 values. In general, the accuracy of the induction predictions, using multiple static models, improved when corrections were made for measured medium concentrations, medium protein binding, and nonspecific binding of the perpetrator, as evidenced by 18-29% reductions in the root mean square error. The relative induction score model performed better than the basic static and mechanistic static models, resulting in lower prediction error and no false-positive or false-negative predictions. However, even when the EC50u value was used, the induction prediction for bosentan, which is a substrate of organic anion transporter proteins, was overpredicted by approximately 2-fold. Accounting for the ratio of unbound intracellular concentrations to unbound medium concentrations (Kpuu,in vitro) (0.5-7.5) and the predicted multiple-dose Kpuu,in vivo (0.6) for bosentan resulted in induction predictions within 35% of the observed interaction.
Copyright © 2017 by The American Society for Pharmacology and Experimental Therapeutics.

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Year:  2017        PMID: 28336578     DOI: 10.1124/dmd.117.075481

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


  4 in total

1.  Characterization of Correction Factors to Enable Assessment of Clinical Risk from In Vitro CYP3A4 Induction Data and Basic Drug-Drug Interaction Models.

Authors:  Diane Ramsden; Cody L Fullenwider
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2022-03-28       Impact factor: 2.569

2.  Impact of Intracellular Concentrations on Metabolic Drug-Drug Interaction Studies.

Authors:  Andrea Treyer; Mohammed Ullah; Neil Parrott; Birgit Molitor; Stephen Fowler; Per Artursson
Journal:  AAPS J       Date:  2019-06-18       Impact factor: 4.009

3.  Evaluation of human primary intestinal monolayers for drug metabolizing capabilities.

Authors:  Jennifer E Speer; Yuli Wang; John K Fallon; Philip C Smith; Nancy L Allbritton
Journal:  J Biol Eng       Date:  2019-11-04       Impact factor: 4.355

4.  Predicting Clinical Effects of CYP3A4 Modulators on Abemaciclib and Active Metabolites Exposure Using Physiologically Based Pharmacokinetic Modeling.

Authors:  Maria M Posada; Bridget L Morse; P Kellie Turner; Palaniappan Kulanthaivel; Stephen D Hall; Gemma L Dickinson
Journal:  J Clin Pharmacol       Date:  2020-02-20       Impact factor: 3.126

  4 in total

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