Accessible Unlicensed Requires Authentication Published by De Gruyter May 21, 2015

Application of the extended clearance concept classification system (ECCCS) to predict the victim drug-drug interaction potential of statins

Annett Kunze, Birk Poller, Jörg Huwyler and Gian Camenisch

Abstract

Background: During drug development, it is an important safety factor to identify the potential of new molecular entities to become a victim of drug-drug interactions (DDIs). In preclinical development, however, anticipation of clinical DDIs remains challenging due to the lack of in vivo human pharmacokinetic data.

Methods: We applied a recently developed in vitro-in vivo extrapolation method, including hepatic metabolism and transport processes, herein referred to as the Extended Clearance Concept Classification System (ECCCS). The human hepatic clearances and the victim DDI potentials were predicted for atorvastatin, cerivastatin, fluvastatin, lovastatin acid, pitavastatin, pravastatin, rosuvastatin, and simvastatin acid.

Results: Hepatic statin clearances were well-predicted by the ECCCS with six out of eight clearances projected within a two-fold deviation to reported values. In addition, worst-case DDI predictions were projected for each statin. Based on the ECCCS class assignment (4 classes), the mechanistic interplay of metabolic and transport processes, resulting in different DDI risks, was well-reflected by our model. Furthermore, predictions of clinically observed statins DDIs in combination with relevant perpetrator drugs showed good quantitative correlations with clinical observations.

Conclusions: The ECCCS represents a powerful tool to anticipate the DDI potential of victim drugs based on in vitro drug metabolism and transport data.


Corresponding author: Gian Camenisch, Novartis Pharma AG, Postfach, 4002 Basel, Switzerland, Phone: +41 616968583, Fax: +41 792785817, E-mail: ; and Drug-Drug Interactions Section, Novartis Institutes for BioMedical Research, Division of Drug Metabolism and Pharmacokinetics, Basel, Switzerland

Acknowledgments

The authors wish to acknowledge the many Novartis Drug Metabolism and Pharmacokinetic scientists of Basel, Switzerland, who have supported this work. Special thanks go to Francis Heitz for technical assistance.

Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

Research funding: None declared.

Employment or leadership: None declared.

Honorarium: None declared.

Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

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Supplemental Material:

The online version of this article (DOI: 10.1515/dmdi-2015-0003) offers supplementary material, available to authorized users.

Received: 2015-1-29
Accepted: 2015-4-8
Published Online: 2015-5-21
Published in Print: 2015-9-1

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