Literature DB >> 24549735

In vitro-in vivo extrapolation method to predict human renal clearance of drugs.

Annett Kunze1, Jörg Huwyler, Birk Poller, Heike Gutmann, Gian Camenisch.   

Abstract

Renal clearance is a key determinant of the elimination of drugs. To date, only few in vitro-in vivo extrapolation (IVIVE) approaches have been described to predict the renal organ clearance as the net result of glomerular filtration, tubular secretion, and tubular reabsorption. In this study, we measured in LLC-PK1 cells the transport of 20 compounds that cover all four classes of the Biopharmaceutical Drug Disposition System. These data were incorporated into a novel kidney model to predict all renal clearance processes in human. We showed that filtration and secretion were main contributors to the renal organ clearance for all compounds, whereas reabsorption was predominant for compounds assigned to classes 1 and 2. Our results suggest that anionic drugs were not significantly secreted in LLC-PK1 cells, resulting in under-predicted clearances. When all study compounds were included a high overall correlation between the reported and predicted renal organ clearances was obtained (R² = 0.83). The prediction accuracy in terms of percentage within twofold and threefold error was 70% and 95%, respectively. In conclusion, our novel IVIVE method allowed to predict the human renal organ clearance and the contribution of each underlying process.
© 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Entities:  

Keywords:  LLC-PK1 cell line; clearance prediction; drug transport; in vitro models; in vitro-in vivo correlations (IVIVC); membrane transport; permeability; pharmacokinetics; renal clearance; renal reabsorption

Mesh:

Substances:

Year:  2014        PMID: 24549735     DOI: 10.1002/jps.23851

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  14 in total

Review 1.  Drug Disposition Classification Systems in Discovery and Development: A Comparative Review of the BDDCS, ECCS and ECCCS Concepts.

Authors:  Gian P Camenisch
Journal:  Pharm Res       Date:  2016-07-20       Impact factor: 4.200

Review 2.  Key to Opening Kidney for In Vitro-In Vivo Extrapolation Entrance in Health and Disease: Part I: In Vitro Systems and Physiological Data.

Authors:  Daniel Scotcher; Christopher Jones; Maria Posada; Amin Rostami-Hodjegan; Aleksandra Galetin
Journal:  AAPS J       Date:  2016-06-30       Impact factor: 4.009

3.  Screening of Drug-Transporter Interactions in a 3D Microfluidic Renal Proximal Tubule on a Chip.

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Journal:  AAPS J       Date:  2018-07-26       Impact factor: 4.009

Review 4.  Human-on-a-chip design strategies and principles for physiologically based pharmacokinetics/pharmacodynamics modeling.

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Journal:  Integr Biol (Camb)       Date:  2015-04       Impact factor: 2.192

Review 5.  Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies.

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Journal:  Clin Pharmacokinet       Date:  2019-06       Impact factor: 6.447

6.  Predicting the Drug Clearance Pathway with Structural Descriptors.

Authors:  Navid Kaboudi; Ali Shayanfar
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2022-02-11       Impact factor: 2.441

7.  An in vitro human mammary epithelial cell permeability assay to assess drug secretion into breast milk.

Authors:  Tao Zhang; Zachary Applebee; Peng Zou; Zhen Wang; Erika Solano Diaz; Yanyan Li
Journal:  Int J Pharm X       Date:  2022-06-22

Review 8.  Key to Opening Kidney for In Vitro-In Vivo Extrapolation Entrance in Health and Disease: Part II: Mechanistic Models and In Vitro-In Vivo Extrapolation.

Authors:  Daniel Scotcher; Christopher Jones; Maria Posada; Aleksandra Galetin; Amin Rostami-Hodjegan
Journal:  AAPS J       Date:  2016-08-09       Impact factor: 4.009

9.  In Vivo-to-In Vitro Extrapolation of Transporter-Mediated Renal Clearance: Relative Expression Factor Versus Relative Activity Factor Approach.

Authors:  Aditya R Kumar; Bhagwat Prasad; Deepak Kumar Bhatt; Sumathy Mathialagan; Manthena V S Varma; Jashvant D Unadkat
Journal:  Drug Metab Dispos       Date:  2021-04-06       Impact factor: 3.579

10.  Novel minimal physiologically-based model for the prediction of passive tubular reabsorption and renal excretion clearance.

Authors:  Daniel Scotcher; Christopher Jones; Amin Rostami-Hodjegan; Aleksandra Galetin
Journal:  Eur J Pharm Sci       Date:  2016-03-28       Impact factor: 4.384

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