Literature DB >> 27519549

Hepatic Clearance Predictions from In Vitro-In Vivo Extrapolation and the Biopharmaceutics Drug Disposition Classification System.

Christine M Bowman1, Leslie Z Benet2.   

Abstract

Predicting in vivo pharmacokinetic parameters such as clearance from in vitro data is a crucial part of the drug-development process. There is a commonly cited trend that drugs that are highly protein-bound and are substrates for hepatic uptake transporters often yield the worst predictions. Given this information, 11 different data sets using human microsomes and hepatocytes were evaluated to search for trends in accuracy, extent of protein binding, and drug classification based on the Biopharmaceutics Drug Disposition Classification System (BDDCS), which makes predictions about transporter effects. As previously reported, both in vitro systems (microsomes and hepatocytes) gave a large number of inaccurate results, defined as predictions falling more than 2-fold outside of in vivo values. The weighted average of the percentage of inaccuracy was 66.5%. BDDCS class 2 drugs, which are subject to transporter effects in vivo unlike class 1 compounds, had a higher percentage of inaccurate predictions and often had slightly larger bias. However, since the weighted average of the percentage of inaccuracy was still high in both classes (81.9% for class 2 and 62.3% for class 1), it may be currently hard to use BDDCS class to predict potential accuracy. The results of this study emphasize the need for improved in vitro to in vivo extrapolation experimental methods, as using physiologically based scaling is still not accurate, and BDDCS cannot currently help predict accurate results.
Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

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Year:  2016        PMID: 27519549     DOI: 10.1124/dmd.116.071514

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


  17 in total

1.  The Presence of a Transporter-Induced Protein Binding Shift: A New Explanation for Protein-Facilitated Uptake and Improvement for In Vitro-In Vivo Extrapolation.

Authors:  Christine M Bowman; Hideaki Okochi; Leslie Z Benet
Journal:  Drug Metab Dispos       Date:  2019-01-23       Impact factor: 3.922

2.  Interlaboratory Variability in Human Hepatocyte Intrinsic Clearance Values and Trends with Physicochemical Properties.

Authors:  Christine M Bowman; Leslie Z Benet
Journal:  Pharm Res       Date:  2019-05-31       Impact factor: 4.200

3.  Integrated Gut and Liver Microphysiological Systems for Quantitative In Vitro Pharmacokinetic Studies.

Authors:  Nikolaos Tsamandouras; Wen Li Kelly Chen; Collin D Edington; Cynthia L Stokes; Linda G Griffith; Murat Cirit
Journal:  AAPS J       Date:  2017-07-27       Impact factor: 4.009

4.  Physiologically based pharmacokinetic modelling prediction of the effects of dose adjustment in drug-drug interactions between levonorgestrel contraceptive implants and efavirenz-based ART.

Authors:  Owain Roberts; Rajith K R Rajoli; David J Back; Andrew Owen; Kristin M Darin; Courtney V Fletcher; Mohammed Lamorde; Kimberly K Scarsi; Marco Siccardi
Journal:  J Antimicrob Chemother       Date:  2018-04-01       Impact factor: 5.790

5.  The Universally Unrecognized Assumption in Predicting Drug Clearance and Organ Extraction Ratio.

Authors:  L Z Benet; S Liu; A R Wolfe
Journal:  Clin Pharmacol Ther       Date:  2017-09-06       Impact factor: 6.875

6.  In Vitro-In Vivo Inaccuracy: The CYP3A4 Anomaly.

Authors:  Christine M Bowman; Leslie Z Benet
Journal:  Drug Metab Dispos       Date:  2019-09-24       Impact factor: 3.922

7.  In Vitro-In Vivo Extrapolation and Hepatic Clearance-Dependent Underprediction.

Authors:  Christine M Bowman; Leslie Z Benet
Journal:  J Pharm Sci       Date:  2019-02-25       Impact factor: 3.534

8.  Reconciling Human-Canine Differences in Oral Bioavailability: Looking beyond the Biopharmaceutics Classification System.

Authors:  Marilyn N Martinez; Ayman El-Kattan; Elias Awji; Mark Papich
Journal:  AAPS J       Date:  2019-08-08       Impact factor: 4.009

9.  Albumin-Mediated Uptake Improves Human Clearance Prediction for Hepatic Uptake Transporter Substrates Aiding a Mechanistic In Vitro-In Vivo Extrapolation (IVIVE) Strategy in Discovery Research.

Authors:  Na Li; Akshay Badrinarayanan; Kazuya Ishida; Xingwen Li; John Roberts; Shuai Wang; Mike Hayashi; Anshul Gupta
Journal:  AAPS J       Date:  2020-11-16       Impact factor: 4.009

10.  Investigating the Theoretical Basis for In Vitro-In Vivo Extrapolation (IVIVE) in Predicting Drug Metabolic Clearance and Proposing Future Experimental Pathways.

Authors:  Leslie Z Benet; Jasleen K Sodhi
Journal:  AAPS J       Date:  2020-09-10       Impact factor: 4.009

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