Literature DB >> 28762489

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

L Z Benet1, S Liu1, A R Wolfe1.   

Abstract

For almost a half-century clearance concepts have been utilized in pharmacokinetics to understand the relationship between the dose administered and the time course of systemic concentrations to predict efficacy and safety, as well as how dosing should be modified in disease states. Various models of organ clearance/elimination have been proposed and tested. Surprisingly, however, the theoretical basis for the appropriate data collection to test these models has never been evaluated. Here we show that in vivo data collection limitations and the extraction ratio concept itself are only consistent with the well-stirred model of hepatic elimination. Evaluating measures of drug concentrations entering and leaving an organ will appear to best fit the well-stirred model, since driving force concentrations within the organ of elimination cannot be measured.
© 2017 American Society for Clinical Pharmacology and Therapeutics.

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Year:  2017        PMID: 28762489      PMCID: PMC6364827          DOI: 10.1002/cpt.802

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.875


  13 in total

1.  Prediction of human clearance of twenty-nine drugs from hepatic microsomal intrinsic clearance data: An examination of in vitro half-life approach and nonspecific binding to microsomes.

Authors:  R S Obach
Journal:  Drug Metab Dispos       Date:  1999-11       Impact factor: 3.922

2.  Prediction of human metabolic clearance from in vitro systems: retrospective analysis and prospective view.

Authors:  David Hallifax; Joanne A Foster; J Brian Houston
Journal:  Pharm Res       Date:  2010-07-27       Impact factor: 4.200

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

Authors:  Christine M Bowman; Leslie Z Benet
Journal:  Drug Metab Dispos       Date:  2016-08-12       Impact factor: 3.922

4.  A dispersion model of hepatic elimination: 1. Formulation of the model and bolus considerations.

Authors:  M S Roberts; M Rowland
Journal:  J Pharmacokinet Biopharm       Date:  1986-06

5.  Clearance concepts in pharmacokinetics.

Authors:  M Rowland; L Z Benet; G G Graham
Journal:  J Pharmacokinet Biopharm       Date:  1973-04

6.  Models of hepatic drug clearance: discrimination between the 'well stirred' and 'parallel-tube' models.

Authors:  A B Ahmad; P N Bennett; M Rowland
Journal:  J Pharm Pharmacol       Date:  1983-04       Impact factor: 3.765

7.  Discrimination between the venous equilibrium and sinusoidal models of hepatic drug elimination in the isolated perfused rat liver by perturbation of propranolol protein binding.

Authors:  D B Jones; D J Morgan; G W Mihaly; L K Webster; R A Smallwood
Journal:  J Pharmacol Exp Ther       Date:  1984-05       Impact factor: 4.030

8.  Hepatic clearance of drugs. I. Theoretical considerations of a "well-stirred" model and a "parallel tube" model. Influence of hepatic blood flow, plasma and blood cell binding, and the hepatocellular enzymatic activity on hepatic drug clearance.

Authors:  K S Pang; M Rowland
Journal:  J Pharmacokinet Biopharm       Date:  1977-12

9.  Hepatic clearance of drugs. II. Experimental evidence for acceptance of the "well-stirred" model over the "parallel tube" model using lidocaine in the perfused rat liver in situ preparation.

Authors:  K S Pang; M Rowland
Journal:  J Pharmacokinet Biopharm       Date:  1977-12

10.  A unified model for predicting human hepatic, metabolic clearance from in vitro intrinsic clearance data in hepatocytes and microsomes.

Authors:  Robert J Riley; D F McGinnity; R P Austin
Journal:  Drug Metab Dispos       Date:  2005-06-02       Impact factor: 3.922

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  9 in total

1.  Protein Binding and Hepatic Clearance: Re-Examining the Discrimination between Models of Hepatic Clearance with Diazepam in the Isolated Perfused Rat Liver Preparation.

Authors:  Hong-Jaan Wang; Leslie Z Benet
Journal:  Drug Metab Dispos       Date:  2019-09-28       Impact factor: 3.922

2.  Are There Any Experimental Perfusion Data that Preferentially Support the Dispersion and Parallel-Tube Models over the Well-Stirred Model of Organ Elimination?

Authors:  Jasleen K Sodhi; Hong-Jaan Wang; Leslie Z Benet
Journal:  Drug Metab Dispos       Date:  2020-04-17       Impact factor: 3.922

Review 3.  Understanding drug-drug interaction and pharmacogenomic changes in pharmacokinetics for metabolized drugs.

Authors:  Leslie Z Benet; Christine M Bowman; Megan L Koleske; Capria L Rinaldi; Jasleen K Sodhi
Journal:  J Pharmacokinet Pharmacodyn       Date:  2019-03-25       Impact factor: 2.745

4.  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

5.  The Extended Clearance Concept Following Oral and Intravenous Dosing: Theory and Critical Analyses.

Authors:  Leslie Z Benet; Christine M Bowman; Shufang Liu; Jasleen K Sodhi
Journal:  Pharm Res       Date:  2018-10-22       Impact factor: 4.200

Review 6.  Successful and Unsuccessful Prediction of Human Hepatic Clearance for Lead Optimization.

Authors:  Jasleen K Sodhi; Leslie Z Benet
Journal:  J Med Chem       Date:  2021-03-25       Impact factor: 7.446

7.  There is Only One Valid Definition of Clearance: Critical Examination of Clearance Concepts Reveals the Potential for Errors in Clinical Drug Dosing Decisions.

Authors:  Leslie Z Benet; Jasleen K Sodhi; George Makrygiorgos; Ali Mesbah
Journal:  AAPS J       Date:  2021-05-10       Impact factor: 4.009

8.  Beyond the Michaelis-Menten: Accurate Prediction of In Vivo Hepatic Clearance for Drugs With Low KM.

Authors:  Hyun-Moon Back; Hwi-Yeol Yun; Sang Kyum Kim; Jae Kyoung Kim
Journal:  Clin Transl Sci       Date:  2020-05-26       Impact factor: 4.689

Review 9.  Misuse of the Michaelis-Menten rate law for protein interaction networks and its remedy.

Authors:  Jae Kyoung Kim; John J Tyson
Journal:  PLoS Comput Biol       Date:  2020-10-22       Impact factor: 4.475

  9 in total

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