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Updated: Feb 3, 2026

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Published on: November 17, 2018
The Extended Clearance Concept Following Oral and Intravenous Dosing: Theory and Critical Analyses
Leslie Z Benet1, Christine M Bowman2, Shufang Liu2
1Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, California, 94143-0912, USA. Leslie.Benet@ucsf.edu.
Purpose:
To derive the theoretical basis for the extended clearance model of organ elimination following both oral and IV dosing, and critically analyze the approaches previously taken.
Methods:
We derived from first principles the theoretical basis for the extended clearance concept of organ elimination following both oral and IV dosing and critically analyzed previous approaches.
Results:
We point out a number of critical characteristics that have either been misinterpreted or not clearly presented in previously published treatments. First, the extended clearance concept is derived based on the well-stirred model. It is not appropriate to use alternative models of hepatic clearance. In analyzing equations, clearance terms are all intrinsic clearances, not total drug clearances. Flow and protein binding parameters should reflect blood measurements, not plasma values. In calculating the AUCR-factor following oral dosing, the AUC terms do not include flow parameters. We propose that calculations of AUCR may be a more useful approach to evaluate drug-drug and pharmacogenomic interactions than evaluating rate-determining steps. Through analyses of cerivastatin and fluvastatin interactions with cyclosporine we emphasize the need to characterize volume of distribution changes resulting from transporter inhibition/induction that can affect rate constants in PBPK models. Finally, we note that for oral doses, prediction of systemic and intrahepatic drug-drug interactions do not require knowledge of fu,H or Kp,uu for substrates/victims.
Conclusions:
The extended clearance concept is a powerful tool to evaluate drug-drug interactions, pharmacogenomic and disease state variance but evaluating the AUCR-factor may provide a more valuable approach than characterizing rate-determining steps.
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