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Pharmaceutical Research

, Volume 27, Issue 10, pp 2150–2161 | Cite as

Prediction of Human Metabolic Clearance from In Vitro Systems: Retrospective Analysis and Prospective View

  • David HallifaxEmail author
  • Joanne A. Foster
  • J. Brian Houston
Research Paper

ABSTRACT

Purpose

To provide a definitive assessment of prediction of in vivo CL int from human liver in vitro systems for assessment of typical underprediction.

Methods

A database of published predictions of clearance from human hepatocytes and liver microsomes was compiled, including only intravenous CL b. The influence of liver model (well-stirred (WS) or parallel tube (PT)), plasma protein binding and clearance level on the relationship between in vitro and in vivo CL int was examined.

Results

Average prediction bias was about 5- and 4-fold for microsomes and hepatocytes, respectively. Reduced bias using the PT model, in preference to the popular WS model, was only marginal across a wide range of clearance with a consequential minor impact on prediction. Increasing underprediction with decreasing fu b, or increasing CL int, was found only for hepatocytes, suggesting fundamental in vitro artefacts rather than failure to model potentially unequilibrated binding during rapid extraction.

Conclusions

In contrast to microsomes, hepatocytes give a disproportionate prediction with increasing clearance suggesting limitations either at the active site, such as cofactor exhaustion, or with intracellular concentration equilibrium, such as rate-limiting cell permeability. A simple log linear empirical relationship can be used to correct hepatocyte predictions.

KEY WORDS

clearance hepatocytes human microsomes prediction 

ABBREVIATIONS

CLint

intrinsic clearance

CLb

blood clearance

WS

‘Well-stirred’ (liver model)

PT

‘Parallel tube’ (liver model)

fub

fraction unbound in blood

CYP

Cytochrome P450

Notes

ACKNOWLEDGEMENTS

J. A. Foster was supported by funding from the EU 6th Framework Programme for Optimisation of Liver and Intestine In Vitro Models for Pharmacokinetics (Liintop/STREP 037499).

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • David Hallifax
    • 1
    • 2
    Email author
  • Joanne A. Foster
    • 1
  • J. Brian Houston
    • 1
  1. 1.Centre for Applied Pharmacokinetic Research School of Pharmacy and Pharmaceutical SciencesUniversity of ManchesterManchesterUK
  2. 2.School of Pharmacy and Pharmaceutical SciencesUniversity of ManchesterManchesterUK

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