Pharmacokinetics, Pharmacodynamics and Drug Transport and Metabolism
Toward a new paradigm for the efficient in vitroin vivo extrapolation of metabolic clearance in humans from hepatocyte data

https://doi.org/10.1002/jps.23502Get rights and content

Abstract

The objective of this study was to follow up a previous study on a comparative analysis of diverse in vitroin vivo extrapolation (IVIVE) methods used for predicting hepatic metabolic clearance (CL) of drugs from intrinsic clearance (CLint) data determined in microsomal incubations, but using hepatocyte data instead. Six IVIVE methods were compared: the “conventional and conventional bias‐corrected methods,” the “regression equation method,” the “direct scaling method,” the “Berezhkovskiy's method,” and the “novel IVIVE method of Poulin et al.” offering a new paradigm. A large and diverse dataset of 49 drugs were collected from the literature for hepatocyte data in human. Based on all statistical parameters, this study confirms that the novel IVIVE method of Poulin et al. shows the greatest prediction performance among the IVIVE methods tested by using hepatocyte data. The superior prediction performance of this novel IVIVE method is again most pronounced for (a) drugs highly bound in blood, (b) drugs bound to albumin, and (c) low CL drugs. Because the novel IVIVE method has been developed particularly to improve the prediction accuracy for drugs with such properties, this study confirms its utility. Furthermore, the results of the current comparative analysis performed using hepatocyte data confirm the findings of a previous analysis made with microsomal data. Overall, the proposed novel IVIVE method offers a new paradigm for the prediction of hepatic metabolic CL particularly for drugs, which have the aforementioned properties, and, hence, this would contribute to a more accurate CL prediction for small molecules in drug discovery and development, interspecies scaling, and can potentially be used for the optimization of driving factors of CL in an attempt to facilitate the simulation of drug disposition by using the physiologically based pharmacokinetics (PBPK) model. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 102:3239–3251, 2013

Section snippets

Abbreviations used:

AAG, alpha1‐acid glycoprotein; AFE, average‐fold error; AL, albumin; CCC, concordance correlation coefficient global; CL, clearance; CLint, intrinsic clearance; fuinc, unbound fraction in incubation; fuliver, unbound fraction in liver; fub, unbound fraction in blood; fub‐app, apparent unbound fraction in blood; IVIVE, in vitroin vivo extrapolation; Km, Michaelis–Menten constant; LBF, blood flow rate to liver; SF, scaling factor; PhRMA, Pharmaceutical Manufacturers of America; RMSE, root

INTRODUCTION

Hepatic metabolic clearance (CL) is one of the more essential pharmacokinetics (PK) parameters to estimate in drug discovery and development. It is common practice to use in vitroin vivo extrapolation (IVIVE) methods to scale up the intrinsic clearance (CLint) determined in vitro in the human liver preparations for predicting CL in vivo of drugs that are mainly eliminated by metabolism.1,2 Recently, a comparative analysis using a dataset of 139 drugs obtained in preclinical species and human

METHOD

The methodology used to attain our goal consisted of comparing predicted CL derived from in vitro hepatocyte data and in vivo CL values observed in humans for several drugs. Five IVIVE methods that have undergone previous comparative assessments1, 2, 3 were the focus of further evaluation in this study. In addition, the recently published “regression method” of Sohlenius‐Sternbeck et al.4 was also included in the current comparative analysis. Therefore, a total of six IVIVE methods were

Comparative Assessment for Various IVIVE Methods for Predicting CL

Six IVIVE calculation methods of CL were compared using the same drug dataset, and the comparative assessment was made on the basis of several statistical parameters. The overall statistical summary in terms of accuracy, precision, and correlation is listed in Tables 3 and 4 for the different scenarios of prediction. The plots of predicted versus observed blood CL values for each method are shown in Figures 1a–1e, whereas Figure 2 compares the precision bias across several IVIVE methods.

Predictivity of Human Dataset

On the

DISCUSSION

The main focus of this study was to provide a comparative analysis between recently published IVIVE methods by predicting blood CL in vivo in humans from hepatocyte data for several drugs. The findings of the current comparative analysis made from hepatocyte data are similar to three other assessments made previously from microsomal data1, 2, 3; the novel IVIVE method of Poulin et al.1,2 offers a significant improvement for the prediction of blood CL over other IVIVE methods. This is

CONCLUSIONS

This study demonstrated the prediction performance of six IVIVE methods for the prediction of blood CL in vivo of drugs in human from hepatocyte data. The results of the current comparative analysis performed from hepatocyte data confirm the findings of a previous analysis made from microsomal data; therefore, the novel IVIVE method proposed in two previous manuscripts1,2 was the most successful in various prediction scenarios over other methods either based on microsomal or hepatocyte data.

Acknowledgements

This work represents an initiative undertaken in collaboration as a part of the research program of Dr. Poulin, and of Dr. Haddad's program, which is supported by a Discovery Grant from the National Sciences and Engineering Research Council of Canada (NSERC). The authors wish to thanks Dr. Cornelis Hop and Dr. Jane Kenny, at Genentech Inc., as precursors of fruitful discussions that have strongly contributed to the conduct of this work.

REFERENCES (37)

  • S. Ekins et al.

    Three‐dimensional quantitative structure activity relationship computational approaches for prediction of human in vitro intrinsic clearance

    J Pharmacol Exp Ther

    (2000)
  • Y. Naritomi et al.

    Utility of hepatocytes in predicting drug metabolism: Comparison of hepatic intrinsic clearance in rats and humans in vitro and in vitro

    Drug Metb Disp

    (2003)
  • D. Halifax et al.

    Clearance‐dependent underprediction of in vivo intrinsic clearance from human hepatocytes: Comparison with permeabilities from artificial membrane (PAMPA) assay, in silico and caco‐2 assay, for 65 drugs

    Eur J Pharm Sci

    (2012)
  • L. Huang et al.

    Relationship between passive permeability, efflux, and predictability of clearance from in vitro metabolic intrinsic clearance

    Drug Metab Disp

    (2010)
  • Product monograph of Irbesartan. http://www.bmscanada.ca/static/products/en/pm_pdf/Avapro_EN_PM.pdf. Assessed 18 of...
  • K.L. Gill et al.

    Characterization of in vitro glucuronidation clearance of a range of drugs in human kidney microsomes: Comparison with liver and intestinal glucuronidation and impact of albumin

    Drug Metab Dispos

    (2012)
  • C.M. Loi et al.

    Clinical pharmacokinetics of troglitazone

    Clin Pharmacokinet

    (1999)
  • T. Morgan

    Clinical pharmacokinetics and pharmacodynamics of carvedilol

    Clin Pharmacokinet

    (1994)
  • Cited by (44)

    • A New Guidance for the Prediction of Hepatic Clearance in the Early Drug Discovery and Development from the in Vitro-to-in Vivo Extrapolation Method and an Approach for Exploring Whether an Albumin-Mediated Hepatic Uptake Phenomenon Could be Present Under in Vivo Conditions

      2021, Journal of Pharmaceutical Sciences
      Citation Excerpt :

      Several scientists have already demonstrated with several drugs and diverse experimental settings that the unbound CLint in the liver seems to increase more than anticipated in the presence versus the absence of ALB.2,5,7-14,16-18 Consequently, specific IVIVE methods have also been developed to add some serum directly in the incubation medium, or particularly to replace the in vitro value of fup in the IVIVEs with new scaling factors as follow 1) the experimentally-determined liver-to-plasma ratio of the unbound drug moiety,17,18 2) the parameters of binding of the ALB-bound drug complex with the hepatocyte membrane according to the old-facilitated dissociation model,14 3) empirically-derived factors covering the differences observed between the in vitro and in vivo unbound CLint values following regression analyses from several drug datasets,16 and 4) an fup value adjusted (fup-adjusted) to cover the in vitro-to-in vivo differences in the pH gradient effect for an ionized drug and in the ALB-mediated hepatic uptake phenomenon for the drugs binding to ALB by considering the difference in the physiological concentration of ALB between the liver and plasma (or the incubation medium) .2,5,7-13 The later model of fup-adjusted is particularly of interest since it only requires knowing the input value of fup, which is an in vitro parameter readily available for drugs.

    View all citing articles on Scopus
    View full text