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Research ArticleArticle

Application of a Physiologically Based Pharmacokinetic Model to Assess Propofol Hepatic and Renal Glucuronidation in Isolation: Utility of In Vitro and In Vivo Data

Katherine L. Gill, Michael Gertz, J. Brian Houston and Aleksandra Galetin
Drug Metabolism and Disposition April 2013, 41 (4) 744-753; DOI: https://doi.org/10.1124/dmd.112.050294
Katherine L. Gill
Centre for Applied Pharmacokinetic Research, School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester, United Kingdom
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Michael Gertz
Centre for Applied Pharmacokinetic Research, School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester, United Kingdom
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J. Brian Houston
Centre for Applied Pharmacokinetic Research, School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester, United Kingdom
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Aleksandra Galetin
Centre for Applied Pharmacokinetic Research, School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester, United Kingdom
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Abstract

A physiologically based pharmacokinetic (PBPK) modeling approach was used to assess the prediction accuracy of propofol hepatic and extrahepatic metabolic clearance and to address previously reported underprediction of in vivo clearance based on static in vitro–in vivo extrapolation methods. The predictive capacity of propofol intrinsic clearance data (CLint) obtained in human hepatocytes and liver and kidney microsomes was assessed using the PBPK model developed in MATLAB software. Microsomal data obtained by both substrate depletion and metabolite formation methods and in the presence of 2% bovine serum albumin were considered in the analysis. Incorporation of hepatic and renal in vitro metabolic clearance in the PBPK model resulted in underprediction of propofol clearance regardless of the source of in vitro data; the predicted value did not exceed 35% of the observed clearance. Subsequently, propofol clinical data from three dose levels in intact patients and anhepatic subjects were used for the optimization of hepatic and renal CLint in a simultaneous fitting routine. Optimization process highlighted that renal glucuronidation clearance was underpredicted to a greater extent than liver clearance, requiring empirical scaling factors of 17 and 9, respectively. The use of optimized clearance parameters predicted hepatic and renal extraction ratios within 20% of the observed values, reported in an additional independent clinical study. This study highlights the complexity involved in assessing the contribution of extrahepatic clearance mechanisms and illustrates the application of PBPK modeling, in conjunction with clinical data, to assess prediction of clearance from in vitro data for each tissue individually.

Footnotes

  • This research was supported by a consortium of pharmaceutical companies within the Centre for Applied Pharmacokinetic Research at the University of Manchester; and a PhD studentship from the Biotechnology and Biological Sciences Research Council [Grant BB/F01760X/1] (to K.L.G.).

  • dx.doi.org/10.1124/dmd.112.050294.

  • ↵Embedded ImageThis article has supplemental material available at dmd.aspetjournals.org.

  • Received November 23, 2012.
  • Accepted January 9, 2013.
  • Copyright © 2013 by The American Society for Pharmacology and Experimental Therapeutics
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Drug Metabolism and Disposition: 41 (4)
Drug Metabolism and Disposition
Vol. 41, Issue 4
1 Apr 2013
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Research ArticleArticle

Applying a PBPK Model to Predict Renal Metabolism

Katherine L. Gill, Michael Gertz, J. Brian Houston and Aleksandra Galetin
Drug Metabolism and Disposition April 1, 2013, 41 (4) 744-753; DOI: https://doi.org/10.1124/dmd.112.050294

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Research ArticleArticle

Applying a PBPK Model to Predict Renal Metabolism

Katherine L. Gill, Michael Gertz, J. Brian Houston and Aleksandra Galetin
Drug Metabolism and Disposition April 1, 2013, 41 (4) 744-753; DOI: https://doi.org/10.1124/dmd.112.050294
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