Literature DB >> 17968737

In vitro-in vivo extrapolation of hepatic clearance: biological tools, scaling factors, model assumptions and correct concentrations.

O Pelkonen1, M Turpeinen.   

Abstract

Although the measurement of metabolite formation or substrate depletion in in vitro systems, from recombinant enzymes to tissue slices, is a relatively routine task, there are a number of more or less unresolved issues in the extrapolation of the enzymatic intrinsic clearance into hepatic metabolic clearance. Nominal concentrations of the drug added to the incubation system are not necessarily the concentration the transporter or the metabolizing enzyme sees. In addition, peculiarities of incubation set-ups should be assessed. Unbound drug fractions (concentrations) in the in vitro system itself should be measured or estimated for the appropriate assessment of enzymatic intrinsic clearance. In addition, blood and/or plasma concentrations to be encountered in the in vivo situation should be measured or estimated for the extrapolation. Extrapolation always means making a number of assumptions and the most important of these, such as scaling factors from recombinant enzymes, microsomes or hepatocytes to the mass unit of the liver, liver weight, blood flow, and distribution volume amongst others, and so on, should be explicitly stated and included in the extrapolation process. Despite all the above-mentioned reservations the in vitro-in vivo extrapolation of metabolic clearance seems to be a useful and mostly fairly precise tool for predicting the important pharmacokinetic processes of a drug.

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Year:  2007        PMID: 17968737     DOI: 10.1080/00498250701620726

Source DB:  PubMed          Journal:  Xenobiotica        ISSN: 0049-8254            Impact factor:   1.908


  12 in total

1.  Ethnic-specific in vitro-in vivo extrapolation and physiologically based pharmacokinetic approaches to predict cytochrome P450-mediated pharmacokinetics in the Chinese population: opportunities and challenges.

Authors:  Guo-Fu Li; Guo Yu; Hong-Xia Liu; Qing-Shan Zheng
Journal:  Clin Pharmacokinet       Date:  2014-02       Impact factor: 6.447

2.  In vivo-in vitro-in silico pharmacokinetic modelling in drug development: current status and future directions.

Authors:  Olavi Pelkonen; Miia Turpeinen; Hannu Raunio
Journal:  Clin Pharmacokinet       Date:  2011-08       Impact factor: 6.447

3.  Parameterization of Microsomal and Cytosolic Scaling Factors: Methodological and Biological Considerations for Scalar Derivation and Validation.

Authors:  Michael J Doerksen; Robert S Jones; Michael W H Coughtrie; Abby C Collier
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2020-12-19       Impact factor: 2.441

4.  Tissue-level modeling of xenobiotic metabolism in liver: An emerging tool for enabling clinical translational research.

Authors:  Marianthi G Lerapetritou; Panos G Georgopoulos; Charles M Roth; Loannis P Androulakis
Journal:  Clin Transl Sci       Date:  2009-06       Impact factor: 4.689

5.  Consideration of the Unbound Drug Concentration in Enzyme Kinetics.

Authors:  Nigel J Waters; R Scott Obach; Li Di
Journal:  Methods Mol Biol       Date:  2021

6.  Fundamentals of Enzyme Kinetics: Michaelis-Menten and Non-Michaelis-Type (Atypical) Enzyme Kinetics.

Authors:  Eleanore Seibert; Timothy S Tracy
Journal:  Methods Mol Biol       Date:  2021

Review 7.  Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non-parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME.

Authors:  Patricio Godoy; Nicola J Hewitt; Ute Albrecht; Melvin E Andersen; Nariman Ansari; Sudin Bhattacharya; Johannes Georg Bode; Jennifer Bolleyn; Christoph Borner; Jan Böttger; Albert Braeuning; Robert A Budinsky; Britta Burkhardt; Neil R Cameron; Giovanni Camussi; Chong-Su Cho; Yun-Jaie Choi; J Craig Rowlands; Uta Dahmen; Georg Damm; Olaf Dirsch; María Teresa Donato; Jian Dong; Steven Dooley; Dirk Drasdo; Rowena Eakins; Karine Sá Ferreira; Valentina Fonsato; Joanna Fraczek; Rolf Gebhardt; Andrew Gibson; Matthias Glanemann; Chris E P Goldring; María José Gómez-Lechón; Geny M M Groothuis; Lena Gustavsson; Christelle Guyot; David Hallifax; Seddik Hammad; Adam Hayward; Dieter Häussinger; Claus Hellerbrand; Philip Hewitt; Stefan Hoehme; Hermann-Georg Holzhütter; J Brian Houston; Jens Hrach; Kiyomi Ito; Hartmut Jaeschke; Verena Keitel; Jens M Kelm; B Kevin Park; Claus Kordes; Gerd A Kullak-Ublick; Edward L LeCluyse; Peng Lu; Jennifer Luebke-Wheeler; Anna Lutz; Daniel J Maltman; Madlen Matz-Soja; Patrick McMullen; Irmgard Merfort; Simon Messner; Christoph Meyer; Jessica Mwinyi; Dean J Naisbitt; Andreas K Nussler; Peter Olinga; Francesco Pampaloni; Jingbo Pi; Linda Pluta; Stefan A Przyborski; Anup Ramachandran; Vera Rogiers; Cliff Rowe; Celine Schelcher; Kathrin Schmich; Michael Schwarz; Bijay Singh; Ernst H K Stelzer; Bruno Stieger; Regina Stöber; Yuichi Sugiyama; Ciro Tetta; Wolfgang E Thasler; Tamara Vanhaecke; Mathieu Vinken; Thomas S Weiss; Agata Widera; Courtney G Woods; Jinghai James Xu; Kathy M Yarborough; Jan G Hengstler
Journal:  Arch Toxicol       Date:  2013-08-23       Impact factor: 5.153

Review 8.  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

9.  Using the concordance of in vitro and in vivo data to evaluate extrapolation assumptions.

Authors:  Gregory S Honda; Robert G Pearce; Ly L Pham; R W Setzer; Barbara A Wetmore; Nisha S Sipes; Jon Gilbert; Briana Franz; Russell S Thomas; John F Wambaugh
Journal:  PLoS One       Date:  2019-05-28       Impact factor: 3.240

10.  Notoginsenoside R1 for Organs Ischemia/Reperfusion Injury: A Preclinical Systematic Review.

Authors:  Qiang Tong; Peng-Chong Zhu; Zhuang Zhuang; Li-Hui Deng; Zi-Hao Wang; Hua Zeng; Guo-Qing Zheng; Yan Wang
Journal:  Front Pharmacol       Date:  2019-10-17       Impact factor: 5.810

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