Literature DB >> 34272702

Prediction of Drug Clearance from Enzyme and Transporter Kinetics.

Priyanka R Kulkarni1, Amir S Youssef2, Aneesh A Argikar3.   

Abstract

Accurate estimation of in vivo clearance in human is pivotal to determine the dose and dosing regimen for drug development. In vitro-in vivo extrapolation (IVIVE) has been performed to predict drug clearance using empirical and physiological scalars. Multiple in vitro systems and mathematical modeling techniques have been employed to estimate in vivo clearance. The models for predicting clearance have significantly improved and have evolved to become more complex by integrating multiple processes such as drug metabolism and transport as well as passive diffusion. This chapter covers the use of conventional as well as recently developed methods to predict metabolic and transporter-mediated clearance along with the advantages and disadvantages of using these methods and the associated experimental considerations. The general approaches to improve IVIVE by use of appropriate scalars, incorporation of extrahepatic metabolism and transport and application of physiologically based pharmacokinetic (PBPK) models with proteomics data are also discussed. The chapter also provides an overview of the advantages of using such dynamic mechanistic models over static models for clearance predictions to improve IVIVE.
© 2021. Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Clearance; Extended clearance model; Extrahepatic metabolism; In vitro–in vivo extrapolation; Intrinsic clearance; Physiologically based pharmacokinetic models; Scaling factors; Well stirred model

Year:  2021        PMID: 34272702     DOI: 10.1007/978-1-0716-1554-6_14

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  224 in total

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Journal:  Pharm Res       Date:  2010-07-27       Impact factor: 4.200

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Review 4.  Sandwich-cultured hepatocytes: an in vitro model to evaluate hepatobiliary transporter-based drug interactions and hepatotoxicity.

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Journal:  Drug Metab Rev       Date:  2010-08       Impact factor: 4.518

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Journal:  J Pharmacokinet Biopharm       Date:  1997-08

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Journal:  J Pharmacokinet Biopharm       Date:  1986-06

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Journal:  J Theor Biol       Date:  1978-05-08       Impact factor: 2.691

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Authors:  Faraz Kazmi; Tiffini Hensley; Chad Pope; Ryan S Funk; Greg J Loewen; David B Buckley; Andrew Parkinson
Journal:  Drug Metab Dispos       Date:  2013-02-01       Impact factor: 3.922

10.  Prediction of drug clearance by glucuronidation from in vitro data: use of combined cytochrome P450 and UDP-glucuronosyltransferase cofactors in alamethicin-activated human liver microsomes.

Authors:  Peter J Kilford; Rowan Stringer; Bindi Sohal; J Brian Houston; Aleksandra Galetin
Journal:  Drug Metab Dispos       Date:  2008-10-02       Impact factor: 3.922

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  1 in total

1.  Towards best use and regulatory acceptance of generic physiologically based kinetic (PBK) models for in vitro-to-in vivo extrapolation (IVIVE) in chemical risk assessment.

Authors:  Abdulkarim Najjar; Ans Punt; John Wambaugh; Alicia Paini; Corie Ellison; Styliani Fragki; Enrica Bianchi; Fagen Zhang; Joost Westerhout; Dennis Mueller; Hequn Li; Quan Shi; Timothy W Gant; Phil Botham; Rémi Bars; Aldert Piersma; Ben van Ravenzwaay; Nynke I Kramer
Journal:  Arch Toxicol       Date:  2022-09-05       Impact factor: 6.168

  1 in total

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