Prediction of Drug Clearance from Enzyme and Transporter Kinetics.

Autor:	Kulkarni PR; Takeda Pharmaceuticals International, Cambridge, MA, USA., Youssef AS; GlaxoSmithKline, Collegeville, PA, USA., Argikar AA; Synteract Inc, Morrisville, NC, USA. Aneesh.Argikar@synteract.com.
Jazyk:	angličtina
Zdroj:	Methods in molecular biology (Clifton, N.J.) [Methods Mol Biol] 2021; Vol. 2342, pp. 369-417.
DOI:	10.1007/978-1-0716-1554-6_14
Abstrakt:	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.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu