Global Sensitivity Analysis of the Rodgers and Rowland Model for Prediction of Tissue: Plasma Partitioning Coefficients: Assessment of the Key Physiological and Physicochemical Factors That Determine Small-Molecule Tissue Distribution-Reference-Cited by-同舟云学术

Global Sensitivity Analysis of the Rodgers and Rowland Model for Prediction of Tissue: Plasma Partitioning Coefficients: Assessment of the Key Physiological and Physicochemical Factors That Determine Small-Molecule Tissue Distribution

Published:2020-02-03 Issue:2 Volume:22 Page:
ISSN:1550-7416
Container-title:The AAPS Journal
language:en
Short-container-title:AAPS J

Author:

Yau Estelle,Olivares-Morales Andrés^ORCID,Gertz Michael,Parrott Neil,Darwich Adam S.,Aarons Leon,Ogungbenro Kayode

Publisher

Springer Science and Business Media LLC

Subject

Pharmaceutical Science

Link

http://link.springer.com/content/pdf/10.1208/s12248-020-0418-7.pdf

Reference81 articles.

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2. Jamei M. Recent advances in development and application of physiologically-based pharmacokinetic (PBPK) models: a transition from academic curiosity to regulatory acceptance. Curr Pharmacol Rep. 2016;2:161–9. https://doi.org/10.1007/s40495-016-0059-9.

3. Luzon E, Blake K, Cole S, Nordmark A, Versantvoort C, Berglund EG. Physiologically based pharmacokinetic modeling in regulatory decision-making at the European Medicines Agency. Clin Pharmacol Ther. 2017;102:98-105. https://doi.org/10.1002/cpt.539.

4. Poulin P, Theil FP. A priori prediction of tissue:plasma partition coefficients of drugs to facilitate the use of physiologically-based pharmacokinetic models in drug discovery. J Pharm Sci. 2000;89(1):16–35. https://doi.org/10.1002/(sici)1520-6017(200001)89:1<16::aid-jps3>3.0.co;2-e.

5. Rodgers T, Leahy D, Rowland M. Physiologically based pharmacokinetic modeling 1: predicting the tissue distribution of moderate-to-strong bases. J Pharm Sci. 2005;94(6):1259–76. https://doi.org/10.1002/jps.20322.

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