Trivariate Linear Regression and Machine Learning Prediction of Possible Roles of Efflux Transporters in Estimated Intestinal Permeability Values of 301 Disparate Chemicals-Reference-Cited by-同舟云学术

Trivariate Linear Regression and Machine Learning Prediction of Possible Roles of Efflux Transporters in Estimated Intestinal Permeability Values of 301 Disparate Chemicals

Published:2022-08-01 Issue:8 Volume:45 Page:1142-1157
ISSN:0918-6158
Container-title:Biological and Pharmaceutical Bulletin
language:en
Short-container-title:Biological & Pharmaceutical Bulletin

Author:

Shimizu Makiko¹,Hayasaka Riku¹,Kamiya Yusuke¹,Yamazaki Hiroshi¹

Affiliation:

1. Showa Pharmaceutical University

Publisher

Pharmaceutical Society of Japan

Subject

Pharmaceutical Science,Pharmacology,General Medicine

Link

https://www.jstage.jst.go.jp/article/bpb/45/8/45_b22-00221/_pdf

Reference109 articles.

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4. 4) Kamiya Y, Omura A, Hayasaka R, Saito R, Sano I, Handa K, Ohori J, Kitajima M, Shono F, Funatsu K, Yamazaki H. Prediction of permeability across intestinal cell monolayers for 219 disparate chemicals using in vitro experimental coefficients in a pH gradient system and in silico analyses by trivariate linear regressions and machine learning. Biochem. Pharmacol., 192, 114749 (2021).

5. 5) Kamiya Y, Otsuka S, Miura T, Takaku H, Yamada R, Nakazato M, Nakamura H, Mizuno S, Shono F, Funatsu K, Yamazaki H. Plasma and hepatic concentrations of chemicals after virtual oral administrations extrapolated using rat plasma data and simple physiologically based pharmacokinetic models. Chem. Res. Toxicol., 32, 211–218 (2019).

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