In Silico Prediction of Human and Rat Liver Microsomal Stability via Machine Learning Methods-Reference-Cited by-同舟云学术

In Silico Prediction of Human and Rat Liver Microsomal Stability via Machine Learning Methods

Published:2022-09-02 Issue:9 Volume:35 Page:1614-1624
ISSN:0893-228X
Container-title:Chemical Research in Toxicology
language:en
Short-container-title:Chem. Res. Toxicol.

Author:

Li Longqiang¹,Lu Zhou¹,Liu Guixia¹^ORCID,Tang Yun¹^ORCID,Li Weihua¹^ORCID

Affiliation:

1. Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China

Funder

Ministry of Science and Technology of the People's Republic of China

National Natural Science Foundation of China

Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, East China University of Science and Technology

Publisher

American Chemical Society (ACS)

Subject

Toxicology,General Medicine

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.chemrestox.2c00207

Reference55 articles.

1. Predicting Clearance in Humans from In Vitro Data

2. Mechanistic insights from comparing intrinsic clearance values between human liver microsomes and hepatocytes to guide drug design

3. Retrospective assessment of rat liver microsomal stability at NCATS: data and QSAR models

4. Methylation of Dietary Flavones Greatly Improves Their Hepatic Metabolic Stability and Intestinal Absorption

5. Development of in silico models for human liver microsomal stability

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