AI/ML Models to Predict the Severity of Drug-Induced Liver Injury for Small Molecules-Reference-Cited by-同舟云学术

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AI/ML Models to Predict the Severity of Drug-Induced Liver Injury for Small Molecules

Published:2023-06-09 Issue:7 Volume:36 Page:1129-1139
ISSN:0893-228X
Container-title:Chemical Research in Toxicology
language:en
Short-container-title:Chem. Res. Toxicol.

Author:

Rao Mohan¹^ORCID,Nassiri Vahid²,Alhambra Cristóbal¹,Snoeys Jan¹,Van Goethem Freddy¹,Irrechukwu Onyi¹,Aleo Michael D.³^ORCID,Geys Helena¹,Mitra Kaushik¹^ORCID,Will Yvonne¹

Affiliation:

1. Discovery, Product Development and Supply (DPDS), Preclinical Sciences and Translational Safety (PSTS), Predictive Investigative and Translational Toxicology (PITT), Janssen Pharmaceutical Companies of Johnson and Johnson, La Jolla, California 92121, United States

2. Open Analytics, Jupiterstraat 20, 2600 Antwerpen, Belgium

3. TOXinsights LLC, Boiling Springs, Pennsylvania 17007, United States

Publisher

American Chemical Society (ACS)

Subject

Toxicology,General Medicine

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.chemrestox.3c00098

Reference62 articles.

1. Drug-Induced Liver Injury

2. Drug-Related Hepatotoxicity

3. Managing the challenge of drug-induced liver injury: a roadmap for the development and deployment of preclinical predictive models

4. Key Challenges and Opportunities Associated with the Use of In Vitro Models to Detect Human DILI: Integrated Risk Assessment and Mitigation Plans

5. Intrinsic versus Idiosyncratic Drug-Induced Hepatotoxicity—Two Villains or One?

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