Advancing Predictive Hepatotoxicity at the Intersection of Experimental, in Silico, and Artificial Intelligence Technologies-Reference-Cited by-同舟云学术

Advancing Predictive Hepatotoxicity at the Intersection of Experimental, in Silico, and Artificial Intelligence Technologies

Published:2018-05-03 Issue:6 Volume:31 Page:412-430
ISSN:0893-228X
Container-title:Chemical Research in Toxicology
language:en
Short-container-title:Chem. Res. Toxicol.

Author:

Fraser Keith¹,Bruckner Dylan M.¹,Dordick Jonathan S.¹^ORCID

Affiliation:

1. Department of Chemical and Biological Engineering and Department of Biological Sciences Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, New York 12180, United States

Funder

National Institute of Environmental Health Sciences

Taconic Biosciences, Inc.

Publisher

American Chemical Society (ACS)

Subject

Toxicology,General Medicine

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.chemrestox.8b00054

Reference148 articles.

1. Idiosyncratic Drug-Induced Liver Injury (IDILI): Potential Mechanisms and Predictive Assays

2. Clinical development success rates for investigational drugs

3. A transcriptomics-based hepatotoxicity comparison between the zebrafish embryo and established human and rodent in vitro and in vivo models using cyclosporine A, amiodarone and acetaminophen

4. Human pluripotent stem cell-derived neural constructs for predicting neural toxicity

5. Characterization of primary human hepatocyte spheroids as a model system for drug-induced liver injury, liver function and disease

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