Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 492

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Cellular Imaging Predictions of Clinical Drug-Induced Liver Injury

Open access
Xu, Jinghai J., Henstock, Peter V., Dunn, Margaret C., Smith, Arthur R., Chabot, Jeffrey R., de Graaf, David·2008·Toxicological Sciences

Abstract

Drug-induced liver injury (DILI) is the most common adverse event causing drug nonapprovals and drug withdrawals. Using drugs as test agents and measuring a panel of cellular phenotypes that are directly linked to key mechanisms of hepatotoxicity, we have developed an in vitro testing strategy that is predictive of many clinical outcomes of DILI. Mitochondrial damage, oxidative stress, and intracellular glutathione, all measured by high content cellular imaging in primary human hepatocyte cultures, are the three most important features contributing to the hepatotoxicity prediction. When applied to over 300 drugs and chemicals including many that caused rare and idiosyncratic liver toxicity in humans, our testing strategy has a true-positive rate of 50-60% and an exceptionally low false-positive rate of 0-5%. These in vitro predictions can augment the performance of the combined traditional preclinical animal tests by identifying idiosyncratic human hepatotoxicants such as nimesulide, telithromycin, nefazodone, troglitazone, tetracycline, sulindac, zileuton, labetalol, diclofenac, chlorzoxazone, dantrolene, and many others. Our findings provide insight to key DILI mechanisms, and suggest a new approach in hepatotoxicity testing of pharmaceuticals.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/toxsci/kfn109

Cites

8 of 8 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 8 references

Cited by

See all 492

Metadata

Authors
Xu, J. J., Henstock, P. V., Dunn, M. C., Smith, A. R., Chabot, J. R., & de Graaf, D.
Venue
Toxicological Sciences
Published
2008-06-03
Volume
105
Issue
1
Pages
97-105
ISSN
  • 1096-0929 (ISSN-L)
  • 1096-6080
OpenAlex
W2132272495
Cited by
492
References
8
FWCI
18.48
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Cellular Imaging Predictions of Clinical Drug-Induced Liver Injury. https://app.cochat.ai/papers/10.1093/toxsci/kfn109
The paper
Xu, J. J., Henstock, P. V., Dunn, M. C., Smith, A. R., Chabot, J. R., & de Graaf, D. (2008). Cellular Imaging Predictions of Clinical Drug-Induced Liver Injury. Toxicological Sciences. https://doi.org/10.1093/toxsci/kfn109

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.