Evidence map›Paper›PMID 34289070›Full record

ArticleToxicological sciences : an official journal of the Society of Toxicology2021

Estimating Hepatotoxic Doses Using High-Content Imaging in Primary Hepatocytes.

Imran Shah, Todor Antonijevic, Bryant Chambers, Joshua Harrill, Russell Thomas

Open access · greenAbstract read
In one paragraph

Article in Toxicological sciences : an official journal of the Society of Toxicology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.8field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 12 citations in OpenAlex.

  1. Incorporating new approach methods (NAMs) data in dose-response assessments: The future is now!Journal of toxicology and environmental health. Part B, Critical reviews · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Imran ShahCenter for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.ORCID 0000-0003-0808-0140
Todor AntonijevicCenter for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.
Bryant ChambersCenter for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.
Joshua HarrillCenter for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.ORCID 0000-0003-4317-6391
Russell ThomasCenter for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.ORCID 0000-0002-2340-0301
Environmental Protection Agency · USOak Ridge Associated Universities · US

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Using in vitro data to estimate point of departure (POD) values is an essential component of new approach methodologies (NAMs)-based chemical risk assessments. In this case study, we evaluated a NAM for hepatotoxicity based on rat primary hepatocytes, high-content imaging (HCI), and toxicokinetic modeling. First, we treated rat primary hepatocytes with 10 concentrations (0.2-100 µM) of 51 chemicals that produced hepatotoxicity in repeat-dose subchronic and chronic exposures. Second, we used HCI to measure endoplasmic reticulum stress, mitochondrial function, lysosomal mass, steatosis, apoptosis, DNA texture, nuclear size, and cell number at 24, 48, and 72 h and calculated concentrations at 50% maximal activity (AC50). Third, we estimated administered equivalent doses (AEDs) from AC50 values using toxicokinetic modeling. AEDs using physiologically based toxicokinetic models were 4.1-fold (SD 6.3) and 8.1-fold (SD 15.5) lower than subchronic and chronic lowest observed adverse effect levels (LOAELs), respectively. In contrast, AEDs from ToxCast and Tox21 assays were 89.8-fold (SD 149.5) and 168-fold (SD 323.7) lower than subchronic and chronic LOAELs. Individual HCI endpoints also estimated AEDs for specific hepatic lesions that were lower than in vivo PODs. Lastly, AEDs were similar for different in vitro exposure durations, but steady-state toxicokinetic models produced 7.6-fold lower estimates than dynamic physiologically based ones. Our findings suggest that NAMs from diverse cell types provide conservative estimates of PODs. In contrast, NAMs based on the same species and cell type as the adverse outcome may produce estimates closer to the traditional in vivo PODs.

Indexed as

Drug-Related Side Effects and Adverse ReactionsHepatocytesAnimalsBiological AssayRatsRisk Assessmentcomputational toxicologyhepatotoxicityhigh-content imagingpoint of departuretoxicokinetics

Identifiers

PMID34289070
PMCPMC9721106
OpenAlexW3184252627

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.