Evidence map›Paper›PMID 37490521›Full record

ArticleToxicological sciences : an official journal of the Society of Toxicology2023

Comparison of in silico, in vitro, and in vivo toxicity benchmarks suggests a role for ToxCast data in ecological hazard assessment.

Christopher M Schaupp, Erin M Maloney, Kali Z Mattingly, Jennifer H Olker, Daniel L Villeneuve

Abstract readComparative Study
In one paragraph

Article in Toxicological sciences : an official journal of the Society of Toxicology, 2023. 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
–field-weighted citation impact
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.

  1. Review
  2. Article
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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.

Christopher M SchauppUS Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Center for Computational Toxicology and Exposure, Duluth, Minnesota 55804, USA.ORCID 0000-0002-7792-3861
Erin M MaloneyIntegrated Biological Sciences Program, University of Minnesota-Duluth, Duluth, Minnesota 55804, USA.
Kali Z MattinglySpec-Pro Professional Services, Duluth, Minnesota 55804, USA.ORCID 0000-0001-7987-6061
Jennifer H OlkerUS Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Center for Computational Toxicology and Exposure, Duluth, Minnesota 55804, USA.ORCID 0000-0002-7877-4773
Daniel L VilleneuveUS Environmental Protection Agency, Great Lakes Toxicology and Ecology Division, Center for Computational Toxicology and Exposure, Duluth, Minnesota 55804, USA.ORCID 0000-0003-2801-0203

Funding

Chemical Safety for Sustainability National Research ProgramIntramural EPA EPA999999United States Environmental Protection Agency Office of Research and Development
6 · The paper itself

Abstract

Large repositories of in vitro bioactivity data such as US EPA's Toxicity Forecaster (ToxCast) provide a wealth of publicly accessible toxicity information for thousands of chemicals. These data can be used to calculate point-of-departure (POD) estimates via concentration-response modeling that may serve as lower bound, protective estimates of in vivo effects. However, the data are predominantly based on mammalian models and discussions to date about their utility have largely focused on potential integration into human hazard assessment, rather than application to ecological risk assessment. The goal of the present study was to compare PODs based on (1) quantitative structure-activity relationships (QSARs), (2) the 5th centile of the activity concentration at cutoff (ACC), and (3) lower-bound cytotoxic burst (LCB) from ToxCast, with the distribution of in vivo PODs compiled in the Ecotoxicology Knowledgebase (ECOTOX). While overall correlation between ToxCast ACC5 and ECOTOX PODs for 649 chemicals was weak, there were significant associations among PODs based on LCB and ECOTOX, LCB and QSARs, and ECOTOX and QSARs. Certain classes of compounds showed moderate correlation across datasets (eg, antimicrobials/disinfectants), while others, such as organophosphate insecticides, did not. Unsurprisingly, more precise classifications of the data based on ECOTOX effect and endpoint type (eg, apical vs biochemical; acute vs chronic) had a significant effect on overall relationships. Results of this research help to define appropriate roles for data from new approach methodologies in chemical prioritization and screening of ecological hazards.

Indexed as

BenchmarkingQuantitative Structure-Activity RelationshipAnimalsComputer SimulationDatabases, FactualEcotoxicologyHazardous SubstancesHumansRisk AssessmentToxicity TestsUnited StatesUnited States Environmental Protection AgencyHazardous Substancesalternative toxicity testingecological risk assessmenthigh-throughput screeningnew approach methodologiesquantitative structure-activity relationships

Identifiers

PMID37490521
PMCPMC11217893

What OpenQuestion holds

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Registered trials

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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.