ArticleComputational toxicology (Amsterdam, Netherlands)2020
An evaluation of the performance of selected (Q)SARs/expert systems for predicting acute oral toxicity.
Article in Computational toxicology (Amsterdam, Netherlands), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- Bioactivity Classification of 2,649 Per- and Polyfluoroalkyl Substances (PFASs) via Quantitative Structure-Activity Relationships and Molecular Docking to Health-Relevant Proteins.Environmental science & technology letters · 2026Article
- Unveiling the interspecies correlation and sensitivity factor analysis of rat and mouse acute oral toxicity of antimicrobial agents: first QSTR and QTTR Modeling report.Toxicology research · 2024Article
- The use of Bayesian methodology in the development and validation of a tiered assessment approach towards prediction of rat acute oral toxicity.Archives of toxicology · 2022Article
- Mapping Mechanistic Pathways of Acute Oral Systemic Toxicity Using Chemical Structure and Bioactivity Measurements.Frontiers in toxicology · 2022Article
- In Silico Models for Predicting Acute Systemic Toxicity.Methods in molecular biology (Clifton, N.J.) · 2022Review
- Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research.Frontiers in toxicology · 2022Article
- CATMoS: Collaborative Acute Toxicity Modeling Suite.Environmental health perspectives · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Multiple US agencies use acute oral toxicity data in a variety of regulatory contexts. One of the ad-hoc groups that the US Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) established to implement the ICCVAM Strategic Roadmap was the Acute Toxicity Workgroup (ATWG) to support the development, acceptance, and actualisation of new approach methodologies (NAMs). One of the ATWG charges was to evaluate
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Registered trials
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.