ArticleComputational toxicology (Amsterdam, Netherlands)2020
Variability in
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 37 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
37 citing papers in PubMed.
- Variability and uncertainty of data from genotoxicity test guidelines: what we know and why it matters.Archives of toxicology · 2026Review
- Review on Predictive Models and Integration Strategies for Holistic Impact Assessment of Chemicals and Materials.Environmental science & technology · 2026Review
- Uncertainty-aware machine learning to predict non-cancer human toxicity for the global chemicals market.Nature communications · 2026Article
- Perspectives on variability ofFrontiers in toxicology · 2026Article
- Lipopolysaccharide-induced alterations in barrier integrity and inflammatory signaling in porcine small intestinal organoids.PloS one · 2026Article
- Interpretation of in vitro concentration-response data for risk assessment and regulatory decision-making: Report from the 2022 IWGT quantitative analysis expert working group meeting.Environmental and molecular mutagenesis · 2025Review
- Article
- Comparative case study on NAMs: towards enhancing specific target organ toxicity analysis.Archives of toxicology · 2024Article
- Community-Engaged Research and the Use of Open Access ToxVal/ToxRef In Vivo Databases and New Approach Methodologies (NAM) to Address Human Health Risks From Environmental Contaminants.Birth defects research · 2024Article
- A systematic analysis of read-across within REACH registration dossiers.Computational toxicology (Amsterdam, Netherlands) · 2024Article
- Probabilistic Reference and 10% Effect Concentrations for Characterizing Inhalation Non-cancer and Developmental/Reproductive Effects for 2,160 Substances.Environmental science & technology · 2024Article
- Evaluation of in silico model predictions for mammalian acute oral toxicity and regulatory application in pesticide hazard and risk assessment.Regulatory toxicology and pharmacology : RTP · 2024Article
- Big Question to Developing Solutions: A Decade of Progress in the Development of Aquatic New Approach Methodologies from 2012 to 2022.Environmental toxicology and chemistry · 2024Article
- Novel Strategy to Assess the Neurotoxicity of Organic Solvents Such as Glycol Ethers: Protocol for Combining In Vitro and In Silico Methods With Human-Controlled Exposure Experiments.JMIR research protocols · 2024Article
- Reproducibility of organ-level effects in repeat dose animal studies.Computational toxicology (Amsterdam, Netherlands) · 2023Article
- New approach methodologies in human regulatory toxicology - Not if, but how and when!Environment international · 2023Review
- G × E interactions as a basis for toxicological uncertainty.Archives of toxicology · 2023Article
- ProfhEX: AI-based platform for small molecules liability profiling.Journal of cheminformatics · 2023Article
- Probabilistic Points of Departure and Reference Doses for Characterizing Human Noncancer and Developmental/Reproductive Effects for 10,145 Chemicals.Environmental health perspectives · 2023Article
- A value of information framework for assessing the trade-offs associated with uncertainty, duration, and cost of chemical toxicity testing.Risk analysis : an official publication of the Society for Risk Analysis · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
New approach methodologies (NAMs) for chemical hazard assessment are often evaluated via comparison to animal studies; however, variability in animal study data limits NAM accuracy. The US EPA Toxicity Reference Database (ToxRefDB) enables consideration of variability in effect levels, including the lowest effect level (LEL) for a treatment-related effect and the lowest observable adverse effect level (LOAEL) defined by expert review, from subacute, subchronic, chronic, multi-generation reproductive, and developmental toxicity studies. The objectives of this work were to quantify the variance within systemic LEL and LOAEL values, defined as potency values for effects in adult or parental animals only, and to estimate the upper limit of NAM prediction accuracy. Multiple linear regression (MLR) and augmented cell means (ACM) models were used to quantify the total variance, and the fraction of variance in systemic LEL and LOAEL values explained by available study descriptors (e.g., administration route, study type). The MLR approach considered each study descriptor as an independent contributor to variance, whereas the ACM approach combined categorical descriptors into cells to define replicates. Using these approaches, total variance in systemic LEL and LOAEL values (in log
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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.