ArticleEnvironmental health perspectives2021
CATMoS: Collaborative Acute Toxicity Modeling Suite.
Article in Environmental health perspectives, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 57 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
57 citing papers in PubMed, 131 citations in OpenAlex.
- AI/ML-based computational models for toxicity prediction.Environmental science and pollution research international · 2026Review
- Predicting Aquatic Species Sensitivity Distributions Using Machine Learning in a Regulatory Setting.Chemical research in toxicology · 2026Article
- Democratizing Artificial Intelligence in Toxicology: Real-World Applications and Automated Computational Workflows.Chemical research in toxicology · 2026Review
- DeepSnap: From Three-Dimensional Molecular Images to Quantitative Structure-Activity Predictions.International journal of molecular sciences · 2026Review
- Integration of Machine Learning With PBPK and QSAR Modeling Approaches to Facilitate Drug Discovery and Development.CPT: pharmacometrics & systems pharmacology · 2026Review
- Article
- Hierarchical Mechanistic Modeling of Complex Toxicity Endpoints from Public Concentration-Response Data.Environmental science & technology · 2026Article
- Towards Explainable Computational Toxicology: Linking Antitargets to Rodent Acute Toxicity.Pharmaceutics · 2025Article
- Expert opinion: Seeking truth through inquiry: A discussion on the online news from Science on November 21, "Exclusive: CDC to end all monkey research".Animal models and experimental medicine · 2025Article
- Comprehensive reexamination of the acute toxicity of nitrogen mustards: HN-1, HN-2 and HN-3 as blister agents: application of multi in silico approach.Archives of toxicology · 2025Article
- Review
- Building a compendium of expert driven read-across cases to facilitate an analysis of the contribution that different similarity contexts play in read-across performance.Computational toxicology (Amsterdam, Netherlands) · 2025Article
- Optimizing the implementation of safe and sustainable by design to better enable sustainable innovation.iScience · 2025Review
- ToxACoL: an endpoint-aware and task-focused compound representation learning paradigm for acute toxicity assessment.Nature communications · 2025Article
- Advancing systemic toxicity risk assessment: Evaluation of a NAM-based toolbox approach.Toxicological sciences : an official journal of the Society of Toxicology · 2025Article
- An advancement in developmental and reproductive toxicity (DART) risk assessment: evaluation of a bioactivity and exposure-based NAM toolbox.Frontiers in toxicology · 2025Article
- Prediction of chemical-induced acute toxicity using in vitro assay data and chemical structure.Toxicology and applied pharmacology · 2024Article
- Two-Stage Machine Learning-Based Approach to Predict Points of Departure for Human Noncancer and Developmental/Reproductive Effects.Environmental science & technology · 2024Article
- The rat acute oral toxicity of trifluoromethyl compounds (TFMs): a computational toxicology study combining the 2D-QSTR, read-across and consensus modeling methods.Archives of toxicology · 2024Article
- The estimation of acute oral toxicity (LDArchives of toxicology · 2024Article
Corrections and comments
- Erratum issued
- Erratum issued
Authors and funding
102 authors at 20 institutions in 9 countries.
Funding
Abstract
backgroundHumans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests.
objectivesThe U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop
methodsAn acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches.
resultsThe resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with DISCUSSION: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for
Indexed as
Identifiers
What OpenQuestion holds
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.