ReviewToxicology and environmental health sciences2020
In silico prediction of toxicity and its applications for chemicals at work.
Review in Toxicology and environmental health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 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
38 citing papers in PubMed.
- A robust, high-content NAM for repeatable and predictive developmental and reproductive toxicity assessment in C. elegans.Scientific reports · 2026Article
- Review
- A Robust, High-Content NAM for Repeatable and Predictive Developmental and Reproductive Toxicity Assessment in C. elegans.Research square · 2026Article
- Qualitative and quantitative in silico toxicity profiling of "angel dust": phencyclidine (PCP) analogues as new psychoactive substances (3-HO-PCP, 3-MeO-PCP, 4-MeO-PCP, 3-HO-PCE, 3-MeO-PCE, 4-MeO-PCE).Archives of toxicology · 2026Article
- Multi-target mechanisms of Creatine in Parkinson's disease: an in-silico and in-vivo investigation.Genes & genomics · 2026Article
- Natural products and dietary bioactives as antiviral agents against herpesviruses: molecular mechanisms, immunomodulatory actions, and nutritional perspectives.Archives of microbiology · 2026Review
- Machine Learning Models for High-Throughput Screening of Obesogens Based on Pathway Network.Environment & health (Washington, D.C.) · 2026Article
- Unlocking the Antioxidant, Enzyme Inhibitory and Acaricidal Potential ofFood science & nutrition · 2025Article
- Analysis of the Toxicological Profile ofPlants (Basel, Switzerland) · 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
- In Silico Forensic Toxicology: Is It Feasible?Toxics · 2025Review
- Anticancer Effects of Withanolides: In Silico Prediction of Pharmacological Properties.Molecules (Basel, Switzerland) · 2025Article
- Computational approaches: atom-based 3D-QSAR, molecular docking, ADME-Tox, MD simulation and DFT to find novel multi-targeted anti-tubercular agents.BMC chemistry · 2025Article
- Bioactive fraction isolated fromFrontiers in pharmacology · 2025Article
- Computational approaches to predict the toxicity of bioactive natural products: a mini review of methodologies.Food science and biotechnology · 2025Review
- Molecular docking andToxicology reports · 2024Article
- An Assessment of the Ocular Toxicity of Two Major Sources of Environmental Exposure.International journal of environmental research and public health · 2024Article
- Technology Readiness Level Roadmap for Developing Innovative Herbal Medicinal Products.Pharmaceuticals (Basel, Switzerland) · 2024Article
- Chloropicrin induced ocular injury: Biomarkers, potential mechanisms, and treatments.Toxicology letters · 2024Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective and methods: This study reviewed the concept of in silico prediction of chemical toxicity for prevention of occupational cancer and future prospects in workers' health. In this review, a new approach to determine the credibility of in silico predictions with raw data is explored, and the method of determining the confidence level of evaluation based on the credibility of data is discussed. I searched various papers and books related to the in silico prediction of chemical toxicity and carcinogenicity. The intention was to utilize the most recent reports after 2015 regarding in silico prediction. Results and conclusion: The application of in silico methods is increasing with the prediction of toxic risks to human and the environment. The various toxic effects of industrial chemicals have triggered the recognition of the importance of using a combination of in silico models in the risk assessments. In silico occupational exposure models, industrial accidents, and occupational cancers are effectively managed and chemicals evaluated. It is important to identify and manage hazardous substances proactively through the rigorous evaluation of chemicals.
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.