ReviewWiley interdisciplinary reviews. Computational molecular science
In silico toxicology: From structure-activity relationships towards deep learning and adverse outcome pathways.
Review in Wiley interdisciplinary reviews. Computational molecular science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 1 of them a synthesis that pooled 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.
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
46 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Hydrazones as Potential Antimelanoma Prototypes: A Systematic and Patent Review.Anti-cancer agents in medicinal chemistry · 2026Pooled it
- Semantic knowledge improves molecular machine learning for chemical toxicity prediction.iScience · 2026Article
- In Vivo Evaluation of Psoralen in a Copper Sulfate-Induced Chick (Gallus gallus domesticus) Emesis Model and In Silico Analysis of Its Interaction With DChemistryOpen · 2026Article
- Integration of in vitro and in silico approaches enables prediction of drug-induced liver injury.Archives of toxicology · 2026Article
- A pipeline for developing AI-driven models to predict molecular initiating events: a case study on neural tube defects.Journal of cheminformatics · 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
- Exploring the pharmacological potential of plant-based hand sanitizer composition: characterization, activity evaluation, and in silico assessment.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- AI-based methods for the assessment of DNA damage and repair mechanisms.Frontiers in systems biology · 2026Review
- Establishment of an Integrated Model for Predicting Compound Mutagenicity with a Feature Importance Analysis.Journal of chemical information and modeling · 2025Article
- HazChemNet: A Deep Learning Model for Hazardous Chemical Prediction.International journal of molecular sciences · 2025Article
- In Silico Forensic Toxicology: Is It Feasible?Toxics · 2025Review
- Article
- The 3C (Cell Culture, Computer Simulation, Clinical Trial) Solution for Optimizing the 3R (Replace, Reduction, Refine) Framework during Preclinical Research Involving Laboratory Animals.ACS pharmacology & translational science · 2025Review
- Absorption of Toxicants from the Ocular Surface: Potential Applications in Toxicology.Biomedicines · 2025Review
- StreamChol: a web-based application for predicting cholestasis.Journal of cheminformatics · 2025Article
- Network pharmacology and molecular dynamics simulation reveal antineoplastic potential of Antarctic sponge-derived suberitenones.Frontiers in chemistry · 2025Article
- Molecular docking andToxicology reports · 2024Article
- Computational Strategies for Assessing Adverse Outcome Pathways: Hepatic Steatosis as a Case Study.International journal of molecular sciences · 2024Review
- Molecular similarity in chemical informatics and predictive toxicity modeling: from quantitative read-across (q-RA) to quantitative read-across structure-activity relationship (q-RASAR) with the application of machine learning.Critical reviews in toxicology · 2024Review
- High-Throughput Molecular Modeling and Evaluation of the Anti-Inflammatory Potential of Açaí Constituents against NLRP3 Inflammasome.International journal of molecular sciences · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
In silico toxicology is an emerging field. It gains increasing importance as research is aiming to decrease the use of animal experiments as suggested in the 3R principles by Russell and Burch. In silico toxicology is a means to identify hazards of compounds before synthesis, and thus in very early stages of drug development. For chemical industries, as well as regulatory agencies it can aid in gap-filling and guide risk minimization strategies. Techniques such as structural alerts, read-across, quantitative structure-activity relationship, machine learning, and deep learning allow to use in silico toxicology in many cases, some even when data is scarce. Especially the concept of adverse outcome pathways puts all techniques into a broader context and can elucidate predictions by mechanistic insights. This article is categorized under:Structure and Mechanism > Computational Biochemistry and BiophysicsData Science > Chemoinformatics.
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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.