ArticleEnvironmental science & technology2017
Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology.
Article in Environmental science & technology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 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
83 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Knowledge-Driven Approaches to Create the MTox700+ Metabolite Panel for Predicting Toxicity.Toxicological sciences : an official journal of the Society of Toxicology · 2022Pooled it
- Micro- and nanoplastics-induced neurotoxicity: a CNS-centered, evidence-graded adverse outcome pathway framework based on systematic weight-of-evidence assessment.Archives of toxicology · 2026Review
- Review
- Network toxicology deciphers micro- and nanoplastics-mediated mixture hazard, predictive risk assessment, and regulatory translation.Archives of toxicology · 2026Review
- Causality analysis of toxicological mechanisms in networked systems such as adverse outcome pathway networks.Archives of toxicology · 2026Review
- The Role of ES&T in Advancing Environmental Toxicology and Chemical Risk Assessment: Past, Present, and Future.Environmental science & technology · 2026Review
- Multimodal Cross-Attentive Graph-Based Framework for Predicting In Vivo Endocrine Disruptors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Signal Amplification in the HPT Axis-Evidence for Its Existence, Location, Significance, and Molecular Mechanisms.Acta physiologica (Oxford, England) · 2026Review
- Recent Trends in the Chemical Modification of Polysaccharides for Food Packaging: A Review.Polymers · 2026Review
- Construction of an Adverse Outcome Pathway Framework for Glyphosate-Induced Female Reproductive Toxicity Based on Toxicity Pathways.Environment & health (Washington, D.C.) · 2026Review
- In Silico Hazard Assessment of Ototoxicants Through Machine Learning and Computational Systems Biology.Toxics · 2026Article
- Mass Spectrometry Proteomics: A Key to Faster Drug Discovery.Journal of medicinal chemistry · 2026Review
- Extrapolation steps in quantitativeCurrent research in toxicology · 2026Review
- Cardiotoxicity adverse outcome pathway network: towards mechanistic and quantitative modelling.Frontiers in toxicology · 2026Article
- Beneficial Outcome Pathways: A New Mechanistic Framework to Map the Health Effects of Fasting in Metabolic Dysfunction-Associated Steatotic Liver Disease.Journal of nutrition and metabolism · 2026Review
- Mapping DEHP-induced metabolic dysregulation through multi-omics and systems biology: an adverse outcome pathway network approach.Frontiers in toxicology · 2026Article
- Review
- Chemosensory tobacco product toxicology part 2: toxicological testing, assays, and state of the science.Toxicological sciences : an official journal of the Society of Toxicology · 2025Review
- Integrating population-level effects into the regulatory assessment of endocrine disrupting substances.Integrated environmental assessment and management · 2025Review
- Adverse Outcome Pathways Mechanistically Describing Hepatotoxicity.Methods in molecular biology (Clifton, N.J.) · 2025Article
23 more citing papers are in PubMed but not listed here.
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
A quantitative adverse outcome pathway (qAOP) consists of one or more biologically based, computational models describing key event relationships linking a molecular initiating event (MIE) to an adverse outcome. A qAOP provides quantitative, dose-response, and time-course predictions that can support regulatory decision-making. Herein we describe several facets of qAOPs, including (a) motivation for development, (b) technical considerations, (c) evaluation of confidence, and (d) potential applications. The qAOP used as an illustrative example for these points describes the linkage between inhibition of cytochrome P450 19A aromatase (the MIE) and population-level decreases in the fathead minnow (FHM; Pimephales promelas). The qAOP consists of three linked computational models for the following: (a) the hypothalamic-pitutitary-gonadal axis in female FHMs, where aromatase inhibition decreases the conversion of testosterone to 17β-estradiol (E2), thereby reducing E2-dependent vitellogenin (VTG; egg yolk protein precursor) synthesis, (b) VTG-dependent egg development and spawning (fecundity), and (c) fecundity-dependent population trajectory. While development of the example qAOP was based on experiments with FHMs exposed to the aromatase inhibitor fadrozole, we also show how a toxic equivalence (TEQ) calculation allows use of the qAOP to predict effects of another, untested aromatase inhibitor, iprodione. While qAOP development can be resource-intensive, the quantitative predictions obtained, and TEQ-based application to multiple chemicals, may be sufficient to justify the cost for some applications in regulatory decision-making.
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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.