ArticleRegulatory toxicology and pharmacology : RTP2023
Advancing the science of a read-across framework for evaluation of data-poor chemicals incorporating systematic and new approach methods.
Article in Regulatory toxicology and pharmacology : RTP, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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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.
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Who cites it
13 citing papers in PubMed, 27 citations in OpenAlex.
- Human vs. cells vs. machine: A comparative analysis of toxicological points of departure derived from quantitative read-across (qRAx), in vitro data, and In silico predictions.Regulatory toxicology and pharmacology : RTP · 2026Article
- NAMs for closing knowledge gaps in assessment of respiratory uptake - a PARC project.Frontiers in toxicology · 2026Article
- Article
- Deliberating the scientific evidence base for influenza transmission to raw milk consumers.Risk analysis : an official publication of the Society for Risk Analysis · 2025Review
- Comparative review of human health reference values of the United States.Toxicological sciences : an official journal of the Society of Toxicology · 2025Review
- Incorporating new approach methods (NAMs) data in dose-response assessments: The future is now!Journal of toxicology and environmental health. Part B, Critical reviews · 2025Review
- Article
- Untangling the chemical complexity of plastics to improve life cycle outcomes.Nature reviews. Materials · 2024Article
- A Systematic Analysis of Read-Across Adaptations in Testing Proposal Evaluations by the European Chemicals Agency.bioRxiv : the preprint server for biology · 2024Article
- Unlocking the Potential of Clustering and Classification Approaches: Navigating Supervised and Unsupervised Chemical Similarity.Environmental health perspectives · 2024Article
- Developing a Novel Read-Across Concept for Ecotoxicological Risk Assessment of Phosphate Chemicals: A Case Study.Toxics · 2024Article
- Assessing human carcinogenicity risk of agrochemicals without the rodent cancer bioassay.Frontiers in toxicology · 2024Article
- Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
The assessment of human health hazards posed by chemicals traditionally relies on toxicity studies in experimental animals. However, most chemicals currently in commerce do not meet the minimum data requirements for hazard identification and dose-response analysis in human health risk assessment. Previously, we introduced a read-across framework designed to address data gaps for screening-level assessment of chemicals with insufficient in vivo toxicity information (Wang et al., 2012). It relies on inference by analogy from suitably tested source analogues to a target chemical, based on structural, toxicokinetic, and toxicodynamic similarity. This approach has been used for dose-response assessment of data-poor chemicals relevant to the U.S. EPA's Superfund program. We present herein, case studies of the application of this framework, highlighting specific examples of the use of biological similarity for chemical grouping and quantitative read-across. Based on practical knowledge and technological advances in the fields of read-across and predictive toxicology, we propose a revised framework. It includes important considerations for problem formulation, systematic review, target chemical analysis, analogue identification, analogue evaluation, and incorporation of new approach methods. This work emphasizes the integration of systematic methods and alternative toxicity testing data and tools in chemical risk assessment to inform 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.