ArticleGreen chemistry : an international journal and green chemistry resource : GC2016
QSAR models of human data can enrich or replace LLNA testing for human skin sensitization.
Article in Green chemistry : an international journal and green chemistry resource : GC, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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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.
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Who cites it
22 citing papers in PubMed.
- Integration of Machine Learning With PBPK and QSAR Modeling Approaches to Facilitate Drug Discovery and Development.CPT: pharmacometrics & systems pharmacology · 2026Review
- Gene regulation and signaling pathways in immune response to respiratory sensitizers: a database analysis.Frontiers in immunology · 2025Article
- QSAR Classification Modeling Using Machine Learning with a Consensus-Based Approach for Multivariate Chemical Hazard End Points.ACS omega · 2024Article
- Estimation of the Skin Sensitization Potential of Chemicals of the Acyl Domain Using DFT-Based Calculations.Chemical research in toxicology · 2024Article
- Article
- The transcriptomic signature of respiratory sensitizers using an alveolar model.Cell biology and toxicology · 2024Article
- An In Vitro Alveolar Model Allows for the Rapid Assessment of Particles for Respiratory Sensitization Potential.International journal of molecular sciences · 2023Article
- PreS/MD: Predictor of Sensitization Hazard for Chemical Substances Released From Medical Devices.Toxicological sciences : an official journal of the Society of Toxicology · 2022Article
- STopTox: AnEnvironmental health perspectives · 2022Article
- Investigative on the Molecular Mechanism of Licorice Flavonoids Anti-Melanoma by Network Pharmacology, 3D/2D-QSAR, Molecular Docking, and Molecular Dynamics Simulation.Frontiers in chemistry · 2022Article
- Advances in Assessing Hazard and Risk to Emerging Threats and Emergency Response: Comparing and Contrasting Efforts of 3 Federal Agencies.Toxicological sciences : an official journal of the Society of Toxicology · 2021Article
- Drug Screening, Oral Bioavailability and Regulatory Aspects: A Need for Human Organoids.Pharmaceutics · 2021Review
- Curated Data In - TrustworthyAlternatives to laboratory animals : ATLA · 2021Review
- Mapping Chemical Respiratory Sensitization: How Useful Are Our Current Computational Tools?Chemical research in toxicology · 2021Article
- Evaluation of the global performance of eight in silico skin sensitization models using human data.ALTEX · 2021Article
- Evaluation of QSAR Equations for Virtual Screening.International journal of molecular sciences · 2020Article
- Cheminformatics-driven discovery of polymeric micelle formulations for poorly soluble drugs.Science advances · 2019Article
- Immunogenicity of Protein Pharmaceuticals.Journal of pharmaceutical sciences · 2019Review
- Multi-Descriptor Read Across (MuDRA): A Simple and Transparent Approach for Developing Accurate Quantitative Structure-Activity Relationship Models.Journal of chemical information and modeling · 2018Article
- Chemotext: A Publicly Available Web Server for Mining Drug-Target-Disease Relationships in PubMed.Journal of chemical information and modeling · 2018Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Skin sensitization is a major environmental and occupational health hazard. Although many chemicals have been evaluated in humans, there have been no efforts to model these data to date. We have compiled, curated, analyzed, and compared the available human and LLNA data. Using these data, we have developed reliable computational models and applied them for virtual screening of chemical libraries to identify putative skin sensitizers. The overall concordance between murine LLNA and human skin sensitization responses for a set of 135 unique chemicals was low (R = 28-43%), although several chemical classes had high concordance. We have succeeded to develop predictive QSAR models of all available human data with the external correct classification rate of 71%. A consensus model integrating concordant QSAR predictions and LLNA results afforded a higher CCR of 82% but at the expense of the reduced external dataset coverage (52%). We used the developed QSAR models for virtual screening of CosIng database and identified 1061 putative skin sensitizers; for seventeen of these compounds, we found published evidence of their skin sensitization effects. Models reported herein provide more accurate alternative to LLNA testing for human skin sensitization assessment across diverse chemical data. In addition, they can also be used to guide the structural optimization of toxic compounds to reduce their skin sensitization potential.
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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.