Leveraging complementary computational models for prioritizing chemicals of developmental and reproductive toxicity concern: an example of food contact materials
Journal
Archives of Toxicology
Journal Volume
94
Journal Issue
2
Pages
485-494
Date Issued
2020
Author(s)
Abstract
The evaluation of developmental and reproductive toxicity of food contact materials (FCMs) is an important task for food safety. Since traditional experiments are both time-consuming and labor-intensive, only a small number of FCMs have sufficient toxicological data for evaluating their effects on human health. While computational methods such as structural alerts and quantitative structure–activity relationships can serve as first-line tools for the identification of chemicals of high toxicity concern, models with binary outputs and unsatisfied accuracy and coverage prevent the use of computational methods for prioritizing chemicals of high concern. This study proposed a genetic algorithm-based method to develop a weight-of-evidence (WoE) model leveraging complementary methods of structural alerts, quantitative structure–activity relationships and in silico toxicogenomics models for chemical prioritization. The WoE model was applied to evaluate 623 food contact chemicals and identify 26 chemicals of high toxicity concern, where 13 chemicals have been reported to be developmental or reproductive toxic and further experiments are suggested for the remaining 13 chemicals without toxicity data related to developmental and reproductive effects. The proposed WoE model is potentially useful for prioritizing chemicals of high toxicity concern and the methodology may be applied to toxicities other than developmental and reproductive toxicity. ? 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
Subjects
Alternative method; Developmental and reproductive toxicity; Food contact materials; Genetic algorithm; Toxicogenomics; Weight of evidence
SDGs
Other Subjects
Article; computer model; developmental toxicity; evaluation study; food contact material; food processing; genetic algorithm; priority journal; quantitative structure activity relation; reproductive toxicity; risk assessment; toxicogenomics; algorithm; animal; developmental disorder; drug effect; food; food analysis; human; procedures; quantitative structure activity relation; reproduction; theoretical model; toxicogenetics; Algorithms; Animals; Developmental Disabilities; Food; Food Analysis; Humans; Models, Theoretical; Quantitative Structure-Activity Relationship; Reproduction; Toxicogenetics
Type
journal article