Application of in silico modelling to estimate toxicity of migrating substances from food packaging

• Published in: Food and chemical toxicology Vol. 71; pp. 136 - 141
• Main Authors: Price, Nicholas, Chaudhry, Qasim
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.09.2014; Elsevier
• Subjects: (Q)SAR; Biological and medical sciences; carcinogenicity; chemical compounds; Computational toxicology; Computer Simulation; Food Packaging; Food toxicology; foods; In silico methods; Medical sciences; Models, Theoretical; mutagenicity; packaging materials; Packaging migrants; rapid methods; Read across; safety assessment; screening; Toxicity Tests; Toxicology; Weight of evidence; In silico methods; Packaging migrants; Computational toxicology; Read across; Weight of evidence; (Q)SAR; Toxicity; Migration; Method; Toxicology; Structure activity relation; Packaging; In silico; Food
• ISSN: 0278-6915; 1873-6351; 1873-6351
• DOI: 10.1016/j.fct.2014.05.022

•In silico modelling is used to draw toxicity estimates for a set of 136 chemical migrants from food packaging materials.•Estimates for mutagenicity/carcinogenicity of the chemical migrants are compared with the available data.•Structural analogues with experimental data on mutagenicity/carcinogenicity are used as a positive comparator.•A weight of evidence scheme from in silico methods is proposed for rapid screening of chemical migrants from food packaging. This study derived toxicity estimates for a set of 136 chemical migrants from food packaging materials using in silico (computational) modelling and read across approaches. Where available, the predicted results for mutagenicity and carcinogenicity were compared with published experimental data. As the packaging compounds are subject to safety assessment, the migrating substances were more likely to be negative for both the endpoints. A set of structural analogues with positive experimental data for carcinogenicity and/or mutagenicity was therefore used as a positive comparator. The results showed that a weight of evidence assembled from different in silico models and read-across from already-tested structurally similar compounds can provide a rapid and reliable means for rapid screening of new yet-untested intentional or unintentional chemical compounds that may migrate to packaged foodstuffs.