(Q)SAR tools for priority setting: A case study with printed paper and board food contact material substances

Melissa Van Bossuyt, Els Van Hoeck, Giuseppa Raitano, Serena Manganelli, Els Braeken, Gamze Ates, Tamara Vanhaecke, Sabine Van Miert, Emilio Benfenati, Birgit Mertens, Vera Rogiers

Research output: Contribution to journalArticlepeer-review


Over the last years, more stringent safety requirements for an increasing number of chemicals across many regulatory fields (e.g. industrial chemicals, pharmaceuticals, food, cosmetics, …) have triggered the need for an efficient screening strategy to prioritize the substances of highest concern. In this context, alternative methods such as in silico (i.e. computational) techniques gain more and more importance. In the current study, a new prioritization strategy for identifying potentially mutagenic substances was developed based on the combination of multiple (quantitative) structure-activity relationship ((Q)SAR) tools. Non-evaluated substances used in printed paper and board food contact materials (FCM) were selected for a case study. By applying our strategy, 106 out of the 1723 substances were assigned 'high priority' as they were predicted mutagenic by 4 different (Q)SAR models. Information provided within the models allowed to identify 53 substances for which Ames mutagenicity prediction already has in vitro Ames test results. For further prioritization, additional support could be obtained by applying local i.e. specific models, as demonstrated here for aromatic azo compounds, typically found in printed paper and board FCM. The strategy developed here can easily be applied to other groups of chemicals facing the same need for priority ranking.

Original languageEnglish
Pages (from-to)109-119
Number of pages11
JournalFood and Chemical Toxicology
Publication statusPublished - Apr 2017


  • Computer Simulation
  • Food Packaging
  • Mutagenicity Tests
  • Organic Chemicals
  • Paper
  • Quantitative Structure-Activity Relationship
  • Software
  • Journal Article


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