Computational Methods in Support of Chemical Risk Assessment
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Computational Methods in Support of Chemical Risk Assessment Mojca Fuart Gatnik A thesis submitted in partial fulfilment of the requirements of Liverpool John Moores University for the degree of Doctor of Philosophy This research programme was carried out in collaboration with the Joint Research Centre of the European Commission June 2016 i Acknowledgements Immense gratitude goes to my Director of Studies and academic supervisor, Mark Cronin. I thank Mark for accepting me at the Liverpool John Moores University and being a truly dedicated mentor, providing me with academic support and encouragement. I am particularly indebted to him for giving me the unique opportunity to present my work at EUROTOX 2015. The same profound gratitude goes to my direct supervisor, Andrew Worth, who gave me the wonderful opportunity to obtain the Grant for a PhD in the field of Computational Toxicology at the Joint Research Centre in Ispra (Italy). And not only for that but also for his dedicated assistance and brain-storming discussions all the way through the period at the JRC and afterwards. I have very fond memories of my time there. A very special thank you goes to my academic supervisor, Judith Madden, for her constant support and for so generously dedicating her time during my stay in Liverpool. I am wholeheartedly grateful to Judy, Mark and Andrew, who believed in me and my work and encouraged me throughout a difficult period, as without their support and understanding the way to this moment would not have been possible. I would also like to extend my gratitude to everyone from the QSAR Laboratory at LJMU for their kindness and generosity, which always made my visits to Liverpool a fulfilling experience. I am hugely appreciative of my work colleague, Rositsa Serafimova, especially for sharing her knowledge of chemistry and for being available for discussion at any time. It was a great pleasure and an inspiring experience to exchange thoughts and ideas with people from different backgrounds. A special mention goes to Chihae Yang for the critical discussion on possibilities regarding the extrapolation of toxicological data for biocides and to Leon van der Wal for his critical opinion on the application of TTC. I would like to thank Susan Owen Molinario for becoming my friend when I moved to Italy and for encouraging me during my advanced English classes. Finally, but by no means least, I would like to thank my husband Flavio and son Lovro for being unbelievably patient and supportive and also to my parents for their unselfish share of childcare in crucial moments. ii Abstract Chemical risk assessment for human health effects is performed in order to establish safe exposure levels of chemicals to which individuals are exposed. The process of risk assessment traditionally involves the generation of toxicological studies from which health based guidance values are derived for a specific chemical. For low level exposures to chemicals, where there are no or limited chemical specific toxicity data, the application of the Threshold of Toxicological Concern (TTC) approach may estimate whether the exposure levels can be considered safe. The TTC approach has recently gained increasing interest as new requirements, under different regulatory frameworks, emerge for the safety assessment of chemicals and to assess chemicals for which testing is not routinely required. The application of TTC relies heavily on computational (in silico) methods. In silico tools are computer implemented models that, based on commonalities in the toxicity of “similar” chemical structures, may predict hazard. In silico methods are rapidly evolving and gaining importance within the context of Integrated Approaches to Testing and Assessment (IATA) and their acceptance for regulatory purposes is expanding. The work presented in this thesis has focused on the use and applicability of a wide range of computational approaches to assist in the application of the TTC concept. In the TTC approach, the identification of genotoxic chemicals is a primary requirement. In silico approaches apply expert knowledge and/or statistical methods to either predict genotoxicity or to identify structural alerts associated with it. This thesis focused, in part, on a group of important environmental pollutants, nitrobenzenes, to assess the applicability of in silico tools to predict genotoxicity. For this purpose a dataset containing 252 nitrobenzenes including Ames test results was compiled. Based on these test results a case study for sodium nitro-guaiacolate, a pesticide active substance, was developed. The case study demonstrated that (Q)SAR and a category approach incorporating read-across, are applicable for the prediction of genotoxicity and supports their use within a weight of evidence approach. Another aspect of the TTC approach is the evaluation of repeat dose, non-cancer endpoints. For that purpose chemicals are separated into groups related to three levels of concern based on the Cramer classification. For each level, namely the Cramer Classes (I, II and III), a safe exposure level has been established. Therefore, as interest to apply TTC expands to new groups of chemicals, the reliability and conservativeness of the established thresholds relative to Cramer Classes for the new chemistries must be established. In this thesis the TTC approach was evaluated for 385 cosmetic ingredients, 77 biocides and 102 compounds classified as reproductive and developmental toxicants. To support the evaluation at different levels, chemical datasets containing toxicological data were utilised and computational tools were applied to compare datasets. The results indicated, that the historical “Munro” dataset is broadly representative for cosmetics and biocides. In addition, that the threshold levels for Cramer Class III are within the range of Munro’s threshold further supports the validity of the TTC approach and its conservativeness for the groups of chemicals analysed. Cramer Class I thresholds were found to be valid only for classified developmental and reproductive toxicants. The results also supported the validity of the classification of chemicals into Cramer class III. It is foreseen that the TTC approach will gain increasing acceptance in the risk assessment of different groups of chemicals. Therefore it is emphasised that the future work should focus on the identification of the limitations of the application of TTC, including the identification of groups of chemicals to which TTC cannot be applied, the expansion of the underlying toxicological datasets, and the development of tools to support the application of TTC so that is transparent and acceptable for regulatory purposes. iii Abbreviations AChE Acetylcholinesterase AO Adverse Outcome AOP Adverse Outcome Pathway BIT Benzisothiazolinone BKC Benzalkonium chloride BMD Benchmark dose BMDL10 Lower confidence limit on a benchmark dose giving 10% increase in tumours BPR Biocidal Products Regulation CAS Chemical Abstracts Service CCRIS Chemical Carcinogenesis Research Information System CDF cumulative distribution function CLP Classification, labelling and packaging of substances and mixtures CMR Carcinogenicity, Mutagenicity and Reproductive substance COC Cohort of Concern COSMOS Integrated In Silico Models for the Prediction of Human Repeated Dose Toxicity of COSMetics to Optimise Safety CPDB Carcinogenicity Potency Database CPNP Cosmetic Products Notification Portal DAR Draft Assessment Report DB Database DDAC Dialkyldimethylammonium chloride DfW Derek for Windows DG SANTE Directorate General for Health and Food Safety DNA Deoxyribonucleic acid DPD Dangerous Preparations Directive DSD Dangerous Substance Directive DSSTox Distributed Structure-Searchable Toxicity DST Dermal Sensitisation Threshold EAFUS "Everything" Added to Food in the United States EBW Exposure Based Waiving EC3 Effective Concentration -threefold ECHA European Chemicals Agency ED Endocrine disruption EDC Endocrine Disrupting Chemicals EFSA European Food Safety Authority EMA European Medicines Agency EPA United States Environmental Protection Agency EPAA European Partnership for Alternative Approaches to Animal Testing EU European Union FAO Food and Agriculture Organization FDA US Food and Drug Administration GRAS Generally Recognized As Safe HBGV Health Based Guidance Values HESI Health and Environmental Sciences Institute IATA Integrated Approach to Testing and Assessment ICCR International Cooperation on Cosmetics Regulation IHCP Institute for Health and Consumer Protection ILSI International Life Sciences Institute IPS Integrated Prediction System iv ISS Istituto Superiore di Sanità ITEM Institute for Toxicology and Experimental Medicine ITS Integrating testing strategy IUPAC International Union of Pure and Applied Chemistry JECFA Joint FAO/WHO Expert Committee on Food Additives JMPR Joint Meeting on Pesticide Residues JRC Joint Research Centre LEL Lowest Effect Level LOAEL Lowest Observed Adverse Effect level LOEL Lowest Observed Effect level MoA Mode of Action MOE Margin of Exposure NCCT United States National Centre for Computational Toxicology NIEHS National Institute of Environmental Health Sciences NL The Netherlands NO(A)EL No Observed (Adverse) Effect Level NTP National Toxicology Program OECD Organisation for Economic Co-operation and Development OPP US EPA Office of Pesticide Programs PAFA Priority-based Assessment of Food Additives POD Point of Departure PPP Plant Protection Products PSA Molecular polar surface area (Q)SAR QSARs and SARs are collectively referred