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Development of Knowledge Within a Chemical-Toxicological Database to Formulate Novel Computational Approaches for Predicting Repeated Dose Toxicity of Cosmetics-Related Compounds

Mostrag-Szlichtyng, AS (2017) Development of Knowledge Within a Chemical-Toxicological Database to Formulate Novel Computational Approaches for Predicting Repeated Dose Toxicity of Cosmetics-Related Compounds. Doctoral thesis, Liverpool John Moores University.

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Abstract

The European Union (EU) Cosmetics Regulation established the ban on animal testing for cosmetics ingredients. This ban does not assume that all cosmetics ingredients are safe, but that the non-testing procedures (in vitro and in silico) have to be applied for their safety assessment. To this end, the SEURAT-1 cluster was funded by EU 7th Framework Programme and Cosmetics Europe. The COSMOS (Integrated In Silico Models for the Prediction of Human Repeated Dose Toxicity of COSMetics to Optimise Safety) project was initiated as one of the seven consortia of the cluster, with the purpose of facilitating the prediction of human repeated dose toxicity associated with exposure to cosmetics-related compounds through in silico approaches. A critical objective of COSMOS was to address the paucity of publicly available data for cosmetics ingredients and related chemicals. Therefore a database was established containing (i) an inventory of cosmetics ingredients and related structures; (ii) skin permeability/absorption data (route of exposure relevant to cosmetics); and (iii) repeated dose toxicity data. This thesis describes the process of “knowledge discovery from the data”, including collation of the content of the COSMOS database and its subsequent application for developing tools to support the prediction of repeated dose toxicity of cosmetics and related compounds. A rigorous strategy of curation and quality control of chemical records was applied in developing the database (as documented in the Standard Operating Procedure, chapter 2). The chemical space of the cosmetics-related compounds was compared to food-related compounds from the U.S. FDA CFSAN PAFA database using the novel approach combining the analysis of structural features (ToxPrint chemotypes) and physicochemical properties. The cosmetics- and food- specific structural classes related to particular use functions and manifested by distinct physicochemical properties were identified (chapter 3). The novel COSMOS Skin Permeability Database containing in vivo and in vitro skin permeability/absorption data was developed by integrating existing databases and enriching them with new data for cosmetics harvested from regulatory documents and scientific literature (chapter 4). Compounds with available data on human in vitro maximal flux (JMAX) were subsequently extracted from the developed database and analysed in terms of their structural features (ToxPrint chemotypes) and physicochemical properties. The profile of compounds exhibiting low or high skin permeability potential was determined. The results of this analysis can support rapid screening and classification of the compounds without experimental data (chapter 5). The new COSMOS oral repeated dose toxicity database was established through consolidation of existing data sources and harvesting new regulatory documents and scientific literature. The unique data structure of the COSMOS oRepeatToxDB allows capturing all toxicological effects observed at particular dose levels and sites, which are hierarchically differentiated as organs, tissues, and cells (chapter 6). Such design of this database enabled the development of liver toxicity ontology, followed by mechanistic mining of in vivo data (chapter 7). As a result, compounds associated with liver steatosis, steatohepatitis and fibrosis phenotypic effects were identified and further analysed. The probable mechanistic reasoning for toxicity (Peroxisome Proliferator-Activated Receptor gamma (PPAR ) activation) was formulated for two hepatotoxicants, namely 1,3-bis-(2,4-diaminophenoxy)-propane and piperonyl butoxide. Key outcomes of this thesis include an extensive curated database, Standard Operating Procedures, skin permeability potential classification rules, and the set of structural features associated with liver steatosis. Such knowledge is particularly important in the light of the 21st Century Toxicology (NRC, 2007) and the ongoing need to move away from animal toxicity testing to non-testing alternatives.

Item Type: Thesis (Doctoral)
Uncontrolled Keywords: COSMOS Database; Liver steatosis; Skin permeability; ToxPrint Chemotypes; In silico; Mode of Action; Adverse Outcome Pathway
Subjects: Q Science > QD Chemistry
Divisions: Pharmacy & Biomolecular Sciences
Date Deposited: 10 Jul 2017 08:49
Last Modified: 11 Jul 2017 08:29
Supervisors: Cronin, MTD and Madden, J and Yang, C
URI: http://researchonline.ljmu.ac.uk/id/eprint/6798

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