Cosmetic products are used daily on a global scale. Therefore, it is necessary to ensure that these products, and their ingredients, do not cause any adverse human health effects under normal usage; to ensure this, risk assessment must be performed. Traditionally, risk assessments are performed in vivo, i.e. conducting tests on animals using the chemical(s) of interest. However, over the past decade there has been an increase in research into the use of alternative toxicity testing methods, such as in vitro, in chemico and in silico. Whilst there are a number of alternative techniques that may be employed, no one method can be used in isolation as a full replacement for an in vivo test. Therefore, the Adverse Outcome Pathway (AOP) concept is an emerging method by which information provided by the in vitro, in chemico, and in silico approaches can be utilised in an integrated testing strategy. The AOP concept links an upstream molecular initiating event to a downstream adverse outcome, via a number of testable key events. In silico approaches utilise computers in order to develop predictive models. Within the AOP paradigm in silico method work to identify the key features of a chemical (structural alerts) that induce a molecular initiating event (MIE). A collection of structural alerts that induce the same MIE are considered to be an in silico profiler. Typically, these in silico profilers are supported by associated toxicity, or mechanistic, information pertaining to the ability to induce a specific MIE. The overall aim of the work presented in this thesis was the development of an in silico profiler, based upon the hypothesis that the induction of mitochondrial toxicity is a key driver of organ-level toxicity. The research presented herein demonstrates the ability to identify, and develop, two types of structural alert; mechanism- and chemistry-based; that pertain to mitochondrial toxicity. Due to the differences inherent in these two types of alert they should be utilised for different purposes. As such, the main usage of the mechanism-based alerts should be in the formation of chemical categories and subsequent data gap filling via read-across. In comparison, the chemistry-based alerts should be utilised for the purposes of prioritising chemicals, within an inventory, that should undergo additional testing in in vitro and/or in chemico assays. It is envisaged that these two types of structural alerts could be used to profile chemical inventories as part of a tiered testing strategy. Therefore, the future work discussed in detail the need to expand the chemical space covered by the alerts. Additional future work involves utilising experimental information from in vitro/in chemico assays to verify the mechanism-based alerts and to refine the chemistry-based alerts by discerning mechanistic information associated with them. Furthermore, it is envisaged that these alerts could be incorporated into predictive tools, such as the OECD QSAR Toolbox, to enable their use for screening and prioritisation purposes.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:647149 |
| Date | January 2015 |
| Creators | Nelms, Mark David |
| Contributors | Enoch, Steven James; Madden, Judith Claire; Cronin, Mark Timothy David |
| Publisher | Liverpool John Moores University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://researchonline.ljmu.ac.uk/4424/ |
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