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Cronin, MTD and Richarz, A (2017) Relationship Between Adverse Outcome Pathways and Chemistry-Based in Silico Models to Predict Toxicity. Applied In Vitro Toxicology, 3 (4). pp. 286-297. ISSN 2332-1512
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Abstract
The current landscape of Adverse Outcome Pathways (AOPs) provides a means of organising information relating to the adverse effects elicited following exposure to chemicals. As such, AOPs are an excellent driver for the development and application of in silico models for predictive toxicology allowing for the direct relationship between chemistry and adverse effects to be established. Information may be extracted from AOPs to support the creation of (quantitative) structure-activity relationships ((Q)SARs) as well as to increase confidence in grouping and read-across. Any part of an AOP can be linked to these various types of in silico models. There is, however, an emphasis on using information from known Molecular Initiating Events (MIEs) to create models including 2D and 3D structural alerts, SARs and QSARs. MIEs can be classified according to the nature of the interaction e.g. covalent reactivity, oxidative stress, phototoxicity, chronic receptor mediated, acute enzyme inhibition, unspecific, physical and other effects. Different types of MIEs require different approaches to their in silico modelling. Modelling Key Events and Key Event Relationships is useful if they represent the rate limiting step or key determinant of toxicity. Modelling of metabolism and chemical interactions will become part of AOP networks, which are also driving species-specific extrapolation and respective adaptation of models. With more information and data being captured, in silico approaches will increasingly support the application of knowledge from AOPs to build weight of evidence and support risk assessment, e.g. in the context of Integrated Assessment and Testing Approaches (IATAs).
| Item Type: | Article |
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| Additional Information: | Final publication is available from Mary Ann Liebert, Inc., publishers http://dx.doi.org/10.1089/aivt.2017.0021 |
| Subjects: | Q Science > QD Chemistry R Medicine > RM Therapeutics. Pharmacology |
| Divisions: | Pharmacy & Biomolecular Sciences |
| Publisher: | Mary Ann Liebert |
| Date Deposited: | 08 Sep 2017 09:48 |
| Last Modified: | 04 Sep 2021 11:14 |
| DOI or ID number: | 10.1089/aivt.2017.0021 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/7060 |
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