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Cronin, MTD, Enoch, SJ, Mellor, CL, Przybylak, KR, Richarz, AN and Madden, JC (2017) In Silico Prediction of Organ Level Toxicity: Linking Chemistry to Adverse Effects. Toxicological Research, 33 (3). pp. 173-182. ISSN 1976-8257
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Abstract
In silico methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs as well as grouping (category formation) allowing for read-across. A challenging area for in silico modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself. This study has focussed on the use of structural alerts to identify potential liver toxicants. In silico profilers, or groups of structural alerts, were developed based on mechanisms of action and informed by current knowledge of Adverse Outcome Pathways. These profilers are robust and can be coded computationally to allow for prediction. However, they do not cover all mechanisms or modes of liver toxicity and recommendations for the improvement of these approaches are given.
| Item Type: | Article |
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| Subjects: | Q Science > QD Chemistry R Medicine > RS Pharmacy and materia medica |
| Divisions: | Pharmacy & Biomolecular Sciences |
| Publisher: | The Korean Society of Toxicology |
| Date Deposited: | 06 Apr 2017 08:14 |
| Last Modified: | 04 Sep 2021 11:44 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/6208 |
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