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Schultz, TW, Richarz, A-N and Cronin, MTD (2018) Assessing Uncertainty in Read-Across: Questions to Evaluate Toxicity Predictions Based on Knowledge Gained from Case Studies. Computational Toxicology. ISSN 2468-1113
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Assessing Uncertainty in Read-Across Questions to Evaluate Toxicity Predictions Based on Knowledge Gained from Case Studies.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) | Preview |
Abstract
Read-across as an alternative assessment method for chemical toxicity has growing interest in both the regulatory and industrial communities. The pivotal means of acquiring acceptance of a read-across prediction is identifying and assessing uncertainties associated with it. This study has identified and summarised in a structured way the variety of uncertainties that potentially impact acceptance of a readacross argument. The main sources of uncertainty were established and divided into four main categories: i) the regulatory use of the prediction, ii) the data for the apical endpoint being assessed, iii) the readacross argumentation, and iv) the similarity justification. Specifically, the context of, and relevance to, the regulatory use of a read-across will dictate the acceptable level of uncertainties. The apical endpoint (or other) data must be of sufficient quality and relevance for data gap filling. Read-Across argumentation uncertainties include: 1) mechanistic plausibility (i.e., the knowledge of the chemical and biological mechanisms leading to toxicity), 2) completeness of the supporting evidence, 3) robustness of the supporting data, and 4) Weight-of-Evidence. In addition, similarity arguments for chemistry, physicochemical properties, toxicokinetics and toxicodynamics are linked to these read-across argumentation issues. To further progress in this area, a series of questions are proposed with the goal of addressing each type of uncertainty.
| Item Type: | Article |
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| Subjects: | R Medicine > RA Public aspects of medicine > RA1190 Toxicology. Poisions R Medicine > RM Therapeutics. Pharmacology |
| Divisions: | Pharmacy & Biomolecular Sciences |
| Publisher: | Elsevier |
| Date Deposited: | 01 Nov 2018 10:25 |
| Last Modified: | 04 Sep 2021 09:58 |
| DOI or ID number: | 10.1016/j.comtox.2018.10.003 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/9580 |
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