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Evaluating Confidence in Toxicity Assessments Based on Experimental Data and In Silico Predictions

Johnson, C, Anger, LT, Benigni, R, Bower, D, Bringezu, F, Crofton, K, Cronin, MTD, Cross, KP, Dettwiler, M, Frericks, M, Melnikov, F, Miller, S, Roberts, DW, Suarez-Rodrigez, D, Roncaglioni, A, Lo Piparo, E, Tice, RR, Zwickl, C and Myatt, GJ (2021) Evaluating Confidence in Toxicity Assessments Based on Experimental Data and In Silico Predictions. Computational Toxicology, 21. ISSN 2468-1113

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Abstract

Understanding the reliability and relevance of a toxicological assessment is important for gauging the overall confidence and communicating the degree of uncertainty related to it. The process involved in assessing reliability and relevance is well defined for experimental data. Similar criteria need to be established for in silico predictions, asthey become increasingly more important to fill data gaps and need to be reasonably integrated as additional lines of evidence. Thus, in silico assessments could be communicated with greater confidence and in a more harmonized manner. The current work expands on previous definitions of reliability, relevance, and confidence and establishes a conceptional framework to apply those to in silico data. The approach is used in two case studies: 1) phthalic anhydride, where experimental data are readily available and 2) 4-hydroxy,3-propoxybenzaldehyde, a data poor case which relies predominantly on in silico methods, showing that reliability, relevance, and confidence of in silico assessments can be effectively communicated within integrated approaches to testing and assessment (IATA).

Item Type: Article
Subjects: R Medicine > RM Therapeutics. Pharmacology
Divisions: Pharmacy & Biomolecular Sciences
Publisher: Elsevier
Date Deposited: 04 Nov 2021 10:39
Last Modified: 03 Dec 2021 11:00
DOI or Identification number: 10.1016/j.comtox.2021.100204
URI: https://researchonline.ljmu.ac.uk/id/eprint/15736

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