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Cronin, MTD, Richarz, A-N and Schultz, T (2019) Identification and Description of the Uncertainty, Variability, Bias and Influence in Quantitative Structure-Activity Relationships (QSARs) for Toxicity Prediction. Regulatory Toxicology and Pharmacology, 106. pp. 90-104. ISSN 0273-2300
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Identification and Description of the Uncertainty, Variability, Bias and Influence in Quantitative Structure-Activity Relationships (QSARs) for Toxicity Prediction.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) | Preview |
Abstract
Improving regulatory confidence in, and acceptance of, a prediction of toxicity from a quantitative structure-activity relationship (QSAR) requires assessment of its uncertainty and determination of whether the uncertainty is acceptable. Thus, it is crucial to identify potential uncertainties fundamental to QSAR predictions. Based on expert review, sources of uncertainties, variabilities and biases, as well as areas of influence in QSARs for toxicity prediction were established. These were grouped into three thematic areas: uncertainties, variabilities, potential biases and influences associated with 1) the creation of the QSAR, 2) the description of the QSAR, and 3) the application of the QSAR, also showing barriers for their use. Each thematic area was divided into a total of 13 main areas of concern with 49 assessment criteria covering all aspects of QSAR development, documentation and use. Two case studies were undertaken on different types of QSARs that demonstrated the applicability of the assessment criteria to identify potential weaknesses in the use of a QSAR for a specific purpose such that they may be addressed and mitigation strategies can be proposed, as well as enabling an informed decision on the adequacy of the model in the considered context.
| Item Type: | Article |
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| Uncontrolled Keywords: | 1115 Pharmacology and Pharmaceutical Sciences |
| Subjects: | R Medicine > RM Therapeutics. Pharmacology |
| Divisions: | Pharmacy & Biomolecular Sciences |
| Publisher: | Elsevier |
| Date Deposited: | 15 Apr 2019 09:30 |
| Last Modified: | 04 Sep 2021 09:30 |
| DOI or ID number: | 10.1016/j.yrtph.2019.04.007 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/10553 |
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