The unreliability of the reliability criteria in the estimation of QSAR for skin sensitivity: A pun or a reliable law?. (1st April 2021)

• Record Type: Journal Article
• Authors: Toropov, Andrey A.; Toropova, Alla P.
• Is Part Of: Toxicology letters. Volume 340(2021)
• Page Start: 133
• Page End: 140
• Publication Date: 2021-04-01
• Subjects: Skin sensitivity -- Safety assessment -- QSAR -- index of ideality of correlation -- Correlation intensity index -- Monte Carlo method; Toxicology -- Periodicals; 363.179
• DOI: 10.1016/j.toxlet.2021.01.015
• Languages: English
• ISSNs: 0378-4274

Abstract

Graphical abstract: Highlights: Quantitative structure - activity relationships (QSAR) is a random event. QSAR must be checked up in several distributions into training and validation sets. Models for skin sensitivity built up using the above principles are represented. New criteria of the predictive potential of QSAR-models are demonstrated. Abstract: Some new products, which include common personal-care products, drugs, household items, can be hazardous in aspect personal care products/cosmetics and their ingredients (i.e. the above can effect human skin). International organizations (e.g. the Organisation for Economic Co-operation and Development-OECD) recommend evaluating individual ingredients when assessing the safety of personal care or cosmetic products. Thus, checking up that "popular at the market" substances are non-toxic, do not penetrate into or through normal or compromised human skin, and therefore, pose no risk to human health is an essential element of modern toxicology. The development of reliable models of toxicological endpoints is a tool to carry out the above checking up via quantitative structure–activity relationships (QSARs). The reliability of the QSAR is the current task of mathematical statistics. Recently, the index of ideality of correlation ( IIC ) and correlation intensity index ( CII ) were suggested as criteria of predictive potential (i.e. reliability) of QSAR-models. Here, the abilities of these criteria were studied for the case of building up models for skin sensitivity (LLNA, local lymph node assay). Computational experiments have confirmed that the IIC demonstrates an obvious ability to improve the predictive potential of models of skin sensitization. The applying of the CII for the case of skin sensitization also improves the quality of the model. However, the best models for skin sensitization were observed if the above-mentioned criteria are applied jointly (n = 268; R 2 = 0.60; RMSE = 0.63).