The CORAL software has been applied to the development of classification models for pesticides relative to two pharmacokinetic properties in humans: (i) gastro-intestinal absorption; and (ii) blood-brain barrier permeation. These models were built up using categorical data on pesticide absorption and brain permeation split into training, invisible training, calibration and external validation sets using Monte Carlo simulations. The models were assessed using several random splits into the training and validation sets. Optimal SMILES-based descriptors sensitive to the presence of different chemical elements and types of covalent bonds have been used to build up models. The range of Matthews correlation coefficient for suggested models is 0.64-0.75. The perspectives of studied approach as a tool to build up models for pharmacokinetic properties of chemicals is discussed. The models are built up according to OECD principles.
Keywords: Binary classification; CORAL software; Monte Carlo method; OECD principle; Pesticide; SAR.
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