Assessment of developmental toxicity potential of chemicals by quantitative structure-toxicity relationship models

• Published in: Chemosphere (Oxford) 1995-07, Vol.31 (1), p.2499-2510
• Main Authors: Gomba, Vijay K., Enslein, Kurt, Blake, Benjamin W.
• Format: Article
• Language: English
• Subjects: Algorithms; Animals; Benzene Derivatives - chemistry; Benzene Derivatives - toxicity; Biological Assay; Computer Simulation; Embryonic and Fetal Development - drug effects; Female; Hazardous Waste - adverse effects; Heterocyclic Compounds - chemistry; Heterocyclic Compounds - toxicity; Humans; Hydrocarbons - chemistry; Hydrocarbons - toxicity; Models, Chemical; Pregnancy; Prenatal Exposure Delayed Effects; Reference Values; Structure-Activity Relationship
• ISSN: 0045-6535; 1879-1298
• DOI: 10.1016/0045-6535(95)00119-S

Statistically significant quantitative structure-toxicity relationship (QSTR) models have been developed for assessing developmental toxicity potential (DTP) of chemicals. Three submodels, one each for aliphatic, heteroaromatic and carboaromatic compounds, have been cross-validated to ascertain their robustness. The specificities of the models range from 86% to 97%, and their sensitivities between 86% and 89%. For convenient computer-assisted application, the models are installed in a toxicity assessment software package, TOPKAT, which has been recently enhanced with algorithms to identify whether or not a query structure is inside the optimum prediction space (OPS) of a QSTR model. Different functionalities of the TOPKAT program have been explained by assessing the DTP of a number of compounds not used in the model training sets. The DTP of 18 existing drugs was assessed using these models; the DT assay results were available for 5 of these. Three of these 5 molecules were identified to be inside the OPS and their TOPKAT assessment matched their experimental assignment.