title: Quantitative structure-activity relationships for predicting mutagenicity and carcinogenicity.
abstract: Quantitative structure-activity relationships (QSARs) for predicting mutagenicity and carcinogenicity were reviewed. The QSARs for predicting mutagenicity and carcinogenicity have been mostly limited to specific classes of chemicals (e.g., aromatic amines and heteroaromatic nitro chemicals). The motivation to develop QSARs for predicting mutagenicity and carcinogenicity to screen inventories of chemicals has produced four major commercially available computerized systems that are able to predict these endpoints: Deductive estimation of risk from existing knowledge (DEREK) toxicity prediction by komputer assisted technology (TOPKAT), computer automated structure evaluation (CASE), and multiple computer automated structure evaluation (Multicase). A brief overview of these and some other expert systems for predicting mutagenicity and carcinogenicity is provided. The other expert systems for predicting mutagenicity and carcinogenicity include automatic data analysis using pattern recognition techniques (ADAPT), QSAR Expert System (QSAR-ES), OncoLogic computer optimized molecular parametric analysis of chemical toxicity system (COMPACT), and common reactivity pattern (COREPA).
authors.affiliation: Safety and Environmental Assurance Centre, SEAC, Unilever Colworth, Colworth House, Sharnbrook, Bedford, Bedfordshire MK44 1LQ, United Kingdom. grace.patlewicz@unilever.com
authors.forename: Grace
authors.initials: G
authors.lastname: Patlewicz
authors.forename: Rosemary
authors.initials: R
authors.lastname: Rodford
authors.forename: John D
authors.initials: JD
authors.lastname: Walker
mesh_terms: D000818:Animals; D002273:Carcinogens / Q000633:toxicity*; D001330:Electronic Data Processing; D005544:Forecasting; D006801:Humans; D008962:Models, Theoretical; D009153:Mutagens / Q000633:toxicity*; D021281:Quantitative Structure-Activity Relationship
chemical_list: D002273:Carcinogens; D009153:Mutagens