title: SAR modeling of genotoxic phenomena: the consequence on predictive performance of deviation from a unity ratio of genotoxicants/non-genotoxicants.
abstract: SAR approaches to the study of genotoxic phenomena are finding increased applications. However, the data being modeled are frequently not considered optimal due to the small size of the dataset and an uneven distribution of genotoxicants and non-genotoxicants in the dataset. The effects of such imbalances on the performance of one SAR approach were investigated with respect to the modeling of the induction of unscheduled DNA synthesis in rat hepotocytes and of sister chromatid exchanges and chromosomal aberrations in cultural CHO cells. The analyses indicate that if genotoxicants exceed non-genotoxicants, the performance of the SAR model can be improved if the dataset is supplemented with physiological chemicals which are assumed to be non-genotoxicants. On the other hand, if non-genotoxicants exceed genotoxicants, it was found that the predictive performance of the resulting SAR model is not improved by removal of genotoxicants from the dataset to achieve a ratio of genotoxicants/genotoxicants of unity. Overall, the present analyses did not result in the development of SAR models of greatly increased predictivity. Conceivably, for the particular datasets and SAR paradigm the limit of predictivity has been reached. The possibility of investigating the use of a "battery" of SAR paradigms should be considered.
authors.affiliation: Department of Biomedical Sciences, Florida Atlantic University, 777 Glades Rd., P.O. Box 3091, Boca Raton, FL 33431, USA. rosenkra@fau.edu
authors.forename: Herbert S
authors.initials: HS
authors.lastname: Rosenkranz
mesh_terms: D008954:Models, Biological; D009152:Mutagenicity Tests / Q000379:methods*; D009153:Mutagens / Q000737:chemistry*; D012107:Research Design; D013329:Structure-Activity Relationship; D014116:Toxicology / Q000379:methods*
chemical_list: D009153:Mutagens