Chemical categories for health hazard identification: a feasibility study.

The use of chemical categories has been suggested in order to lower the number of chemicals tested in the High Production Volume (HPV) Chemical Challenge Program. In this investigation we examined the reliability of using organic chemical categories to classify chemicals as either toxic or nontoxic for individual toxicological effects as well as for panels of such endpoints. The analyses indicate that chemical categories are unable to consistently identify groups of chemicals with similar toxic responses either for a multiplicity of endpoints or for single effects. Our analyses suggest that if chemical categories are to be used to identify health hazards, that computer-based SAR approaches appear to be superior to arbitrary chemical categories for predicting specific toxicological effects but they are not, at this time, useful for defining the overall toxicity.

[1]  R. Tennant,et al.  Definitive relationships among chemical structure, carcinogenicity and mutagenicity for 301 chemicals tested by the U.S. NTP. , 1991, Mutation research.

[2]  H. Rosenkranz,et al.  Structural basis of the in vivo induction of micronuclei. , 1992, Mutation research.

[3]  Herbert S. Rosenkranz,et al.  Perspective on the Use of Structure-Activity Expert Systems in Toxicology , 1995 .

[4]  H. Rosenkranz,et al.  The structural basis of the mutagenicity of chemicals in Salmonella typhimurium: the National Toxicology Program Data Base. , 1990, Mutation research.

[5]  H. Rosenkranz,et al.  Structural determinants of developmental toxicity in hamsters. , 1999, Teratology.

[6]  H S Rosenkranz,et al.  Development, characterization and application of predictive-toxicology models. , 1999, SAR and QSAR in environmental research.

[7]  H. Rosenkranz,et al.  The High Production Volume Chemical Challenge Program: The Rodent LD50 and its Possible Replacement , 2000, Alternatives to laboratory animals : ATLA.

[8]  H S Rosenkranz,et al.  Value-of-information analysis of testing strategies: estimating the effect of uncertainty about the proportion of chemicals that are true human carcinogens. , 1990, Progress in clinical and biological research.

[9]  G Klopman,et al.  Structure-activity relations: maximizing the usefulness of mutagenicity and carcinogenicity databases. , 1991, Environmental health perspectives.

[10]  H S Rosenkranz,et al.  International Commission for Protection Against Environmental Mutagens and Carcinogens. Approaches to SAR in carcinogenesis and mutagenesis. Prediction of carcinogenicity/mutagenicity using MULTI-CASE. , 1994, Mutation research.

[11]  H S Rosenkranz,et al.  Toxicity estimation by chemical substructure analysis: the TOX II program. , 1995, Toxicology letters.

[12]  H. Rosenkranz,et al.  The structural basis of the mutagenicity of chemicals in Salmonella typhimurium: the Gene-Tox data base. , 1990, Mutation research.

[13]  H S Rosenkranz,et al.  Identification of 'genotoxic' and 'non-genotoxic' alerts for cancer in mice: the carcinogenic potency database. , 1998, Mutation research.

[14]  Herbert S. Rosenkranz,et al.  Information value of the rodent bioassay , 1988, Nature.

[15]  Gilles Klopman,et al.  Multiple Computer Automated Structure Evaluation Methodology as an Alternative to In Vivo Eye Irritation Testing , 1993 .

[16]  H. Rosenkranz,et al.  Prediction of the carcinogenicity in rodents of chemicals currently being tested by the US National Toxicology Program: structure-activity correlations. , 1990, Mutagenesis.

[17]  H S Rosenkranz,et al.  Modeling the mouse lymphoma forward mutational assay: the Gene-Tox program database. , 2000, Mutation research.

[18]  H. Rosenkranz,et al.  Estimation of the optimal data base size for structure-activity analyses: the Salmonella mutagenicity data base. , 1996, Mutation research.

[19]  L. Libowitz.  Letter from CAAT , 1999 .