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Use of selected toxicology information resources in assessing relationships between chemical structure and biological activity.
Author(s) -
J.S. Wassom
Publication year - 1985
Publication title -
environmental health perspectives
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.257
H-Index - 282
eISSN - 1552-9924
pISSN - 0091-6765
DOI - 10.1289/ehp.8561287
Subject(s) - information center , toxicology , computer science , agency (philosophy) , data science , biology , psychology , philosophy , mathematics education , epistemology , educational research
This paper addresses the subject of the use of selected toxicology information resources in assessing relationships between chemical structure and specific biological end points. To assist the researcher in how to access the primary literature of genetic toxicology, teratogenesis, and carcinogenesis, three specific specialized information centers are discussed--Environmental Mutagen Information Center, Environmental Teratology Information Center, and Environmental Carcinogenesis Information Center. Also included are descriptions of information resources that contain evaluated (peer-reviewed) biological research results. The U.S. Environmental Protection Agency Genetic Toxicology Program, the International Agency for Research on Cancer Monographs, and the Toxicology Data Bank are the best sources currently available to obtain peer-reviewed results for compounds tested for genotoxicity, carcinogenicity, and other toxicological end points. The value of published information lies in its use. It has become evident that most information cannot be accepted at face value for interpretation and analysis when subjected to stringent quality evaluation criteria. This deficit can be corrected by rigid editorship and the cognizance of authors. Increased interest in alternative methods to in vivo animal testing will be exemplified by use of short-term bioassays and in structure-activity relationship studies. With respect to this latter area, it must be remembered that mechanically (computer generated) derived data cannot substitute, at least at this stage, for data obtained from actual animal testing. The future of structure-activity relationship studies will rest only in their use as a predictive tool.

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