Record Display for the EPA National Library Catalog


OLS Field Name OLS Field Data
Main Title Toward a Quantitative Comparative Toxicology of Organic Compounds.
Author Hansch, C. ; Kim, D. ; Leo, A. J. ; Novellino, E. ; Silipo, C. ;
CORP Author Pomona Coll., Claremont, CA. ;Naples Univ. (Italy).;Environmental Research Lab.-Duluth, MN.
Publisher 1989
Year Published 1989
Report Number EPA-R-809295 ;EPA-R-811927; EPA/600/J-89/159;
Stock Number PB90-128000
Additional Subjects Toxicology ; Organic compounds ; Chemical tests ; Correlation techniques ; Tables(Data) ; Comparison ; Chemical reactions ; Fishes ; Mammals ; Plants ; Microorganisms ; Formulas(Mathematics) ; Reprints ; Risk assessment ; Structure-activity relationships
Library Call Number Additional Info Location Last
NTIS  PB90-128000 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 03/10/1990
Collation 44p
There are more than 70,000 man-made chemicals in widespread usage in our world today, with additions coming along at a clip of more than 5,000 per year. Besides these, hundreds of thousands of new structures are synthesized each year in many academic and industrial laboratories. Toxicological problems which may be associated with the latter must be ignored, at least until some serious accident forces them onto us or until they move into the marketplace. It is impossible to test all of these chemicals in all of the tests which have been devised and are continuing to appear. To make matters more confusing, there is no generally accepted way to collect and organize the streams of data from all kinds of tests on all kinds of compounds that flow from many laboratories. With governments and industrial laboratories planning to spend billions in the coming decades, it is urgent that more systematic means for the organization and discussion of these results be developed. It is viewed that a long-term objective of toxicology must be to devise a computerized data base of numerically defined, statistically validated, structure-activity relationships.