| dc.description.abstract | Over 60,000 chemicals exist in United States commerce (U.S. EPA, 1982). This inventory
expands each year as 200 to l,000 new chemicals are advanced into commercial production
(Muir, 1980). Fortunately, most of these chemicals have not posed any known threats
to the environment. However, several chemicals have presented serious environmental
hazards, and an increased awareness of these hazards developed in the 1960 1 s and 1970 1
s. This resulted in passage by the U.S. Congress in 1976 of the Toxic Substances
Control Act (TSCA).
The governmental focus via TSCA has been on the prevention of potentially harmful
situations (Kissman and Wexler, 1983). Thus, the act attempts to control the
introduction, production, distribution or use in commerce of any chemical that presents an
unreasonable risk to human
health or the environment, which is not adequately regulated by other laws. This act
has empowered the U.S. Environmental Protection Agency (EPA) with authority over the
regulation, reporting and testing of these chemicals
(Muir, 198.0).
Because of the large and ever-increasing number of chemicals in the
TSCA inventory, resources simply are not available to test the vast majority of these
chemicals for their hazard potential in the environment. Therefore, approaches have been
adopted by EPA which are designed to
result in the selection for further study of chemicals with real hazard potential and
the elimination from further study of those which are judged to be relatively
innocuous. The area of predictive environmental toxicology
has been used in this process of chemical selection.
Principles of quantitative structure-activity relationships (QSAR)
are applied in predictive toxicology. For development of toxicity prediction models, a subset of
chemicals from a given class or from a group with a common mode of toxic action are tested for
their toxicities to the test organism. Structural or physicochemical features of the test
compounds are correlated with toxicity test endpoints to determine the strength of relationships.
QSAR models which exhibit high correlations between basic molecular properties and toxicity may be
used to predict toxicity with a certain degree of accuracy.
Very few aquatic toxicology data bases exist which can be applied to. QSAR model development.
Ideally, such data bases should consist of tests conducted with the same species in the same water
under identical test conditions. Concentrations of toxicants in the exposure chambers should be
measured. In cooperation with EPA, the University of Wisconsin
Superior has been developing a data base for application in predictive toxicology model
development. This volume provides the methods and results from 198 acute toxicity tests conducted
with the fathead minnow (Pimephales promelas) in Lake Superior water. | en_US |
