Complex Mixtures Methods for In Vivo Toxicity Testing (1988) / Chapter Skim
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1. Introduction
1. Introduction
Pages 5-9
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From page 5... ...
It does not review testing of environmental toxicity. Toxicity testing to predict effects on humans has traditionally studied chemical compounds one at a time, for various reasons: dealing with agents singly has been more convenient to investigators; physicochemical properties of single agents were often readily defined; dosage could be easily controlled; biologic fate could usually be monitored in a straightforward manner; concentrations in air, water, and tissue could be accurately measured; target-organ toxicity was predictable on the basis of experience with agents related to the one in question; and relevant data were often available from human occupational exposures.
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From page 6... ...
Consideration of human experience with complex mixtures is important, because many toxic effects of chemical mixtures were not, and in some cases could not have been, predicted on the basis of experiments with animal models. For example, the extent to which cigarette-smoking and alcohol consumption affect the risk of oral cancer would not have been predicted on the basis of animal experiments, because experimental models for detecting oral cancer due to either cigarette-smoking or alcohol consumption are inadequate.
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From page 7... ...
The latteris the quantity of material that interacts with the biologic receptor responsible for a particular effect. Because determination of a biologically effective dose requires intimate knowledge of the mechanisms of action, in many instances imperfect knowledge leads to the use of surrogates for this quantity.
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From page 8... ...
A proposed classification scheme considers degree of complexity, sample origin, physical state, and chemical properties. Chemical characterization of a complex mixture might not be necessary before testing, but predicting effects of chronic exposure and extrapolating test results to other mixtures are often improved by such characterization.
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From page 9... ...
The assumptions underlying successfully predictive models can in themselves stimulate additional biologic research into the mechanisms of toxicity. The conclusions derived in the chapter are expanded in appendixes that describe their mathematical bases.
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