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A toxicological basis to derive generic interspecies uncertainty factors for application in human and ecological risk assessment
Authors:Edward J Calabrese  Linda A Baldwin
Institution:School of Public Health , University of Massachusetts , Amherst, MA, 01003 Phone: 413–545–3164 Fax: 413–545–3164
Abstract:A new method is proposed to derive the size of the interspecies uncertainty factor (UF) that is toxicologically and statistically based. The method is based on the biological/evolutionary assumption that similarity in susceptibility to toxic substances is a function of phylogenetic relatedness. This assumption is assessed via a large and highly structured aquatic database with over 500 agents tested in specific binary toxicity comparison (i.e., when two species have been tested with the same chemical under identical conditions) for dozens of species of wide phylogenetic relatedness. The methodology takes into account the generic need to estimate a response in any species (not just human) and the need to predict responses for new chemical agents. The method involves quantifying interspecies variation in susceptibility to numerous toxic substances via the use of binary interspecies comparisons that are converted to a 95% UF. This interspecies UF represents an estimate of the upper 95% of the population of 95% prediction intervals (PI) for binary interspecies comparisons within four categories of phylogenetic relatedness (species‐within‐genus, genera‐within‐family, families‐within‐order, orders‐within‐class). The 95% interspecies UFs range from a low of 10 for species‐within‐genus up to 65 for orders‐within‐class. Most mammalian toxicology studies involving mice, rats, cats, dogs, gerbils, and rabbits are orders‐within‐class categories for human risk assessment and would be provided a 65‐fold UF. Larger or smaller interspecies UF values could be selected based on the level of protection desired. The procedures described have application to both human and ecological risk assessment.
Keywords:uncertainty factors  phylogenetic relatedness  risk assessment
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