Hazard extrapolation test models

In the past, risk assessment consisted largely of computer-based models written to start from hazard assessment assays, such as chronic toxicity assays on rodents, encompass the necessary extrapolations between species and between high and low doses, and then produce a numerical assessment of the risk to human health. Although the hazard assessment tests and the toxic end points are different, an analogous situation exists in environmental risk assessment. A matter of considerable importance, now getting some belated attention, is the integration of human health and environmental risk assessments. 

Adequate extrapolation of results from standard laboratory toxicity tests to other time scales of exposure and response requires observations on the time course of toxic effects. These observations can then be used to construct time-to-event models, such as the DEBtox model mentioned above. These models explicitly address both intensity and duration of exposure to hazardous chemicals, and better use is made of the data gathered from toxicity experiments. Diverse endpoints in time can be addressed, and individual organism characteristics and/or environmental circumstances (e.g., temperature) can be incorporated as covariables. An overview of time-to-event models and approaches and their use in the risk assessment of chemicals is provided by Crane et al. (2002). 

The Community-Level Aquatic Systems Studies Interpretation Studies (CLASSIC) guidance document, which deals with the interpretation of results of microcosm and mesocosm tests in the risk assessment procedure of pesticides, recommends that regulatory model ecosystem experiments be conducted in spring to midsummer (Giddings et al. 2002). On the basis of the limited number of model ecosystem experiments described above, it seems that threshold concentrations for effects observed in early-season studies are reasonably predictive for threshold concentrations later in the season. Above these threshold concentrations, however, the intensity and duration of the responses (direct and indirect effects) may vary during different periods of the year. Consequently, the extrapolation of NOECcommunity values from one season to another seems to be possible with lower uncertainty than hazard estimates of higher concentrations in which both direct and indirect effects are involved. 

The TEC may be a test end-point, a test end-point corrected by a factor or other extrapolation model or a regulatory criterion or other benchmark value. A hazard quotient (HQ) greater than unity is treated as evidence that the chemical is worthy of concern. Suter (1996) also suggests that, if numerous chemicals occur at potentially toxic concentrations, an index of total toxicity could be calculated by the sum of toxic units (XTUs). This permits a comparison of COPECs and examines their distribution across areas within a site. The TUs are quotients of the concentration of a chemical in a medium divided by the standard test end-point concentration for that chemical. 

Even the most sophisticated risk assessment has limitations. It involves numerous assumptions about both exposure and hazard. Exposure assessments typically reflect modeled concentrations or extrapolations from measured data. The degree of exposure by different individuals may vary, and their response can depend on factors such as general health, genetic predisposition, or other factors. Dose-response factors are typically extrapolated from animal studies and thus inherently introduce the imcertainty of relating the response of laboratory animals to that of humans or one of the many species in an ecosystem. The endpoints characterized may not include all of the potential effects for example, the potential for endocrine disruption has not been considered in many risk assessments and in fact standardized testing methods were not published until approximately 2007 or later [90]. And risk assessment tools only model relatively simple scenarios. They rarely account for exposure to multiple chemicals, or fully accoimt for the effects on a complex web of organisms in an ecosystem. 

For about 20 commonly used substances, there is some information on dose-response relationships that can be applied to a probit function to quantify the number of fataUties that are likely to occur with a given exposure. Where sufficient information exists, use of the probit function can refine the hazard assessment however, despite the appearance of greater precision, it is important to remember that probit relationships for specific substances are typically extrapolated experimental animal data and, therefore, uncertainty surrounds these risk estimates when they are apphed to human populations. Many probit models are the result of the combination of a wide range of animal tests involving different animal species producing widely varying responses. There has been litde efibrt to... 

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