Risk assessment animal data

In practice, animal bioassay data are generally the primary data used in risk assessments. Animal studies are well-controlled with known exposures, and they are carried out with detailed, careful clinical and pathological examinations. The use of laboratory animals to determine potential toxic effects in humans is a necessary and accepted procedure. It is a recognized fact that effects in laboratory animals are usually similar to those observed in humans at comparable dose levels. Exceptions are primarily attributable to differences in the pharmacokinetics and metabolism of the xenobiotics. 

In the absence of information to demonstrate that such a selection is incorrect, data from the animal species, strain, and sex showing the greatest sensitivity to a chemical s toxic properties will be selected as the basis for human risk assessment. Animal toxicity data collected by the same route of exposure as that experienced by humans are preferred for risk assessment, but if the toxic effect is a systemic one, then data from other routes can be used. 

Risk characterization is tlie process of estimating tlie incidence of a healtli effect under tlie various conditions of human or animal exposure as described in the exposure assessment. It evolves from both dose exposure assessment and toxicity response assessment. The data are then combined to obtain qualitative and quantitative expression of risk. 

A hallmark of PB-PK models is the ability to scale up animal-based models to humans, thus allowing tissue drug concentrations to be predicted in the absence of data that are difficult or impossible to collect. Initial efforts to apply interspecies extrapolations to anticancer drugs have been greatly extended to chemical risk assessment based on PB-PK models [14]. Empirical allometric equations based on animal body weight have been the mainstay to scale organ weights and... 

Estimates of exposure levels posing minimal risk to humans (MRLs) have been made, where data were believed reliable, for the most sensitive noncancer end point for each exposure duration. MRLs include adjustments to reflect human variability and, where appropriate, the uncertainty of extrapolating from laboratory animal data to humans. Although methods have been established to derive these levels (Barnes et al. 1987 EPA 1989a), uncertainties are associated with the techniques. Furthermore, ATSDR acknowledges additional uncertainties inherent in the application of these procedures to derive less than lifetime MRLs. As an example, acute inhalation MRLs may not be protective for health effects that are delayed in development or are acquired following repeated acute insults, such as hypersensitivity reactions, asthma, or chronic bronchitis. As these kinds of health effects data become available and methods to assess levels of significant human exposure improve, these MRLs will be revised. 

Immunotoxicology data most often available for use in risk assessment is derived from experimental animal studies. Although animal models provide an opportunity to establish more reliable exposure estimates and conduct more informative tests than human studies, the level of accuracy that can be achieved using such data in extrapolating to humans is often a matter of debate. In immunotoxicology testing, a set of tests usually referred to... 

In animal experiments exposures can be carefully controlled, and dose-response curves can be formally estimated. Extrapolating such information to the human situation is often done for regulatory purposes. There are several models for estimating a lifetime cancer risk in humans based on extrapolation from animal data. These models, however, are premised on empirically unverified assumptions that limit their usefulness for quantitative purposes. While quantitative cancer risk assessment is widely used, it is by no means universally accepted. Using different models, one can arrive at estimates of potential cancer incidence in humans that vary by several orders of magnitude for a given level of exposure. Such variations make it rather difficult to place confidence intervals around benefits estimations for regulatory purposes. Furthermore, low dose risk estimation methods have not been developed for chronic health effects other than cancer. The... 

In this paper I have tried to show that measurement of health benefits attributable to TSCA is not feasible. I hope that in doing so I have not belabored the obvious. For new chemicals and for most existing chemicals, prospective evaluation of health benefits to be achieved by various exposure controls will have to be based on extrapolation from microbial and animal data. However, while such extrapolation may be useful in a qualitative sense, quantitative risk assessment techniques involve considerable uncertainty, and in any case have not been developed for chronic effects other than cancer. 

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