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Wiley, Contact Dermatitis, 5(47), p. 257-266, 2002

DOI: 10.1034/j.1600-0536.2002.470502.x

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A review of the scientific basis for uncertainty factors for use in quantitative risk assessment for the induction of allergic contact dermatitis

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Safety evaluations for chemicals which possess the ability to cause sensitization by skin contact have traditionally been done using an ad hoc comparative risk assessment technique. Recently, several papers have been published supporting the use of an alternative, and potentially better, quantitative risk assessment approach. While they represent a relatively new approach to risk assessment for sensitizers, quantitative methods have been used for decades to support risk assessments for systemic toxicity. Historically, these methods have involved the extrapolation of toxicity data - generally from studies in laboratory animals at relatively high doses to human exposures at lower doses. For toxicity endpoints with a threshold, this process has traditionally involved the use of uncertainty factors. For example, uncertainty factors are commonly used to extrapolate from laboratory animals to humans, and from 'average' humans to sensitive subpopulations. In the absence of data to support a different value, a default factor of 10 is widely accepted for each of these areas. Recent papers have advocated the use of a similar approach to characterize the risk of the induction of skin sensitization by allergens of varying potency and potential for skin contact. As with other forms of toxicity, a quantitative assessment of risk for allergic skin reactions can be approached by identifying a NOAEL (no observed adverse effect level) and applying appropriate uncertainty factors. Three major areas of data extrapolation have been identified: inter-individual susceptibility, the influence of vehicle or product matrix, and exposure considerations. This paper provides an overview of each of these areas with an evaluation of the available scientific database to support an uncertainty factor in the range of 1-10 for each area.