Although regulatory agencies formally encourage the integration of all available data in chemical risk assessment, consistent implementation of this practice has been constrained by the lack of a clear, systematic method for doing so. In this paper, we describe a methodology for evaluating, classifying and integrating human and animal data into the risk assessment process that incorporates: (1) a balanced appraisal of human and animal data, (2) relevance to different stages of the risk assessment process, and (3) accommodation for different data quality requirements. The proposed framework offers a flexible, step-wise approach for determining which set of available data best support the chemical risk assessment that involves the rating and relative ranking of human and animal data quality.
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