Quantitative risk assessment provides formalized scientific input to regulatory agencies that set occupational and environmental standards for potentially toxic exposures. Current practice relies heavily on statistical extrapolation from high-dose animal studies. Human data obviate the need for interspecies extrapolation and reduce the range of high-to-low dose extrapolation. This paper proposes a framework for classifying individual epidemiologic studies as to their adequacy for use in dose-response extrapolation. The framework considers five criteria: (1) a stable positive association with an adverse health outcome; (2) high overall study quality; (3) no substantial confounding; (4) quantitative exposure assessment for individuals; (5) evidence of a dose-response relationship. With these criteria, studies can be categorized as (1) suitable to serve as a basis for extrapolation; (2) inadequate to be the basis for direct extrapolation but appropriate to use for evaluating the plausibility of animal-derived risk estimates; or (3) useful only for hazard identification, not for dose-response assessment. Methods for using studies in the first two categories are briefly described. The emphasis is not on establishing rigid rules, but rather on ensuring a consistent, reliable process that makes optimum use of available data.