Complex and dynamic physiologic processes underlie the exposure-response relations that occupational and environmental epidemiologists study. Simple summary measures of exposure such as the average, cumulative exposure, or duration of exposure, can be applied suitably in exposure-response analyses in many instances. However, there are situations where these metrics may not be directly proportional to risk, in which case their use will result in misclassification and biased estimates of exposure-response associations. We outline methods for developing exposure or dose metrics which may reduce misclassification, as illustrated with some recent examples. Selecting better exposure or dose metrics can be thought of as a problem of choosing appropriate weights on the exposure history of each cohort member. Dosimetric modeling involves choosing exposure weights based on formal hypotheses about underlying physiologic or pathogenetic processes. Dosimetric modeling is still not widely used in epidemiology, and so the forms of mathematical models and the criteria for choosing one model over another are not yet standardized. We hope to stimulate further applications through this presentation.