COMPREHENSIVE REALISMS WEIGHT-OF-EVIDENCE BASED DISTRIBUTIONAL DOSE-RESPONSE CHARACTERIZATION

Challenges to low-dose Linearity and other default assumptions in canc er risk assessment and the limitations associated with NOAELs, LOAELs, and constant uncertainty factor values in the evaluation of noncancer health effects have stimulated the continued evolution of risk assess ment methodologies. The increasing need for more realistic estimates o f the dose-response relationship, better uncertainty characterization, and greater utilization of cost-benefit analyses have also contribute d to this evolution. ''Comprehensive Realism'' is an emerging quantita tive weight-of-evidence based risk assessment methodology for both can cer and noncancer health effects which utilizes probability distributi ons and decision analysis techniques to reflect more of the relevant h uman exposure data, more of the available and pertinent human and anim al dose-response data, and the current state of knowledge about the re lative plausibility of alternative dose-response analyses. A tree (lik e a decision tree and a probability tree) is used to decompose the dos e-response assessment into component factors, to provide a structure f or explicitly considering multiple alternatives for each factor, and t o explicitly incorporate the current state of knowledge about the rela tive plausibility of these alternatives. Groundbreaking work has demon strated the feasibility of weight-of-evidence based distributional cha racterizations, and provided initial examples. Computer software imple mentations are also available.