title: What role for biologically based dose-response models in estimating low-dose risk?
abstract: BACKGROUND
  Biologically based dose-response (BBDR) models can incorporate data on biological processes at the cellular and molecular level to link external exposure to an adverse effect.
  
  
  OBJECTIVE
  Our goal was to examine the utility of BBDR models in estimating low-dose risk.
  
  
  METHODS
  We reviewed the utility of BBDR models in risk assessment.
  
  
  RESULTS
  BBDR models have been used profitably to evaluate proposed mechanisms of toxicity and identify data gaps. However, these models have not improved the reliability of quantitative predictions of low-dose human risk. In this commentary we identify serious impediments to developing BBDR models for this purpose. BBDR models do not eliminate the need for empirical modeling of the relationship between dose and effect, but only move it from the whole organism to a lower level of biological organization. However, in doing this, BBDR models introduce significant new sources of uncertainty. Quantitative inferences are limited by inter- and intraindividual heterogeneity that cannot be eliminated with available or reasonably anticipated experimental techniques. BBDR modeling does not avoid uncertainties in the mechanisms of toxicity relevant to low-level human exposures. Although implementation of BBDR models for low-dose risk estimation have thus far been limited mainly to cancer modeled using a two-stage clonal expansion framework, these problems are expected to be present in all attempts at BBDR modeling.
  
  
  CONCLUSIONS
  The problems discussed here appear so intractable that we conclude that BBDR models are unlikely to be fruitful in reducing uncertainty in quantitative estimates of human risk from low-level exposures in the foreseeable future. Use of in vitro data from recent advances in molecular toxicology in BBDR models is not likely to remove these problems and will introduce new issues regarding extrapolation of data from in vitro systems.
authors.affiliation: Louisiana Tech University, Ruston, Louisiana 71272 , USA. kennycrump@email.com
authors.forename: Kenny S
authors.initials: KS
authors.lastname: Crump
authors.forename: Chao
authors.initials: C
authors.lastname: Chen
authors.forename: Weihsueh A
authors.initials: WA
authors.lastname: Chiu
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Louis
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Portier
authors.forename: Ravi P
authors.initials: RP
authors.lastname: Subramaniam
authors.forename: Paul D
authors.initials: PD
authors.lastname: White
mesh_terms: D000818:Animals; D004305:Dose-Response Relationship, Drug; D004781:Environmental Exposure; D004782:Environmental Health; D006801:Humans; D008954:Models, Biological; D018570:Risk Assessment