Journal article
Improving Weight of Evidence Approaches to Chemical Evaluations
Risk analysis, Vol.35(2), pp.186-192
02/2015
Handle:
https://hdl.handle.net/2376/105569
PMID: 25516407
Abstract
Federal and other regulatory agencies often use or claim to use a weight of evidence (WoE) approach in chemical evaluation. Their approaches to the use of WoE, however, differ significantly, rely heavily on subjective professional judgment, and merit improvement. We review uses of WoE approaches in key articles in the peer‐reviewed scientific literature, and find significant variations. We find that a hypothesis‐based WoE approach, developed by Lorenz Rhomberg et al., can provide a stronger scientific basis for chemical assessment while improving transparency and preserving the appropriate scope of professional judgment. Their approach, while still evolving, relies on the explicit specification of the hypothesized basis for using the information at hand to infer the ability of an agent to cause human health impacts or, more broadly, affect other endpoints of concern. We describe and endorse such a hypothesis‐based WoE approach to chemical evaluation.
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Details
- Title
- Improving Weight of Evidence Approaches to Chemical Evaluations
- Creators
- Randall Lutter - University of VirginiaLinda Abbott - U.S. Department of AgricultureRick Becker - American Chemistry CouncilChris Borgert - Applied Pharmacology and Toxicology IncAnn Bradley - Integral Consulting IncGail Charnley - Health Risk StrategiesSusan Dudley - George Washington UniversityAlan Felsot - Washington State UniversityNancy Golden - U.S. Fish and Wildlife ServiceGeorge Gray - George Washington UniversityDaland Juberg - Dow AgroSciencesMary Mitchell - Pest Management Regulatory Agency of CanadaNancy Rachman - ILSI North AmericaLorenz Rhomberg - Gradient CorporationKeith Solomon - University of GuelphStephen Sundlof - University of MarylandKate Willett - Humane Society of the United States
- Publication Details
- Risk analysis, Vol.35(2), pp.186-192
- Academic Unit
- Entomology, Department of
- Number of pages
- 7
- Identifiers
- 99900546964201842
- Language
- English
- Resource Type
- Journal article