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A WEIGHT OF EVIDENCE APPROACH FOR HAZARD SCREENING OF ENGINEERED NANOMATERIALS.
MedLine Citation:
PMID:  23153309     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Abstract Hazard identification is an important step in assessing nanomaterial risk and is required under multiple regulatory frameworks in the US, Europe and worldwide. Given the emerging nature of the field and complexity of nanomaterials, multiple studies on even basic material properties often result in varying data pointing in different directions when data interpretation is attempted. Weight of Evidence (WOE) evaluation has been recommended for nanomaterial risk assessment, but the majority of WOE frameworks are qualitative in nature and do not satisfy the growing needs for objectivity and transparency that are necessary for regulatory decision making. This paper implements a quantitative WOE framework that utilizes Multi-Criteria Decision Analysis methodology for integrating individual studies on nanomaterial hazard resulting from physico-chemical and toxicological properties of nanomaterials. For the first time, a WOE approach explicitly integrates expert evaluation of data quality of available information. Application of the framework is illustrated for titanium dioxide nanoparticles (nano-TiO2), but the approach is designed to compare the relative hazard of several nanomaterials as well as emerging stressors in general.
Authors:
Danail Hristozov; Alex Zabeo; Christy M Foran; Andrea Critto; Antonio Marcomini; Panagiotis Isigonis; Igor Linkov
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-11-16
Journal Detail:
Title:  Nanotoxicology     Volume:  -     ISSN:  1743-5404     ISO Abbreviation:  Nanotoxicology     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-11-16     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101233132     Medline TA:  Nanotoxicology     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Ca Foscari University of Venice, Department of Environmental Sciences, Informatics and Statistics, Calle Larga S. Marta 2137, Venice, Italy, 30123, 00393450864758.
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