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A weight of evidence approach for hazard screening of engineered nanomaterials
Link to Journal 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.
This paper implements a quantitative Weight of evidence (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. Application of the framework is illustrated for titanium dioxide nanoparticles (nano-TiO2).
Peer Reviewed Journal Article
Exposure Or Hazard Target
Method Of Study
Risk Exposure Group
Nanotoxicology, 2014, 8(1): 72-87
Hristozov DR, Zabeo A, Foran C, Isigonis P, Marcomini A, Linkov I
Last updated on December 11, 2013
This work is supported in part by the Nanoscale Science and Engineering Initiative of the National Science Foundation
under NSF Award Number EEC-0118007.
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