Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 510282
Title A Tractable Method for Measuring Nanomaterial Risk Using Bayesian Networks
Author(s) Murphy, Finbarr; Sheehan, Barry; Mullins, Martin; Bouwmeester, Hans; Marvin, Hans J.P.; Bouzembrak, Yamine; Costa, Anna L.; Das, Rasel; Stone, Vicki; Tofail, Syed A.M.
Source Nanoscale Research Letters 11 (2016)1. - ISSN 1931-7573
DOI https://doi.org/10.1186/s11671-016-1724-y
Department(s) RIKILT - BU Toxicology Bioassays & Novel Foods
VLAG
Publication type Refereed Article in a scientific journal
Publication year 2016
Keyword(s) Bayesian - Control banding - Risk assessment
Abstract

While control banding has been identified as a suitable framework for the evaluation and the determination of potential human health risks associated with exposure to nanomaterials (NMs), the approach currently lacks any implementation that enjoys widespread support. Large inconsistencies in characterisation data, toxicological measurements and exposure scenarios make it difficult to map and compare the risk associated with NMs based on physicochemical data, concentration and exposure route. Here we demonstrate the use of Bayesian networks as a reliable tool for NM risk estimation. This tool is tractable, accessible and scalable. Most importantly, it captures a broad span of data types, from complete, high quality data sets through to data sets with missing data and/or values with a relatively high spread of probability distribution. The tool is able to learn iteratively in order to further refine forecasts as the quality of data available improves. We demonstrate how this risk measurement approach works on NMs with varying degrees of risk potential, namely, carbon nanotubes, silver and titanium dioxide. The results afford even non-experts an accurate picture of the occupational risk probabilities associated with these NMs and, in doing so, demonstrated how NM risk can be evaluated into a tractable, quantitative risk comparator.

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