title: A Tractable Method for Measuring Nanomaterial Risk Using Bayesian Networks.
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.
authors.affiliation: Kemmy Business School, University of Limerick, Limerick, Ireland. Finbarr.Murphy@ul.ie.
authors.forename: Finbarr
authors.identifier: http://orcid.org/0000-0002-7463-7923
authors.initials: F
authors.lastname: Murphy
authors.affiliation: Kemmy Business School, University of Limerick, Limerick, Ireland.
authors.forename: Barry
authors.initials: B
authors.lastname: Sheehan
authors.affiliation: Kemmy Business School, University of Limerick, Limerick, Ireland.
authors.forename: Martin
authors.initials: M
authors.lastname: Mullins
authors.affiliation: RIKILT Wageningen University & Research (WR), Akkermaalsbos 2, 6708 PD, Wageningen, The Netherlands.|Division of Toxicology, Wageningen University, Stippeneng 4, 6708 WE, Wageningen, The Netherlands.
authors.forename: Hans
authors.initials: H
authors.lastname: Bouwmeester
authors.affiliation: RIKILT Wageningen University & Research (WR), Akkermaalsbos 2, 6708 PD, Wageningen, The Netherlands.
authors.forename: Hans J P
authors.initials: HJ
authors.lastname: Marvin
authors.affiliation: RIKILT Wageningen University & Research (WR), Akkermaalsbos 2, 6708 PD, Wageningen, The Netherlands.
authors.forename: Yamine
authors.initials: Y
authors.lastname: Bouzembrak
authors.affiliation: ISTEC-CNR, Via Granarolo, 64, I-48018, Faenza, RA, Italy.
authors.forename: Anna L
authors.initials: AL
authors.lastname: Costa
authors.affiliation: Nanotechnology and Catalysis Research Center, University of Malaya, 50603, Kuala Lumpur, Malaysia.
authors.forename: Rasel
authors.initials: R
authors.lastname: Das
authors.affiliation: Heriot-Watt University, Edinburgh, EH14 4AS, Scotland, UK.
authors.forename: Vicki
authors.initials: V
authors.lastname: Stone
authors.affiliation: Department of Physics, and Bernal Institute, University of Limerick, Limerick, Ireland.
authors.forename: Syed A M
authors.initials: SA
authors.lastname: Tofail
keywords: Bayesian; Control banding; Risk assessment