Details

Autor(en) / Beteiligte

• Marvin, Hans J. P.
• Bouzembrak, Yamine
• Janssen, Esmée M.
• van der Zande, Meike
• Murphy, Finbarr
• Sheehan, Barry
• Mullins, Martin
• Bouwmeester, Hans

Titel

Application of Bayesian networks for hazard ranking of nanomaterials to support human health risk assessment

Ist Teil von

• Nanotoxicology, 2017-02, Vol.11 (1), p.123-133

Ort / Verlag

England: Taylor & Francis

Erscheinungsjahr

2017

Quelle

MEDLINE

Beschreibungen/Notizen

• In this study, a Bayesian Network (BN) was developed for the prediction of the hazard potential and biological effects with the focus on metal- and metal-oxide nanomaterials to support human health risk assessment. The developed BN captures the (inter) relationships between the exposure route, the nanomaterials physicochemical properties and the ultimate biological effects in a holistic manner and was based on international expert consultation and the scientific literature (e.g., in vitro/in vivo data). The BN was validated with independent data extracted from published studies and the accuracy of the prediction of the nanomaterials hazard potential was 72% and for the biological effect 71%, respectively. The application of the BN is shown with scenario studies for TiO 2 , SiO 2 , Ag, CeO 2 , ZnO nanomaterials. It is demonstrated that the BN may be used by different stakeholders at several stages in the risk assessment to predict certain properties of a nanomaterials of which little information is available or to prioritize nanomaterials for further screening.