Application of Bayesian networks for hazard ranking of nanomaterials to support human health risk assessment
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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 TiO2, SiO2, Ag, CeO2, 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.
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Previous studies have demonstrated the value of BNs for developing qualitative "toxicity/hazard" classification of ENMs based on using physicochemical and specialized descriptors.
“Previous studies have demonstrated the value of BNs for developing qualitative “toxicity/hazard” classification of ENMs based on using physicochemical and specialized descriptors .251”
From QSAR without borders (2020) · cites this paper as [251]
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Money, E. S., Barton, L. E., Dawson, J., Reckhow, K. H., & Wiesner, M. R. (2014) · Science of The Total Environment · doi:10.1016/j.scitotenv.2013.12.100 · Cited by 30 · see citing works
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Muratov, E. N., Bajorath, J., Sheridan, R. P., Tetko, I. V., Filimonov, D., Poroikov, V., Oprea, T. I., Baskin, I. I., Varnek, A., Roitberg, A., et al. (2020) · Chemical Society Reviews · doi:10.1039/d0cs00098a · Cited by 913 · see citing works
- Authors
- Marvin, H. J. P., Bouzembrak, Y., Janssen, E. M., van der Zande, M., Murphy, F., Sheehan, B., Mullins, M., & Bouwmeester, H.
- Affiliations
- Wageningen University & Research (NL)
- Wageningen University and Research, RIKILT, Wageningen, the Netherlands;
- University of Limerick (IE)
- Corresponding author
- Marvin, Hans J. P.
- ORCID
- Venue
- Nanotoxicology
- Publisher
- Informa UK Limited
- Published
- 2017-01-02
- Volume
- 11
- Issue
- 1
- Pages
- 123-133
- ISSN
- 1743-5390 (ISSN-L)
- 1743-5404
- OpenAlex
- W2561239230
- Cited by
- 82
- References
- 1
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 4 · 2023: 5 · 2022: 10 · 2021: 12 · 2020: 14 · 2019: 10 · 2018: 9 · 2017: 4
- FWCI
- 4.27
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nanotoxicology (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Socio-Environmental Systems Modeling (acceptedVersion, cc-by-nc-nd)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by-nc-nd)
- Funders
- The Netherlands Ministry of Economic Affairs
- NanoNextNL
- Topics
- Physical Sciences › Materials Science › Materials Chemistry › Nanoparticles: synthesis and applications
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Risk and Safety Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Carcinogens and Genotoxicity Assessment
- Keywords
- Bayesian networks, human health risk assessment, exposure routes, physicochemical properties, titanium dioxide, silica, silver, cerium oxide, zinc oxide, expert consultation
- MeSH terms
- Bayes Theorem, Cerium, Data Collection, Humans, Models, Theoretical, Silicon Dioxide, Silver, Zinc Oxide, Hazardous Substances, Risk Assessment, Nanostructures
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