NanonextNL risico's nano in kaart brengen (KB-23-002-008, KB-15-003-022)

  • Marvin, Hans (Project Leader)

Project: LVVN project

Project Details

Description

Nanomaterials (NMs) are used in a great variety of products spanning a diverse range of industrial sectors (e.g. energy, coatings, textiles, medicine, food and agri-sector). It is eminent that human and environment will be exposed to these new materials. To perform a conventional risk assessment might not be feasible for all nanomaterials given the fast moving market of nanomaterials. There is a need to prioritize and band/group nanomaterials for subsequent risk assessment. For this purpose, in the NanonextNL 01A01 project, we develop a Decision Support System (DSS) based on Bayesian networks (BN) to aid the risk assessors to prioritize NMs for a full risk assessment. BNs have been proposed as tool to model safety of nanoparticles and have been applied successfully to model complex environmental systems. These networks allow for a meta-analysis of the available information on (eco) toxicological and exposure data in relation to the measured physicochemical properties of the NMs tested.

 

We have developed a BN for human and environmental hazard ranking of NMs and linked these networks to a database which was populated with data from literature and expert knowledge. The constructed BN for hazard ranking in human was also validated by means of an international expert consultation (N: 15).The human BN model consists of three interlinked main categories of variables, i.e. NMs characteristics, exposure routes and biological effects. Linkages between both BN networks (i.e. human and environment) are proposed which enables exploitation of knowledge and experimental data (for example on biological effects of NMs, mode of actions etc.) from both domains.

StatusFinished
Effective start/end date1/01/1231/12/16

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