DEVELOPING A PBPK MODEL FOR THE HIGH LEVEL INTEGRATED SENSOR FOR NANOTOXICITY SCREENING

1 Dubaj Tibor
Co-authors:
1 Šimon Peter 1 Cibulková Zuzana 1 Vykydalová Anna 1 Breza Martin
Institution:
1 Department of Physical Chemistry, Faculty of Chemical and Food Technology, Slovak University of Technology, Radlinského 9, 812 37 Bratislava, Slovakia, tibor.dubaj@stuba.sk
Conference:
9th International Conference on Nanomaterials - Research & Application, Hotel Voronez I, Brno, Czech Republic, EU, October 18th - 20th 2017
Proceedings:
Proceedings 9th International Conference on Nanomaterials - Research & Application
Pages:
752-757
ISBN:
978-80-87294-81-9
ISSN:
2694-930X
Published:
8th March 2018
Proceedings of the conference were published in Web of Science and Scopus.
Metrics:
19 views / 2 downloads
Abstract

Toxicity of any substance is determined by its physico-chemical properties and tissue exposure. In the case of nanoparticles (NPs), the relevant properties include the size, aspect ratio, surface charge, chemical composition etc.; the tissue exposure represents the NPs’ concentration and exposure duration. The HISENTS project aims to develop a platform of integrated modules for nanotoxicity screening. The PBPK model is an integral part of the platform as it provides information on the tissue exposure to nanomaterials via their ADME (absorption, distribution, metabolism, and excretion) behaviour. For this reason, a simple perfusion rate-limited PBPK model requiring only one NP-specific parameter per tissue was developed. The model treats all tissues as well-stirred compartments and the rate of NP exchange is only limited by the tissue perfusion. The model was calibrated against in vivo data for nano-TiO2 and, despite its simplicity, gave a reasonable agreement between predicted and measured NPs concentrations in the tissues. The main advantage of the model is that the biodistribution of NPs is described using only thermodynamic parameters (partition coefficients) which can be estimated from equilibrium responses of the individual modules.

Keywords: nanotoxicity, pharmacokinetics, modelling
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