A physiologically based pharmacokinetic model to predict the superparamagnetic iron oxide nanoparticles (SPIONs) accumulation in vivo

A Henrique Silva, E Lima Jr… - European Journal of …, 2017 - degruyter.com
European Journal of Nanomedicine, 2017degruyter.com
Superparamagnetic iron oxide nanoparticles (SPIONs) have been identified as a promising
material for biomedical applications. These include as contrast agents for medical imaging,
drug delivery and/or cancer cell treatment. The nanotoxicological profile of SPIONs has
been investigated in different studies and the distribution of SPIONs in the human body has
not been fully characterized. The aim of this study was to develop a physiologically-based
pharmacokinetic (PBPK) model to predict the pharmacokinetics of SPIONs. The distribution …
Abstract
Superparamagnetic iron oxide nanoparticles (SPIONs) have been identified as a promising material for biomedical applications. These include as contrast agents for medical imaging, drug delivery and/or cancer cell treatment. The nanotoxicological profile of SPIONs has been investigated in different studies and the distribution of SPIONs in the human body has not been fully characterized. The aim of this study was to develop a physiologically-based pharmacokinetic (PBPK) model to predict the pharmacokinetics of SPIONs. The distribution and accumulation of SPIONs in organs were simulated taking into consideration their penetration through capillary walls and their active uptake by specialized macrophages in the liver, spleen and lungs. To estimate the kinetics of SPION uptake, a novel experimental approach using primary macrophages was developed. The murine PBPK model was validated against in vivo pharmacokinetic data, and accurately described accumulation in liver, spleen and lungs. After validation of the murine model, a similar PBPK approach was developed to simulate the distribution of SPIONs in humans. These data demonstrate the utility of PBPK modeling for estimating biodistribution of inorganic nanoparticles and represents an initial platform to provide computational prediction of nanoparticle pharmacokinetics.
De Gruyter
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