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dc.contributor.authorMinnema, Jordi
dc.contributor.authorBorgos, Sven Even F.
dc.contributor.authorLiptrott, Neill
dc.contributor.authorVandebriel, Rob J.
dc.contributor.authorDelmaar, Christiaan
dc.date.accessioned2023-01-24T10:18:08Z
dc.date.available2023-01-24T10:18:08Z
dc.date.created2022-08-22T17:26:59Z
dc.date.issued2022
dc.identifier.citationDrug Delivery and Translational Research. 2022, 12 2132-2144.en_US
dc.identifier.issn2190-393X
dc.identifier.urihttps://hdl.handle.net/11250/3045768
dc.description.abstractThe use of nanobiomaterials (NBMs) is becoming increasingly popular in the field of medicine. To improve the understanding on the biodistribution of NBMs, the present study aimed to implement and parametrize a physiologically based pharmacokinetic (PBPK) model. This model was used to describe the biodistribution of two NBMs after intravenous administration in rats, namely, poly(alkyl cyanoacrylate) (PACA) loaded with cabazitaxel (PACA-Cbz), and LipImage™ 815. A Bayesian parameter estimation approach was applied to parametrize the PBPK model using the biodistribution data. Parametrization was performed for two distinct dose groups of PACA-Cbz. Furthermore, parametrizations were performed three distinct dose groups of LipImage™ 815, resulting in a total of five different parametrizations. The results of this study indicate that the PBPK model can be adequately parametrized using biodistribution data. The PBPK parameters estimated for PACA-Cbz, specifically the vascular permeability, the partition coefficient, and the renal clearance rate, substantially differed from those of LipImage™ 815. This emphasizes the presence of kinetic differences between the different formulations and substances and the need of tailoring the parametrization of PBPK models to the NBMs of interest. The kinetic parameters estimated in this study may help to establish a foundation for a more comprehensive database on NBM-specific kinetic information, which is a first, necessary step towards predictive biodistribution modeling. This effort should be supported by the development of robust in vitro methods to quantify kinetic parameters.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.subjectBayesian parameter estimationen_US
dc.subjectBiodistributionen_US
dc.subjectNanobiomaterials (NBMs)en_US
dc.subjectPhysiologically based pharmacokinetic modelingen_US
dc.titlePhysiologically based pharmacokinetic modeling of intravenously administered nanoformulated substancesen_US
dc.title.alternativePhysiologically based pharmacokinetic modeling of intravenously administered nanoformulated substancesen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© The Author(s) 2022en_US
dc.source.pagenumber2132-2144en_US
dc.source.volume12en_US
dc.source.journalDrug Delivery and Translational Researchen_US
dc.identifier.doi10.1007/s13346-022-01159-w
dc.identifier.cristin2045100
dc.relation.projectEC/H2020/761104en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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