2016
DOI: 10.2147/ijn.s94370
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Toward a general physiologically-based pharmacokinetic model for intravenously injected nanoparticles

Abstract: To assess the potential toxicity of nanoparticles (NPs), information concerning their uptake and disposition (biokinetics) is essential. Experience with industrial chemicals and pharmaceutical drugs reveals that biokinetics can be described and predicted accurately by physiologically-based pharmacokinetic (PBPK) modeling. The nano PBPK models developed to date all concern a single type of NP. Our aim here was to extend a recent model for pegylated polyacrylamide NP in order to develop a more general PBPK model… Show more

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Cited by 77 publications
(93 citation statements)
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References 61 publications
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“…The lower percentage of NC uptake by the liver observed in our experiments with increasing PLA and PLA-PEG NC polymeric doses suggests some degree of saturation of the MPS uptake pathways. Higher depletion of blood opsonins or complement consumption would possibly result in a decrease in the liver uptake of PLA NC compared to PLA-PEG NC as a function of an increase in the administered dose, as estimated for similar polymeric nanocarriers (Carlander et al, 2016). However, in the present study, no significant differences in liver uptake between both formulations were observed (p>0.05).…”
contrasting
confidence: 42%
“…The lower percentage of NC uptake by the liver observed in our experiments with increasing PLA and PLA-PEG NC polymeric doses suggests some degree of saturation of the MPS uptake pathways. Higher depletion of blood opsonins or complement consumption would possibly result in a decrease in the liver uptake of PLA NC compared to PLA-PEG NC as a function of an increase in the administered dose, as estimated for similar polymeric nanocarriers (Carlander et al, 2016). However, in the present study, no significant differences in liver uptake between both formulations were observed (p>0.05).…”
contrasting
confidence: 42%
“…The model was optimized by best fit to intravenous rat experimental data obtained with polyethylene glycolylated polyacrylamide (PAA-PEG) NMs (Li et al 2014). Carlander et al (2016) have slightly modified this model for simultaneous predictions of the following NMs: PAA-PEG, uncoated PAA, gold and TiO 2 NMs. These NMs were selected since sufficient experimental biokinetic data for optimization are available.…”
Section: Introductionmentioning
confidence: 99%
“…Further, the simulations demonstrated that the dose exerts a profound impact on the biokinetics, since saturation of the phagocytic cells at higher doses becomes a major limiting step. The fitted model parameters that were most dependent on NM-type included blood:tissue partition coefficients and the rate constant for phagocytic uptake (Carlander et al 2016). Since only four types of NMs with several differences in characteristics were used, the relationship between these characteristics and the NM-dependent model parameters could not be elucidated and more experimental data are required.…”
Section: Introductionmentioning
confidence: 99%
“…M t,cap [μg per g] – PCs uptake capacity for nanoparticles per organ t weight, which is determined as the PCs number per organ weight (nanoparticle type independent) multiplied by the maximum uptake capacity in individual PCs (the same for all organs except the spleen) [35]. …”
Section: Methodsmentioning
confidence: 99%