Physiologically Based Pharmacokinetics of Molecular Imaging Nanoparticles for mRNA Detection Determined in Tumor-Bearing Mice

Opitz, Armin W.; Wickstrom, Eric; Thakur, Mathew L.; Wagner, Norman J.

doi:10.1089/oli.2009.0216

Cited by 23 publications

(17 citation statements)

References 48 publications

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“…59 In any case, most, if not all, investigators incorporate partition coefficients into their nano PBPK models. 10,[17][18][19][20][21][22][24][25][26][27] Here, we found that at least in the case of PAA-PEG, PAA, and gold NPs, the biokinetics cannot be accurately described without introducing a P factor and a similar conclusion was reached by Lin et al 25 The exchange of NPs between blood and organs is strongly influenced by the ability to cross the endothelium. This endothelial permeability varies between organs as a result of differences in the degree of fenestration, as well as phagocytic capacity.…”

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confidence: 71%

Toward a general physiologically-based pharmacokinetic model for intravenously injected nanoparticles

Carlander

Jolliet

et al. 2016

IJN

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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 for nondegradable NPs injected intravenously into rats. The same model and physiological parameters were applied to pegylated polyacrylamide, uncoated polyacrylamide, gold, and titanium dioxide NPs, whereas NP-specific parameters were chosen on the basis of the best fit to the experimental time-courses of NP accumulation in various tissues. Our model describes the biokinetic behavior of all four types of NPs adequately, despite extensive differences in this behavior as well as in their physicochemical properties. In addition, this simulation 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 NP type included the blood:tissue coefficients of permeability and the rate constant for phagocytic uptake. Since only four types of NPs with several differences in characteristics (dose, size, charge, shape, and surface properties) were used, the relationship between these characteristics and the NPdependent model parameters could not be elucidated and more experimental data are required in this context. In this connection, intravenous biodistribution studies with associated PBPK analyses would provide the most insight.

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supporting

confidence: 71%

Toward a general physiologically-based pharmacokinetic model for intravenously injected nanoparticles

Carlander

Jolliet

et al. 2016

IJN

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“…Typical preclinical tumor models average data across multiple animals to characterize biodistribution and pharmacokinetics, which are not translational approaches 39, 40 . In contrast, the molecular imaging approach used here can deliver quantitative spatio-temporal data within an individual.…”

Section: Discussionmentioning

confidence: 99%

Kinetic quantification of protein polymer nanoparticles using non-invasive imaging

Janib

Liu

Park

et al. 2012

Integrative Biology

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Protein polymers are repetitive amino acid sequences that can assemble monodisperse nanoparticles with potential applications as cancer nanomedicines. Of the currently available molecular imaging methods, positron emission tomography (PET) is the most sensitive and quantitative; therefore, this work explores microPET imaging to track protein polymer nanoparticles over several days. To achieve reliable imaging, the polypeptides were modified by site-specific conjugation using a heterobifunctional sarcophagine chelator, AmBaSar, which was subsequently complexed with 64Cu. AmBaSar/64Cu was selected because it can label particles in vivo over periods of days, which is consistent with the timescales required to follow long-circulating nanotherapeutics. Using an orthotopic model of breast cancer, we observed four elastin-like polypeptides (ELPs)-based protein polymers of varying molecular weight, amino acid sequence, and nanostructure. To analyze this data, we developed a six-compartment image-driven pharmacokinetic model capable of describing their distribution within individual subjects. Surprisingly, the assembly of an ELP block copolymer (78 kD) into nanoparticles (Rh = 37.5 nm) minimally influences pharmacokinetics or tumor accumulation compared to a free ELP of similar length (74 kD). Instead, ELP molecular weight is the most important factor controlling the fate of these polymers, whereby long ELPs (74 kD) have a heart activity half-life of 8.7 hours and short ELPs (37 kD) have a half-life of 2.1 hrs. These results suggest that ELP-based protein polymers may be a viable platform for the development of multifunctional therapeutic nanoparticles that can be imaged using clinical PET scanners.

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“…Through measurement of the cell area, volume and the partition coefficient, our method can isolate the fundamental uptake behavior that describes the effective overall process of cellular uptake. This can be used then, for example, in physiologically-based pharmacokinetic (PBPK) models [31]. In a typical PBPK model the various organs in the body are described by two compartments, a vascular and an extravascular compartment.…”

Section: Methodsmentioning

confidence: 99%

“…Further, we develop a simple, lumped mass transfer model that is used to extract the effective mass transfer coefficients from the quantitative uptake experiments and determination of the cell volume and surface area. As the mass transfer coefficient gives the fundamental rate of transport of a species independent of the area available for transport, these mass transfer coefficients can be used in physiologically-based pharmacokinetic models, e. g. [31]. Determining a mass transfer coefficient for a compound allows for a fundamental understanding of how the compound is internalized.…”

Section: Introductionmentioning

confidence: 99%

Uptake, efflux, and mass transfer coefficient of fluorescent PAMAM dendrimers into pancreatic cancer cells

Opitz

Czymmek

Wickstrom

et al. 2013

Biochimica et Biophysica Acta (BBA) - Biomembranes

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Targeted delivery of imaging agents to cells can be optimized with the understanding of uptake and efflux rates. Cellular uptake of macromolecules is studied frequently with fluorescent probes. We hypothesized that the internalization and efflux of fluorescently labeled macromolecules into and out of mammalian cells could be quantified by confocal microscopy to determine the rate of uptake and efflux, from which the mass transfer coefficient is calculated. The cellular influx and efflux of a third generation poly(amido amine) (PAMAM) dendrimer labeled with an Alexa Fluor 555 dye was measured in Capan-1 pancreatic cancer cells using confocal fluorescence microscopy. The Capan-1 cells were also labeled with 5-chloromethylfluorescein diacetate (CMFDA) green cell tracker dye to delineate cellular boundaries. A dilution curve of the fluorescently labeled PAMAM dendrimer enabled quantification of the concentration of dendrimer in the cell. A simple mass transfer model described the uptake and efflux behavior of the PAMAM dendrimer. The effective mass transfer coefficient was found to be 0.054 ± 0.043 μm/min, which corresponds to a rate constant of 0.035 ± 0.023 min−1 for uptake of the PAMAM dendrimer into the Capan-1 cells. The effective mass transfer coefficient was shown to predict the efflux behavior of the PAMAM dendrimer from the cell if the fraction of labeled dendrimer undergoing non-specific binding is accounted for. This work introduces a novel method to quantify the mass transfer behavior of fluorescently labeled macromolecules into mammalian cells.

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Physiologically Based Pharmacokinetics of Molecular Imaging Nanoparticles for mRNA Detection Determined in Tumor-Bearing Mice

Cited by 23 publications

References 48 publications

Toward a general physiologically-based pharmacokinetic model for intravenously injected nanoparticles

Toward a general physiologically-based pharmacokinetic model for intravenously injected nanoparticles

Kinetic quantification of protein polymer nanoparticles using non-invasive imaging

Uptake, efflux, and mass transfer coefficient of fluorescent PAMAM dendrimers into pancreatic cancer cells

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