Toxicology and Applied Pharmacology
1 December 2019
Author links open overlay panel, , , , ,
The physiologically based pharmacokinetic (PBPK) model is a useful tool to predict the pharmacokinetics of various types of nanoparticles (NPs). The endocytosis mechanism plays a key role in pharmacokinetics of NPs. However, the effect of endocytosis mechanism both in the blood and tissue are seldom considered in PBPK model.
To investigate the biodistribution of intravenously injected pegylated AuNPs in mice and human using PBPK model considering the endocytosis mechanism both in the blood and tissue.
Taking polyethylene glycol-coated gold nanoparticles (AuNPs) as an example, we developed a PBPK model to explore biodistribution of different size AuNPs. In the model, we considered the role of endocytosis mechanism both in the blood and tissue. In addition, the size-dependent permeability coefficient, excretion rate constant, phagocytic capacity, uptake rate, and release rate were derived from literatures. The mice PBPK model was extrapolated to the human by changing physiology parameters and the number of phagocytic cell (PCs).
AuNPs were primarily distributed in the blood, liver, and spleen regardless of particle size, and almost all captured by the PCs in the liver and spleen, while few was captured in the blood. There are more organ distribution and longer circulation for smaller NPs. The 24-h accumulation of AuNPs decreased with increasing size in the most organ, while the accumulation of AuNPs showed an inverted U-shaped curve in the liver and slight U-shaped curve in the blood. The human results of model-predicted displayed a similar tendency with those in mice. Size, partition coefficients, and body weight were the key factors influencing the organ distribution of AuNPs.
The size played an important role on the distribution and accumulation of AuNPs in various tissues. Our PBPK model was well predicted the NPs distribution in mice and human. A better understanding of these mechanisms could provide effective guides for nanomedine delivery.
Air pollution has become a serious problem in China with the rapid development of urbanization and economic growth (Brauer et al., 2012; Deng et al., 2018a). Particulate matter (PM) is a key ingredient of air pollution. Although much attention has been paid to PM10 with particle diameter ≤ 10 μm, the ultrafine particles (≤100 nm in diameter) should be not ignored. The ultrafine particles are potentially hazards to health (Nel, 2005). Nanoparticles (NPs) are the particles whose physical diameters are ≤100 nm (Islam et al., 2017). Therefore, it increases the likelihood of intentional and unintentional exposure at the workplace and in the environment (Khlebtsov and Dykman, 2011). The rapidly developing field of nanotechnology is likely to become the source for human exposures to NPs, which is harmful to human health, such as inducing inflammatory reactions and oxidative stress (Deng et al., 2018b; Limbach et al., 2007; Manke et al., 2013; Salvi et al., 1999).
Epidemiological studies have shown that nanoparticles are harmful to health, and even can be distributed to tissues (Liou et al., 2012; Reijnders, 2012). The particle size, shape, surface chemistry and species of NPs determine the biodistribution in the body, which have a significant influence on NPs toxicity (Chithrani and Chan, 2007; Jiang et al., 2009; Pan et al., 2007; Pernodet et al., 2006). Among those parameters, the particle size plays an important role in the interaction with the biological system (Chithrani et al., 2006). As particle decreases in size, the specific surface area increases rapidly. Since surface area can influence the interaction with the biological components, smaller NPs can be more reactive in comparison to larger particle (Brown et al., 2001; Hagens et al., 2007). Smaller NPs show high accumulation and the most widespread organ distribution, whereas larger NPs have a low distribution in all tissues (De Jong et al., 2008; Semmler-Behnke et al., 2008; Sonavane et al., 2008; Zhang et al., 2011).
Although the study about kinetics and tissue distribution of NPs has been reported recently (Balogh et al., 2007; De Jong et al., 2008; Hirn et al., 2011), the knowledge in this field remains limited. A physiologically based pharmacokinetic (PBPK) model is adopted to predict the pharmacokinetics of various types of NPs. PBPK models have been successfully applied for the study of the absorption, distribution, metabolism, and excretion (ADME) of small molecules. Recently, the PBPK model has been used to predict ADME of NPs. Compared to the pharmacokinetics of small molecule, the physiological process of NPs also includes endocytosis. However, the effect of endocytosis behaviors on organ distribution, as well as the effect of particle size on endocytosis behavior used PBPK model, has not yet been addressed.
Endocytosis behaviors are a key process of NPs biodistribution (Cho et al., 2019b). Péry et al. (2009) developed the first PBPK model was able to use imaging data to describe the absorption and distribution of NPs. Bachler et al. (2013) are the first to attempt to simulate the endocytosis of NPs. Li et al. (2014) further incorporated the NPs endocytosis mechanism into PBPK model and successfully simulated the biodistribution of intravenous exposure of polyethylene on glycol coated polyacrylamide NPs, however it is not considering the particle size effect. The PBPK model of Lin et al. (2015) has just considered the endocytosis mechanism in the tissues, not in the plasma. However, the PBPK model about considering endocytosis both in the tissue and the plasma is limited. In fact, endocytosis behaviors of NPs are size-dependent (Chithrani et al., 2006; Chithrani and Chan, 2007; Lu et al., 2009; Osaki et al., 2004; Shan et al., 2011). The maximum uptake by phagocytizing cells (PCs) occurs at a NP size of 50 nm (Chithrani et al., 2006; Chithrani and Chan, 2007; Lu et al., 2009; Osaki et al., 2004).
It is important for better understanding of the NPs toxicokinetics. To improve the understanding of the toxicokinetics of NPs, the present study developed the PBPK model for polyethylene glycol-coated (pegylated) AuNPs applied in mice and humans. The model has considered the effect of endocytosis behaviors and the effects of particle size on the biodistribution and accumulation of AuNPs in various tissues. This study would provide a sound basis for tissue biodistribution of different size NPs in mice, especially for human.
Engineered NPs are widely used in diverse areas, including drug delivery systems, medical devices, food products, and consumer products. Recently, gold nanoparticles (AuNPs) become the attractive candidates for imaging, diagnostics, and therapies because of their relatively simple generation, ease of surface modification and biocompatibility (Daniel and Astruc, 2004; Kim et al., 2005).
Particle mass concentration is always applied to describe the biodistribution and pharmacokinetic of NPs (Cho
Model application: prediction of biodistribution of AuNPs
Fig. 5 displays the model predicted result of different size AuNPs (13,15,20,40,80,100 nm) in the plasma, liver, spleen, kidneys, lungs and brain of healthy mice after intravenous injection (iv) particle number with 1.0 × 1012/kg. The study found that AuNPs accumulated primarily in the liver and spleen, and the results showed a much lower accumulation in brain. Moreover, smaller AuNPs showed more widespread organ distribution, higher accumulation, and longer retention time (exception in the
This is the first study, to our best knowledge, to predict biodistribution of different size pegylated AuNPs after intravenous injection both in mice and human by considering the endocytosis both in the plasma and the tissues. The article was designed for intravenously administered NPs, the results can also be considered useful for other routes of exposure (e.g. inhalation, oral or dermal exposure). NPs endocytosis mechanism was first incorporated into a developed PBPK model and consideredthe
This is the first systematical study to predict biodistribution of different size pegylated AuNPs after intravenous injection both in mice and human. The PBPK model has considered endocytosis both in the tissues and the blood. As particle size plays a key role in their interaction with the biological system, understanding the effect of particle size on the biodistribution and accumulation is necessary. The results revealed that pegylated AuNPs in various organs are size-dependent. The results
Declaration of competing interest
The authors declare no conflict of interest.
This work was supported by the National Natural Science Foundation of China (51576214 and 21777193) and the Key Research and Development Program of Hunan Province, China (2017SK2091).
- G. Sonavane et al.
Biodistribution of colloidal gold nanoparticles after intravenous administration: effect of particle size
Colloids Surf. B: Biointerfaces
- E.A. Smith et al.
Environmental degradation of polyacrylamides
Ecotoxicol. Environ. Saf.
- E.A. Smith et al.
Environmental degradation of polyacrylamides. 1. Effects of artificial environmental conditions: temperature, light, and ph
Ecotoxicol. Environ. Saf.
- A. Seaton et al.
Particulate air pollution and acute health effects
- D. Lankveld et al.
The kinetics of the tissue distribution of silver nanoparticles of different sizes
- S. Hirn et al.
Particle size-dependent and surface charge-dependent biodistribution of gold nanoparticles after intravenous administration
Eur. J. Pharm. Biopharm.
- W.I. Hagens et al.
What do we (need to) know about the kinetic properties of nanoparticles in the body?
Regul. Toxicol. Pharmacol.
- Q. Deng et al.
Particle deposition in the human lung: health implications of particulate matter from different sources
- Q. Deng et al.
Particle deposition in tracheobronchial airways of an infant, child and adult
Sci. Total Environ.
- Q. Deng et al.
Parental stress and air pollution increase childhood asthma in china
Particle size-dependent organ distribution of gold nanoparticles after intravenous administration
Size-dependent tissue kinetics of peg-coated gold nanoparticles
Toxicol. Appl. Pharmacol.
The impact of size on tissue distribution and elimination by single intravenous injection of silica nanoparticles
Acute toxicity and pharmacokinetics of 13 nm-sized peg-coated gold nanoparticles
Toxicol. Appl. Pharmacol.
Size-dependent proinflammatory effects of ultrafine polystyrene particles: a role for surface area and oxidative stress in the enhanced activity of ultrafines
Toxicol. Appl. Pharmacol.
Significant effect of size on the in vivo biodistribution of gold composite nanodevices in mouse tumor models
The effect of nanoparticle size, shape, and surface chemistry on biological systems
Annu. Rev. Biomed. Eng.
A physiologically based pharmacokinetic model for ionic silver and silver nanoparticles
Int. J. Nanomedicine
Using physiologically based pharmacokinetic (pbpk) modeling for dietary risk assessment of titanium dioxide (tio2) nanoparticles
Exposure assessment for estimation of the global burden of disease attributable to outdoor air pollution
Environ. Sci. Technol.
Elucidating the mechanism of cellular uptake and removal of protein-coated gold nanoparticles of different sizes and shapes
Determining the size and shape dependence of gold nanoparticle uptake into mammalian cells
Gold nanoparticles: assembly, supramolecular chemistry, quantum-size-related properties, and applications toward biology, catalysis, and nanotechnology
Pulmonary retention of ultrafine and fine particles in rats
Am. J. Respir. Cell Mol. Biol.
In vivo biodistribution and urinary excretion of mesoporous silica nanoparticles: effects of particle size and pegylation
Noninvasive detection of macrophages using a nanoparticulate contrast agent for computed tomography
Ultrafine particle transport and deposition in a large scale 17-generation lung model
Characterization of size, surface charge, and agglomeration state of nanoparticle dispersions for toxicological studies
J. Nanopart. Res.
Cited by (11)
Modelling the biodistribution of inhaled gold nanoparticles in rats with interspecies extrapolation to humans
2022, Toxicology and Applied Pharmacology
Citation Excerpt :
It is assumed that the limiting mechanism for nanoparticle exchange between tissue and capillary is diffusion through the tissue membrane, as in the case of (Lin et al., 2016a). The sequestered sub-compartment is used to simulate the uptake and release from phagocytic cells in the respective organ(Deng et al., 2019; Yuan et al., 2019). Phagocytic cells are used as an operational term in PBK models to describe cells that can engulf NPs such as macrophages(Lin et al., 2016b), reticuloendothelial system cells (Cho et al., 2010), mononuclear phagocyte cells(Bachler et al., 2015b), liver Kupffer and kidney mesangial cells(van Furth et al., 1972).
The increasing intentional and non-intentional exposure to nanoparticles (NPs) has raised the interest concerning their fate and biodistribution in the body of animals and humans after inhalation. In this context, Physiologically Based (pharmaco)Kinetic (PBK) modelling has emerged as an in silico approach that simulates the biodistribution kinetics of NPs in the body using mathematical equations. Due to restrictions in data availability, such models are first developed for rats or mice. In this work, we present the interspecies extrapolation of a PBK model initially developed for rats, in order to estimate the biodistribution of inhaled gold NPs (AuNPs) in humans. The extrapolation framework is validated by comparing the model results with experimental data from a clinical study performed on humans for inhaled AuNPs of two different sizes, namely 34nm and 4nm. The novelty of this work lies in the extrapolation of a PBK model for inhaled AuNPs to humans and comparison with clinical data. The extrapolated model is in good agreement with the experimental data, and provides insights for the mechanisms of inhaled AuNP translocation to the blood circulation, after inhalation. Finally, the biodistribution of the two sizes of AuNPs in the human body after 28days post-exposure is estimated by the model and discussed.
Potential human health effects following exposure to nano- and microplastics, lessons learned from nanomaterials
2022, Present Knowledge in Food Safety: A Risk-Based Approach through the Food Chain
A substantial part of the plastic produced worldwide ends up in the environment and degrades into nano- and microplastics. The particles are ubiquitously present in the air and enter the food production chain as contaminants. Ingestion of nano- and microplastics present in food and drinking water, or those present in swallowed lung mucus that contain trapped particles, represent the main route of human exposure. Yet much remains to be studied on the intestinal uptake by humans and the potential this exposure has to result in adverse health effects. Here we review the current knowledge and relate this to lessons learned from the field of nanotoxicology. We discuss how in vitro and in silico approaches can be used to support the risk assessment of nano- and microplastics.
Physiologically Based Pharmacokinetic Modeling of Nanoparticle Biodistribution: A Review of Existing Models, Simulation Software, and Data Analysis Tools
2022, International Journal of Molecular Sciences
Modeling of clearance, retention, and translocation of inhaled gold nanoparticles in rats
2022, Inhalation Toxicology
Recommended articles (6)
Advances in experimental and mechanistic computational models to understand pulmonary exposure to inhaled drugs
European Journal of Pharmaceutical Sciences, Volume 113, 2018, pp. 41-52
Prediction of local exposure following inhalation of a locally acting pulmonary drug is central to the successful development of novel inhaled medicines, as well as generic equivalents. This work provides a comprehensive review of the state of the art with respect to multiscale computer models designed to provide a mechanistic prediction of local and systemic drug exposure following inhalation. The availability and quality of underpinning in vivo and in vitro data informing the computer based models is also considered.
Mechanistic modelling of local exposure has the potential to speed up and improve the chances of successful inhaled API and product development. Although there are examples in the literature where this type of modelling has been used to understand and explain local and systemic exposure, there are two main barriers to more widespread use. There is a lack of generally recognised commercially available computational models that incorporate mechanistic modelling of regional lung particle deposition and drug disposition processes to simulate free tissue drug concentration. There is also a need for physiologically relevant, good quality experimental data to inform such modelling. For example, there are no standardized experimental methods to characterize the dissolution of solid drug in the lungs or measure airway permeability.
Hence, the successful application of mechanistic computer models to understand local exposure after inhalation and support product development and regulatory applications hinges on: (i) establishing reliable, bio-relevant means to acquire experimental data, and (ii) developing proven mechanistic computer models that combine: a mechanistic model of aerosol deposition and post-deposition processes in physiologically-based pharmacokinetic models that predict free local tissue concentrations.
Invivo distribution of nanosilver in the rat: The role of ions and de novo-formed secondary particles
Food and Chemical Toxicology, Volume 97, 2016, pp. 327-335
Silver nanoparticles are advertised as antimicrobial agents in a wide range of products. The majority of available studies suggest that silver nanoparticle toxicity is mainly caused by silver ions released from the particles. However, it remains challenging to distinguish between the effect of silver nanoparticles and silver ions. Here we used a combination of a short-term invivo study in rats and an in silico-based toxicokinetic model to determine tissue distribution of administered ionic and nanoparticulate silver, and to estimate mixture ratios of the different silver species, namely primary nanoparticles, ions and secondary particles. Our data indicate that silver nanoparticles and silver ions are not or only marginally bioavailable after oral ingestion of a single, non-toxic dose. Experimental data on organ distribution after intravenous injection were accurately reflected by the predictions of the in silico model. Toxicokinetic modeling suggests systemic distribution of a major proportion of the injected ionic silver as de novo formed secondary nanoparticles, and the presence of such particles was proven by electron microscopy. The observation that silver ions form secondary particles, underlines the difficulties in distinguishing between particle- and ion-dependent effects of silver nanoparticles.
Health effects of physical activity as predicted by particle deposition in the human respiratory tract
Science of The Total Environment, Volume 657, 2019, pp. 819-826
Although health benefits of physical activity are well known, the risk of physical activity in polluted air is unclear. Our objective is to investigate health effects resulting from physical activity in polluted air by looking at particle deposition in human tracheobronchial (TB) airways. Airflow and particle deposition in TB airways were investigated using a computational fluid dynamics (CFD) method. We chose three regional airways: upper (G3–G5), central (G9–G11) and lower (G14–G16). Physical activity was described by breathing rate at the mouth, for three levels of activity: sedentary (15 l/min), moderate (30 l/min) and intense (60 l/min). We found that particle deposition was strongly affected by physical activity. Particles are deposited in greater number in the lower airways (G14–G16) during sedentary activity, more in the upper airways (G3–G5) during intense activity, and uniformly in the airways during moderate activity. The difference in the deposition pattern was due to the reason that physical activity increased the airflow which increased inertial impaction. Our modeling of particle deposition in the human respiratory airways shows that there are different health effects for different activity levels: sedentary activity leads to chronic health effects, intense activity results in acute effects, and moderate activity minimizes the adverse health effects of physical activity in polluted air.
A two-step model of TiO2 nanoparticle toxicity in human liver tissue
Toxicology and Applied Pharmacology, Volume 334, 2017, pp. 47-54
We examine the toxicity of titanium dioxide (TiO2) nanoparticles on human liver through a two-step approach, including a physiologically-based pharmacokinetic (PBPK) model and a cell-response model. The PBPK model predicts the bio-distribution of nanoparticles that remain in the human body after exposure, with special attention to their accumulation in liver tissue. The cell-response model predicts liver cell death as a consequence of the accumulated TiO2 nanoparticles by considering cell fate dynamics through the interplay between cellular uptake of the nanoparticles and their dilution due to cell division. The results suggest that tissue damage from a low nanoparticle dose is negligible due to renewal cell division, but for higher doses larger fractions of cells must participate in the cell cycle to recover the original tissue mass. By combining the two models, it becomes possible to explain the liver cell viability and cell death after TiO2 nanoparticle exposure.
Development and intercomparison of single and multicompartment physiologically-based toxicokinetic models: Implications for model selection and tiered modeling frameworks
Environment International, Volume 154, 2021, Article 106557
This study describes the development and intercomparison of generic physiologically-based toxicokinetic (PBTK) models for humans comprised of internally consistent one-compartment (1Co-) and multi-compartment (MCo-) implementations (G-PBTK). The G-PBTK models were parameterized for an adult male (70kg) using common physiological parameters and in vitro biotransformation rate estimates and subsequently evaluated using independent concentration versus time data (n=6) and total elimination half-lives (n=15) for diverse organic chemicals. The model performance is acceptable considering the inherent uncertainty in the biotransformation rate data and the absence of model calibration. The G-PBTK model was then applied using hypothetical neutral organics, acidic ionizable organics and basic ionizable organics (IOCs) to identify combinations of partitioning properties and biotransformation rates leading to substantial discrepancies between 1Co- and MCo-PBTK calculations for whole body concentrations and half-lives. The 1Co- and MCo-PBTK model calculations for key toxicokinetic parameters are broadly consistent unless biotransformation is rapid (e.g., half-life less than five days). When half-lives are relatively short, discrepancies are greatest for the neutral organics and least for the acidic IOCs which follows from the estimated volumes of distribution (e.g., VDSS=9.6–15.4L/kg vs 0.3–1.6L/kg for the neutral and acidic compounds respectively) and the related approach to internal chemical equilibrium. The model intercomparisons demonstrate that 1Co-PBTK models can be applied with confidence to many exposure scenarios, particularly those focused on chronic or repeat exposures and for prioritization and screening-level decision contexts. However, MCo-PBTK models may be necessary in certain contexts, particularly for intermittent, short-term and highly variable exposures. A key recommendation to guide model selection and the development of tiered PBTK modeling frameworks that emerges from this study is the need to harmonize models with respect to parameterization and process descriptions to the greatest extent possible when proceeding from the application of simpler to more complex modeling tools as part of chemical assessment activities.
Bayesian evaluation of a physiologically-based pharmacokinetic (PBPK) model of long-term kinetics of metal nanoparticles in rats
Regulatory Toxicology and Pharmacology, Volume 73, Issue 1, 2015, pp. 151-163
Biomathematical modeling quantitatively describes the disposition of metal nanoparticles in lungs and other organs of rats. In a preliminary model, adjustable parameters were calibrated to each of three data sets using a deterministic approach, with optimal values varying among the different data sets. In the current effort, Bayesian population analysis using Markov chain Monte Carlo (MCMC) simulation was used to recalibrate the model while improving assessments of parameter variability and uncertainty. The previously-developed model structure and some physiological parameter values were modified to improve physiological realism. The data from one of the three previously-identified studies and from two other studies were used for model calibration. The data from the one study that adequately characterized mass balance were used to generate parameter distributions. When data from a second study of the same nanomaterial (iridium) were added, the level of agreement was still acceptable. Addition of another data set (for silver nanoparticles) led to substantially lower precision in parameter estimates and large discrepancies between the model predictions and experimental data for silver nanoparticles. Additional toxicokinetic data are needed to further evaluate the model structure and performance and to reduce uncertainty in the kinetic processes governing invivo disposition of metal nanoparticles.
© 2019 Elsevier Inc. All rights reserved.