Toxicokinetic Modeling Challenges for Aquatic Nanotoxicology

Chen, Wei Yu

doi:10.3389/fmars.2015.00114

Cited by 8 publications

(5 citation statements)

References 38 publications

(56 reference statements)

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“…Unfortunately, the manner in which they assessed the levels of these NMs could not differentiate between the accumulated species (ionic or particulate) in these various organs. Although these examples confirm the applicability of PBPK modeling for the prediction of bioaccumulation in experimental animals, there is as yet no indication for its applicability to aquatic organisms due to insufficient physiological and physicochemical parameters (Chen 2016).…”

Section: Applicability Of Kinetic Models To Predict the Bioaccumulatimentioning

confidence: 94%

“…In the model of Silva et al (2017), the simulated pharmacokinetics for SPIONPs were also in good agreement with the in vivo experimental data, with higher accumulation predicted in the spleen, lung, and liver. Although these examples confirm the applicability of PBPK modeling for the prediction of bioaccumulation in experimental animals, there is as yet no indication for its applicability to aquatic organisms due to insufficient physiological and physicochemical parameters (Chen 2016). Although these examples confirm the applicability of PBPK modeling for the prediction of bioaccumulation in experimental animals, there is as yet no indication for its applicability to aquatic organisms due to insufficient physiological and physicochemical parameters (Chen 2016).…”

Section: Applicability Of Kinetic Models To Predict the Bioaccumulatimentioning

confidence: 95%

See 1 more Smart Citation

An assessment of applicability of existing approaches to predicting the bioaccumulation of conventional substances in nanomaterials

Utembe

Wepener

Yu³

et al. 2018

Enviro Toxic and Chemistry

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The experimental determination of bioaccumulation is challenging, and a number of approaches have been developed for its prediction. It is important to assess the applicability of these predictive approaches to nanomaterials (NMs), which have been shown to bioaccumulate. The octanol/water partition coefficient (K ) may not be applicable to some NMs that are not found in either the octanol or water phases but rather are found at the interface. Thus the K values obtained for certain NMs are shown not to correlate well with the experimentally determined bioaccumulation. Implementation of quantitative structure-activity relationships (QSARs) for NMs is also challenging because the bioaccumulation of NMs depends on nano-specific properties such as shape, size, and surface area. Thus there is a need to develop new QSAR models based on these new nanodescriptors; current efforts appear to focus on digital processing of NM images as well as the conversion of surface chemistry parameters into adsorption indices. Water solubility can be used as a screening tool for the exclusion of NMs with short half-lives. Adaptation of fugacity/aquivalence models, which include physicochemical properties, may give some insights into the bioaccumulation potential of NMs, especially with the addition of a biota component. The use of kinetic models, including physiologically based pharmacokinetic models, appears to be the most suitable approach for predicting bioaccumulation of NMs. Furthermore, because bioaccumulation of NMs depends on a number of biotic and abiotic factors, it is important to take these factors into account when one is modeling bioaccumulation and interpreting bioaccumulation results. Environ Toxicol Chem 2018;37:2972-2988. © 2018 SETAC.

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Section: Applicability Of Kinetic Models To Predict the Bioaccumulatimentioning

confidence: 94%

Section: Applicability Of Kinetic Models To Predict the Bioaccumulatimentioning

confidence: 95%

An assessment of applicability of existing approaches to predicting the bioaccumulation of conventional substances in nanomaterials

Utembe

Wepener

Yu³

et al. 2018

Enviro Toxic and Chemistry

View full text Add to dashboard Cite

show abstract

“…However, the design and applications of appropriate PBPK models will also require further understanding on the uptake, elimination, and biodistribution behavior of NMs in specific organisms, which provide certain evidence for the correct establishment of compartments and derivation of kinetics. Due to the lack of physiological and physicochemical parameters, the feasible models describing NM uptake by aquatic organisms need further development. , …”

Section: Modeling Approaches For Predicting the Bioaccumulation Of Na...mentioning

confidence: 99%

Predicting Bioaccumulation of Nanomaterials: Modeling Approaches with Challenges

Zeng,

Lv,

Sun

et al. 2024

Environ. Health

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Understanding the bioaccumulation of nanomaterials (NMs) by organisms is essential in evaluating their potential ecotoxicity. However, the experimental determination of bioaccumulation is substantially challenging, which spawned the development of prediction approaches via establishing models for various NMs. Conventional modeling approaches, such as the biotic ligand model (BLM), partition coefficients, accumulation factor models, and quantitative structure−activity relationship (QSAR) models, were initially used in the application of NMs, aiming to provide a reliable quantitative dose in a resource-saving way. These methods, which are based on the uptake patterns of substances, probably lead to deviated results due to the different uptake behaviors of NMs. In this study, currently developed models to evaluate the bioaccumulation of NMs are critically reviewed, with their feasibilities and limitations being analyzed. In addition, the recently developed machine learning amended models have taken great efforts in realizing biological behaviors of NMs in organisms by providing in silico predictions. Though this data-driven approach has limitations in mechanism exploration, it may give different insights into the bioaccumulation model establishment and critical feature identification.

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“…This suggests that exposure conditions may modulate the accumulation pattern of MNPs in fish and the different types of material may have a bearing on this also. No studies have investigated the systemic distribution of MNPs within tissues and organs via the circulation, and information would be essential for setting up physiology-based pharmacokinetic models Chen 2016). Given immune organs are highly vascularized immune organs, they are likely to be exposed to MNPs circulating in the blood.…”

Section: Mnps Interaction With Immune Components Of Epithelial Barrie...mentioning

confidence: 99%

Immunotoxic effects of metal-based nanoparticles in fish and bivalves

et al. 2022

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There is a global research interest in metal nanoparticles (MNPs) due to their diverse applications, rapidly increasing use, and increased presence in the aquatic environment. Currently, most MNPs in the environment are at levels unlikely to cause overt toxicity. Sub-lethal effects that MNPs may induce, notable immunotoxicity, could however have significant health implications. Thus, deciphering the immunological interactions of MNPs with aquatic organisms constitutes a much-needed area of research. In this article, we critically assess the evidence for immunotoxic effects of MNPs in bivalves and fish, as key wildlife sentinels with widely differing ecological niches that are used as models in ecotoxicology. The first part of this review details the properties, fate, and fundamental physicochemical behavior of MNPs in the aquatic ecosystem. We then consider the toxicokinetics of MNP uptake, accumulation, and deposition in fish and bivalves. The main body of the review then focuses on immune reactions in response to MNPs exposure in bivalves and fish illustrating their immunotoxic potential. Finally, we identify major knowledge gaps in our current understanding of the implications of MNPs exposure for immunological functions and the associated health consequences for bivalves and fish, as well as the general lessons learned on the immunotoxic properties of the emerging class of nanoparticulate contaminants in fish and bivalves.

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Toxicokinetic Modeling Challenges for Aquatic Nanotoxicology

Cited by 8 publications

References 38 publications

An assessment of applicability of existing approaches to predicting the bioaccumulation of conventional substances in nanomaterials

An assessment of applicability of existing approaches to predicting the bioaccumulation of conventional substances in nanomaterials

Predicting Bioaccumulation of Nanomaterials: Modeling Approaches with Challenges

Immunotoxic effects of metal-based nanoparticles in fish and bivalves

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