A recent review highlights the complexities of nanoparticle behaviour in the body and emphasises the need for physiologically based pharmacokinetic (PBPK) models to better predict their transport and elimination. Insufficient data on kinetic properties of nanoparticles hinder the effective use of PBPK models, particularly regarding the interaction of nanoparticles with the mononuclear phagocyte system (MPS) and the lymphatic circulation. Improving the associated model parameters requires more relevant data, for example, through in vitro testing, and exploring machine learning techniques to establish quantitative relationships between nanoparticle properties and key kinetic parameters.

Understanding nanoparticle behaviour in the body

A recent literature review by researchers at China Medical University in Shenyang highlights the complexities surrounding the behaviour of nanoparticles in vivo and the limitations of current modelling techniques. The review emphasises the potential of physiologically based pharmacokinetic (PBPK) models to more accurately predict the transport and elimination of nanoparticles in biological systems.

The difference between nanoparticles and small-molecule drugs

Nanoparticles display distinct behaviours compared to small-molecule drugs after administration, particularly with their interaction with the body’s mononuclear phagocyte system (MPS) and lymphatic circulation. The MPS plays a crucial role in removing harmful substances, including nanoparticles, from various tissues and the bloodstream. The review advocates for PBPK models to include detailed compartments that represent these processes to enhance their predictive capabilities.

Model validation

For PBPK models to be routinely used in nanoparticle research, a validation process is needed to ensure that the models accurately reflect relevant physiological processes and that their predictions align with observed data. However, model validation presents a significant challenge, as many PBPK models for nanoparticles lack sufficient data or fail to accurately predict the behaviour of different nanoparticle types. Among the 61 models reviewed, only 40 underwent external validation, of which 8 did not meet all established criteria.

Remaining challenges

Challenges continue to exist in developing quantitative relationships between key nanoparticle properties - such as size, shape, and surface characteristics - and critical kinetic parameters needed for effective modelling. Furthermore, the effects of lymphatic circulation and protein corona formation are often inadequately represented in current models, which hinders interspecies extrapolation from animals to humans. To improve the accuracy and applicability of PBPK models for nanoparticles, the article suggests that standardised experimental protocols and more data are needed.

Reflection by RIVM

Understanding how nanoparticles and other substances behave in the body is an essential step for assessing their potential adverse health effects. Pharmaceutical research increasingly uses PBPK models to obtain such information. Similarly, there is a growing interest in using physiologically based kinetic (PBK) models for regulatory safety assessments of conventional chemicals.
However, significant knowledge gaps remain in making PBK models applicable in regulatory settings. While the OECD guidance on the characterisation, validation and reporting of PBK models provides several considerations on the development of PBK models for conventional chemicals, it does not address the specific challenges related to nanoparticles, such as estimating model parameters related to the MPS.
The review article showed that MPS parameters have a significant impact on the in vivo kinetic properties of nanoparticles, highlighting the importance of accurately estimating these parameters. Although various methods have been proposed to estimate MPS uptake rates, they heavily rely on extensive in vivo kinetic data. Further research should ideally focus on new and better approaches to predict (MPS-related) model parameters.
In vitro models for quantitatively estimating MPS uptake and release rates are at various stages of development. For transport across the intestinal barrier, the OECD guidance document on in vitro testing for intestinal fate of orally ingested nanomaterials presents promising in vitro models. Their applicability for generating quantitative data to parametrise PBK models requires further investigation. Another research direction could be to develop new in silico methods that establish quantitative relationships between nanoparticle properties and key parameters. Such relationships could enhance our understanding of nanoparticle behaviour in vivo and help develop new in silico methods for estimating model parameters specific to a given nanomaterial. It would be interesting to explore the potential of machine learning in deriving these quantitative relationships.
Another challenge is the lack of understanding of how to incorporate the effects of lymphatic circulation and protein corona formation into PBK models. These challenges are specific to nanoparticles and limit the applicability of PBK models in this context. Addressing this challenge will require relevant data, which could be obtained through in vitro testing.