Endocytosis mechanism in physiologically-based pharmacokinetic modeling of nanoparticles

Nano- and microplastic PBK modeling in the context of human exposure and risk assessment

Insufficient data on nano- and microplastics (NMP) hinder robust evaluation of their potential health risks. Methodological disparities and the absence of established toxicity thresholds impede the comparability and practical application of research findings. The diverse attributes of NMP, such as variations in sizes, shapes, and compositions, complicate human health risk assessment. Although probability density functions (PDFs) show promise in capturing this diversity, their integration into risk assessment frameworks is limited. Physiologically based kinetic (PBK) models offer a potential solution to bridge the gap between external exposure and internal dosimetry for risk evaluation. However, the heterogeneity of NMP poses challenges for accurate biodistribution modeling. A literature review, encompassing both experimental and modeling studies, was conducted to examine biodistribution studies of monodisperse micro- and nanoparticles. The literature search in PubMed and Scopus databases yielded 39 studies that met the inclusion criteria. Evaluation criteria were adapted from previous Quality Assurance and Quality Control (QA-QC) studies, best practice guidelines from WHO (2010), OECD guidance (2021), and additional criteria specific to NMP risk assessment. Subsequently, a conceptual framework for a comprehensive NMP-PBK model was developed, addressing the multidimensionality of NMP particles. Parameters for an NMP-PBK model are presented. QA-QC evaluations revealed that most experimental studies scored relatively well (>0) in particle characterizations and environmental settings but fell short in criteria application for biodistribution modeling. The evaluation of modeling studies revealed that information regarding the model type and allometric scaling requires improvement. Three potential applications of PDFs in PBK modeling of NMP are identified: capturing the multidimensionality of the NMP continuum, quantifying the probabilistic definition of external exposure, and calculating the bio-accessibility fraction of NMP in the human body. A framework for an NMP-PBK model is proposed, integrating PDFs to enhance the assessment of NMP's impact on human health.

Computational Nanotoxicology Models for Environmental Risk Assessment of Engineered Nanomaterials

Although engineered nanomaterials (ENMs) have tremendous potential to generate technological benefits in numerous sectors, uncertainty on the risks of ENMs for human health and the environment may impede the advancement of novel materials. Traditionally, the risks of ENMs can be evaluated by experimental methods such as environmental field monitoring and animal-based toxicity testing. However, it is time-consuming, expensive, and impractical to evaluate the risk of the increasingly large number of ENMs with the experimental methods. On the contrary, with the advancement of artificial intelligence and machine learning, in silico methods have recently received more attention in the risk assessment of ENMs. This review discusses the key progress of computational nanotoxicology models for assessing the risks of ENMs, including material flow analysis models, multimedia environmental models, physiologically based toxicokinetics models, quantitative nanostructure-activity relationships, and meta-analysis. Several challenges are identified and a perspective is provided regarding how the challenges can be addressed.

An updated overview of some factors that influence the biological effects of nanoparticles

Nanoparticles (NPs) can be extremely effective in the early diagnosis and treatment of cancer due to their properties. The nanotechnology industry is developing rapidly. The number of multifunctional NPs has increased in the market and hundreds of NPs are in various stages of preclinical and clinical development. Thus, the mechanism underlying the effects of NPs on biological systems has received much attention. After NPs enter the body, they interact with plasma proteins, tumour cell receptors, and small biological molecules. This interaction is closely related to the size, shape, chemical composition and surface modification properties of NPs. In this review, the effects of the size, shape, chemical composition and surface modification of NPs on the biological effects of NPs were summarised, including the mechanism through which NPs enter cells, the resulting oxidative stress response, and the interaction with proteins. This review of the biological effects of NPs can not only provide theoretical support for the preparation of safer and more efficient NPs but also lay the foundation for their clinical application.

Physiologically-Based Kinetic Modeling of Intravenously Administered Gold (Au) Nanoparticles

Physiologically-based kinetic (PBK) modeling is a valuable tool to understand the kinetics of nanoparticles (NPs) in vivo. However, estimating PBK parameters remains challenging and commonly requires animal studies. To develop predictive models to estimate PBK parameter values based on NP characteristics, a database containing PBK parameter values and corresponding NP characteristics is needed. As a first step toward this objective, this study estimates PBK parameters for gold NPs (AuNPs) and provides a comparison of two different NPs. Two animal experiments are conducted in which varying doses of AuNPs attached with polyethylene glycol (PEG) are administered intravenously to rats. The resulting Au concentrations are used to estimate PBK model parameters. The parameters are compared with PBK parameters previously estimated for poly(alkyl cyanoacrylate) NPs loaded with cabazitaxel and for LipImage 815. This study shows that a small initial database of PBK parameters collected for three NPs is already sufficient to formulate new hypotheses on NP characteristics that may be predictive of PBK parameter values. Further research should focus on developing a larger database and on developing quantitative models to predict PBK parameter values.

Integration of In Vitro and In Vivo Models to Predict Cellular and Tissue Dosimetry of Nanomaterials Using Physiologically Based Pharmacokinetic Modeling

Nanomaterials (NMs) have been increasingly used in a number of areas, including consumer products and nanomedicine. Target tissue dosimetry is important in the evaluation of safety, efficacy, and potential toxicity of NMs. Current evaluation of NM efficacy and safety involves the time-consuming collection of pharmacokinetic and toxicity data in animals and is usually completed one material at a time. This traditional approach no longer meets the demand of the explosive growth of NM-based products. There is an emerging need to develop methods that can help design safe and effective NMs in an efficient manner. In this review article, we critically evaluate existing studies on in vivo pharmacokinetic properties, in vitro cellular uptake and release and kinetic modeling, and whole-body physiologically based pharmacokinetic (PBPK) modeling studies of different NMs. Methods on how to simulate in vitro cellular uptake and release kinetics and how to extrapolate cellular and tissue dosimetry of NMs from in vitro to in vivo via PBPK modeling are discussed. We also share our perspectives on the current challenges and future directions of in vivo pharmacokinetic studies, in vitro cellular uptake and kinetic modeling, and whole-body PBPK modeling studies for NMs. Finally, we propose a nanomaterial in vitro to in vivo extrapolation via physiologically based pharmacokinetic modeling (Nano-IVIVE-PBPK) framework for high-throughput screening of target cellular and tissue dosimetry as well as potential toxicity of different NMs in order to meet the demand of efficient evaluation of the safety, efficacy, and potential toxicity of a rapidly increasing number of NM-based products.

Modelling the biodistribution of inhaled gold nanoparticles in rats with interspecies extrapolation to humans

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 34 nm and 4 nm. 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 28 days post-exposure is estimated by the model and discussed.

Physiologically Based Pharmacokinetic Modeling of Nanoparticle Biodistribution: A Review of Existing Models, Simulation Software, and Data Analysis Tools

Cancer treatment and pharmaceutical development require targeted treatment and less toxic therapeutic intervention to achieve real progress against this disease. In this scenario, nanomedicine emerged as a reliable tool to improve drug pharmacokinetics and to translate to the clinical biologics based on large molecules. However, the ability of our body to recognize foreign objects together with carrier transport heterogeneity derived from the combination of particle physical and chemical properties, payload and surface modification, make the designing of effective carriers very difficult. In this scenario, physiologically based pharmacokinetic modeling can help to design the particles and eventually predict their ability to reach the target and treat the tumor. This effort is performed by scientists with specific expertise and skills and familiarity with artificial intelligence tools such as advanced software that are not usually in the “cords” of traditional medical or material researchers. The goal of this review was to highlight the advantages that computational modeling could provide to nanomedicine and bring together scientists with different background by portraying in the most simple way the work of computational developers through the description of the tools that they use to predict nanoparticle transport and tumor targeting in our body.

Modeling of clearance, retention, and translocation of inhaled gold nanoparticles in rats

Objective: The increasing exposure to gold nanoparticles (AuNPs), due to their wide range of applications, has led to the need for thorough understanding of their biodistribution, following exposure. The objective of this paper is to develop a PBK model in order to study the clearance, retention and translocation of inhaled gold nanoparticles in rats, providing a basis for the understanding of the absorption, distribution, metabolism and elimination (ADME) mechanisms of AuNPs in various organs.Materials and methods: A rat PBK computational model was developed, connected to a detailed respiratory model, including the olfactory, tracheobronchial, and alveolar regions. This model was coupled with a Multiple Path Particle Dosimetry (MPPD) model to appropriately simulate the exposure to AuNPs. Three existing in vivo experimental datasets from scientific literature for the biodistribution of inhaled AuNPs for different AuNP sizes and exposure scenarios were utilized for model calibration and validation.Results and Discussion: The model was calibrated using two individual datasets for nose only inhaled and intratracheally instilled AuNPs, while an independent dataset for nose only inhaled AuNPs was used as external validation. The overall fitting over the three datasets was proved acceptable as shown by the relevant statistical metrics. The influence of several physiological parameters is also studied via a sensitivity analysis, providing useful insights into the mechanisms of NP pharmacokinetics. The key aspects of the inhaled AuNPs biodistribution are discussed, revealing the key mechanisms for the AuNPs absorption routes, the AuNP uptake by secondary organs and the influence of the AuNP size on the translocation from the lungs to blood circulation.Conclusions: The model results together with the model sensitivity analysis clarified the key mechanisms for the inhaled AuNPs biodistribution to secondary organs. It was observed that nose-only inhaled AuNPs of smaller size can enter the blood circulation through secondary routes, such as absorption through the gastrointestinal (GI) lumen, showing that such translocations should not be underestimated in biodistribution modelling. Finally, the computational framework presented in this study can be used as a basis for a more wide investigation of inhaled nanoparticles biodistribution, including interspecies extrapolation of the resulting PBK model for the inhalation and subsequent biodistribution of AuNPs in humans.

DNA Logic Nanodevices for Real-Time Monitoring of ATP in Lysosomes

DNA logic nanodevices have prospects in molecular recognitions but still face challenges in achieving DNA computation-controlled regulation in specific compartments of living cells. By incorporating the i-motif sequence and ATP aptamers into a Y-shaped DNA (Y-DNA) structure, and applying gold nanoparticles (AuNPs) as the transporting carrier, herein we present a new type of DNA logic nanodevices to monitor the ATP levels in lysosomes of living cells. Triple energy transfers including dual fluorescent resonance energy transfers (FRETs) and a nanometal surface energy transfer (NSET) occurred in the DNA logic nanodevices. It was identified that the proposed nanodevices perform an AND logic operation to output FRET signals only when an endogenous proton and ATP simultaneously exist in the cellular microenvironment. Owing to the use of the i-motif sequence, the nanodevices have lysosome-recognizing capacity without causing alkalization of the acidic organelle, making DNA computation-controlled regulation at the level of cellular organelles achievable. These DNA logic nanodevices show high application prospects in lysosome-related cellular function and disease treatment.

Nanotherapeutics and nanotheragnostics for cancers: properties, pharmacokinetics, biopharmaceutics, and biosafety

With the worldwide increasing rate of chronic diseases, such as cancer, the development of novel techniques to improve the efficacy of therapeutic agents is highly demanded. Nanoparticles are especially well suited to encapsulate drugs and other therapeutic agents, bringing additional advantages, such as less frequent dosage requirements, reduced side effects due to specific targeting, and therefore increased patient compliance. However, with the increasing use of nanoparticles and their recent launch on the pharmaceutical market it is important to achieve high quality control of these advanced systems. In this review, we discuss the properties of different nanoparticles, the pharmacokinetics, the biosafety issues of concern, and conclude with novel nanotherapeutics and nanotheragnostics for cancer drug delivery.

Current Approaches and Techniques in Physiologically Based Pharmacokinetic (PBPK) Modelling of Nanomaterials

There have been efforts to develop physiologically based pharmacokinetic (PBPK) models for nanomaterials (NMs). Since NMs have quite different kinetic behaviors, the applicability of the approaches and techniques that are utilized in current PBPK models for NMs is warranted. Most PBPK models simulate a size-independent endocytosis from tissues or blood. In the lungs, dosimetry and the air-liquid interface (ALI) models have sometimes been used to estimate NM deposition and translocation into the circulatory system. In the gastrointestinal (GI) tract, kinetics data are needed for mechanistic understanding of NM behavior as well as their absorption through GI mucus and their subsequent hepatobiliary excretion into feces. Following absorption, permeability (P_t) and partition coefficients (PCs) are needed to simulate partitioning from the circulatory system into various organs. Furthermore, mechanistic modelling of organ- and species-specific NM corona formation is in its infancy. More recently, some PBPK models have included the mononuclear phagocyte system (MPS). Most notably, dissolution, a key elimination process for NMs, is only empirically added in some PBPK models. Nevertheless, despite the many challenges still present, there have been great advances in the development and application of PBPK models for hazard assessment and risk assessment of NMs.