Biodistribution and Physiologically-Based Pharmacokinetic Modeling of Gold Nanoparticles in Mice with Interspecies Extrapolation

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.

PBPK Modeling as an Alternative Method of Interspecies Extrapolation that Reduces the Use of Animals: A Systematic Review

INTRODUCTION

Physiologically based pharmacokinetic (PBPK) modeling is a computational approach that simulates the anatomical structure of the studied species and presents the organs and tissues as compartments interconnected by arterial and venous blood flows.

AIM

The aim of this systematic review was to analyze the published articles focused on the development of PBPK models for interspecies extrapolation in the disposition of drugs and health risk assessment, presenting to this modeling an alternative to reduce the use of animals.

METHODS

For this purpose, a systematic search was performed in PubMed using the following search terms: "PBPK" and "Interspecies extrapolation". The revision was performed according to PRISMA guidelines.

RESULTS

In the analysis of the articles, it was found that rats and mice are the most commonly used animal models in the PBPK models; however, most of the physiological and physicochemical information used in the reviewed studies were obtained from previous publications. Additionally, most of the PBPK models were developed to extrapolate pharmacokinetic parameters to humans and the main application of the models was for toxicity testing.

CONCLUSION

PBPK modeling is an alternative that allows the integration of in vitro and in silico data as well as parameters reported in the literature to predict the pharmacokinetics of chemical substances, reducing in large quantity the use of animals that are required in traditional studies.

A physiologically-based pharmacokinetic model for predicting doxorubicin disposition in multiple tissue levels and quantitative toxicity assessment

Doxorubicin is a widely-used chemotherapeutic drug, however its high toxicity poses a significant challenge for its clinical use. To address this issue, a physiologically-based pharmacokinetic (PBPK) model was implemented to quantitatively assess doxorubicin toxicity at cellular scale. Due to its unique pharmacokinetic behavior (e.g. high volume of distribution and affinity to extra-plasma tissue compartments), we proposed a modified PBPK model structure and developed the model with multispecies extrapolation to compensate for the limitation of obtaining clinical tissue data. Our model predicted the disposition of doxorubicin in multiple tissues including clinical tissue data with an overall absolute average fold error (AAFE) of 2.12. The model's performance was further validated with 8 clinical datasets in combined with intracellular doxorubicin concentration with an average AAFE of 1.98. To assess the potential cellular toxicity, toxicity levels and area under curve (AUC) were defined for different dosing regimens in toxic and non-toxic scenarios. The cellular concentrations of doxorubicin in multiple organ sites associated with commonly observed adverse effects (AEs) were simulated and calculated the AUC for quantitative assessments. Our findings supported the clinical dosing regimen of 75 mg/m2 with a 21-day interval and suggest that slow infusion and separated single high doses may lower the risk of developing AEs from a cellular level, providing valuable insights for the risk assessment of doxorubicin chemotherapy. In conclusion, our work highlights the potential of PBPK modelling to provide quantitative assessments of cellular toxicity and supports the use of clinical dosing regimens to mitigate the risk of adverse effects.

Gold Nanorods with Mesoporous Silica Shell: A Promising Platform for Cisplatin Delivery

The versatile combination of metal nanoparticles with chemotherapy agents makes designing multifunctional drug delivery systems attractive. In this work, we reported cisplatin's encapsulation and release profile using a mesoporous silica-coated gold nanorods system. Gold nanorods were synthesized by an acidic seed-mediated method in the presence of cetyltrimethylammonium bromide surfactant, and the silica-coated state was obtained by modified Stöber method. The silica shell was modified first with 3-aminopropyltriethoxysilane and then with succinic anhydride to obtain carboxylates groups to improve cisplatin encapsulation. Gold nanorods with an aspect ratio of 3.2 and silica shell thickness of 14.74 nm were obtained, and infrared spectroscopy and ζ potential studies corroborated surface modification with carboxylates groups. On the other hand, cisplatin was encapsulated under optimal conditions with an efficiency of ~58%, and it was released in a controlled manner over 96 h. Furthermore, acidic pH promoted a faster release of 72% cisplatin encapsulated compared to 51% in neutral pH.

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.

Application of Computing as a High-Practicability and -Efficiency Auxiliary Tool in Nanodrugs Discovery

Research and development (R&D) of nanodrugs is a long, complex and uncertain process. Since the 1960s, computing has been used as an auxiliary tool in the field of drug discovery. Many cases have proven the practicability and efficiency of computing in drug discovery. Over the past decade, computing, especially model prediction and molecular simulation, has been gradually applied to nanodrug R&D, providing substantive solutions to many problems. Computing has made important contributions to promoting data-driven decision-making and reducing failure rates and time costs in discovery and development of nanodrugs. However, there are still a few articles to examine, and it is necessary to summarize the development of the research direction. In the review, we summarize application of computing in various stages of nanodrug R&D, including physicochemical properties and biological activities prediction, pharmacokinetics analysis, toxicological assessment and other related applications. Moreover, current challenges and future perspectives of the computing methods are also discussed, with a view to help computing become a high-practicability and -efficiency auxiliary tool in nanodrugs discovery and development.

Nanoparticle biodistribution coefficients: A quantitative approach for understanding the tissue distribution of nanoparticles

The objective of this manuscript is to provide quantitative insights into the tissue distribution of nanoparticles. Published pharmacokinetics of nanoparticles in plasma, tumor and 13 different tissues of mice were collected from literature. A total of 2018 datasets were analyzed and biodistribution of graphene oxide, lipid, polymeric, silica, iron oxide and gold nanoparticles in different tissues was quantitatively characterized using Nanoparticle Biodistribution Coefficients (NBC). It was observed that typically after intravenous administration most of the nanoparticles are accumulated in the liver (NBC = 17.56 %ID/g) and spleen (NBC = 12.1 %ID/g), while other tissues received less than 5 %ID/g. NBC values for kidney, lungs, heart, bones, brain, stomach, intestine, pancreas, skin, muscle and tumor were found to be 3.1 %ID/g, 2.8 %ID/g, 1.8 %ID/g, 0.9 %ID/g, 0.3 %ID/g, 1.2 %ID/g, 1.8 %ID/g, 1.2 %ID/g, 1.0 %ID/g, 0.6 %ID/g and 3.4 %ID/g, respectively. Significant variability in nanoparticle distribution was observed in certain organs such as liver, spleen and lungs. A large fraction of this variability could be explained by accounting for the differences in nanoparticle physicochemical properties such as size and material. A critical overview of published nanoparticle physiologically-based pharmacokinetic (PBPK) models is provided, and limitations in our current knowledge about in vitro and in vivo pharmacokinetics of nanoparticles that restrict the development of robust PBPK models is also discussed. It is hypothesized that robust quantitative assessment of whole-body pharmacokinetics of nanoparticles and development of mathematical models that can predict their disposition can improve the probability of successful clinical translation of these modalities.

Interspecies evaluation of a physiologically based pharmacokinetic model to predict the biodistribution dynamics of dendritic nanoparticles

The exposure of a dendritic nanoparticle and its conjugated active pharmaceutical ingredient (API) was determined in mouse, rat and dog, with the aim of investigating interspecies differences facilitating clinical translation. Plasma area under the curves (AUCs) were found to be dose proportional across species, while dose normalized concentration time course profiles in plasma, liver and spleen were superimposable in mouse, rat and dog. A physiologically based pharmacokinetic (PBPK) model, previously developed for mouse, was evaluated as a suitable framework to prospectively capture concentration dynamics in rat and dog. The PBPK model, parameterized either by considering species-specific physiology or using alternate scaling methods such as allometry, was shown to capture exposure profiles across species. A sensitivity analysis highlighted API systemic clearance as a key parameter influencing released API levels. The PBPK model was utilized to simulate human exposure profiles, which overlaid dose-normalized data from mouse, rat and dog. The consistency in measured interspecies exposures as well as the capability of the PBPK model to simulate observed dynamics support its use as a powerful translational tool.

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.

Insights into the mapping of green synthesis conditions for ZnO nanoparticles and their toxicokinetics

Research on ZnO nanoparticles (NPs) has broad medical applications. However, the green synthesis of ZnO NPs involves a wide range of properties requiring optimization. ZnO NPs show toxicity at lower doses. This toxicity is a function of NP properties and pharmacokinetics. Moreover, NP toxicity and pharmacokinetics are affected by the species type and age of the animals tested. Physiologically based pharmacokinetic (PBPK) modeling offers a mechanistic platform to scrutinize the colligative effect of the interplay between these factors, which reduces the need for in vivo studies. This review provides a guide to choosing green synthesis conditions that result in minimal toxicity using a mechanistic tool, namely PBPK modeling.

Blood-brain barrier crossing using magnetic stimulated nanoparticles

Due to the low permeability and high selectivity of the blood-brain barrier (BBB), existing brain therapeutic technologies are limited by the inefficient BBB crossing of conventional drugs. Magnetic nanoparticles (MNPs) have shown great potential as nano-carriers for efficient BBB crossing under the external static magnetic field (SMF). To quantify the impact of SMF on MNPs' in vivo dynamics towards BBB crossing, we developed a physiologically based pharmacokinetic (PBPK) model for intraperitoneal (IP) injected superparamagnetic iron oxide nanoparticles coated by gold and conjugated with poly (ethylene glycol) (PEG) (SPIO-Au-PEG NPs) in mice. Unlike most reported PBPK models that ignore brain permeability, we first obtained the brain permeabilities with and without SMF by determining the concentration of SPIO-Au-PEG NPs in the cerebral blood and brain tissue. This concentration in the brain was simulated by the advection-diffusion equations and was numerically solved in COMSOL Multiphysics. The results from the PBPK model after incorporating the brain permeability showed a good agreement (regression coefficient R² = 0.848) with the in vivo results, verifying the capability of using the proposed PBPK model to predict the in vivo biodistribution of SPIO-Au-PEG NPs under the exposure to SMF. Furthermore, the in vivo results revealed that the distribution coefficient from blood to brain under the exposure to SMF (4.01%) is slightly better than the control group (3.68%). In addition, the modification of SPIO-Au-PEG NPs with insulin (SPIO-Au-PEG-insulin) showed an improvement of the brain bioavailability by 24.47% in comparison to the non-insulin group. With the SMF stimulation, the brain bioavailability of SPIO-Au-PEG-insulin was further improved by 3.91% compared to the group without SMF. The PBPK model and in vivo validation in this paper lay a solid foundation for future study on non-invasive targeted drug delivery to the brain.

Nanomedicine Ex Machina: Between Model-Informed Development and Artificial Intelligence

Today, a growing number of computational aids and simulations are shaping model-informed drug development. Artificial intelligence, a family of self-learning algorithms, is only the latest emerging trend applied by academic researchers and the pharmaceutical industry. Nanomedicine successfully conquered several niche markets and offers a wide variety of innovative drug delivery strategies. Still, only a small number of patients benefit from these advanced treatments, and the number of data sources is very limited. As a consequence, “big data” approaches are not always feasible and smart combinations of human and artificial intelligence define the research landscape. These methodologies will potentially transform the future of nanomedicine and define new challenges and limitations of machine learning in their development. In our review, we present an overview of modeling and artificial intelligence applications in the development and manufacture of nanomedicines. Also, we elucidate the role of each method as a facilitator of breakthroughs and highlight important limitations.

Physiologically Based Pharmacokinetic (PBPK) Model of Gold Nanoparticle-Based Drug Delivery System for Stavudine Biodistribution

Computational modelling has gained attention for evaluating nanoparticle-based drug delivery systems. Physiologically based pharmacokinetic (PBPK) modelling provides a mechanistic approach for evaluating drug biodistribution. The aim of this work is to develop a specific PBPK model to simulate stavudine biodistribution after the administration of a 40 nm gold nanoparticle-based drug delivery system in rats. The model parameters used have been obtained from literature, in vitro and in vivo studies, and computer optimization. Based on these, the PBPK model was built, and the compartments included were considered as permeability rate-limited tissues. In comparison with stavudine solution, a higher biodistribution of stavudine into HIV reservoirs and the modification of pharmacokinetic parameters such as the mean residence time (MRT) have been observed. These changes are particularly noteworthy in the liver, which presents a higher partition coefficient (from 0.27 to 0.55) and higher MRT (from 1.28 to 5.67 h). Simulated stavudine concentrations successfully describe these changes in the in vivo study results. The average fold error of predicted concentrations after the administration of stavudine-gold nanoparticles was within the 0.5–2-fold error in all of the tissues. Thus, this PBPK model approach may help with the pre-clinical extrapolation to other administration routes or the species of stavudine gold nanoparticles.

Model-Based Assessment of the Contribution of Monocytes and Macrophages to the Pharmacokinetics of Monoclonal Antibodies

PURPOSE

We have hypothesized that a high concentration of circulating monocytes and macrophages may contribute to the fast weight-based clearance of monoclonal antibodies (mAbs) in young children. Exploring this hypothesis, this work uses modeling to clarify the role of monocytes and macrophages in the elimination of mAbs.

METHODS

Leveraging pre-clinical data from mice, a minimal physiologically-based pharmacokinetic model was developed to characterize mAb uptake and FcRn-mediated recycling in circulating monocytes, macrophages, and endothelial cells. The model characterized IgG disposition in complex scenarios of site-specific FcRn deletion and variable endogenous IgG levels. Evaluation was performed for predicting IgG disposition with co-administration of high dose IVIG. A one-at-a-time sensitivity analysis quantified the role of relevant cellular parameters on IgG elimination in various scenarios.

RESULTS

The plasma AUC of mAbs was highly sensitive to endothelial cell parameters, but had near-nil sensitivity to monocyte and macrophage parameters, even in scenarios with 90% loss of FcRn expression/activity. In mice with normal FcRn expression, simulations suggest that less than 2% of an IV dose is eliminated in macrophages, while endothelial cells are predicted to dominate mAb elimination.

CONCLUSIONS

The model suggests that the role of monocytes and macrophages in IgG homeostasis includes extensive uptake and highly efficient FcRn-mediated protection, but not appreciable degradation when FcRn is present. Therefore, it is very unlikely that a high concentration of circulating monocytes can contribute to explaining the fast weight-based clearance of mAbs in very young children, even if FcRn expression/activity was 90% lower in children than in adults.

The Hitchhiker's Guide to Human Therapeutic Nanoparticle Development

Nanomedicine plays an essential role in developing new therapies through novel drug delivery systems, diagnostic and imaging systems, vaccine development, antibacterial tools, and high-throughput screening. One of the most promising drug delivery systems are nanoparticles, which can be designed with various compositions, sizes, shapes, and surface modifications. These nanosystems have improved therapeutic profiles, increased bioavailability, and reduced the toxicity of the product they carry. However, the clinical translation of nanomedicines requires a thorough understanding of their properties to avoid problems with the most questioned aspect of nanosystems: safety. The particular physicochemical properties of nano-drugs lead to the need for additional safety, quality, and efficacy testing. Consequently, challenges arise during the physicochemical characterization, the production process, in vitro characterization, in vivo characterization, and the clinical stages of development of these biopharmaceuticals. The lack of a specific regulatory framework for nanoformulations has caused significant gaps in the requirements needed to be successful during their approval, especially with tests that demonstrate their safety and efficacy. Researchers face many difficulties in establishing evidence to extrapolate results from one level of development to another, for example, from an in vitro demonstration phase to an in vivo demonstration phase. Additional guidance is required to cover the particularities of this type of product, as some challenges in the regulatory framework do not allow for an accurate assessment of NPs with sufficient evidence of clinical success. This work aims to identify current regulatory issues during the implementation of nanoparticle assays and describe the major challenges that researchers have faced when exposing a new formulation. We further reflect on the current regulatory standards required for the approval of these biopharmaceuticals and the requirements demanded by the regulatory agencies. Our work will provide helpful information to improve the success of nanomedicines by compiling the challenges described in the literature that support the development of this novel encapsulation system. We propose a step-by-step approach through the different stages of the development of nanoformulations, from their design to the clinical stage, exemplifying the different challenges and the measures taken by the regulatory agencies to respond to these challenges.

Nanogold-based materials in medicine: from their origins to their future

The properties of gold-based materials have been explored for centuries in several research fields, including medicine. Multiple published production methods for gold nanoparticles (AuNPs) have shown that the physicochemical and optical properties of AuNPs depend on the production method used. These different AuNP properties have allowed exploration of their usefulness in countless distinct biomedical applications over the last few years. Here we present an extensive overview of the most commonly used AuNP production methods, the resulting distinct properties of the AuNPs and the potential application of these AuNPs in diagnostic and therapeutic approaches in biomedicine.

Gold nanostructures as mediators of hyperthermia therapies in breast cancer

Breast cancer is the leading cause of cancer-related deaths among women. Due to the limitations of the current therapeutics, new treatment options are needed. Hyperthermia is a promising approach to improve breast cancer therapy, particularly when combined with chemo and radiotherapy. This area has gained more attention following association with nanotechnology, with the emergence of modalities, such as photothermal therapy (PTT). PTT is a simple, minimally invasive technique that requires a near infrared (NIR) light source and a PTT agent. Gold nanostructures are excellent PTT agents as they offer biocompatibility, versatility, high photothermal conversion efficiency, imaging contrast and an easily-modified surface. In this review, we describe the molecular basis and the current clinical aspects of hyperthermia-based therapies. The emergent area of nanoparticle-induced hyperthermia will be explored, in particular gold nanostructure-mediated PTT, focusing on recent preclinical studies for breast cancer management.

Epigallocatechin-3-Gallate-Loaded Gold Nanoparticles: Preparation and Evaluation of Anticancer Efficacy in Ehrlich Tumor-Bearing Mice

Epigallocatechin-3-gallate (EGCG) is a pleiotropic compound with anticancer, anti-inflammatory, and antioxidant properties. To enhance EGCG anticancer efficacy, it was loaded onto gold nanoparticles (GNPs). EGCG-GNPs were prepared by a simple green synthesis method and were evaluated using different techniques. Hemocompatibility with human blood and in vivo anticancer efficacy in Ehrlich ascites carcinoma-bearing mice were evaluated. EGCG/gold chloride molar ratio had a marked effect on the formation and properties of EGCG-GNPs where well-dispersed spherical nanoparticles were obtained at a molar ratio not more than 0.8:1. The particle size ranged from ~26 to 610 nm. High drug encapsulation efficiency and loading capacity of ~93 and 32%, respectively were obtained. When stored at 4 °C for three months, EGCG-GNPs maintained over 90% of their drug payload and had small changes in their size and zeta potential. They were non-hemolytic and had no deleterious effects on partial thromboplastin time, prothrombin time, and complement protein C3 concentration. EGCG-GNPs had significantly better in vivo anticancer efficacy compared with pristine EGCG as evidenced by smaller tumor volume and weight and higher mice body weight. These results confirm that EGCG-GNPs could serve as an efficient delivery system for EGCG with a good potential to enhance its anticancer efficacy.

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.

Best Practices for Preclinical In Vivo Testing of Cancer Nanomedicines

Significant advances have been made in the development of nanoparticles for cancer treatment in recent years. Despite promising results in preclinical animal models, cancer nanomedicines often fail in clinical trials. This failure rate could be reduced by defining stringent criteria for testing and quality control during the design and development stages, and by performing carefully planned preclinical studies in relevant animal models. This article discusses best practices for the evaluation of nanomedicines in murine tumor models. First, a recommended set of experiments to perform is introduced, including discussion of the types of data to collect during these studies. This is followed by an outline of various tumor models and their clinical relevance. Next, different routes of nanoparticle administration are overviewed, followed by a summary of important controls to include in in vivo studies of nanomedicine. Finally, animal welfare considerations are discussed, and an overview of the steps involved in achieving US Food and Drug Administration approval after animal studies are completed is provided. Researchers should use this report as a guideline for effective preclinical evaluation of cancer nanomedicine. As the community adopts best practices for in vivo testing, the rate of clinical translation of cancer nanomedicines is likely to improve.

Image-guided mathematical modeling for pharmacological evaluation of nanomaterials and monoclonal antibodies

While plasma concentration kinetics has traditionally been the predictor of drug pharmacological effects, it can occasionally fail to represent kinetics at the site of action, particularly for solid tumors. This is especially true in the case of delivery of therapeutic macromolecules (drug-loaded nanomaterials or monoclonal antibodies), which can experience challenges to effective delivery due to particle size-dependent diffusion barriers at the target site. As a result, disparity between therapeutic plasma kinetics and kinetics at the site of action may exist, highlighting the importance of target site concentration kinetics in determining the pharmacodynamic effects of macromolecular therapeutic agents. Assessment of concentration kinetics at the target site has been facilitated by non-invasive in vivo imaging modalities. This allows for visualization and quantification of the whole-body disposition behavior of therapeutics that is essential for a comprehensive understanding of their pharmacokinetics and pharmacodynamics. Quantitative non-invasive imaging can also help guide the development and parameterization of mathematical models for descriptive and predictive purposes. Here, we present a review of the application of state-of-the-art imaging modalities for quantitative pharmacological evaluation of therapeutic nanoparticles and monoclonal antibodies, with a focus on their integration with mathematical models, and identify challenges and opportunities. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Diagnostic Tools > in vivo Nanodiagnostics and Imaging Nanotechnology Approaches to Biology > Nanoscale Systems in Biology.

Gold nanoparticles enhance immune responses in mice against recombinant classical swine fever virus E2 protein

OBJECTIVE

To create a novel subunit vaccine that used AuNPs as carriers to enhance immune responses in mice against recombinant classical swine fever virus E2 protein (CSFV E2).

RESULTS

Gold nanoparticles (AuNPs) were successfully coupled to the E2 protein and formed stable particle complexes called E2 conjugated AuNPs (E2-AuNPs). In vitro studies have shown that the E2-AuNPs complex has the same immunogenicity as the E2 protein, and AuNPs can promote the phagocytosis of the E2 protein by antigen-presenting cells (APCs). In vivo results of BALB/c mice showed that the antibody levels, lymphocyte proliferation index, IFN-γ and IL-10 cytokines induced by E2-AuNPs were relatively higher than those of E2 or AuNPs group.

CONCLUSIONS

This finding demonstrated the potential of using AuNPs as a carrier to enhance the body's immune response for developing CSFV subunit vaccines. This model also contributes to the development of other flavivirus subunit vaccines, such as hepatitis C virus (HCV) and bovine viral diarrhea virus (BVDV).

Targeting of Hepatic Macrophages by Therapeutic Nanoparticles

Hepatic macrophage populations include different types of cells with plastic properties that can differentiate into diverse phenotypes to modulate their properties in response to different stimuli. They often regulate the activity of other cells and play an important role in many hepatic diseases. In response to those pathological situations, they are activated, releasing cytokines and chemokines; they may attract circulating monocytes and exert functions that can aggravate the symptoms or drive reparation processes. As a result, liver macrophages are potential therapeutic targets that can be oriented toward a variety of aims, with emergent nanotechnology platforms potentially offering new perspectives for macrophage vectorization. Macrophages play an essential role in the final destination of nanoparticles (NPs) in the organism, as they are involved in their uptake and trafficking in vivo. Different types of delivery nanosystems for macrophage recognition and targeting, such as liposomes, solid-lipid, polymeric, or metallic nanoparticles, have been developed. Passive targeting promotes the accumulation of the NPs in the liver due to their anatomical and physiological features. This process is modulated by NP characteristics such as size, charge, and surface modifications. Active targeting approaches with specific ligands may also be used to reach liver macrophages. In order to design new systems, the NP recognition mechanism of macrophages must be understood, taking into account that variations in local microenvironment may change the phenotype of macrophages in a way that will affect the uptake and toxicity of NPs. This kind of information may be applied to diseases where macrophages play a pathogenic role, such as metabolic disorders, infections, or cancer. The kinetics of nanoparticles strongly affects their therapeutic efficacy when administered in vivo. Release kinetics could predict the behavior of nanosystems targeting macrophages and be applied to improve their characteristics. PBPK models have been developed to characterize nanoparticle biodistribution in organs of the reticuloendothelial system (RES) such as liver or spleen. Another controversial issue is the possible toxicity of non-degradable nanoparticles, which in many cases accumulate in high percentages in macrophage clearance organs such as the liver, spleen, and kidney.