Predicting the impact of biocorona formation kinetics on interspecies extrapolations of nanoparticle biodistribution modeling

Predicting tissue distribution and tumor delivery of nanoparticles in mice using machine learning models

Nanoparticles (NPs) can be designed for targeted delivery in cancer nanomedicine, but the challenge is a low delivery efficiency (DE) to the tumor site. Understanding the impact of NPs' physicochemical properties on target tissue distribution and tumor DE can help improve the design of nanomedicines. Multiple machine learning and artificial intelligence models, including linear regression, support vector machine, random forest, gradient boosting, and deep neural networks (DNN), were trained and validated to predict tissue distribution and tumor delivery based on NPs' physicochemical properties and tumor therapeutic strategies with the dataset from Nano-Tumor Database. Compared to other machine learning models, the DNN model had superior predictions of DE to tumors and major tissues. The determination coefficients (R2) for the test datasets were 0.41, 0.42, 0.45, 0.79, 0.87, and 0.83 for DE in tumor, heart, liver, spleen, lung, and kidney, respectively. All the R2 and root mean squared error (RMSE) results of the test datasets were similar to the 5-fold cross validation results. Feature importance analysis showed that the core material of NPs played an important role in output predictions among all physicochemical properties. Furthermore, multiple NP formulations with greater DE to the tumor were determined by the DNN model. To facilitate model applications, the final model was converted to a web dashboard. This model could serve as a high-throughput pre-screening tool to support the design of new and efficient nanomedicines with greater tumor DE and serve as an alternative tool to reduce, refine, and partially replace animal experimentation in cancer nanomedicine research.

Ulgen K. Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling of Nanomaterials

Nanoparticles (NPs) have been widely used to improve the pharmacokinetic properties and tissue distribution of small molecules such as targeting to a specific tissue of interest, enhancing their systemic circulation, and enlarging their therapeutic properties. NPs have unique and complicated in vivo disposition properties compared to small molecule drugs due to their complex multifunctionality. Physiologically based pharmacokinetic (PBPK) modeling has been a powerful tool in the simulation of the absorption, distribution, metabolism, and elimination (ADME) characteristics of the materials, and it can be used in the characterization and prediction of the systemic disposition, toxicity, efficacy, and target exposure of various types of nanoparticles. In this review, recent advances in PBPK model applications related to the nanoparticles with unique properties, and dispositional features in the biological systems, ADME characteristics, the description of transport processes of nanoparticles in the PBPK model, and the challenges in PBPK model development of nanoparticles are delineated and juxtaposed with those encountered in small molecule models. Nanoparticle related, non-nanoparticle-related, and interspecies-scaling methods applied in PBPK modeling are reviewed. In vitro to in vivo extrapolation (IVIVE) methods being a promising computational tool to provide in vivo predictions from the results of in vitro and in silico studies are discussed. Finally, as a recent advancement ML/AI-based approaches and challenges in PBPK modeling in the estimation of ADME parameters and pharmacokinetic (PK) analysis results are introduced.

An artificial intelligence-assisted physiologically-based pharmacokinetic model to predict nanoparticle delivery to tumors in mice

The critical barrier for clinical translation of cancer nanomedicine stems from the inefficient delivery of nanoparticles (NPs) to target solid tumors. Rapid growth of computational power, new machine learning and artificial intelligence (AI) approaches provide new tools to address this challenge. In this study, we established an AI-assisted physiologically based pharmacokinetic (PBPK) model by integrating an AI-based quantitative structure-activity relationship (QSAR) model with a PBPK model to simulate tumor-targeted delivery efficiency (DE) and biodistribution of various NPs. The AI-based QSAR model was developed using machine learning and deep neural network algorithms that were trained with datasets from a published "Nano-Tumor Database" to predict critical input parameters of the PBPK model. The PBPK model with optimized NP cellular uptake kinetic parameters was used to predict the maximum delivery efficiency (DEmax) and DE at 24 (DE24) and 168 h (DE168) of different NPs in the tumor after intravenous injection and achieved a determination coefficient of R2 = 0.83 [root mean squared error (RMSE) = 3.01] for DE24, R2 = 0.56 (RMSE = 2.27) for DE168, and R2 = 0.82 (RMSE = 3.51) for DEmax. The AI-PBPK model predictions correlated well with available experimentally-measured pharmacokinetic profiles of different NPs in tumors after intravenous injection (R2 ≥ 0.70 for 133 out of 288 datasets). This AI-based PBPK model provides an efficient screening tool to rapidly predict delivery efficiency of a NP based on its physicochemical properties without relying on an animal training dataset.

Pharmacokinetics and tumor delivery of nanoparticles

Nanoparticles (NPs) have been widely used in different areas, including consumer products and medicine. In terms of biomedical applications, NPs or NP-based drug formulations have been extensively investigated for cancer diagnostics and therapy in preclinical studies, but the clinical translation rate is low. Therefore, a thorough and comprehensive understanding of the pharmacokinetics of NPs, especially in drug delivery efficiency to the target therapeutic tissue tumor, is important to design more effective nanomedicines and for proper assessment of the safety and risk of NPs. This review article focuses on the pharmacokinetics of both organic and inorganic NPs and their tumor delivery efficiencies, as well as the associated mechanisms involved. We discuss the absorption, distribution, metabolism, and excretion (ADME) processes following different routes of exposure and the mechanisms involved. Many physicochemical properties and experimental factors, including particle type, size, surface charge, zeta potential, surface coating, protein binding, dose, exposure route, species, cancer type, and tumor size can affect NP pharmacokinetics and tumor delivery efficiency. NPs can be absorbed with varying degrees following different exposure routes and mainly accumulate in liver and spleen, but also distribute to other tissues such as heart, lung, kidney and tumor tissues; and subsequently get metabolized and/or excreted mainly through hepatobiliary and renal elimination. Passive and active targeting strategies are the two major mechanisms of tumor delivery, while active targeting tends to have less toxicity and higher delivery efficiency through direct interaction between ligands and receptors. We also discuss challenges and perspectives remaining in the field of pharmacokinetics and tumor delivery efficiency of NPs.

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.

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.

Toxicokinetics, dose-response, and risk assessment of nanomaterials: Methodology, challenges, and future perspectives

The rapid growth of nanomaterial applications has raised safety concerns for human health. A number of studies have been conducted to assess the toxicokinetics, toxicology, dose-response, and risk assessment of different nanomaterials using in vitro and in vivo animal and human models. However, current studies cannot meet the demand for efficient assessment of toxicokinetics, dose-response relationships, or the toxicological risk arising from the rapidly increasing number of newly synthesized nanomaterials. In this article, we review the methods for conducting toxicokinetics, hazard identification, dose-response, exposure, and risk assessment studies of nanomaterials, identify the knowledge gaps, and discuss the challenges remaining. We provide the rationale behind the appropriate design of nanomaterial plasma toxicokinetic and tissue distribution studies, including caveats on the interpretation and correlation of in vitro and in vivo toxicology studies. The potential of using physiologically based pharmacokinetic (PBPK) models to extrapolate toxicokinetic and toxicity findings from in vitro to in vivo and from animals to humans is discussed, and the knowledge gaps of PBPK modeling for nanomaterials are identified. While challenges still exist, there has been progress in the toxicokinetics, hazard identification, and risk assessment of nanomaterials in the past two decades. Recent advancements in the field are highlighted with relevant examples. We also share latest guidelines as well as our perspectives on future studies needed to characterize the toxicokinetics, toxicity, and dose-response relationship in support of nanomaterial risk assessment. This article is categorized under: Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials Toxicology and Regulatory Issues in Nanomedicine > Regulatory and Policy Issues in Nanomedicine.

Development of a multi-route physiologically based pharmacokinetic (PBPK) model for nanomaterials: a comparison between a traditional versus a new route-specific approach using gold nanoparticles in rats

BACKGROUND

Physiologically based pharmacokinetic (PBPK) modeling is an important tool in predicting target organ dosimetry and risk assessment of nanoparticles (NPs). The methodology of building a multi-route PBPK model for NPs has not been established, nor systematically evaluated. In this study, we hypothesized that the traditional route-to-route extrapolation approach of PBPK modeling that is typically used for small molecules may not be appropriate for NPs. To test this hypothesis, the objective of this study was to develop a multi-route PBPK model for different sizes (1.4-200 nm) of gold nanoparticles (AuNPs) in adult rats following different routes of administration (i.e., intravenous (IV), oral gavage, intratracheal instillation, and endotracheal inhalation) using two approaches: a traditional route-to-route extrapolation approach for small molecules and a new approach that is based on route-specific data that we propose to be applied generally to NPs.

RESULTS

We found that the PBPK model using this new approach had superior performance than the traditional approach. The final PBPK model was optimized rigorously using a Bayesian hierarchical approach with Markov chain Monte Carlo simulations, and then converted to a web-based interface using R Shiny. In addition, quantitative structure-activity relationships (QSAR) based multivariate linear regressions were established to predict the route-specific key biodistribution parameters (e.g., maximum uptake rate) based on the physicochemical properties of AuNPs (e.g., size, surface area, dose, Zeta potential, and NP numbers). These results showed the size and surface area of AuNPs were the main determinants for endocytic/phagocytic uptake rates regardless of the route of administration, while Zeta potential was an important parameter for the estimation of the exocytic release rates following IV administration.

CONCLUSIONS

This study suggests that traditional route-to-route extrapolation approaches for PBPK modeling of small molecules are not applicable to NPs. Therefore, multi-route PBPK models for NPs should be developed using route-specific data. This novel PBPK-based web interface serves as a foundation for extrapolating to other NPs and to humans to facilitate biodistribution estimation, safety, and risk assessment of NPs.

Streamlining physiologically‐based pharmacokinetic model design for intravenous delivery of nanoparticle drugs

Physiologically‐based pharmacokinetic (PBPK) modeling for nanoparticles elucidates the nanoparticle drug’s disposition in the body and serves a vital role in drug development and clinical studies. This paper offers a systematic and tutorial‐like approach to developing a model structure and writing distribution ordinary differential equations based on asking binary questions involving the physicochemical nature of the drug in question. Further, by synthesizing existing knowledge, we summarize pertinent aspects in PBPK modeling and create a guide for building model structure and distribution equations, optimizing nanoparticle and non‐nanoparticle specific parameters, and performing sensitivity analysis and model validation. The purpose of this paper is to facilitate a streamlined model development process for students and practitioners in the field.

Complex Factors and Challenges that Affect the Pharmacology, Safety and Efficacy of Nanocarrier Drug Delivery Systems

Major developments in nanomedicines, such as nanoparticles (NPs), nanosomes, and conjugates, have revolutionized drug delivery capabilities over the past four decades. Although nanocarrier agents provide numerous advantages (e.g., greater solubility and duration of systemic exposure) compared to their small-molecule counterparts, there is considerable inter-patient variability seen in the systemic disposition, tumor delivery and overall pharmacological effects (i.e., anti-tumor efficacy and unwanted toxicity) of NP agents. This review aims to provide a summary of fundamental factors that affect the disposition of NPs in the treatment of cancer and why they should be evaluated during preclinical and clinical development. Furthermore, this chapter will highlight some of the translational challenges associated with elements of NPs and how these issues can only be addressed by detailed and novel pharmacology studies.

Guidelines for the experimental design of pharmacokinetic studies with nanomaterials in preclinical animal models

A shared feature in the value proposition of every nanomaterial-based drug delivery systems is the desirable improvement in the disposition (or ADME) and pharmacokinetic profiles of the encapsulated drug being delivered. Remarkable progress has been made towards understanding the complex and multifactorial relationships between pharmacokinetic profiles and nanomaterial physicochemical properties, biological interactions, species physiology, etc. These advances have fuelled the rational design of numerous nanomaterials with long-circulation times and improved tissue accumulation (e.g., in tumours). Unfortunately, a central weakness in many of these research efforts has been the inconsistent and insufficient characterisation of the pharmacokinetic profiles of nanomaterials in scientific reporting-a problem affecting the majoirty of of contemporary nanomaterials literature and innovative nanomaterials in early stages of preclinical development especially. Given the significant role of pharmacokinetic assessments to serve as guideposts for deciding whether to continue with the preclinical development and clinical translation of drug delivery systems, the prevalence of poor pharmacokinetic characterisations in nanomaterials research is particularly alarming. A conspicuous problem in many reports is the inappropriate selection of experimental designs and methodologies for studying nanomaterial pharmacokinetics, the consequences of which are increased uncertainty over the accurate interpretation of reported pharmacokinetic data and diminished experimental reproducibility throughout the field. Thus, there is renewed interest in the establishment of consistent and comprehensive strategies for designing preclinical experiments to assess the pharmacokinetics of nanomaterials with diverse physicochemical properties. Towards this end, herein are proposed simple guidelines for the experimental design of pharmacokinetic studies with nanomaterials drawn from the best research practices, principle strategies, and important considerations used in industry for collecting pharmacokinetic data in preclinical animal models. Specifically, key experimental design factors in these studies are identified and examined in the context of nanomaterials for optimality, including blood sampling strategy and technique, sample allocation and sampling time window, test species selection, experimental sources of pharmacokinetic variability, etc. Methods for noninvasive imaging-derived pharmacokinetic assessments of theranostic nanomaterials are also explored with particular focus on emission tomography imaging modalities. Taken together, this review will provide nanomaterial researchers with practical knowledge and pragmatic recommendations for selecting the best designs and methodologies for assessing the pharmacokinetic profiles of their nanomaterials, and hopefully maximise the chances of translational success of these innovative products into humans.

Meta-Analysis of Nanoparticle Delivery to Tumors Using a Physiologically Based Pharmacokinetic Modeling and Simulation Approach

Numerous studies have engineered nanoparticles with different physicochemical properties to enhance the delivery efficiency to solid tumors, yet the mean and median delivery efficiencies are only 1.48% and 0.70% of the injected dose (%ID), respectively, according to a study using a nonphysiologically based modeling approach based on published data from 2005 to 2015. In this study, we used physiologically based pharmacokinetic (PBPK) models to analyze 376 data sets covering a wide range of nanomedicines published from 2005 to 2018 and found mean and median delivery efficiencies at the last sampling time point of 2.23% and 0.76%ID, respectively. Also, the mean and median delivery efficiencies were 2.24% and 0.76%ID at 24 h and were decreased to 1.23% and 0.35%ID at 168 h, respectively, after intravenous administration. While these delivery efficiencies appear to be higher than previous findings, they are still quite low and represent a critical barrier in the clinical translation of nanomedicines. We explored the potential causes of this poor delivery efficiency using the more mechanistic PBPK perspective applied to a subset of gold nanoparticles and found that low delivery efficiency was associated with low distribution and permeability coefficients at the tumor site (P < 0.01). We also demonstrate how PBPK modeling and simulation can be used as an effective tool to investigate tumor delivery efficiency of nanomedicines.

Research tools for extrapolating the disposition and pharmacokinetics of nanomaterials from preclinical animals to humans

A critical step in the translational science of nanomaterials from preclinical animal studies to humans is the comprehensive investigation of their disposition (or ADME) and pharmacokinetic behaviours. Disposition and pharmacokinetic data are ideally collected in different animal species (rodent and nonrodent), at different dose levels, and following multiple administrations. These data are used to assess the systemic exposure and effect to nanomaterials, primary determinants of their potential toxicity and therapeutic efficacy. At toxic doses in animal models, pharmacokinetic (termed toxicokinetic) data are related to toxicologic findings that inform the design of nonclinical toxicity studies and contribute to the determination of the maximum recommended starting dose in clinical phase 1 trials. Nanomaterials present a unique challenge for disposition and pharmacokinetic investigations owing to their prolonged circulation times, nonlinear pharmacokinetic profiles, and their extensive distribution into tissues. Predictive relationships between nanomaterial physicochemical properties and behaviours in vivo are lacking and are confounded by anatomical, physiological, and immunological differences amongst preclinical animal models and humans. These challenges are poorly understood and frequently overlooked by investigators, leading to inaccurate assumptions of disposition, pharmacokinetic, and toxicokinetics profiles across species that can have profoundly detrimental impacts for nonclinical toxicity studies and clinical phase 1 trials. Herein are highlighted two research tools for analysing and interpreting disposition and pharmacokinetic data from multiple species and for extrapolating this data accurately in humans. Empirical methodologies and mechanistic mathematical modelling approaches are discussed with emphasis placed on important considerations and caveats for representing nanomaterials, such as the importance of integrating physiological variables associated with the mononuclear phagocyte system (MPS) into extrapolation methods for nanomaterials. The application of these tools will be examined in recent examples of investigational and clinically approved nanomaterials. Finally, strategies for applying these extrapolation tools in a complementary manner to perform dose predictions and in silico toxicity assessments in humans will be explained. A greater familiarity with the available tools and prior experiences of extrapolating nanomaterial disposition and pharmacokinetics from preclinical animal models to humans will hopefully result in a more straightforward roadmap for the clinical translation of promising nanomaterials.

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

Gold nanoparticles (AuNPs) are a focus of growing medical research applications due to their unique chemical, electrical and optical properties. Because of uncertain toxicity, "green" synthesis methods are emerging, using plant extracts to improve biological and environmental compatibility. Here we explore the biodistribution of green AuNPs in mice and prepare a physiologically-based pharmacokinetic (PBPK) model to guide interspecies extrapolation. Monodisperse AuNPs were synthesized and capped with epigallocatechin gallate (EGCG) and curcumin. 64 CD-1 mice received the AuNPs by intraperitoneal injection. To assess biodistribution, groups of six mice were sacrificed at 1, 7, 14, 28 and 56 days, and their organs were analyzed for gold content using inductively coupled plasma mass spectrometry (ICP-MS). A physiologically-based pharmacokinetic (PBPK) model was developed to describe the biodistribution data in mice. To assess the potential for interspecies extrapolation, organism-specific parameters in the model were adapted to represent rats, and the rat PBPK model was subsequently evaluated with PK data for citrate-capped AuNPs from literature. The liver and spleen displayed strong uptake, and the PBPK model suggested that extravasation and phagocytosis were key drivers. Organ predictions following interspecies extrapolation were successful for rats receiving citrate-capped AuNPs. This work lays the foundation for the pre-clinical extrapolation of the pharmacokinetics of AuNPs from mice to larger species.

Physiologically based mathematical models of nanomaterials for regulatory toxicology: A review

The development of physiologically based (PB) models to support safety assessments in the field of nanotechnology has grown steadily during the last decade. This review reports on the availability of PB models for toxicokinetic (TK) and toxicodynamic (TD) processes, including in vitro and in vivo dosimetry models applied to manufactured nanomaterials (MNs). In addition to reporting on the state-of-the-art in the scientific literature concerning the availability of physiologically based kinetic (PBK) models, we evaluate their relevance for regulatory applications, mainly considering the EU REACH regulation. First, we performed a literature search to identify all available PBK models. Then, we systematically reported the content of the identified papers in a tailored template to build a consistent inventory, thereby supporting model comparison. We also described model availability for physiologically based dynamic (PBD) and in vitro and in vivo dosimetry models according to the same template. For completeness, a number of classical toxicokinetic (CTK) models were also included in the inventory. The review describes the PBK model landscape applied to MNs on the basis of the type of MNs covered by the models, their stated applicability domain, the type of (nano-specific) inputs required, and the type of outputs generated. We identify the main assumptions made during model development that may influence the uncertainty in the final assessment, and we assess the REACH relevance of the available models within each model category. Finally, we compare the state of PB model acceptance for chemicals and for MNs. In general, PB model acceptance is limited by the absence of standardised reporting formats, psychological factors such as the complexity of the models, and technical considerations such as lack of blood:tissue partitioning data for model calibration/validation.

Hide and Seek: Nanomaterial Interactions With the Immune System

Engineered nanomaterials hold promise for a wide range of applications in medicine. However, safe use of nanomaterials requires that interactions with biological systems, not least with the immune system, are understood. Do nanomaterials elicit novel or unexpected effects, or is it possible to predict immune responses to nanomaterials based on how the immune system handles pathogens? How does the bio-corona of adsorbed biomolecules influence subsequent immune interactions of nanomaterials? How does the grafting of polymers such as poly(ethylene glycol) onto nanomaterial surfaces impact on these interactions? Can ancient immune evasion or “stealth” strategies of pathogens inform the design of nanomaterials for biomedical applications? Can nanoparticles co-opt immune cells to target diseased tissues? The answers to these questions may prove useful for the development of nanomedicines.

Nanoparticle Properties for Delivery to Cartilage: The Implications of Disease State, Synovial Fluid, and Off-Target Uptake

A major hurdle limiting the ability to treat and cure osteoarthritis, a common and debilitating disease, is rapid joint clearance and limited cartilage targeting of intra-articular therapies. Nanoscale drug carriers have the potential to improve therapeutic targeting and retention in the joint after direct injection; however, there still lacks a fundamental understanding of how the physicochemical properties of nanoparticles (NPs) influence localization to the degenerating cartilage and how joint conditions such as disease state and synovial fluid impact NP biodistribution. The goal of this study was to assess how physicochemical properties of NPs influence their interactions with joint tissues and, ultimately, cartilage localization. Ex vivo models of joint tissues were used to study how poly(lactide- co-glycolide) (PLGA) and polystyrene (PS) NP size, charge, and surface chemistry influence cartilage retention under normal and disease-mimicking conditions. Of the particles investigated, PLGA NPs surface-modified with a quaternary ammonium cation had the greatest retention within cartilage explants; however, retention was diminished 2- to 2.9-fold in arthritic tissue and in the presence of synovial fluid. Interactions with synovial fluid induced changes to NP surface properties and colloidal stability in vitro. The impact of NP charge on "off-target" synoviocyte uptake was also dependent on synovial fluid interactions. The results suggest that the design of nanocarriers for targeted drug delivery within the joint cannot be based on a single parameter such as zeta potential or size, and that the fate of injected delivery systems will likely be influenced by the disease state of the joint and the presence of synovial fluid.

Physiologically Based Pharmacokinetic Modeling of Nanoparticles

Nanoparticles are frequently designed to improve the pharmacokinetics profiles and tissue distribution of small molecules to prolong their systemic circulation, target specific tissue, or widen the therapeutic window. The multifunctionality of nanoparticles is frequently presented as an advantage but also results in distinct and complicated in vivo disposition properties compared with a conventional formulation of the same molecules. Physiologically based pharmacokinetic (PBPK) modeling has been a useful tool in characterizing and predicting the systemic disposition, target exposure, and efficacy and toxicity of various types of drugs when coupled with pharmacodynamic modeling. Here we review the unique disposition characteristics of nanoparticles, assess how PBPK modeling takes into account the unique disposition properties of nanoparticles, and comment on the applications and challenges of PBPK modeling in characterizing and predicting the disposition and biological effects of nanoparticles.

Probabilistic risk assessment of gold nanoparticles after intravenous administration by integrating in vitro and in vivo toxicity with physiologically based pharmacokinetic modeling

This study aimed to conduct an integrated and probabilistic risk assessment of gold nanoparticles (AuNPs) based on recently published in vitro and in vivo toxicity studies coupled to a physiologically based pharmacokinetic (PBPK) model. Dose-response relationships were characterized based on cell viability assays in various human cell types. A previously well-validated human PBPK model for AuNPs was applied to quantify internal concentrations in liver, kidney, skin, and venous plasma. By applying a Bayesian-based probabilistic risk assessment approach incorporating Monte Carlo simulation, probable human cell death fractions were characterized. Additionally, we implemented in vitro to in vivo and animal-to-human extrapolation approaches to independently estimate external exposure levels of AuNPs that cause minimal toxicity. Our results suggest that under the highest dosing level employed in existing animal studies (worst-case scenario), AuNPs coated with branched polyethylenimine (BPEI) would likely induce ∼90-100% cellular death, implying high cytotoxicity compared to <10% cell death induced by low-to-medium animal dosing levels, which are commonly used in animal studies. The estimated human equivalent doses associated with 5% cell death in liver and kidney were around 1 and 3 mg/kg, respectively. Based on points of departure reported in animal studies, the human equivalent dose estimates associated with gene expression changes and tissue cell apoptosis in liver were 0.005 and 0.5 mg/kg, respectively. Our analyzes provide insights into safety evaluation, risk prediction, and point of departure estimation of AuNP exposure for humans and illustrate an approach that could be applied to other NPs when sufficient data are available.

A multiscale modeling study of particle size effects on the tissue penetration efficacy of drug-delivery nanoparticles

BACKGROUND

Particle size is a key parameter for drug-delivery nanoparticle design. It is believed that the size of a nanoparticle may have important effects on its ability to overcome the transport barriers in biological tissues. Nonetheless, such effects remain poorly understood. Using a multiscale model, this work investigates particle size effects on the tissue distribution and penetration efficacy of drug-delivery nanoparticles.

RESULTS

We have developed a multiscale spatiotemporal model of nanoparticle transport in biological tissues. The model implements a time-adaptive Brownian Dynamics algorithm that links microscale particle-cell interactions and adhesion dynamics to tissue-scale particle dispersion and penetration. The model accounts for the advection, diffusion, and cellular uptakes of particles. Using the model, we have analyzed how particle size affects the intra-tissue dispersion and penetration of drug delivery nanoparticles. We focused on two published experimental works that investigated particle size effects in in vitro and in vivo tissue conditions. By analyzing experimental data reported in these two studies, we show that particle size effects may appear pronounced in an in vitro cell-free tissue system, such as collagen matrix. In an in vivo tissue system, the effects of particle size could be relatively modest. We provide a detailed analysis on how particle-cell interactions may determine distribution and penetration of nanoparticles in a biological tissue.

CONCLUSION

Our work suggests that the size of a nanoparticle may play a less significant role in its ability to overcome the intra-tissue transport barriers. We show that experiments involving cell-free tissue systems may yield misleading observations of particle size effects due to the absence of advective transport and particle-cell interactions.

An apolipoprotein-enriched biomolecular corona switches the cellular uptake mechanism and trafficking pathway of lipid nanoparticles

Following exposure to biological milieus (e.g. after systemic administration), nanoparticles (NPs) get covered by an outer biomolecular corona (BC) that defines many of their biological outcomes, such as the elicited immune response, biodistribution, and targeting abilities. In spite of this, the role of BC in regulating the cellular uptake and the subcellular trafficking properties of NPs has remained elusive. Here, we tackle this issue by employing multicomponent (MC) lipid NPs, human plasma (HP) and HeLa cells as models for nanoformulations, biological fluids, and target cells, respectively. By conducting confocal fluorescence microscopy experiments and image correlation analyses, we quantitatively demonstrate that the BC promotes a neat switch of the cell entry mechanism and subsequent intracellular trafficking, from macropinocytosis to clathrin-dependent endocytosis. Nano-liquid chromatography tandem mass spectrometry identifies apolipoproteins as the most abundant components of the BC tested here. Interestingly, this class of proteins target the LDL receptors, which are overexpressed in clathrin-enriched membrane domains. Our results highlight the crucial role of BC as an intrinsic trigger of specific NP-cell interactions and biological responses and set the basis for a rational exploitation of the BC for targeted delivery.

The biocorona: a challenge for the biomedical application of nanoparticles

Formation of the biocorona on the surface of nanoparticles is a significant obstacle for the development of safe and effective nanotechnologies, especially for nanoparticles with biomedical applications. Following introduction into a biological environment, nanoparticles are rapidly coated with biomolecules resulting in formation of the nanoparticle-biocorona. The addition of these biomolecules alters the nanoparticle's physicochemical characteristics, functionality, biodistribution, and toxicity. To synthesize effective nanotherapeutics and to more fully understand possible toxicity following human exposures, it is necessary to elucidate these interactions between the nanoparticle and the biological media resulting in biocorona formation. A thorough understanding of the mechanisms by which the addition of the biocorona governs nanoparticle-cell interactions is also required. Through elucidating the formation and the biological impact of the biocorona, the field of nanotechnology can reach its full potential. This understanding of the biocorona will ultimately allow for more effective laboratory screening of nanoparticles and enhanced biomedical applications. The importance of the nanoparticle-biocorona has been appreciated for a decade; however, there remain numerous future directions for research which are necessary for study. This perspectives article will summarize the unique challenges presented by the nanoparticle-biocorona and avenues of future needed investigation.

Determinants of Alanine Dipeptide Conformational Equilibria on Graphene and Hydroxylated Derivatives

Understanding the interaction of carbon nanomaterials with proteins is essential for determining the potential effects of these materials on health and in the design of biotechnology based on them. Here we leverage explicit-solvent molecular simulation and multidimensional free-energy calculations to investigate how adsorption to carbon nanomaterial surfaces affects the conformational equilibrium of alanine dipeptide, a widely used model of protein backbone structure. We find that the two most favorable structures of alanine dipeptide on graphene (or large carbon nanotubes) correspond to the two amide linkages lying in the same plane, flat against the surface, rather than the nonplanar α-helix-like and β-sheet-like conformations that predominate in aqueous solution. On graphenic surfaces, the latter conformations are metastable and most often correspond to amide-π stacking of the N-terminal amide. The calculations highlight the key role of amide-π interactions in determining the conformational equilibrium. Lesser but significant contributions from hydrogen bonding to the high density interfacial water layer or to the hydroxy groups of hydroxylated graphene also define the most favorable conformations. This work should yield insight on the influence of carbon nanotubes, graphene, and their functionalized derivatives on protein structure.

Label-free protein sensing by employing blue phase liquid crystal

Blue phases (BPs) are mesophases existing between the isotropic and chiral nematic phases of liquid crystals (LCs). In recent years, blue phase LCs (BPLCs) have been extensively studied in the field of LC science and display technology. However, the application of BPLCs in biosensing has not been explored. In this study, a BPLC-based biosensing technology was developed for the detection and quantitation of bovine serum albumin (BSA). The sensing platform was constructed by assembling an empty cell with two glass slides coated with homeotropic alignment layers and with immobilized BSA atop. The LC cells were heated to isotropic phase and then allowed to cool down to and maintained at distinct BP temperatures for spectral measurements and texture observations. At BSA concentrations below 10^-6 g/ml, we observed that the Bragg reflection wavelength blue-shifted with increasing concentration of BSA, suggesting that the BP is a potentially sensitive medium in the detection and quantitation of biomolecules. By using the BPLC at 37 °C and the same polymorphic material in the smectic A phase at 20 °C, two linear correlations were established for logarithmic BSA concentrations ranging from 10^-9 to 10^-6 g/ml and from 10^-6 to 10^-3 g/ml. Our results demonstrate the potential of BPLCs in biosensing and quantitative analysis of biomolecules.

Protein bio-corona: critical issue in immune nanotoxicology

With the expansion of the nanomedicine field, the knowledge focusing on the behavior of nanoparticles in the biological milieu has rapidly escalated. Upon introduction to a complex biological system, nanomaterials dynamically interact with all the encountered biomolecules and form the protein "bio-corona." The decoration with these surface biomolecules endows nanoparticles with new properties. The present review will address updates of the protein bio-corona characteristics as influenced by nanoparticle's physicochemical properties and by the particularities of the encountered biological milieu. Undeniably, bio-corona generation influences the efficacy of the nanodrug and guides the actions of innate and adaptive immunity. Exploiting the dynamic process of protein bio-corona development in combination with the new engineered horizons of drugs linked to nanoparticles could lead to innovative functional nanotherapies. Therefore, bio-medical nanotechnologies should focus on the interactions of nanoparticles with the immune system for both safety and efficacy reasons.

In vivo protein corona patterns of lipid nanoparticles

In vitro and in vivo biological identity of nanoparticles are substantially different.

Physiologically Based Pharmacokinetic (PBPK) Modeling of Pharmaceutical Nanoparticles

With the great interests in the discovery and development of drug products containing nanoparticles, there is a great demand of quantitative tools for assessing quality, safety, and efficacy of these products. Physiologically based pharmacokinetic (PBPK) modeling and simulation approaches provide excellent tools for describing and predicting in vivo absorption, distribution, metabolism, and excretion (ADME) of nanoparticles administered through various routes. PBPK modeling of nanoparticles is an emerging field, and more than 20 PBPK models of nanoparticles used in pharmaceutical products have been published in the past decade. This review provides an overview of the ADME characteristics of nanoparticles and how these ADME processes are described in PBPK models. Recent advances in PBPK modeling of pharmaceutical nanoparticles are summarized. The major challenges in model development and validation and possible solutions are also discussed.

Biological and environmental surface interactions of nanomaterials: characterization, modeling, and prediction

The understanding of nano-bio interactions is deemed essential in the design, application, and safe handling of nanomaterials. Proper characterization of the intrinsic physicochemical properties, including their size, surface charge, shape, and functionalization, is needed to consider the fate or impact of nanomaterials in biological and environmental systems. The characterizations of their interactions with surrounding chemical species are often hindered by the complexity of biological or environmental systems, and the drastically different surface physicochemical properties among a large population of nanomaterials. The complexity of these interactions is also due to the diverse ligands of different chemical properties present in most biomacromolecules, and multiple conformations they can assume at different conditions to minimize their conformational free energy. Often these interactions are collectively determined by multiple physical or chemical forces, including electrostatic forces, hydrogen bonding, and hydrophobic forces, and calls for multidimensional characterization strategies, both experimentally and computationally. Through these characterizations, the understanding of the roles surface physicochemical properties of nanomaterials and their surface interactions with biomacromolecules can play in their applications in biomedical and environmental fields can be obtained. To quantitatively decipher these physicochemical surface interactions, computational methods, including physical, statistical, and pharmacokinetic models, can be used for either analyses of large amounts of experimental characterization data, or theoretical prediction of the interactions, and consequent biological behavior in the body after administration. These computational methods include molecular dynamics simulation, structure-activity relationship models such as biological surface adsorption index, and physiologically-based pharmacokinetic models. WIREs Nanomed Nanobiotechnol 2017, 9:e1440. doi: 10.1002/wnan.1440 For further resources related to this article, please visit the WIREs website.

Biocorona Bound Gold Nanoparticles Augment Their Hematocompatibility Irrespective of Size or Surface Charge

Despite colloidal gold nanoparticles (AuNP) being proposed for a multitude of biomedical applications, there is a lack of understanding on how the protein corona (PC) formation over AuNP influences its interaction with blood components. Herein, 40 and 80 nm AuNP with branched polyethylenimine, lipoic acid, and polyethylene glycol surface coatings were exposed to human plasma, and time-dependent evolution of the PC was evaluated using differential centrifugation sedimentation. Further, the impact of PC-AuNP interaction with human blood components was studied by evaluating red blood cell (RBC) aggregation, hemolysis, platelet activation and aggregation, prothrombin time, activated partial thromboplastin time, complement activation and cytokine release. In contrast to bare AuNP, PC-coated AuNP exhibited enhanced compatibility with RBC, platelets, and lymphocytes. More importantly, PC-AuNP did not activate the platelet coagulation cascade or complement system or elicit an immune response up to a relatively higher dose of 100 μg/mL. This study suggests that, irrespective of the physicochemical properties, the adsorption of the PC over AuNP significantly influences its biological impact by alleviating adverse hematotoxicity of bare NP.

Effects of the protein corona on liposome-liposome and liposome-cell interactions

A thorough understanding of interactions occurring at the interface between nanocarriers and biological systems is crucial to predict and interpret their biodistribution, targeting, and efficacy, and thus design more effective drug delivery systems. Upon intravenous injection, nanoparticles are coated by a protein corona (PC). This confers a new biological identity on the particles that largely determines their biological fate. Liposomes have great pharmaceutical versatility, so, as proof of concept, their PC has recently been implicated in the mechanism and efficiency of their internalization into the cell. In an attempt to better understand the interactions between nanocarriers and biological systems, we analyzed the plasma proteins adsorbed on the surface of multicomponent liposomes. Specifically, we analyzed the physical properties and ultrastructure of liposome/PC complexes and the aggregation process that occurs when liposomes are dispersed in plasma. The results of combined confocal microscopy and flow cytometry experiments demonstrated that the PC favors liposome internalization by both macrophages and tumor cells. This work provides insights into the effects of the PC on liposomes' physical properties and, consequently, liposome-liposome and liposome-cell interactions.

NANOMEDICINE: will it offer possibilities to overcome multiple drug resistance in cancer?

This review is written with the purpose to review the current nanomedicine literature and provide an outlook on the developments in utilizing nanoscale drug constructs in treatment of solid cancers as well as in the potential treatment of multi-drug resistant cancers. No specific design principles for this review have been utilized apart from our active choice to avoid results only based on in vitro studies. Few drugs based on nanotechnology have progressed to clinical trials, since most are based only on in vitro experiments which do not give the necessary data for the research to progress towards pre-clinical studies. The area of nanomedicine has indeed spark much attention and holds promise for improved future therapeutics in the treatment of solid cancers. However, despite much investment few targeted therapeutics have successfully progressed to early clinical trials, indicating yet again that the human body is complicated and that much more understanding of the fundamentals of receptor interactions, physics of nanomedical constructs and their circulation in the body is indeed needed. We believe that nanomedical therapeutics can allow for more efficient treatments of resistant cancers, and may well be a cornerstone for RNA based therapeutics in the future given their general need for shielding from the harsh environment in the blood stream.

Toward a general physiologically-based pharmacokinetic model for intravenously injected nanoparticles

To assess the potential toxicity of nanoparticles (NPs), information concerning their uptake and disposition (biokinetics) is essential. Experience with industrial chemicals and pharmaceutical drugs reveals that biokinetics can be described and predicted accurately by physiologically-based pharmacokinetic (PBPK) modeling. The nano PBPK models developed to date all concern a single type of NP. Our aim here was to extend a recent model for pegylated polyacrylamide NP in order to develop a more general PBPK model for nondegradable NPs injected intravenously into rats. The same model and physiological parameters were applied to pegylated polyacrylamide, uncoated polyacrylamide, gold, and titanium dioxide NPs, whereas NP-specific parameters were chosen on the basis of the best fit to the experimental time-courses of NP accumulation in various tissues. Our model describes the biokinetic behavior of all four types of NPs adequately, despite extensive differences in this behavior as well as in their physicochemical properties. In addition, this simulation demonstrated that the dose exerts a profound impact on the biokinetics, since saturation of the phagocytic cells at higher doses becomes a major limiting step. The fitted model parameters that were most dependent on NP type included the blood:tissue coefficients of permeability and the rate constant for phagocytic uptake. Since only four types of NPs with several differences in characteristics (dose, size, charge, shape, and surface properties) were used, the relationship between these characteristics and the NP-dependent model parameters could not be elucidated and more experimental data are required in this context. In this connection, intravenous biodistribution studies with associated PBPK analyses would provide the most insight.

Engineered biomimetic nanoabsorbent for cellular detoxification of chemotherapeutics

An approach to reduce the nonspecific cytotoxicity of chemotherapeutics has been put-forth using a biomimetic nanoabsorbent (NAb) as a detoxifying agent.

Translational radionanomedicine: a clinical perspective

Many nanomaterials were developed for the anticipated in vivo theranostic use exploiting their unique characteristics as a multifunctional platform. Nevertheless, only a few nanomaterials are under investigation for human use, most of which have not entered clinical trials yet. Radionanomedicine, a convergent discipline of radiotracer technology and use of nanomaterials in vivo, can facilitate clinical nanomedicine because of its advantages of radionuclide imaging and internal radiation therapy. In this review, we focuse on how radionanomedicine would impact profoundly on clinical translation of nanomaterial theranostics. Up-to-date advances and future challenges are critically reviewed regarding the issues of how to radiolabel and engineer radionanomaterials, in vivo behavior tracing of radionanomaterials and then the desired clinical radiation dosimetry. Radiolabeled extracellular vesicles were further discussed as endogenous nanomaterials radiolabeled for possible clinical use.

A computational framework for interspecies pharmacokinetics, exposure and toxicity assessment of gold nanoparticles

Aim: To develop a comprehensive computational framework to simulate tissue distribution of gold nanoparticles (AuNP) across several species. Materials & methods: This framework was built on physiologically based pharmacokinetic modeling, calibrated and evaluated with multiple independent datasets. Results: Rats and pigs seem to be more appropriate models than mice in animal-to-human extrapolation of AuNP pharmacokinetics and that the dose and age should be considered. Incorporation of in vitro and/or in vivo cellular uptake and toxicity data into the model improved toxicity assessment of AuNP. Conclusion: These results partially explain the current low translation rate of nanotechnology-based drug delivery systems from mice to humans. This simulation approach may be applied to other nanomaterials and provides guidance to design future translational studies.

Nanotechnology in the war against cancer: new arms against an old enemy – a clinical view

ABSTRACT 

Clinical oncology is facing a paradigm shift. A new treatment philosophy is emerging and new targets are appearing that require new active agents. The medical use of nanotechnology – nanomedicine – holds several promising possibilities in the war against cancer. Some of these include: new formats for old drugs, that is, increasing efficacy while diminishing side effects; and new administration routes – that is, dermal, oral and pulmonary. In this overview, we describe some nanoparticles and their medical uses as well as highlight advantages of nanoparticles compared with conventional pharmaceuticals. We also point to some of the many technical challenges and potential risks with using nanotechnology for oncological applications.

Design attributes of long-circulating polymeric drug delivery vehicles

Following systemic administration polymeric drug delivery vehicles allow for a controlled and targeted release of the encapsulated medication at the desired site of action. For an elevated and organ specific accumulation of their cargo, nanocarriers need to avoid opsonization, activation of the complement system and uptake by macrophages of the mononuclear phagocyte system. In this respect, camouflaged vehicles revealed a delayed elimination from systemic circulation and an improved target organ deposition. For instance, a steric shielding of the carrier surface by poly(ethylene glycol) substantially decreased interactions with the biological environment. However, recent studies disclosed possible deficits of this approach, where most notably, poly(ethylene glycol)-modified drug delivery vehicles caused significant immune responses. At present, identification of novel potential carrier coating strategies facilitating negligible immune reactions is an emerging field of interest in drug delivery research. Moreover, physical carrier properties including geometry and elasticity seem to be very promising design attributes to surpass numerous biological barriers, in order to improve the efficacy of the delivered medication.

Gold and silver nanoparticle interactions with human proteins: impact and implications in biocorona formation

Metallic NP interaction with human proteins, biocorona formation and their impact on cellular uptake.

The nanoparticle biomolecule corona: lessons learned – challenge accepted?

Besides the wide use of engineered nanomaterials (NMs) in technical products, their applications are not only increasing in biotechnology and biomedicine, but also in the environmental field.