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

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.

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.

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.

PEGylated Gold Nanoparticles Target Age-Associated B Cells In Vivo

Engineered gold nanoparticles (GNPs) have become a useful tool in various therapeutic and diagnostic applications. Uncertainty remains regarding the possible impact of GNPs on the immune system. In this regard, we investigated the interactions of polymer-coated GNPs with B cells and their functions in mice. Surprisingly, we observed that polymer-coated GNPs mainly interact with the recently identified subpopulation of B lymphocytes named age-associated B cells (ABCs). Importantly, we also showed that GNPs did not affect cell viability or the percentages of other B cell populations in different organs. Furthermore, GNPs did not activate B cell innate-like immune responses in any of the tested conditions, nor did they impair adaptive B cell responses in immunized mice. Together, these data provide an important contribution to the otherwise limited knowledge about GNP interference with B cell immune function, and demonstrate that GNPs represent a safe tool to target ABCs in vivo for potential clinical applications.

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.

Generic prediction of exocytosis rate constants by size-based surface energies of nanoparticles and cells

Nanotechnology brings benefits in fields such as biomedicine but nanoparticles (NPs) may also have adverse health effects. The effects of surface-modified NPs at the cellular level have major implications for both medicine and toxicology. Semi-empirical and mechanism-based models aid to understand the cellular transport of various NPs and its implications for quantitatively biological exposure while avoiding large-scale experiments. We hypothesized relationships between NPs-cellular elimination, surface functionality and elimination pathways by cells. Surface free energy components were used to characterize the transport of NPs onto membranes and with lipid vesicles, covering both influences by size and hydrophobicity of NPs. The model was built based on properties of neutral NPs and cells, defining Van de Waals forces, electrostatic forces and Lewis acid-base (polar) interactions between NPs and vesicles as well as between vesicles and cell membranes. We yielded a generic model for estimating exocytosis rate constants of various neutral NPs by cells based on the vesicle-transported exocytosis pathways. Our results indicate that most models are well fitted (R² ranging from 0.61 to 0.98) and may provide good predictions of exocytosis rate constants for NPs with differing surface functionalities (prediction errors are within 2 times for macrophages). Exocytosis rates differ between cancerous cells with metastatic potential and non-cancerous cells. Our model provides a reference for cellular elimination of NPs, and intends for medical applications and risk assessment.

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.

In vivo bio-distribution and acute toxicity evaluation of greenly synthesized ultra-small gold nanoparticles with different biological activities

Ultra-small gold nanoparticles (Au-NPs) “≤ 10 nm diameters” have potent biomedical applications. Hence, the present study aimed to greenly synthesize ultra-small gold nanoparticles using Egyptian propolis extract. Different biological activities, in vivo bio-distribution and acute toxicity study were assessed. Results revealed that, Egyptian propolis extract can successfully synthesize the highly pure and stable ultra-small Au-NPs with average diameter 7.8 nm. In vitro antimicrobial and antimycobacterial activities revealed the powerful effect of the prepared Au-NPs. Moreover, the cytotoxic effect on human cancer cell lines revealed the potent inhibition of the cancer cells’ proliferation with high reactive oxygen species-mediated apoptosis induction. In vivo bio-distribution and acute toxicity studies were performed (10 and 100 mg/kg doses) in male albino rats. The ultra-small Au-NPs showed low or no toxicity upon using the Au-NPs low dose. The mean area accumulation (%) of the Au-NPs was higher in the liver, kidney, and brain tissues (4.41, 2.96, and 0.3 times, respectively) treated with high Au-NPs dosage compared to those treated with the low dose. Surprisingly, Au-NP accumulation in brain tissue was observed in the glial cells only. Accordingly, the low dose (10 mg/kg) of Au-NPs can be used safely in a variety of biomedical applications.

Ferritin-Nanocaged ATP Traverses the Blood-Testis Barrier and Enhances Sperm Motility in an Asthenozoospermia Model

Sperm motility can be enhanced by adding ATP exogenously during in vitro fertilization. However, administering exogenous ATP to the testis to improve sperm motility for in vivo asthenozoospermia treatment has not been investigated yet. Inspired by the recent advances in nanomedicine, we investigated whether the capability of drug delivery nanocarriers to traverse the blood-testis barrier (BTB) can facilitate ATP-dependent asthenozoospermia treatment. We found that the human H-ferritin (HFn) nanocarrier possesses the capability to traverse the BTB and specifically targets the head of elongated sperm cells. Specifically, the HFn nanocarrier traversed the BTB and accumulated in the sperm heads by binding with the HFn receptor (HFR), whose expression was relatively low in Sertoli cells but high in sperm heads. In a gossypol-induced mouse asthenozoospermia model, the administration of an ATP-loaded HFn nanocage through a tail vein injection significantly improved sperm motility. Moreover, the HFn nanocarrier was not toxic to mice in the short (1d) and long terms (30d, 90d) nor did it affect their reproductive health. Thus, the ATP-loaded HFn nanocarrier can potentially serve as a drug-delivery system for treating asthenozoospermia.

Pharmacokinetics of PEGylated Gold Nanoparticles: In Vitro-In Vivo Correlation

Data suitable for assembling a physiologically-based pharmacokinetic (PBPK) model for nanoparticles (NPs) remain relatively scarce. Therefore, there is a trend in extrapolating the results of in vitro and in silico studies to in vivo nanoparticle hazard and risk assessment. To evaluate the reliability of such approach, a pharmacokinetic study was performed using the same polyethylene glycol-coated gold nanoparticles (PEG-AuNPs) in vitro and in vivo. As in vitro models, human cell lines TH1, A549, Hep G2, and 16HBE were employed. The in vivo PEG-AuNP biodistribution was assessed in rats. The internalization and exclusion of PEG-AuNPs in vitro were modeled as first-order rate processes with the partition coefficient describing the equilibrium distribution. The pharmacokinetic parameters were obtained by fitting the model to the in vitro data and subsequently used for PBPK simulation in vivo. Notable differences were observed in the internalized amount of Au in individual cell lines compared to the corresponding tissues in vivo, with the highest found for renal TH1 cells and kidneys. The main reason for these discrepancies is the absence of natural barriers in the in vitro conditions. Therefore, caution should be exercised when extrapolating in vitro data to predict the in vivo NP burden and response to exposure.

Machine Learning Models for Predicting Cytotoxicity of Nanomaterials

The wide application of nanomaterials in consumer and medical products has raised concerns about their potential adverse effects on human health. Thus, more and more biological assessments regarding the toxicity of nanomaterials have been performed. However, the different ways the evaluations were performed, such as the utilized assays, cell lines, and the differences of the produced nanoparticles, make it difficult for scientists to analyze and effectively compare toxicities of nanomaterials. Fortunately, machine learning has emerged as a powerful tool for the prediction of nanotoxicity based on the available data. Among different types of toxicity assessments, nanomaterial cytotoxicity was the focus here because of the high sensitivity of cytotoxicity assessment to different treatments without the need for complicated and time-consuming procedures. In this review, we summarized recent studies that focused on the development of machine learning models for prediction of cytotoxicity of nanomaterials. The goal was to provide insight into predicting potential nanomaterial toxicity and promoting the development of safe nanomaterials.

Development of a Gestational and Lactational Physiologically Based Pharmacokinetic (PBPK) Model for Perfluorooctane Sulfonate (PFOS) in Rats and Humans and Its Implications in the Derivation of Health-Based Toxicity Values

BACKGROUND

There is a great concern on potential adverse effects of exposure to perfluorooctane sulfonate (PFOS) in sensitive subpopulations, such as pregnant women, fetuses, and neonates, due to its reported transplacental and lactational transfer and reproductive and developmental toxicities in animals and humans.

OBJECTIVES

This study aimed to develop a gestational and lactational physiologically based pharmacokinetic (PBPK) model in rats and humans for PFOS to aid risk assessment in sensitive human subpopulations.

METHODS

Based upon existing PBPK models for PFOS, the present model addressed a data gap of including a physiologically based description of basolateral and apical membrane transporter-mediated renal reabsorption and excretion in kidneys during gestation and lactation. The model was calibrated with published rat toxicokinetic and human biomonitoring data and was independently evaluated with separate data. Monte Carlo simulation was used to address the interindividual variability.

RESULTS

Model simulations were generally within 2-fold of observed PFOS concentrations in maternal/fetal/neonatal plasma and liver in rats and humans. Estimated fifth percentile human equivalent doses (HEDs) based on selected critical toxicity studies in rats following U.S. Environmental Protection Agency (EPA) guidelines ranged from 0.08 to 0.91 μ g / kg  per day . These values are lower than the HEDs estimated in U.S. EPA guidance (0.51 - 1.6 μ g / kg  per day ) using an empirical toxicokinetic model in adults.

CONCLUSIONS

The results support the importance of renal reabsorption/excretion during pregnancy and lactation in PFOS dosimetry and suggest that the derivation of health-based toxicity values based on developmental toxicity studies should consider gestational/lactational dosimetry estimated from a life stage-appropriate PBPK model. This study provides a quantitative tool to aid risk reevaluation of PFOS, especially in sensitive human subpopulations, and it provides a basis for extrapolating to other per- and polyfluoroalkyl substances (PFAS). All model codes and detailed tutorials are provided in the Supplemental Materials to allow readers to reproduce our results and to use this model. https://doi.org/10.1289/EHP7671.

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.

Probabilistic human health risk assessment of perfluorooctane sulfonate (PFOS) by integrating in vitro, in vivo toxicity, and human epidemiological studies using a Bayesian-based dose-response assessment coupled with physiologically based pharmacokinetic (PBPK) modeling approach

BACKGROUND

Environmental exposure to perfluorooctane sulfonate (PFOS) is associated with various adverse outcomes in humans. However, risk assessment for PFOS with the traditional risk estimation method is faced with multiple challenges because there are high variabilities and uncertainties in its toxicokinetics and toxicity between species and among different types of studies.

OBJECTIVES

This study aimed to develop a robust probabilistic risk assessment framework accounting for interspecies and inter-experiment variabilities and uncertainties to derive the human equivalent dose (HED) and reference dose for PFOS.

METHODS

A Bayesian dose-response model was developed to analyze selected 34 critical studies, including human epidemiological, animal in vivo, and ToxCast in vitro toxicity datasets. The dose-response results were incorporated into a multi-species physiologically based pharmacokinetic (PBPK) model to reduce the toxicokinetic/toxicodynamic variabilities. In addition, a population-based probabilistic risk assessment of PFOS was performed for Asian, Australian, European, and North American populations, respectively, based on reported environmental exposure levels.

RESULTS

The 5th percentile of HEDs derived from selected studies was estimated to be 21.5 (95% CI: 10.6-36.3) ng/kg/day. After exposure to environmental levels of PFOS, around 50% of the population in all studied populations would likely have >20% of increase in serum cholesterol, but the effects on other endpoints were estimated to be minimal (<10% changes). There was a small population (~10% of the population) that was highly sensitive to endocrine disruption and cellular response by environmental PFOS exposure.

CONCLUSION

Our results provide insights into a complete risk characterization of PFOS and may help regulatory agencies in the reevaluation of PFOS risk. Our new probabilistic approach can conduct dose-response analysis of different types of toxicity studies simultaneously and this method could be used to improve risk assessment for other perfluoroalkyl substances (PFAS).

An integrated pathway based on in vitro data for the human hazard assessment of nanomaterials

In line with the 3R concept, nanotoxicology is shifting from a phenomenological to a mechanistic approach based on in vitro and in silico methods, with a consequent reduction in animal testing. Risk Assessment (RA) and Life Cycle Assessment (LCA) methodologies, which traditionally rely on in vivo toxicity studies, will not be able to keep up with the pace of development of new nanomaterials unless they adapt to use this new type of data. While tools and models are already available and show a great potential for future use in RA and LCA, currently none is able alone to quantitatively assess human hazards (i.e. calculate chronic NOAEL or ED₅₀ values). By highlighting which models and approaches can be used in a quantitative way with the available knowledge and data, we propose an integrated pathway for the use of in vitro data in RA and LCA. Starting with the characterization of nanoparticles' properties, the pathway then investigates how to select relevant in vitro human data, and how to bridge in vitro dose-response relationships to in vivo effects. If verified, this approach would allow RA and LCA to stir up the development of nanotoxicology by giving indications about the data and quality requirements needed in risk methodologies.

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.

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.

Bayesian evaluation of a physiologically based pharmacokinetic (PBPK) model for perfluorooctane sulfonate (PFOS) to characterize the interspecies uncertainty between mice, rats, monkeys, and humans: Development and performance verification

A challenge in the risk assessment of perfluorooctane sulfonate (PFOS) is the large interspecies differences in its toxicokinetics that results in substantial uncertainty in the dosimetry and toxicity extrapolation from animals to humans. To address this challenge, the objective of this study was to develop an open-source physiologically based pharmacokinetic (PBPK) model accounting for species-specific toxicokinetic parameters of PFOS. Considering available knowledge about the toxicokinetic properties of PFOS, a PBPK model for PFOS in mice, rats, monkeys, and humans after intravenous and oral administrations was created. Available species-specific toxicokinetic data were used for model calibration and optimization, and independent datasets were used for model evaluation. Bayesian statistical analysis using Markov chain Monte Carlo (MCMC) simulation was performed to optimize the model and to characterize the uncertainty and interspecies variability of chemical-specific parameters. The model predictions well correlated with the majority of datasets for all four species, and the model was validated with independent data in rats, monkeys, and humans. The model was applied to predict human equivalent doses (HEDs) based on reported points of departure in selected critical toxicity studies in rats and monkeys following U.S. EPA's guidelines. The lower bounds of the model-derived HEDs were overall lower than the HEDs estimated by U.S. EPA (e.g., 0.2 vs. 1.3 μg/kg/day based on the rat plasma data). This integrated and comparative analysis provides an important step towards improving interspecies extrapolation and quantitative risk assessment of PFOS, and this open-source model provides a foundation for developing models for other perfluoroalkyl substances.

An integrated experimental and physiologically based pharmacokinetic modeling study of penicillin G in heavy sows

Penicillin G is widely used in food-producing animals at extralabel doses and is one of the most frequently identified violative drug residues in animal-derived food products. In this study, the plasma pharmacokinetics and tissue residue depletion of penicillin G in heavy sows after repeated intramuscular administrations at label (6.5 mg/kg) and 5 × label (32.5 mg/kg) doses were determined. Plasma, urine, and environmental samples were tested as potential antemortem markers for penicillin G residues. The collected new data and other available data from the literature were used to develop a population physiologically based pharmacokinetic (PBPK) model for penicillin G in heavy sows. The results showed that antemortem testing of urine provided potential correlation with tissue residue levels. Based on the United States Department of Agriculture Food Safety and Inspection Service action limit of 25 ng/g, the model estimated a withdrawal interval of 38 days for penicillin G in heavy sows after 3 repeated intramuscular injections at 5 × label dose. This study improves our understanding of penicillin G pharmacokinetics and tissue residue depletion in heavy sows and provides a tool to predict proper withdrawal intervals after extralabel use of penicillin G in heavy sows, thereby helping safety assessment of sow-derived meat products.

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.

Modeling gold nanoparticle biodistribution after arterial infusion into perfused tissue: effects of surface coating, size and protein corona

A detailed understanding of the factors governing nanomaterial biodistribution is needed to rationally design safe nanomedicines. This research details the pharmacokinetics of gold nanoparticle (AuNP) biodistribution after arterial infusion of 40 or 80 nm AuNP (1 μg/ml) into the isolated perfused porcine skin flap (IPPSF). AuNP had surface coatings consisting of neutral polyethylene glycol (PEG), anionic lipoic acid (LA), or cationic branched polyethylenimine (BPEI). Effect of a porcine plasma corona (PPC) on 40 nm BPEI and PEG-AuNP were assessed in the IPPSF. Au concentrations were determined by ICP/MS and arterial to venous concentration-time profiles were analyzed over 8 hr (4 hr infusion, 4 hr washout) using a two-compartment pharmacokinetic model. IPPSF viability and vascular function were assessed by change in glucose utilization, vascular resistance, or weight gain after perfusion. All AuNP demonstrated some degree of AuNP arterial extraction and skin flap retention, as well as enhanced kinetic parameters of tissue uptake; with BPEI-AuNP consistently having the greatest biodistribution even with a PPC. Toxicological effects were not detected. Transmission electron microscopy confirmed intracellular uptake of AuNP. These studies paralleled previous in vitro cell culture studies using the same AuNP in human endothelial and renal proximal tubule cells, hepatocytes, keratinocytes, showing BPEI-AuNP having the greatest uptake, although the presence of a PPC did not reduce IPPSF biodistribution as in the cell culture studies. These findings clearly indicate arterial to the venous extraction of AuNP after infusion with the magnitude of extraction being greatest with the BPEI surface coating and provide data and model structure necessary to construct the whole body physiologically based pharmacokinetic models capable of utilizing available in vitro data.