Comparison of in vitro membrane permeabilities of diverse environmental chemicals with in silico predictions.

The parallel artificial membrane permeability assay (PAMPA) is widely used for estimating biomembrane permeabilities of experimental drugs in pharmaceutical research. However, there are few reports of studies using PAMPA to measure membrane permeabilities of chemicals of environmental concern (CECs) outside the pharmaceutical domain, many of which differ substantially from drugs in their physicochemical properties. We applied PAMPA methods simulating gastrointestinal (PAMPA-GIT) and blood-brain barrier (PAMPA-BBB) membranes under consistent conditions to 51 CECs, including some pharmaceuticals. A backward stepwise multivariate linear regression was implemented to explore the correlation between the differences of measured permeabilities from PAMPA-GIT and PAMPA-BBB and Abraham solute descriptors. In addition, a previously reported in silico model was evaluated by comparing predicted and measured permeability results. PAMPA-GIT and PAMPA-BBB experimental permeability results agreed relatively well. The backward stepwise multivariate linear regression identified excess molar refraction and polarizability to be significant at the 0.10 level in predicting the differences between PAMPA-GIT and PAMPA-BBB. The in silico model performed well - with predicted permeability of most compounds within two-fold of experimentally measured values. We found that CECs pose experimental challenges to the PAMPA method in terms of having lower solubility and lower stability compared to most drugs.

Parameter grouping and co-estimation in physiologically based kinetic models using genetic algorithms.

Physiologically based kinetic (PBK) models are widely used in pharmacology and toxicology for predicting the internal disposition of substances upon exposure, voluntarily or not. Due to their complexity, a large number of model parameters need to be estimated, either through in silico tools, in vitro experiments, or by fitting the model to in vivo data. In the latter case, fitting complex structural models on in vivo data can result in overparameterization and produce unrealistic parameter estimates. To address these issues, we propose a novel parameter grouping approach, which reduces the parametric space by co-estimating groups of parameters across compartments. Grouping of parameters is performed using genetic algorithms and is fully automated, based on a novel goodness-of-fit metric. To illustrate the practical application of the proposed methodology, two case studies were conducted. The first case study demonstrates the development of a new PBK model, while the second focuses on model refinement. In the first case study, a PBK model was developed to elucidate the biodistribution of titanium dioxide (TiO2) nanoparticles in rats following intravenous injection. A variety of parameter estimation schemes were employed. Comparative analysis based on goodness-of-fit metrics demonstrated that the proposed methodology yields models that outperform standard estimation approaches, while utilizing a reduced number of parameters. In the second case study, an existing PBK model for perfluorooctanoic acid (PFOA) in rats was extended to incorporate additional tissues, providing a more comprehensive portrayal of PFOA biodistribution. Both models were validated through independent in vivo studies to ensure their reliability.

Assessing disparities in Americans' exposure to PCBs and PBDEs based on NHANES pooled biomonitoring data.

The National Health and Nutrition Examination Survey (NHANES) has been continuously biomonitoring Americans' exposure to two families of harmful environmental chemicals: polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs). However, biomonitoring these chemicals is expensive. To save cost, in 2005, NHANES resorted to pooled biomonitoring; i.e., amalgamating individual specimens to form a pool and measuring chemical levels from pools. Despite being publicly available, these pooled data gain limited applications in health studies. Among the few studies using these data, racial/age disparities were detected, but there is no control for confounding effects. These disadvantages are due to the complexity of pooled measurements and a dearth of statistical tools. Herein, we developed a regression-based method to unzip pooled measurements, which facilitated a comprehensive assessment of disparities in exposure to these chemicals. We found increasing dependence of PCBs on age and income, whereas PBDEs were the highest among adolescents and seniors and were elevated among the low-income population. In addition, Hispanics had the lowest PCBs and PBDEs among all demographic groups after controlling for potential confounders. These findings can guide the development of population-specific interventions to promote environmental justice. Moreover, both chemical levels declined throughout the period, indicating the effectiveness of existing regulatory policies.

Explore the Dosimetric Relationship between the Intake of Chemical Contaminants and Their Occurrence in Blood and Urine.

The dosimetric relationship between the human intake dose of a chemical contaminant (an "external dose") and its concentrations in bodily fluids such as blood and urine (related to an "internal dose"), often characterized by a dose-to-concentration ratio, has critical applications in exposure science, toxicology, and risk assessment, especially in the "new approach methods" era. However, there is a lack of a mechanistic, systematic understanding of how such a dosimetric relationship depends on fundamental chemical properties, such as partition coefficients and biotransformation half-lives. Here, we investigate this issue using a well-evaluated toxicokinetic model, which links external and internal doses by quantifying the absorption and elimination of chemicals. Results are visualized in a series of chemical partitioning space plots, whereby a chemical's dose-to-concentration ratio can be approximately predicted based on its partitioning between air, water, and octanol phases. Our results indicate that when taken in equal doses, chemicals with low volatility and moderate to high hydrophobicity exhibit the highest concentrations in the blood, and chemicals undergoing significant biotransformation tend to exhibit lower concentrations in comparison to their counterparts undergoing negligible biotransformation but possessing similar partitioning properties. Chemicals with high hydrophilicity have the highest concentrations in urine. Such revealed property dependence is similar for both adults and children and for individuals with normal body weights and with obesity. Overall, insights gained from this study are important in predicting blood and urinary concentrations from exposure information and in determining the exposure rate that produces the blood or urinary concentrations observed in biomonitoring studies.

Quaternary Ammonium Compounds: A Chemical Class of Emerging Concern.

Quaternary ammonium compounds (QACs), a large class of chemicals that includes high production volume substances, have been used for decades as antimicrobials, preservatives, and antistatic agents and for other functions in cleaning, disinfecting, personal care products, and durable consumer goods. QAC use has accelerated in response to the COVID-19 pandemic and the banning of 19 antimicrobials from several personal care products by the US Food and Drug Administration in 2016. Studies conducted before and after the onset of the pandemic indicate increased human exposure to QACs. Environmental releases of these chemicals have also increased. Emerging information on adverse environmental and human health impacts of QACs is motivating a reconsideration of the risks and benefits across the life cycle of their production, use, and disposal. This work presents a critical review of the literature and scientific perspective developed by a multidisciplinary, multi-institutional team of authors from academia, governmental, and nonprofit organizations. The review evaluates currently available information on the ecological and human health profile of QACs and identifies multiple areas of potential concern. Adverse ecological effects include acute and chronic toxicity to susceptible aquatic organisms, with concentrations of some QACs approaching levels of concern. Suspected or known adverse health outcomes include dermal and respiratory effects, developmental and reproductive toxicity, disruption of metabolic function such as lipid homeostasis, and impairment of mitochondrial function. QACs' role in antimicrobial resistance has also been demonstrated. In the US regulatory system, how a QAC is managed depends on how it is used, for example in pesticides or personal care products. This can result in the same QACs receiving different degrees of scrutiny depending on the use and the agency regulating it. Further, the US Environmental Protection Agency's current method of grouping QACs based on structure, first proposed in 1988, is insufficient to address the wide range of QAC chemistries, potential toxicities, and exposure scenarios. Consequently, exposures to common mixtures of QACs and from multiple sources remain largely unassessed. Some restrictions on the use of QACs have been implemented in the US and elsewhere, primarily focused on personal care products. Assessing the risks posed by QACs is hampered by their vast structural diversity and a lack of quantitative data on exposure and toxicity for the majority of these compounds. This review identifies important data gaps and provides research and policy recommendations for preserving the utility of QAC chemistries while also seeking to limit adverse environmental and human health effects.

In silico model-based exploration of the applicability of parallel artificial membrane permeability assay (PAMPA) to screen chemicals of environmental concern.

Parallel Artificial Membrane Permeability Assay (PAMPA) is an in vitro laboratory method for screening the transmembrane permeability of chemicals. Stemming from medicinal chemistry, PAMPA has the potential for use in the cost-effective high-throughput evaluation of chemicals of environmental concern. However, many chemicals of environmental concern differ substantially from pharmaceuticals in hydrophobicity and volatility. Here, we develop an in silico mass balance model to explore the impacts of chemical properties on chemical mass transfer in PAMPA and PAMPA's applicability to hydrophobic or volatile chemicals of environmental concern. The model's performance is evaluated by agreement between predicted and measured permeabilities of 1383 chemicals. The model predicts that the PAMPA measured permeability can be highly uncertain for hydrophobic chemicals because of considerable retention by the artificial membrane and for volatile chemicals because of substantial volatilization to the headspace. Notably, the permeabilities of hydrophobic chemicals are remarkably sensitive to specific experimental conditions, for example, the frequency of stirring and incubation time, challenging the comparison between measurements under different conditions. For hydrophobic chemicals, the PAMPA measured permeability may largely indicate the permeability of the unstirred water layer over the membrane, instead of the "intrinsic" permeability of the membrane, and therefore, may not be of interest for environmental exposure and risk assessments. The model also predicts that the time for mass transfer of highly hydrophobic chemicals to reach the steady state likely exceeds the incubation time, which violates the steady-state assumption used in calculating permeability from measured concentrations. Overall, our theoretical analysis underscores the importance to consider chemical properties when applying the current design of PAMPA to chemicals of environmental concern.

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.

Accelerating the pace of ecotoxicological assessment using artificial intelligence.

Species Sensitivity Distribution (SSD) is a key metric for understanding the potential ecotoxicological impacts of chemicals. However, SSDs have been developed to estimate for only handful of chemicals due to the scarcity of experimental toxicity data. Here we present a novel approach to expand the chemical coverage of SSDs using Artificial Neural Network (ANN). We collected over 2000 experimental toxicity data in Lethal Concentration 50 (LC50) for 8 aquatic species and trained an ANN model for each of the 8 aquatic species based on molecular structure. The R2 values of resulting ANN models range from 0.54 to 0.75 (median R2 = 0.69). We applied the predicted LC50 values to fit SSD curves using bootstrapping method, generating SSDs for 8424 chemicals in the ToX21 database. The dataset is expected to serve as a screening-level reference SSD database for understanding potential ecotoxicological impacts of chemicals.

A cross-sectional analysis of associations between environmental indices and asthma in U.S. counties from 2003 to 2012.

BACKGROUND: To capture the impacts of environmental stressors, environmental indices like the Air Quality Index, Toxic Release Inventory, and Environmental Quality Index have been used to investigate the environmental quality and its association with public health issues. However, past studies often rely on relatively small sample sizes, and they have typically not adjusted for important individual-level disease risk factors. OBJECTIVE: We aim to estimate associations between existing environmental indices and asthma prevalence over a large population and multiple years. METHODS: Based on data availability, we assessed the predictive capability of these indices for prevalent asthma across U.S. counties from 2003 to 2012. We gathered asthma data from the U.S. CDC Behavioral Risk Factor Surveillance System by county and used multivariable weighted logistic regression models to estimate the associations between the environmental indices and asthma, adjusting for individual factors such as smoking, income level, and obesity. RESULTS: Environmental indices showed little to no correlation with one another and with prevalent asthma over time. Associations of environmental indices with prevalent asthma were very weak; whereas individual factors were more substantially associated with prevalent asthma. SIGNIFICANCE: Our study suggests that an improved environmental index is needed to predict population-level asthma prevalence.

Human Chemical Exposure from Background Emissions in the United States and the Implication for Quantifying Risks from Marginal Emission Increase.

The linear dose-response relationship has long been assumed in assessments of health risk from an incremental chemical emission relative to background emissions. In this study, we systematically examine the relevancy of such an assumption with real-world data. We used the reported emission data, as background emissions, from the 2017 U.S. National Emission Inventory for 95 organic chemicals to estimate the central tendencies of exposures of the general U.S. population. Previously published nonlinear dose-response relationships for chemicals were used to estimate health risk from exposure. We also explored and identified four intervals of exposure in which the nonlinear dose-response relationship may be linearly approximated with fixed slopes. Predicted rates of exposure to these 95 chemicals are all within the lowest of the four intervals and associated with low health risk. The health risk may be overestimated if a slope on the dose-response relationship extrapolated from toxicological assays based on high response rates is used for a marginal increase in emission not substantially higher than background emissions. To improve the confidence of human health risk estimates for chemicals, future efforts should focus on deriving a more accurate dose-response relationship at lower response rates and interface it with exposure assessments.

Evaluating consumer exposure to disinfecting chemicals against coronavirus disease 2019 (COVID-19) and associated health risks.

Disinfection of surfaces has been recommended as one of the most effective ways to combat the spread of novel coronavirus (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, overexposure to disinfecting chemicals may lead to unintended human health risks. Here, using an indoor fate and chemical exposure model, we estimate human exposure to 22 disinfecting chemicals on the lists recommended by various governmental agencies against COVID-19, resulting from contact with disinfected surfaces and handwashing. Three near-field exposure routes, i.e., mouthing-mediated oral ingestion, inhalation, and dermal absorption, are considered to calculate the whole-body uptake doses and blood concentrations caused by single use per day for three age groups (3, 14, and 24-year-old). We also assess the health risks by comparing the predicted whole-body uptake doses with in vivo toxicological data and the predicted blood concentrations with in vitro bioactivity data. Our results indicate that both the total exposure and relative contribution of each exposure route vary considerably among the disinfecting chemicals due to their diverse physicochemical properties. 3-year-old children have consistent higher exposure than other age groups, especially in the scenario of contact with disinfected surfaces, due to their more frequent hand contact and mouthing activities. Due to the short duration of handwashing, we do not expect any health risk from the use of disinfecting chemicals in handwashing. In contrast, exposure from contact with disinfected surfaces may result in health risks for certain age groups especially children, even the surfaces are disinfected once a day. Interestingly, risk assessments based on whole-body uptake doses and in vivo toxicological data tend to give higher risk estimates than do those based on blood concentrations and in vitro bioactivity data. Our results reveal the most important exposure routes for disinfecting chemicals used in the indoor environment; they also highlight the need for more accurate data for both chemical properties and toxicity to better understand the risks associated with the increased use of disinfecting chemicals in the pandemic.

Health risks of chemicals in consumer products: A review.

Increasingly diverse chemicals are used in consumer products, while our understanding of their exposure pathways and associated human health risks still lags behind. This paper aims to identify the dominant patterns of exposure pathways and associated health risks of chemicals used in consumer products reported in the peer-reviewed literature. We analyzed 342 articles covering 202 unique chemicals, and distilled the information on the functional uses, product applications, exposure routes, exposure pathways, toxicity endpoints and their combinations. We found that the volume of the literature addressing human health risks of chemicals in consumer products is increasing. Among others, phthalates, bisphenol-A, and polybrominated diphenyl ethers were the most frequently discussed chemical groups in the literature reviewed. Emerged from our review were a number of frequently reported functional use/product application combinations, including plasticizers, polymers/monomers, and flame retardants used in food contact products, personal care products, cosmetics, furniture, flooring, and electronics. We also observed a strong tendency that the number of publications on a chemical surges following major regulatory changes or exposure incidents associated with the chemical. We highlight the need to develop the capacity and the mechanism through which human health risks of chemicals in consumer products can be identified prior to their releases.

Advancements in Life Cycle Human Exposure and Toxicity Characterization.

BACKGROUND: The Life Cycle Initiative, hosted at the United Nations Environment Programme, selected human toxicity impacts from exposure to chemical substances as an impact category that requires global guidance to overcome current assessment challenges. The initiative leadership established the Human Toxicity Task Force to develop guidance on assessing human exposure and toxicity impacts. Based on input gathered at three workshops addressing the main current scientific challenges and questions, the task force built a roadmap for advancing human toxicity characterization, primarily for use in life cycle impact assessment (LCIA). OBJECTIVES: The present paper aims at reporting on the outcomes of the task force workshops along with interpretation of how these outcomes will impact the practice and reliability of toxicity characterization. The task force thereby focuses on two major issues that emerged from the workshops, namely considering near-field exposures and improving dose­response modeling. DISCUSSION: The task force recommended approaches to improve the assessment of human exposure, including capturing missing exposure settings and human receptor pathways by coupling additional fate and exposure processes in consumer and occupational environments (near field) with existing processes in outdoor environments (far field). To quantify overall aggregate exposure, the task force suggested that environments be coupled using a consistent set of quantified chemical mass fractions transferred among environmental compartments. With respect to dose­response, the task force was concerned about the way LCIA currently characterizes human toxicity effects, and discussed several potential solutions. A specific concern is the use of a (linear) dose­response extrapolation to zero. Another concern addresses the challenge of identifying a metric for human toxicity impacts that is aligned with the spatiotemporal resolution of present LCIA methodology, yet is adequate to indicate health impact potential. CONCLUSIONS: Further research efforts are required based on our proposed set of recommendations for improving the characterization of human exposure and toxicity impacts in LCIA and other comparative assessment frameworks. https://doi.org/10.1289/EHP3871.

OrganoRelease - A framework for modeling the release of organic chemicals from the use and post-use of consumer products.

Chemicals in consumer products have become the focus of recent regulatory developments including California's Safer Consumer Products Act. However, quantifying the amount of chemicals released during the use and post-use phases of consumer products is challenging, limiting the ability to understand their impacts. Here we present a comprehensive framework, OrganoRelease, for estimating the release of organic chemicals from the use and post-use of consumer products given limited information. First, a novel Chemical Functional Use Classifier estimates functional uses based on chemical structure. Second, the quantity of chemicals entering different product streams is estimated based on market share data of the chemical functional uses. Third, chemical releases are estimated based on either chemical product categories or functional uses by using the Specific Environmental Release Categories and EU Technological Guidance Documents. OrganoRelease connects 19 unique functional uses and 14 product categories across 4 data sources and provides multiple pathways for chemical release estimation. Available user information can be incorporated in the framework at various stages. The Chemical Functional Use Classifier achieved an average accuracy above 84% for nine functional uses, which enables the OrganoRelease to provide release estimates for the chemical, mostly using only the molecular structure. The results can be can be used as input for methods estimating environmental fate and exposure.

In vivo biodistribution and physiologically based pharmacokinetic modeling of inhaled fresh and aged cerium oxide nanoparticles in rats.

BACKGROUND: Cerium oxide (CeO2) nanoparticles used as a diesel fuel additive can be emitted into the ambient air leading to human inhalation. Although biological studies have shown CeO2 nanoparticles can cause adverse health effects, the extent of the biodistribution of CeO2 nanoparticles through inhalation has not been well characterized. Furthermore, freshly emitted CeO2 nanoparticles can undergo an aging process by interaction with other ambient airborne pollutants that may influence the biodistribution after inhalation. Therefore, understanding the pharmacokinetic of newly-generated and atmospherically-aged CeO2 nanoparticles is needed to assess the risks to human health. METHODS: A novel experimental system was designed to integrate the generation, aging, and inhalation exposure of Sprague Dawley rats to combustion-generated CeO2 nanoparticles (25 and 90 nm bimodal distribution). Aging was done in a chamber representing typical ambient urban air conditions with UV lights. Following a single 4-hour nose-only exposure to freshly emitted or aged CeO2 for 15 min, 24 h, and 7 days, ICP-MS detection of Ce in the blood, lungs, gastrointestinal tract, liver, spleen, kidneys, heart, brain, olfactory bulb, urine, and feces were analyzed with a mass balance approach to gain an overarching understanding of the distribution. A physiologically based pharmacokinetic (PBPK) model that includes mucociliary clearance, phagocytosis, and entry into the systemic circulation by alveolar wall penetration was developed to predict the biodistribution kinetic of the inhaled CeO2 nanoparticles. RESULTS: Cerium was predominantly recovered in the lungs and feces, with extrapulmonary organs contributing less than 4 % to the recovery rate at 24 h post exposure. No significant differences in biodistribution patterns were found between fresh and aged CeO2 nanoparticles. The PBPK model predicted the biodistribution well and identified phagocytizing cells in the pulmonary region accountable for most of the nanoparticles not eliminated by feces. CONCLUSIONS: The biodistribution of fresh and aged CeO2 nanoparticles followed the same patterns, with the highest amounts recovered in the feces and lungs. The slow decrease of nanoparticle concentrations in the lungs can be explained by clearance to the gastrointestinal tract and then to the feces. The PBPK model successfully predicted the kinetic of CeO2 nanoparticles in various organs measured in this study and suggested most of the nanoparticles were captured by phagocytizing cells.

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.

Physiologically based pharmacokinetic modeling of polyethylene glycol-coated polyacrylamide nanoparticles in rats.

Nanoparticles' health risks depend on their biodistribution in the body. Phagocytosis may greatly affect this distribution but has not yet explicitly accounted for in whole body pharmacokinetic models. Here, we present a physiologically based pharmacokinetic model that includes phagocytosis of nanoparticles to explore the biodistribution of intravenously injected polyethylene glycol-coated polyacrylamide nanoparticles in rats. The model explains 97% of the observed variation in nanoparticles amounts across organs. According to the model, phagocytizing cells quickly capture nanoparticles until their saturation and thereby constitute a major reservoir in richly perfused organs (spleen, liver, bone marrow, lungs, heart and kidneys), storing 83% of the nanoparticles found in these organs 120 h after injection. Key determinants of the nanoparticles biodistribution are the uptake capacities of phagocytizing cells in organs, the partitioning between tissue and blood, and the permeability between capillary blood and tissues. This framework can be extended to other types of nanoparticles by adapting these determinants.

Combined toxicity of cadmium and lead on the earthworm Eisenia fetida (Annelida, Oligochaeta).

Cadmium (Cd) and lead (Pb) in soil have received extensive attention due to their potential toxicological effects. This study analyzed the combined toxicity of Cd and Pb on the earthworm Eisenia fetida. Cellulase activity and DNA damage were chosen as toxic endpoints. Factorial analysis was applied to identify the interaction of Cd and Pb. The results showed that single Pb and Cd could increase the cellulase activity and DNA damage of coelomocytes. The combination of both metals could significantly inhibit cellulase activity. For low Cd concentration, the addition of Pb could increase the DNA damage. However, for high Cd concentration, Pb could decrease the DNA damage. Factorial analysis showed that the changes of Cd concentrations exerted the highest influence on the combined toxicity, followed by factor "Cd*Pb" and "Pb". The combined toxicological effects between Cd and Pb were complex, which might be influenced by the competition adsorption of both metals in soil and biomembrane and their bioavailability. The results of this study are useful for understanding of combined toxicity of Cd and Pb on terrestrial invertebrates.