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This study describes the development and evaluation of six new models for predicting physical-chemical (PC) properties that are highly relevant for chemical hazard, exposure, and risk estimation: solubility (in water S W and octanol S O ), vapor pressure (VP), and the octanol-water (K OW ), octanol-air (K OA ), and air-water (K AW ) partition ratios. The models are implemented in the Iterative Fragment Selection Quantitative Structure-Activity Relationship (IFSQSAR) python package, Version 1.1.0. These models are implemented as Poly-Parameter Linear Free Energy Relationship (PPLFER) equations which combine experimentally calibrated system parameters and solute descriptors predicted with QSPRs. Two other ancillary models have been developed and implemented, a QSPR for Molar Volume (MV) and a classifier for the physical state of chemicals at room temperature. The IFSQSAR methods for characterizing applicability domain (AD) and calculating uncertainty estimates expressed as 95% prediction intervals (PI) for predicted properties are described and tested on 9,000 measured partition ratios and 4,000 VP and S W values. The measured data are external to IFSQSAR training and validation datasets and are used to assess the predictivity of the models for "novel chemicals" in an unbiased manner. The 95% PI intervals calculated from validation datasets for partition ratios needed to be scaled by a factor of 1.25 to capture 95% of the external data. Predictions for VP and S W are more uncertain, primarily due to the challenges in differentiating their physical state (i.e., liquids or solids) at room temperature. The prediction accuracy of the models for log K OW , log K AW and log K OA of novel, data-poor chemicals is estimated to be in the range of 0.7 to 1.4 root mean squared error of prediction (RMSEP), with RMSEP in the range 1.7-1.8 for log VP and log S W . Scientific contributionNew partitioning models integrate empirical PPLFER equations and QSARs, allowing for seamless integration of experimental data and model predictions. This work tests the real predictivity of the models for novel chemicals which are not in the model training or external validation datasets., (© 2024. The Author(s).)

Reliable estimation of chemical sorption from water to solid phases is an essential prerequisite for reasonable assessments of chemical hazards and risks. However, current fate and exposure models mostly rely on algorithms that lack the capability to quantify chemical sorption resulting from interactions with multiple soil constituents, including amorphous organic matter, carbonaceous organic matter, and mineral matter. Here, we introduce a novel, generic approach that explicitly combines the gravimetric composition of various solid constituents and poly-parameter linear free energy relationships to calculate the solid-water sorption coefficient ( K d ) for non-ionizable or predominantly neutral organic chemicals with diverse properties in a neutral environment. Our approach demonstrates an overall statistical uncertainty of approximately 0.9 log units associated with predictions for different types of soil. By applying this approach to estimate the sorption of 70 diverse chemicals from water to two types of soils, we uncover that different chemicals predominantly exhibit sorption onto different soil constituents. Moreover, we provide mechanistic insights into the limitation of relying solely on organic carbon normalized sorption coefficient ( K OC ) in chemical hazard assessment, as the measured K OC can vary significantly across different soil types, and therefore, a universal cut-off threshold may not be appropriate. This research highlights the importance of considering chemical properties and multiple solid constituents in sorption modeling and offers a valuable theoretical approach for improved chemical hazard and exposure assessments., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)

A significant number of chemicals registered in national and regional chemical inventories require assessments of their potential "hazard" concerns posed to humans and ecological receptors. This warrants knowledge of their partitioning and reactivity properties, which are often predicted by quantitative structure-property relationships (QSPRs) and other semiempirical relationships. It is imperative to evaluate the applicability domain (AD) of these tools to ensure their suitability for assessment purpose. Here, we investigate the extent to which the ADs of commonly used QSPRs and semiempirical relationships cover seven partitioning and reactivity properties of a chemical "space" comprising 81,000+ organic chemicals registered in regulatory and academic chemical inventories. Our findings show that around or more than half of the chemicals studied are covered by at least one of the commonly used QSPRs. The investigated QSPRs demonstrate adequate AD coverage for organochlorides and organobromines but limited AD coverage for chemicals containing fluorine and phosphorus. These QSPRs exhibit limited AD coverage for atmospheric reactivity, biodegradation, and octanol-air partitioning, particularly for ionizable organic chemicals compared to nonionizable ones, challenging assessments of environmental persistence, bioaccumulation capability, and long-range transport potential. We also find that a predictive tool's AD coverage of chemicals depends on how the AD is defined, for example, by the distance of a predicted chemical from the centroid of the training chemicals or by the presence or absence of structural features.

The Quantitative Structure Use Relationship (QSUR) Summit, held on November 2-4, 2022, focused on advancing the development, refinement, and use of QSURs to support chemical substance prioritization and risk assessment and mitigation. QSURs utilize chemical structures to predict the function of a chemical within a formulated product or an industrial process. This presumed function can then be used to develop chemical use categories or other information necessary to refine exposure assessments. The invited expert meeting was attended by 38 scientists from Canada, Finland, France, the UK, and the USA, representing government, business, and academia, with expertise in exposure science, chemical engineering, risk assessment, formulation chemistry, and machine learning. Workshop discussions emphasized the importance of collection and sharing of data and quantification of relative chemical quantities to progress QSUR development. Participants proposed collaborative approaches to address key challenges, including mechanisms for aggregating information while still protecting proprietary product composition and other confidential business information. Discussions also led to proposals for applications beyond exposure and risk modeling, including sustainable formulation discovery. In addition, discussions continue to construct, conduct, and circulate case studies tied to various specific problem formulations in which QSURs supply or derive information on chemical functions, concentrations, and exposures., Competing Interests: Declaration of competing interest Some authors received ACC-LRI funding as described above. A number of authors participated in the workshop and in the preparation of the manuscript as a part of their regular research activities supported by their employers. US government representatives received no ACC funding for this initiative. The contents of this manuscript are solely the responsibility of the authors and do not necessarily reflect the views or policies of their employers., (Copyright © 2023. Published by Elsevier Inc.)

Persistent and mobile (PM) chemicals are considered emerging threats to the environment and drinking water because they can be transported over long distances, penetrate natural and artificial barriers, and resist removal by traditional water treatment procedures. Current chemical regulatory frameworks raise concerns over PM chemicals due to their potential to cause high human exposure through drinking water contamination. However, the criteria used to screen and identify these chemicals often rely on hazard properties related to stability and sorption, such as biodegradation half-lives and organic-carbon-normalized sorption coefficients as respective measures of P and M. Here, we conduct a model-based assessment to examine the consistency between hazard-based and exposure-based approaches in assessing PM chemicals, by evaluating whether chemicals identified as highly P and M are consistently associated with high drinking water exposure potential (DWEP). We discover that chemicals with the top DWEPs tend to be PM chemicals, but the reverse is not always true, because DWEPs are also impacted by volatilization for air-distributed chemicals and advective particle-bound transport for particle-bound chemicals. Our findings suggest that the hazard metrics are better suited for de-prioritizing, as opposed to prioritizing, chemicals that are unlikely to result in significant human exposure through drinking water, as unfavorable values of hazard metrics are a necessary but not sufficient condition for a high DWEP. We also find that distinct mechanisms determine the DWEP in different sources of drinking water: Sorption and stability are more influential on the DWEP of chemicals in groundwater and surface water, respectively, whereas both sorption and stability equally impact water undergoing riverbank filtration. Future studies should focus on optimizing the identification of persistent and mobile chemicals to ensure that exposure potential is taken into consideration., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Li Li reports financial support was provided by European Chemical Industry Council. Todd Gouin reports financial support was provided by European Union Horizon 2020., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Bioaccumulation assessments conducted by regulatory agencies worldwide use a variety of methods, types of data, metrics, and categorization criteria. Lines of evidence (LoE) for bioaccumulation assessment can include bioaccumulation metrics such as in vivo bioconcentration factor (BCF) and biomagnification factor (BMF) data measured from standardized laboratory experiments, and field (monitoring) data such as BMFs, bioaccumulation factors (BAFs), and trophic magnification factors (TMFs). In silico predictions from mass-balance models and quantitative structure-activity relationships (QSARs) and a combination of in vitro biotransformation rates and in vitro-in vivo extrapolation (IVIVE) models can also be used. The myriad bioaccumulation metrics and categorization criteria and underlying uncertainty in measured or modeled data can make decision-making challenging. A weight of evidence (WoE) approach is recommended to address uncertainty. The Bioaccumulation Assessment Tool (BAT) guides a user through the process of collecting and generating various LoE required for assessing the bioaccumulation of neutral and ionizable organic chemicals in aquatic (water-respiring) and air-breathing organisms. The BAT includes data evaluation templates (DETs) to critically evaluate the reliability of the LoE used in the assessment. The DETs were developed from standardized testing guidance. The approach used in the BAT is consistent with OECD and SETAC WoE principles and facilitates the implementation of chemical policy objectives in chemical assessment and management. The recommended methods are also iterative and tiered, providing pragmatic methods to reduce unnecessary animal testing. General concepts of the BAT are presented and case study applications of the tool for hexachlorobenzene (HCB) and β-hexachlorocyclohexane (β-HCH) are demonstrated. The BAT provides a consistent and transparent WoE framework to address uncertainty in bioaccumulation assessment and is envisaged to evolve with scientific and regulatory developments. Integr Environ Assess Manag 2023;19:1235-1253. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)., (© 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).)

Surfactants are a class of chemicals released in large quantities to water, and therefore bioconcentration in fish is an important component of their safety assessment. Their structural diversity, which encompasses nonionic, anionic, cationic and zwitterionic molecules with a broad range of lipophilicity, makes their evaluation challenging. A strong influence of environmental pH adds a further layer of complexity to their bioconcentration assessment. Here we present a framework that penetrates this complexity. Using simple equations derived from current understanding of the relevant underlying processes, we plot the key bioconcentration parameters (uptake rate constant, elimination rate constant and bioconcentration factor) as a function of its membrane lipid/water distribution ratio and the neutral fraction of the chemical in water at pH 8.1 and at pH 6.1. On this chemical space plot, we indicate boundaries at which four resistance terms (perfusion with water, transcellular, paracellular, and perfusion with blood) limit transport of surfactants across the gills. We then show that the bioconcentration parameters predicted by this framework align well with in vivo measurements of anionic, cationic and nonionic surfactants in fish. In doing so, we demonstrate how the framework can be used to explore expected differences in bioconcentration behavior within a given sub-class of surfactants, to assess how pH will influence bioconcentration, to identify the underlying processes governing bioconcentration of a particular surfactant, and to discover knowledge gaps that require further research. This framework for amphiphilic chemicals may function as a template for improved understanding of the accumulation potential of other ionizable chemicals of environmental concern, such as pharmaceuticals or dyes.

Measured rates of in vitro intrinsic clearance for fish may be extrapolated to the whole animal as a means of estimating a whole-body biotransformation rate constant ( k B ; d -1 ). This estimate of k B can then be used as an input to existing bioaccumulation prediction models. Most in vitro - in vivo extrapolation / bioaccumulation (IVIVE/B) modeling efforts to date have focused on predicting the chemical bioconcentration in fish (aqueous only exposure), with less attention paid to dietary exposures. Following dietary uptake, biotransformation in the gut lumen, intestinal epithelia, and liver can reduce chemical accumulation; however, current IVIVE/B models do not consider these first pass clearance effects on dietary uptake. Here we present an amended IVIVE/B model that accounts for first pass clearance. The model is then used to examine how biotransformation in the liver and intestinal epithelia (alone or combined) may impact chemical accumulation that occurs during dietary exposure. First pass clearance by the liver can greatly reduce dietary uptake of contaminants, but these effects are only apparent at rapid rates of in vitro biotransformation (first order depletion rate constant k DEP ≥ 10 h -1 ). The impact of first pass clearance becomes more pronounced when biotransformation in the intestinal epithelia is included in the model. Modelled results suggest that biotransformation in the liver and intestinal epithelia cannot entirely explain reduced dietary uptake reported in several in vivo bioaccumulation tests. This unexplained reduction in dietary uptake is attributed to chemical degradation in the gut lumen. These findings underscore the need for research to directly investigate luminal biotransformation in fish.

Background: Threshold of Toxicological Concern (TTC) approaches are used for chemical safety assessment and risk-based priority setting for data poor chemicals. TTCs are derived from in vivo No Observed Effect Level (NOEL) datasets involving an external administered dose from a single exposure route, e.g., oral intake rate. Thus, a route-specific TTC can only be compared to a route-specific exposure estimate and such TTCs cannot be used for other exposure scenarios such as aggregate exposures., Objective: Develop and apply a method for deriving internal TTCs (iTTCs) that can be used in chemical assessments for multiple route-specific exposures (e.g., oral, inhalation or dermal) or aggregate exposures., Methods: Chemical-specific toxicokinetics (TK) data and models are applied to calculate internal concentrations (whole-body and blood) from the reported administered oral dose NOELs used to derive the Munro TTCs. The new iTTCs are calculated from the 5th percentile of cumulative distributions of internal NOELs and the commonly applied uncertainty factor of 100 to extrapolate animal testing data for applications in human health assessment., Results: The new iTTCs for whole-body and blood are 0.5 nmol/kg and 0.1 nmol/L, respectively. Because the iTTCs are expressed on a molar basis they are readily converted to chemical mass iTTCs using the molar mass of the chemical of interest. For example, the median molar mass in the dataset is 220 g/mol corresponding to an iTTC of 22 ng/L-blood (22 pg/mL-blood). The iTTCs are considered broadly applicable for many organic chemicals except those that are genotoxic or acetylcholinesterase inhibitors. The new iTTCs can be compared with measured or estimated whole-body or blood exposure concentrations for chemical safety screening and priority-setting., Significance: Existing Threshold of Toxicological Concern (TTC) approaches are limited in their applications for route-specific exposure scenarios only and are not suitable for chemical risk and safety assessments under conditions of aggregate exposure. New internal Threshold of Toxicological Concern (iTTC) values are developed to address data gaps in chemical safety estimation for multi-route and aggregate exposures., (© 2022. The Author(s).)

The National Pollutant Release Inventory (NPRI) is a Canadian inventory of facility-reported data on releases, transfers, and disposals of over 300 pollutants, but it does not contain information on chemical properties or other characteristics critical to understanding environmental and human health risks. To reconcile this gap, we use the Risk Assessment IDentification And Ranking (RAIDAR) model to integrate NPRI release data with chemical property information in a multimedia mass balance model to combine exposure estimates with toxicity hazard data yielding an estimate of risk for 198 NPRI organic substances reported in 2010-2019. The presented case study further corroborates the hypothesis that risk-based ranking gives rise to different chemical priorities versus ranking based on release quantity alone. Chemicals like propane and hexane (except n-hexane) are in the top 10 highest-ranked organic substances based on emission quantities reported to NPRI but are ranked outside the top 10 based on corresponding regional-scale risk estimates. On the contrary, dioxins and furans are ranked very low based on emissions quantities reported to NPRI but are ranked higher based on corresponding risk estimates. The results also suggest that although quantities of some NPRI organic pollutant releases change over time, the ensuing risk estimates are not always directly proportional to these changes. This can be explained by changes in mode of entry to the environment that can influence the overall fate and exposure of the same chemicals, highlighting the complex dynamics that can occur when simulating fate and risk as opposed to quantity alone. Limitations are discussed and recommendations are provided for improving the priority setting methods, including reducing the uncertainty of the NPRI data and the need for multimedia models to address point source emissions. Integr Environ Assess Manag 2022;18:1722-1732. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)., (© 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).)

Biotransformation assays using primary hepatocytes from rainbow trout, Oncorhynchus mykiss , were validated as a reliable in vitro tool to predict in vivo bioconcentration factors (BCF) of chemicals in fish. Given the pronounced interspecies differences of chemical biotransformation, the present study aimed to compare biotransformation rate values and BCF predictions obtained with hepatocytes from the cold-water species, rainbow trout, to data obtained with hepatocytes of the warm-water species, common carp ( Cyprinus carpio ). In a first step, we adapted the protocol for the trout hepatocyte assay, including the cryopreservation method, to carp hepatocytes. The successful adaptation serves as proof of principle that the in vitro hepatocyte biotransformation assays can be technically transferred across fish species. In a second step, we compared the in vitro intrinsic clearance rates (CL in vitro, int ) of two model xenobiotics, benzo[a]pyrene (BaP) and methoxychlor (MXC), in trout and carp hepatocytes. The in vitro data were used to predict in vivo biotransformation rate constants (k B ) and BCFs, which were then compared to measured in vivo k B and BCF values. The CL in vitro, int values of BaP and MXC did not differ significantly between trout and carp hepatocytes, but the predicted BCF values were significantly higher in trout than in carp. In contrast, the measured in vivo BCF values did not differ significantly between the two species. A possible explanation of this discrepancy is that the existing in vitro-in vivo prediction models are parameterized only for trout but not for carp. Therefore, future research needs to develop species-specific extrapolation models., Competing Interests: JA is employed by the ARC Arnot Research and Consulting, Toronto, ON, Canada. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Bischof, Arnot, Jürling, Knipschild, Schlechtriem, Schauerte and Segner.)

As toxicologists and risk assessors move away from animal testing and more toward using in vitro models and biological modeling, it is necessary to produce tools to quantify the chemical distribution within the in vitro environment prior to extrapolating in vitro concentrations to human equivalent doses. Although models predicting chemical distribution in vitro have been developed, very little has been done for repeated dosing scenarios, which are common in prolonged experiments where the medium needs to be refreshed. Failure to account for repeated dosing may lead to inaccurate estimations of exposure and introduce bias into subsequent in vitro to in vivo extrapolations. Our objectives were to develop a dynamic mass balance model for repeated dosing in in vitro systems; to evaluate model accuracy against experimental data; and to perform illustrative simulations to assess the impact of repeated doses on predicted cellular concentrations. A novel dynamic in vitro partitioning mass balance model (IV-MBM DP v1.0) was created based on the well-established fugacity approach. We parameterized and applied the dynamic mass balance model to single dose and repeat dosing scenarios, and evaluated the predicted medium and cellular concentrations against available empirical data. We also simulated repeated dosing scenarios for organic chemicals with a range of partitioning properties and compared the in vitro distributions over time. In single dose scenarios, for which only medium concentrations were available, simulated concentrations predicted measured concentrations with coefficients of determination ( R 2 ) of 0.85-0.89, mean absolute error within a factor of two and model bias of nearly one. Repeat dose scenario simulations displayed model bias <2 within the cell lysate, and ∼1.5-3 in the medium. The concordance between simulated and available experimental data supports the predictive capacity of the IV-MBM DP v1.0 tool, but further evaluation as empirical data becomes available is warranted, especially for cellular concentrations., Competing Interests: JMA is employed by AES Armitage Environmental Sciences, Inc. JAA is employed by ARC Arnot Research and Consulting. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Bloch, Arnot, Kramer, Armitage and Verner.)

Reliable chemical property data are the key to defensible and unbiased assessments of chemical emissions, fate, hazard, exposure, and risks. However, the retrieval, evaluation, and use of reliable chemical property data can often be a formidable challenge for chemical assessors and model users. This comprehensive review provides practical guidance for use of chemical property data in chemical assessments. We assemble available sources for obtaining experimentally derived and in silico predicted property data; we also elaborate strategies for evaluating and curating the obtained property data. We demonstrate that both experimentally derived and in silico predicted property data can be subject to considerable uncertainty and variability. Chemical assessors are encouraged to use property data derived through the harmonization of multiple carefully selected experimental data if a sufficient number of reliable laboratory measurements is available or through the consensus consolidation of predictions from multiple in silico tools if the data pool from laboratory measurements is not adequate., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

Bioconcentration factors (BCFs) in rainbow trout were measured for 10 anionic surfactants with a range of alkyl chain lengths and different polar head groups. The BCFs ranged from 0.04 L kg -1 ww (for C 10 SO 3 ) to 1370 L kg -1 ww (C 16 SO 3 ). There was a strong correlation between the log BCF and log membrane lipid-water distribution ratio ( D MLW , r 2 = 0.96), and biotransformation was identified as the dominant elimination mechanism. The strong positive influence of D MLW on BCF was attributed to two phenomena: (i) increased partitioning from water into the epithelial membrane of the gill, leading to more rapid diffusion across this barrier and more rapid uptake, and (ii) increased sequestration of the surfactant body burden into membranes and other body tissues, resulting in lower freely dissolved concentrations available for biotransformation. Estimated whole-body in vivo biotransformation rate constants k B-BCF are within a factor three of rate constants estimated from S9 in vitro assays for six of the eight test chemicals for which k B-BCF could be determined. A model-based assessment indicated that the hepatic clearance rate of freely dissolved chemicals was similar for the studied surfactants. The dataset will be useful for evaluation of in silico and in vitro methods to assess bioaccumulation.

Fish bioconcentration factors (BCFs) are commonly used in chemical hazard and risk assessment. For neutral organic chemicals BCFs are positively correlated with the octanol-water partition ratio ( K OW ), but K OW is not a reliable parameter for surfactants. Membrane lipid-water distribution ratios ( D MLW ) can be accurately measured for all kinds of surfactants, using phospholipid-based sorbents. This study first demonstrates that D MLW values for ionic surfactants are more than 100 000 times higher than the partition ratio to fish-oil, representing neutral storage lipid. A non-ionic alcohol ethoxylate surfactant showed almost equal affinity for both lipid types. Accordingly, a baseline screening BCF value for surfactants (BCF baseline ) can be approximated for ionic surfactants by multiplying D MLW by the phospholipid fraction in tissue, and for non-ionic surfactants by multiplying D MLW by the total lipid fraction. We measured D MLW values for surfactant structures, including linear and branched alkylbenzenesulfonates, an alkylsulfoacetate and an alkylethersulfate, bis(2-ethylhexyl)-surfactants ( e.g. , docusate), zwitterionic alkylbetaines and alkylamine-oxides, and a polyprotic diamine. Together with sixty previously published D MLW values for surfactants, structure-activity relationships were derived to elucidate the influence of surfactant specific molecular features on D MLW . For 23 surfactant types, we established the alkyl chain length at which BCF baseline would exceed the EU REACH bioaccumulation (B) threshold of 2000 L kg -1 , and would therefore require higher tier assessments to further refine the BCF estimate. Finally, the derived BCF baseline are compared with measured literature in vivo BCF data where available, suggesting that refinements, most notably reliable estimates of biotransformation rates, are needed for most surfactant types.

Background: Large numbers of chemicals require evaluation to determine if their production and use pose potential risks to ecological and human health. For most chemicals, the inadequacy and uncertainty of chemical-specific data severely limit the application of exposure- and risk-based methods for screening-level assessments, priority setting, and effective management., Objective: We developed and evaluated a holistic, mechanistic modeling framework for ecological and human health assessments to support the safe and sustainable production, use, and disposal of organic chemicals., Methods: We consolidated various models for simulating the PROduction-To-EXposure (PROTEX) continuum with empirical data sets and models for predicting chemical property and use function information to enable high-throughput (HT) exposure and risk estimation. The new PROTEX-HT framework calculates exposure and risk by integrating mechanistic computational modules describing chemical behavior and fate in the socioeconomic system (i.e., life cycle emissions), natural and indoor environments, various ecological receptors, and humans. PROTEX-HT requires only molecular structure and chemical tonnage (i.e., annual production or consumption volume) as input information. We evaluated the PROTEX-HT framework using 95 organic chemicals commercialized in the United States and demonstrated its application in various exposure and risk assessment contexts., Results: Seventy-nine percent and 97% of the PROTEX-HT human exposure predictions were within one and two orders of magnitude, respectively, of independent human exposure estimates inferred from biomonitoring data. PROTEX-HT supported screening and ranking chemicals based on various exposure and risk metrics, setting chemical-specific maximum allowable tonnage based on user-defined toxicological thresholds, and identifying the most relevant emission sources, environmental media, and exposure routes of concern in the PROTEX continuum. The case study shows that high chemical tonnage did not necessarily result in high exposure or health risks., Conclusion: Requiring only two chemical-specific pieces of information, PROTEX-HT enables efficient screening-level evaluations of existing and premanufacture chemicals in various exposure- and risk-based contexts. https://doi.org/10.1289/EHP9372.

This study demonstrates the utility of an updated mass balance model for predicting the distribution of organic chemicals in in vitro test systems (IV-MBM EQP v2.0) and evaluates its performance with empirical data. The IV-MBM EQP v2.0 tool was parameterized and applied to four independent data sets with measured ratios of bulk medium or freely-dissolved to initial nominal concentrations (e.g., C24/C0 where C24 is the measured concentration after 24 h of exposure and C0 is the initial nominal concentration). Model performance varied depending on the data set, chemical properties (e.g., "volatiles" vs. "non-volatiles", neutral vs. ionizable organics), and model assumptions but overall is deemed acceptable. For example, the r 2 was greater than 0.8 and the mean absolute error ( MAE ) in the predictions was less than a factor of two for most neutral organics included. Model performance was not as good for the ionizable organic chemicals included but the r 2 was still greater than 0.7 and the MAE less than a factor of three. The IV-MBM EQP v2.0 model was subsequently applied to several hundred chemicals on Canada's Domestic Substances List (DSL) with nominal effects data ( AC 50s) reported for two in vitro assays. We report the frequency of chemicals with AC 50s corresponding to predicted cell membrane concentrations in the baseline toxicity range (i.e., >20-60 mM) and tabulate the number of chemicals with "volatility issues" (majority of chemical in headspace) and "solubility issues" (freely-dissolved concentration greater than water solubility after distribution). In addition, the predicted "equivalent EQP blood concentrations" (i.e., blood concentration at equilibrium with predicted cellular concentration) were compared to the AC 50s as a function of hydrophobicity (log octanol-water partition or distribution ratio). The predicted equivalent EQP blood concentrations exceed the AC 50 by up to a factor of 100 depending on hydrophobicity and assay conditions. The implications of using AC 50s as direct surrogates for human blood concentrations when estimating the oral equivalent doses using a toxicokinetic model (i.e., reverse dosimetry) are then briefly discussed.

Biotransformation may substantially reduce the extent to which organic environmental contaminants accumulate in fish. Presently, however, relatively little is known regarding the biotransformation of ionized chemicals, including cationic surfactants, in aquatic organisms. To address this deficiency, a rainbow trout liver S9 substrate depletion assay (RT-S9) was used to measure in vitro intrinsic clearance rates (CL int ; ml min -1 g liver -1 ) for 22 cationic surfactants that differ with respect to alkyl chain length and degree of methylation on the charged nitrogen atom. None of the quaternary N,N,N-trimethylalkylammonium compounds exhibited significant clearance. Rapid clearance was observed for N,N-dimethylalkylamines, and slower rates of clearance were measured for N-methylalkylamine analogs. Clearance rates for primary alkylamines were generally close to or below detectable levels. For the N-methylalkylamines and N,N-dimethylalkylamines, the highest CL int values were measured for C 10 -C 12 homologs; substantially lower clearance rates were observed for homologs containing shorter or longer carbon chains. Based on its cofactor dependency, biotransformation of C 12 -N,N-dimethylamine appears to involve one or more cytochrome P450-dependent reaction pathways, and sulfonation. On a molar basis, N-demethylation metabolites accounted for up to 25% of the N,N-dimethylalkylamines removed during the 2-h assay, and up to 55% of the removed N-methylalkylamines. These N-demethylation products possess greater metabolic stability in the RT-S9 assay than the parent structures from which they derive and may contribute to the overall risk of ionizable alkylamines. The results of these studies provide a set of consistently determined CL int values that may be extrapolated to whole trout to inform in silico bioaccumulation assessments. Environ Toxicol Chem 2021;40:3123-3136. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC., (© 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.)

Bioaccumulation (B) assessment is challenging because there are various B-metrics from laboratory and field studies, multiple criteria and thresholds for classifying bioaccumulative (B), very bioaccumulative (vB), and not bioaccumulative (nB) chemicals, as well as inherent variability and uncertainty in the data. These challenges can be met using a weight of evidence (WoE) approach. The Bioaccumulation Assessment Tool (BAT) provides a transparent WoE assessment framework that follows Organisation for Economic Co-operation and Development (OECD) principles for performing a WoE analysis. The BAT guides an evaluator through the process of data collection, generation, evaluation, and integration of various lines of evidence (LoE) (i.e., B-metrics) to inform decision-making. Phenanthrene (PHE) is a naturally occurring chemical for which extensive B and toxicokinetics data are available. A B assessment for PHE using the BAT is described that includes a critical evaluation of 74 measured in vivo LoE for fish and invertebrate species from laboratory and field studies. The number of LoE are reasonably well balanced across taxa (i.e., fish and invertebrates) and the different B-metrics. Additionally, in silico and in vitro biotransformation rate estimates and corresponding model-predicted B-metrics are included as corroborating evidence. Application of the BAT provides a consistent, coherent, and scientifically defensible WoE evaluation to conclude that PHE is not bioaccumulative (nB) because the overwhelming majority of the bioconcentration, bioaccumulation, and biomagnification metrics for both fish and invertebrates are below regulatory thresholds. An analysis of the relevant data using fugacity ratios is also provided, showing that PHE does not biomagnify in aquatic food webs. The critical review identifies recommendations to increase the consistency of B assessments, such as improved standardization of B testing guidelines, data reporting requirements for invertebrate studies, and consideration of temperature and salinity effects on certain B-metrics. Integr Environ Assess Manag 2021;17:911-925. © 2021 Concawe. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)., (© 2021 Concawe. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).)

This study describes the development and intercomparison of generic physiologically-based toxicokinetic (PBTK) models for humans comprised of internally consistent one-compartment (1Co-) and multi-compartment (MCo-) implementations (G-PBTK). The G-PBTK models were parameterized for an adult male (70 kg) using common physiological parameters and in vitro biotransformation rate estimates and subsequently evaluated using independent concentration versus time data (n = 6) and total elimination half-lives (n = 15) for diverse organic chemicals. The model performance is acceptable considering the inherent uncertainty in the biotransformation rate data and the absence of model calibration. The G-PBTK model was then applied using hypothetical neutral organics, acidic ionizable organics and basic ionizable organics (IOCs) to identify combinations of partitioning properties and biotransformation rates leading to substantial discrepancies between 1Co- and MCo-PBTK calculations for whole body concentrations and half-lives. The 1Co- and MCo-PBTK model calculations for key toxicokinetic parameters are broadly consistent unless biotransformation is rapid (e.g., half-life less than five days). When half-lives are relatively short, discrepancies are greatest for the neutral organics and least for the acidic IOCs which follows from the estimated volumes of distribution (e.g., VD SS  = 9.6-15.4 L/kg vs 0.3-1.6 L/kg for the neutral and acidic compounds respectively) and the related approach to internal chemical equilibrium. The model intercomparisons demonstrate that 1Co-PBTK models can be applied with confidence to many exposure scenarios, particularly those focused on chronic or repeat exposures and for prioritization and screening-level decision contexts. However, MCo-PBTK models may be necessary in certain contexts, particularly for intermittent, short-term and highly variable exposures. A key recommendation to guide model selection and the development of tiered PBTK modeling frameworks that emerges from this study is the need to harmonize models with respect to parameterization and process descriptions to the greatest extent possible when proceeding from the application of simpler to more complex modeling tools as part of chemical assessment activities., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Cationic surfactants have a strong affinity to sorb to phospholipid membranes and thus possess an inherent potential to bioaccumulate, but there are few measurements of bioconcentration in fish. We measured the bioconcentration of 10 alkylamines plus two quaternary ammonium compounds in juvenile rainbow trout at pH 7.6, and repeated the measurements at pH 6.2 for 6 of these surfactants. The BCF of the amines with chain lengths ≤ C 14 was positively correlated with chain length, increasing ∼0.5 log units per carbon. Their BCF was also pH dependent and approximately proportional to the neutral fraction of the amine in the water. The BCFs of the quaternary ammonium compounds showed no pH dependence and were >2 orders of magnitude less than for amines of the same chain length at pH 7.6. This indicates that systemic uptake of permanently charged cationic surfactants is limited. The behavior of the quaternary ammonium compounds and the two C 16 amines studied was consistent with previous observations that these surfactants accumulate primarily to the gills and external surfaces of the fish. At pH 7.6 the BCF exceeded 2000 L kg -1 for 4 amines with chains ≥ C 13 , showing that bioconcentration can be considerable for some longer chained cationic surfactants.

Following a recent proposal of normalizing the experimentally derived biomagnification factor (BMF) to a 5% lipid content in fish, we explore the normalization of the BMF of lipophilic chemicals in fish. We illustrate with theoretical models and experimental data that the BMF of lipophilic chemicals is a function of the lipid content of the diet and that poorly metabolizable, lipophilic chemicals biomagnify in organisms to a greater degree when present in higher-lipid content food. The proposed normalization of the laboratory BMF to the lipid content of the fish and subsequent standardization to a 5% fish lipid content, which is numerically identical to normalizing the BMF to a 5% dietary lipid content, has the potential to underestimate the biomagnification potential of lipophilic substances in aquatic food webs. The BMF normalized to both the lipid content of the fish and the lipid content of the diet, which is the biomagnification metric included in the Organisation for Economic Co-operation and Development's bioaccumulation testing guideline 305, better represents real-world biomagnification than the proposed BMF normalized and standardized to a 5% lipid content in fish. Environ Toxicol Chem 2021;40:1204-1211. © 2020 SETAC., (© 2020 SETAC.)

In indoor environments, humans ingest chemicals present as surface residues and bound to settled particles (dust), through mouthing hands (hand-to-mouth transfer) and objects (object-to-mouth transfer). Here, we introduce a novel modeling approach in support of systematic investigation into the mouthing-mediated ingestion of chemicals present in indoor environments. This model explicitly considers the indoor dynamics of dust and chemicals, building on mechanistic links with physicochemical properties of chemicals, features of the indoor environment, and human activity patterns. The evaluation of this model demonstrates that it satisfactorily reproduces chemical hand loadings and exposure data reported in the literature. We then use the evaluated model to investigate the response of mouthing-mediated ingestion to chemical partitioning between the gas phase and solid phases, expressed as the octanol-air partition coefficient (K OA ). Assuming a unit emission rate to the indoor environment, we find that low-volatility chemicals (with a K OA greater than 10 9 ) are more efficiently enriched in hand skin, resulting in higher mouthing-mediated ingestion than other compounds. For individuals living in a room with a typical level of dustiness, more than half of the chemical mass found in their hands comes from dust transfer, whereas more than half of the chemical mass ingested is the fraction present as residues on hands. We also use the new model to explore how the mouthing-mediated ingestion of chemicals is dependent on factors describing the indoor environment and human behavior. The model predicts that less frequent cleaning leads to higher accumulation of dust on indoor surfaces, thereby transferring more chemicals to hands and mouth in each contact. Introducing more dust into the room, but maintaining the same cleanup frequency, increases the dustiness of indoor surfaces, which promotes the transfer of relatively volatile chemicals (with a K OA lower than 10 9 ) to hands and mouth but decreases the transfer of chemicals with low volatility. More frequent hand contact with indoor surfaces increases both the hand loading and mouthing-mediated ingestion of chemicals, but the increases are more remarkable for adults than children because the higher surface contact frequency of children "saturates" hand loadings. An increase in handwashing frequency lowers the hand loading and mouthing-mediated ingestion of chemicals and this mitigating process is more prominent for relatively volatile chemicals. The new evaluated modeling approach can facilitate the prediction of mouthing-mediated ingestion for various age groups and the model predictions can be used to aid future fate and (bio)monitoring studies focusing on indoor contamination., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In vitro biotransformation rates were determined for 30 chemicals, mostly fragrance ingredients, using trout liver S9 fractions (RT-S9) and incorporated into in vitro-in vivo extrapolation (IVIVE) models to predict bioconcentration factors (BCFs). Predicted BCFs were compared against empirical BCFs to explore potential major uncertainties involved in the in vitro methods and IVIVE models: (i) in vitro chemical test concentrations; (ii) different gill uptake rate constant calculations ( k 1 ); (iii) protein binding (different calculations and measurement of the fraction of unbound chemical, f U ); (iv) species differences; and (v) extrahepatic biotransformation. Predicted BCFs were within 0.5 log units for 44% of the chemicals compared to empirical BCFs, whereas 56% were overpredicted by >0.5 log units. This trend of overprediction was reduced by alternative k 1 calculations to 32% of chemicals being overpredicted. Moreover, hepatic in vitro rates scaled to whole body biotransformation rates ( k B ) were compared against in vivo k B estimates. In vivo k B was underestimated for 79% of the chemicals. Neither lowering the test concentration, nor incorporation of new measured f U values, nor species matching avoided the tendency to overpredict BCFs indicating that further improvements to the IVIVE models are needed or extrahepatic biotransformation plays an underestimated role.

Bioaccumulation assessment is important for cationic surfactants in light of their use in a wide variety of consumer products and industrial processes. Because they sorb strongly to natural surfaces and to cell membranes, their bioaccumulation behavior is expected to differ from other classes of chemicals. Divided over two mixtures, we exposed rainbow trout to water containing 10 alkyl amines and 2 quaternary alkylammonium surfactants for 7 days, analyzed different fish tissues for surfactant residues, and calculated the tissues' contribution to fish body burden. Mucus, skin, gills, liver, and muscle each contributed at least 10% of body burden for the majority of the test chemicals. This indicates that both sorption to external surfaces and systemic uptake contribute to bioaccumulation. In contrast to the analogue alkylamine bases, the permanently charged quaternary ammonium compounds accumulated mostly in the gills and were nearly absent in internal tissues, indicating that systemic uptake of the charged form of cationic surfactants is very slow. Muscle-blood distribution coefficients were close to 1 for all alkyl amines, whereas liver-blood distribution coefficients ranged from 13 to 90, suggesting that the dominant considerations for sorption in liver are different from those in blood and muscle. The significant fraction of body burden on external surfaces can have consequences for bioaccumulation assessment.

The hazard and risk from organic chemicals present in the environment are routinely evaluated using P (persistence), B (bioaccumulation) and T (toxicity) criteria. We present a perspective on how models based on the equilibrium criteria of fugacity and chemical activity can contribute to all three evaluations, thus providing a consistent and seamless assessment process. Persistence and its closely related, but fundamentally different property, chemical residence time can be determined from degradation half-lives (typically obtained from monitoring data) and multi-media mass balance models describing chemical fate and transport in real or evaluative environments. Bioaccumulation is driven by equilibrium partitioning processes that can be estimated from fugacity models treating uptake by respiration and diet in single organisms and in food webs, most commonly for aquatic systems for which confirmatory monitoring data can be obtained. Biomagnification is readily evaluated both experimentally and as a fugacity (or activity) increase from prey to predator. Toxicokinetic evaluations of chemical uptake and disposition in a variety of organisms, including humans, can be obtained using fugacity- and physiologically-based pharmacokinetic models. Toxicodynamic processes of chemical interactions with organisms leading to adverse toxic outcomes are less obviously amenable to fugacity assessment with the notable exception of baseline toxicity (narcosis), the most common mode of action of commercial chemicals. It is shown that a range of fugacities can be defined and correlated for specific species thus enabling direct comparison of fugacities estimated or monitored in the environment with fugacities resulting in baseline toxicity. Finally, it is shown that fugacity and activity can serve as multi-media metrics of chemical contamination in ecosystems, thus enabling identification of specific regions and species at greatest risk in a pictorial format that is readily understandable to scientific and regulatory communities and to the general public.

Human biomonitoring data collected from individuals of the same age sampled in different years provide within-age temporal trends, which are often employed to evaluate the effectiveness of chemical regulatory policies. For polybrominated diphenyl ethers (PBDEs), this within-age temporal trend has been observed to vary between congeners and age groups. We systematically explore the mechanisms responsible for such variability through simulating human exposure via multiple exposure pathways to PBDEs released from multiple lifecycle stages. Our simulation indicates that, after new use of PBDEs is banned, emissions to the outdoor environment from use and waste disposal outlast those to the indoor environment from the indoor use phase, leading to slower decline rates in the contamination of food items sourced from the outdoor environment than that from indoors. Compared with indoor exposure pathways, the consumption of contaminated food contributes more to the exposure (i) to more hydrophobic, recalcitrant congeners, and (ii) of adults than children, which results in slower rates of decline in the within-age temporal trend of those congeners and in adults. The within-age temporal trend is influenced to a lesser extent by the elimination of PBDEs from the human body, e.g., differences in biotransformation potential of congeners, growth dilution, and pre- and postnatal exposures by children.

Exposure models provide critical information for risk assessment of personal care product ingredients, but there have been limited opportunities to compare exposure model predictions to observational exposure data. Urinary excretion data from a biomonitoring study in eight individuals were used to estimate minimum absorbed doses for triclosan and methyl-, ethyl-, and n-propyl- parabens (TCS, MP, EP, PP). Three screening exposure models (European Commission Scientific Commission on Consumer Safety [SCCS] algorithms, ConsExpo in deterministic mode, and RAIDAR-ICE) and two higher-tier probabilistic models (SHEDS-HT, and Creme Care & Cosmetics) were used to model participant exposures. Average urinary excretion rates of TCS, MP, EP, and PP for participants using products with those ingredients were 16.9, 3.32, 1.9, and 0.91 μg/kg-d, respectively. The SCCS default aggregate and RAIDAR-ICE screening models generally resulted in the highest predictions compared to other models. Approximately 60-90% of the model predictions for most of the models were within a factor of 10 of the observed exposures; ~30-40% of the predictions were within a factor of 3. Estimated exposures from urinary data tended to fall in the upper range of predictions from the probabilistic models. This analysis indicates that currently available exposure models provide estimates that are generally realistic. Uncertainties in preservative product concentrations and dermal absorption parameters as well as degree of metabolism following dermal absorption influence interpretation of the modeled vs. measured exposures. Use of multiple models may help characterize potential exposures more fully than reliance on a single model.

Humans are exposed to organic chemicals released to indoor air through near-field exposure routes such as air inhalation and nondietary dust ingestion as well as far-field exposure routes such as consumption of food. Here, we explore the relative importance of near- and far-field exposure routes and its variability between chemicals, age groups, and subpopulations, by modeling aggregate human exposure to indoor-released chemicals with diverse partitioning behavior and degradability. Our model results indicate that if chemicals are assumed to be perfectly persistent, dietary and nondietary ingestion dominates human exposure to hydrophobic chemicals of relatively low volatility (with an octanol-air partition coefficient K OA > 10 6.5 and an octanol-water partition coefficient K OW < 10 11 ), whereas inhalation of indoor air dominates human exposure to volatile chemicals. Other exposure routes, for example, dermal absorption and drinking water, make a relatively small contribution to human exposure. Reduced chemical persistence in environmental media and biota lowers the contribution of dietary ingestion. For most chemicals other than those with a K OA between 10 9 and 10 12 and a K OW between 10 6 and 10 9 (e.g., polybrominated diphenyl ethers), the relative importance of near- and far-field exposure routes is primarily governed by chemical partitioning and degradability rather than age- and population-dependent human exposure factors.

The main objective of this study is to develop and evaluate novel Quantitative Structure-Property Relationships (QSPRs) for predicting entropy of fusion (ΔS M ) and melting point (T M ) of organic chemicals from chemical structure. The QSPRs are developed using the Iterative Fragment Selection (IFS) method that requires only 2D structural information from the user (SMILES codes) for property prediction. The QSPRs also provide information on the applicability domain for each calculation and uncertainty estimates for the predictions. The root mean square error (RMSE) for the external validation sets are 11.8 J mol -1  K -1 and 46.9 K for the ΔS M and T M QSPRs, respectively. The performance of the new QSPRs is comparable to other predictive methods but has advantages with respect to availability and ease of use as well as the guidance on applicability domain for each prediction. Limitations of the new QSPRs are discussed. The QSPRs are coded as a user-friendly, freely available tool., (© 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

This study describes the development and evaluation of a new bioenergetically balanced bioaccumulation (3B) model for organic chemicals in fish. The 3B model is developed from a large database of routine metabolic (oxygen consumption) rates composed of a range of species, body mass, and temperatures. The chemical uptake and elimination rates of the 3B model are compared against those from three existing bioaccumulation models. A time-variant version of the 3B model is evaluated against measured concentrations of five polychlorinated biphenyls in different-size fish depurated over the course of a year, during which water temperature changed by 22 °C. The "generic" species 3B model predicts fish concentrations to within a factor of 3 of the measured data for the majority of observations ( n = 438) and outperforms a previously published "species-specific" bioenergetics model. Bioenergetics aspects of the 3B model are further evaluated by comparing predicted feeding rates and growth rates to measured rates obtained from diverse laboratory conditions ( n 572). While bioenergetics performance is acceptable, the 3B model seems to generally perform better when ingestion rates are calculated from growth rates rather than vice versa. For field applications, parametrization of the activity multiplier remains a key uncertainty underlying the bioenergetics calculations.

Prioritizing the potential risk posed to human health by chemicals requires tools that can estimate exposure from limited information. In this study, chemical structure and physicochemical properties were used to predict the probability that a chemical might be associated with any of four exposure pathways leading from sources-consumer (near-field), dietary, far-field industrial, and far-field pesticide-to the general population. The balanced accuracies of these source-based exposure pathway models range from 73 to 81%, with the error rate for identifying positive chemicals ranging from 17 to 36%. We then used exposure pathways to organize predictions from 13 different exposure models as well as other predictors of human intake rates. We created a consensus, meta-model using the Systematic Empirical Evaluation of Models framework in which the predictors of exposure were combined by pathway and weighted according to predictive ability for chemical intake rates inferred from human biomonitoring data for 114 chemicals. The consensus model yields an R 2 of ∼0.8. We extrapolate to predict relevant pathway(s), median intake rate, and credible interval for 479 926 chemicals, mostly with minimal exposure information. This approach identifies 1880 chemicals for which the median population intake rates may exceed 0.1 mg/kg bodyweight/day, while there is 95% confidence that the median intake rate is below 1 μg/kg BW/day for 474572 compounds.

Background: Chemical biomarker concentrations are driven by complex interactions between chemical use patterns, exposure pathways, and toxicokinetic parameters such as biological half-lives. Criteria to differentiate legacy from current exposures are helpful for interpreting variation in age-based and time trends of chemical exposure and identifying chemicals to which children are highly exposed. A systematic approach is needed to study temporal trends for a wide range of chemicals in the US population., Objectives: Using National Health and Nutrition Examination Survey (NHANES) data on measured biomarker concentrations for 141 chemicals from 1999 to 2014, we aim to 1) understand the influence of temporal determinants, in particular time trends, biological half-lives, and restriction dates on age-based trends, 2) systematically define an age-based pattern to identify chemicals with ongoing and high exposure in children, and 3) characterize how age-based trends for six Per- and Polyfluoroalkyl Substances (PFASs) are changing over time., Methods: We performed an integrated analysis of biological half-lives and restriction dates, compared distributions of chemical biomarker concentrations by age group, and then applied a series of regression models to evaluate the linear (β age ) and nonlinear (β age 2 ) relationships between age and chemical biomarker levels., Results: For restricted chemicals, a minimum persistence of 1 year in the human body is needed to observe substantial differences between the less exposed young population and historically exposed adults. We define a metric ( [Formula: see text] ) that identifies several phthalates, brominated flame retardants, pesticides, and metals such as lead and tungsten as elevated and ongoing exposures in children. While a substantial reduction in children's exposures was reflected in PFOS and PFOA, levels of PFNA and PFHxS in children were higher in 2013-2014 compared to those in 1999-2000., Conclusions: Integrating a series of regression models with systemized stratified analyses by age group enabled us to define an age-based pattern to identify chemicals that are of higher levels in children., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Exposure- and risk-based assessments for chemicals used indoors or applied to humans (i.e., in near-field environments) necessitate an aggregate exposure pathway framework that aligns chemical exposure information from use sources to internal dose and eventually to their potential for health effects. Such a source-to-effect continuum is advocated to balance the complexity of human exposure and the insufficiency of relevant data for thousands of existing and emerging chemicals. Here, we introduce the Risk Assessment, IDentification And Ranking-Indoor and Consumer Exposure (RAIDAR-ICE) model, which establishes an integrated framework to evaluate human exposure due to indoor use and direct application of chemicals to humans. As a model evaluation, RAIDAR-ICE faithfully reproduces exposure estimates inferred from biomonitoring data for 37 chemicals with direct and indirect near-field sources. RAIDAR-ICE generates different rankings for 131 chemicals based on different exposure- and risk-based assessment metrics, demonstrating its versatility for diverse chemical screening goals. When coupled with a far-field RAIDAR model, the near-field RAIDAR-ICE model enables assessment of aggregate human exposure. Overall, RAIDAR-ICE is a powerful tool for high-throughput screening and prioritization of human exposure to neutral organic chemicals used indoors.

Chemical activity quantifies the energetic level of an organic compound relative to its pure liquid [0-1], and several studies have reported that baseline toxicity generally requires chemical activities of 0.01-0.1. The first aim was to challenge this chemical activity range for baseline toxicity. Algal growth inhibition data (median effective concentrations, EC 50 ) were compiled from two recent studies and included 108 compounds categorised as non-polar (mode of toxic action, MOA1) and polar (MOA2) narcotics. These data were linked to chemical activity by (1) plotting them relative to a regression for (subcooled) liquid solubility (S L ), which served as visual reference for chemical activity of unity and (2) determining EC 50 /S L ratios that essentially equal median effective chemical activity (Ea 50 ). Growth inhibition required chemical activity >0.01 for MOA1 and >0.001 for MOA2 compounds. The second aim was to identify compounds exerting excess toxicity, i.e., when growth inhibition occurred at chemical activity <0.001. From a recent review with 2323 data entries, 315 EC 50 values passed our selection criteria. 280 of these EC 50 values were within or near the baseline toxicity range (Ea 50 >0.001), and 25 compounds were found to exert excess toxicity (Ea 50 <0.001). Of these compounds, 16 are pesticides or precursors. Methodologically, this study includes two methods for translating EC 50 values into the chemical activity framework, each having advantages and limitations. Scientifically, this study confirms that baseline toxicity generally requires chemical activities of 0.01-0.1 and extends the application of the chemical activity approach beyond baseline toxicity, by demonstrating its utility to identify compounds that exert excess toxicity., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Indoor environments and urban areas are hubs of chemical stocks and emissions, which contaminate those indoor and urban areas as well as the surrounding rural areas. Here, we introduce a newly developed nested multimedia indoor-urban-rural chemical fate model, coupled with a substance flow analysis, aiming to provide an integrated and dynamic understanding of the mass distribution, concentrations, and major pathways of contaminants within and between indoor, urban and rural environments. The model is applied to simulate the emissions, transport and fate of polychlorinated biphenyl (PCB) congeners 28 and 153 in the Western Baltic drainage basin over time. Whereas >90% of PCBs were used in the urban outdoor environment, the model indicates that ~80% of emissions occurred indoors because of higher emission factors in open-end usage. Atmospheric advection is highly effective in transporting the bulk of the PCBs emitted indoors to urban (>85%) and rural (>75%) environments. The rural environment is identified as the main locale for accommodating (>80%) and removing (>50%) the emitted PCBs. Contamination of exposure-relevant compartments in the rural environment is anticipated to decrease slower than, and thus outlast, that in the indoor environment, which implies an increasing importance of the food chain accumulation in overall human exposure to PCBs over time. Our model demonstrates that, whereas the indoor environment contains an insignificant fraction of the total emissions remaining in the regional environment, it experiences orders of magnitude higher concentrations than the rural environment. Therefore, while including indoor and urban environments in modeling influences little the modeled overall chemical fate on a regional scale, it strongly affects modeling the human exposure associated with multimedia concentrations., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

The general population is exposed to polychlorinated biphenyls (PCBs) by consuming food from far-field contaminated agricultural and aquatic environments, and inhalation and nondietary ingestion in near-field indoor or residential environments. Here, we seek to evaluate the relative importance of far- and near-field routes by simulating the time-variant aggregate exposure of Swedish females to PCB congeners from 1930 to 2030. We rely on a mechanistic model, which integrates a food-chain bioaccumulation module and a human toxicokinetic module with dynamic substance flow analysis and nested indoor-urban-rural environmental fate modeling. Confidence in the model is established by successfully reproducing the observed PCB concentrations in Swedish human milk between 1972 and 2016. In general, far-field routes contribute most to total PCB uptake. However, near-field exposure is notable for (i) children and teenagers, who have frequent hand-to-mouth contact, (ii) cohorts born in earlier years, e.g., in 1956, when indoor environments were severely contaminated, and (iii) lighter chlorinated congeners. The relative importance of far- and near-field exposure in a cross-section of individuals of different age sampled at the same time is shown to depend on the time of sampling. The transition from the dominance of near- to far-field exposure that has happened for PCBs may also occur for other chemicals used indoors.

The bioaccumulation assessment of chemicals is challenging because of various metrics and criteria, multiple lines of evidence and underlying uncertainty in the data. Measured in vivo laboratory and field bioaccumulation data are generally considered preferable; however, quantitative structure-activity relationships (QSARs), mass balance models and in vitro data can also be considered. This case study critically evaluates in vivo, in vitro and in silico data and provides new data for the bioaccumulation assessment of triclosan (TCS). The review focusses on measured fish bioconcentration factors (BCFs) because this is the most commonly used regulatory metric. Reported measured fish BCFs range from about 20 to 8700L/kg-ww spanning a range of possible bioaccumulation assessment outcomes, i.e. from "not bioaccumulative" to "very bioaccumulative". Estimated biotransformation rate constants for fish obtained from in vivo, in vitro and in silico methods show general consensus fostering confidence in the selection of plausible values to confront uncertainty in the measured fish BCF tests. Other measurements (lines of evidence) from various species are also collected and reviewed. The estimated biotransformation rate constants and selected chemical property data are used to parameterize bioaccumulation models for aquatic species. Collectively the available lines of evidence are presented using a weight of evidence approach for assessing the bioaccumulation of TCS in aquatic species. Acceptable quality measured data and model predictions for TCS BCFs and bioaccumulation factors are lower than 2000L/kg. Biomagnification factors are <1 (kg/kg). The general consistency in the acceptable quality data is largely explained by the relatively efficient rates of TCS biotransformation in a range of species including measurements of significant in vitro activity of phase II conjugation reactions. The review demonstrates the value of combining models and measurements and, when necessary, applying multiple lines of evidence for chemical assessment., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Toxicokinetics heavily influence chemical toxicity as the result of Absorption, Distribution, Metabolism (Biotransformation) and Elimination (ADME) processes. Biotransformation (metabolism) reactions can lead to detoxification or, in some cases, bioactivation of parent compounds to more toxic chemicals. Moreover, biotransformation has been recognized as a key process determining chemical half-life in an organism and is thus a key determinant for bioaccumulation assessment for many chemicals. This study addresses the development of QSAR models for the prediction of in vivo whole body human biotransformation (metabolism) half-lives measured or empirically-derived for over 1000 chemicals, mainly represented by pharmaceuticals. Models presented in this study meet regulatory standards for fitting, validation and applicability domain. These QSARs were used, in combination with literature models for the prediction of biotransformation half-lives in fish, to refine the screening of the potential PBT behaviour of over 1300 Pharmaceuticals and Personal Care Products (PPCPs). The refinement of the PBT screening allowed, among others, for the identification of PPCPs, which were predicted as PBTs on the basis of their chemical structure, but may be easily biotransformed. These compounds are of lower concern in comparison to potential PBTs characterized by large predicted biotransformation half-lives., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The chemical dietary absorption efficiency (E D ) quantifies the amount of chemical absorbed by an organism relative to the amount of chemical an organism is exposed to following ingestion. In particular, E D can influence the extent of bioaccumulation and biomagnification for hydrophobic chemicals. A new E D model is developed to quantify chemical process rates in the gastrointestinal tract (GIT). The new model is calibrated with critically evaluated measured E D values (n = 250) for 80 hydrophobic persistent chemicals. The new E D model is subsequently used to estimate chemical reaction rate constants (k R ) assumed to occur in the lumen of the GIT from experimental dietary exposure tests (n = 255) for 165 chemicals. The new k R estimates are corroborated with k R estimates for the same chemicals from the same data derived previously by other methods. The roles of k R and the biotransformation rate constant (k B ) on biomagnification factors (BMFs) determined under laboratory test conditions and on BMFs and bioaccumulation factors (BAFs) in the environment are examined with the new model. In this regard, differences in lab and field BMFs are highlighted. Recommendations to address uncertainty in E D and k R data are provided.

Quantifying the transfer of organic chemicals from the environment into terrestrial plants is essential for assessing human and ecological risks, using plants as environmental contamination biomonitors, and predicting phytoremediation effectiveness. Experimental data describing chemical uptake by plants are often expressed as ratios of chemical concentrations in the plant compartments of interest (e.g., leaves, shoots, roots, xylem sap) to those in the exposure medium (e.g., soil, soil porewater, hydroponic solution, air). These ratios are generally referred to as "bioconcentration factors" but have also been named for the specific plant compartment sampled, such as "root concentration factors," "leaf concentration factors," or "transpiration stream (xylem sap) concentrations factors." We reviewed over 350 articles to develop a database with 7049 entries of measured bioaccumulation data for 310 organic chemicals and 112 terrestrial plant species. Various experimental approaches have been used; therefore, interstudy comparisons and data-quality evaluations are difficult. Key exposure and plant growth conditions were often missing, and units were often unclear or not reported. The lack of comparable high-confidence data also limits model evaluation and development. Standard test protocols or, at a minimum, standard reporting guidelines for the measurement of plant uptake data are recommended to generate comparable, high-quality data that will improve mechanistic understanding of organic chemical uptake by plants. Environ Toxicol Chem 2018;37:21-33. © 2017 SETAC., (© 2017 SETAC.)

A 1-compartment toxicokinetic model is used to characterize the chemical exposure toxicity space (CETS), providing a novel graphic tool that can aid in the design of aquatic toxicity tests for fish and for interpreting their results. The graph depicts the solution to the differential equation describing the uptake kinetics of a chemical by a modeled fish under conventional bioassay conditions. The model relates the exposure concentration in the water to a dimensionless time and the onset of toxicity as determined by an estimated or assumed critical body residue or incipient lethal aqueous concentration. These concentration graphs are specific to each chemical and exposure and organism parameters and clearly demonstrate differences in toxicity between chemicals and how factors such as hydrophobicity influence the toxic endpoint. The CETS plots can also be used to assess bioconcentration test conditions to ensure that concentrations are well below toxic levels. Illustrative applications are presented using a recent set of high-quality toxicity data. Conversion of concentrations to chemical activities in the plots enables results for different baseline toxicants to be superimposed. For chemicals that have different modes of toxic action, the increased toxicity then becomes apparent. Implications for design and interpretation of aquatic toxicity tests are discussed. The model, and pictorial visualization of the time-course of aquatic toxicity tests, may contribute to improvements in test design, implementation, and interpretation, and to reduced animal usage. Environ Toxicol Chem 2017;36:1389-1396. © 2016 The Authors. Environmental Toxicology and Chemistry Published by Wiley Periodicals, Inc. on behalf of SETAC., (© 2016 The Authors. Environmental Toxicology and Chemistry Published by Wiley Periodicals, Inc. on behalf of SETAC.)

The objective of the present study was to review the current knowledge regarding the bioaccumulation potential of ionizable organic compounds (IOCs), with a focus on the availability of empirical data for fish. Aspects of the bioaccumulation potential of IOCs in fish that can be characterized relatively well include the pH dependence of gill uptake and elimination, uptake in the gut, and sorption to phospholipids (membrane-water partitioning). Key challenges include the lack of empirical data for biotransformation and binding in plasma. Fish possess a diverse array of proteins that may transport IOCs across cell membranes. Except in a few cases, however, the significance of this transport for uptake and accumulation of environmental contaminants is unknown. Two case studies are presented. The first describes modeled effects of pH and biotransformation on the bioconcentration of organic acids and bases, while the second employs an updated model to investigate factors responsible for accumulation of perfluorinated alkyl acids. The perfluorinated alkyl acid case study is notable insofar as it illustrates the likely importance of membrane transporters in the kidney and highlights the potential value of read-across approaches. Recognizing the current need to perform bioaccumulation hazard assessments and ecological and exposure risk assessment for IOCs, the authors provide a tiered strategy that progresses (as needed) from conservative assumptions (models and associated data) to more sophisticated models requiring chemical-specific information. Environ Toxicol Chem 2017;36:882-897. © 2016 SETAC., (© 2016 SETAC.)

Greater knowledge of biotransformation rates for ionizable organic compounds (IOCs) in fish is required to properly assess the bioaccumulation potential of many environmentally relevant contaminants. In this study, we measured in vitro hepatic clearance rates for 50 IOCs using a pooled batch of liver S9 fractions isolated from rainbow trout (Oncorhynchus mykiss). The IOCs included four types of strongly ionized acids (carboxylates, phenolates, sulfonates, and sulfates), three types of strongly ionized bases (primary, secondary, tertiary amines), and a pair of quaternary ammonium compounds (QACs). Included in this test set were several surfactants and a series of beta-blockers. For linear alkyl chain IOC analogues, biotransformation enzymes appeared to act directly on the charged terminal group, with the highest clearance rates for tertiary amines and sulfates and no clearance of QACs. Clearance rates for C 12 -IOCs were higher than those for C 8 -IOC analogues. Several analogue series with multiple alkyl chains, branched alkyl chains, aromatic rings, and nonaromatic rings were evaluated. The likelihood of multiple reaction pathways made it difficult to relate all differences in clearance to specific molecular features the tested IOCs. Future analysis of primary metabolites in the S9 assay is recommended to further elucidate biotransformation pathways for IOCs in fish.

Experimental data and models for plant bioaccumulation of organic contaminants play a crucial role for assessing the potential human and ecological risks associated with chemical use. Plants are receptor organisms and direct or indirect vectors for chemical exposures to all other organisms. As new experimental data are generated they are used to improve our understanding of plant-chemical interactions that in turn allows for the development of better scientific knowledge and conceptual and predictive models. The interrelationship between experimental data and model development is an ongoing, never-ending process needed to advance our ability to provide reliable quality information that can be used in various contexts including regulatory risk assessment. However, relatively few standard experimental protocols for generating plant bioaccumulation data are currently available and because of inconsistent data collection and reporting requirements, the information generated is often less useful than it could be for direct applications in chemical assessments and for model development and refinement. We review existing testing guidelines, common data reporting practices, and provide recommendations for revising testing guidelines and reporting requirements to improve bioaccumulation knowledge and models. This analysis provides a list of experimental parameters that will help to develop high quality datasets and support modeling tools for assessing bioaccumulation of organic chemicals in plants and ultimately addressing uncertainty in ecological and human health risk assessments., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

High-throughput screening (HTS) models are being developed and applied to prioritize chemicals for more comprehensive exposure and risk assessment. Dermal pathways are possible exposure routes to humans for thousands of chemicals found in personal care products and the indoor environment. HTS exposure models rely on skin permeability coefficient (KP; cm/h) models for exposure predictions. An initial database of approximately 1000 entries for empirically-based KP data was compiled from the literature and a subset of 480 data points for 245 organic chemicals derived from testing with human skin only and using only water as a vehicle was selected. The selected dataset includes chemicals with log octanol-water partition coefficients (KOW) ranging from -6.8 to 7.6 (median=1.8; 95% of the data range from -2.5 to 4.6) and molecular weight (MW) ranging from 18 to 765g/mol (median=180); only 3% >500g/mol. Approximately 53% of the chemicals in the database have functional groups which are ionizable in the pH range of 6 to 7.4, with 31% being appreciably ionized. The compiled log KP values ranged from -5.8 to 0.1cm/h (median=-2.6). The selected subset of the KP data was then used to evaluate eight representative KP models that can be readily applied for HTS assessments, i.e., parameterized with KOW and MW. The analysis indicates that a version of the SKINPERM model performs the best against the selected dataset. Comparisons of representative KP models against model input parameter property ranges (sensitivity analysis) and against chemical datasets requiring human health assessment were conducted to identify regions of chemical properties that should be tested to address uncertainty in KP models and HTS exposure assessments., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Background: Traditional food (TF) consumption represents the main route of persistent organic pollutant (POP) exposure for indigenous Arctic Canadians. Ongoing dietary transitions away from TFs and toward imported foods (IFs) may contribute to decreasing POP exposures observed in these groups., Methods: To explore this issue, we combined the global fate and transport model GloboPOP and the human food chain bioaccumulation model ACC-Human Arctic to simulate polychlorinated biphenyl (PCB) exposure in two indigenous Arctic Canadian communities from the Inuvik region, Northwest Territories and Baffin region, Nunavut. Using dietary survey information from initial (1996-98) and follow-up (2005-07) biomonitoring campaigns in Inuvik and Baffin, we simulated PCB exposures (PCB-118, -138, -153, and -180) for each individual study participant and also whole study populations., Results: TF intake rates, particularly of marine mammals (MMs), were the most important predictors of modeled PCB exposure, while TF consumption did not associate consistently with measured PCB exposures. Further, reported mean TF intake increased from baseline to follow-up in both Inuvik (from 8 to 183gd(-1)) and Baffin (from 60 to 134gd(-1)), opposing both the expected dietary transition direction and the observed decrease in human PCB exposures in these communities (ΣPCB Inuvik: from 43 to 29ngglipid(-1), ΣPCB Baffin: from 213 to 82ngglipid(-1)). However dietary questionnaire data are frequently subject to numerous biases (e.g., recall, recency, confirmation), and thus casts doubt on the usefulness of these data., Conclusions: Ultimately, our model's capability to reproduce historic PCB exposure data in these two groups was highly sensitive to TF intake, further underscoring the importance of accurate TF consumption reporting, and clarification of the role of dietary transitions in future POP biomonitoring of indigenous Arctic populations., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Bioconcentration factors (BCFs) and bioaccumulation factors (BAFs) are widely used in scientific and regulatory programs to assess chemical hazards. There is increasing interest in also using biomagnification factors (BMFs) and trophic magnification factors (TMFs) for this purpose, especially for highly hydrophobic substances that may reach high concentrations in predatory species that occupy high trophic level positions in ecosystems. Measurements of TMFs in specific ecosystems can provide invaluable confirmation that biomagnification or biodilution has occurred across food webs, but their use in a regulatory context can be controversial because of uncertainties related to the reliability of measurements and their regulatory interpretation. The objective of this study is to explore some of the recognized uncertainties and dependencies in field BMFs and TMFs. This is accomplished by compiling a set of three simple food web models (pelagic, demersal and combined pelagic-demersal) consisting of up to seven species to simulate field BMFs and TMFs and to explore their dependences on hydrophobicity (expressed as log KOW), rates of biotransformation and growth, sediment-water fugacity ratios, and extent of food web omnivory and issues that arise when chemical concentration gradients exist in aquatic ecosystems. It is shown that empirical TMFs can be highly sensitive to these factors, thus the use of TMFs in a regulatory context must recognize these sensitivities. It is suggested that simple but realistic evaluative food web models could be used to extend BCF and BAF assessments to include BMFs and TMFs, thus providing a tool to address bioaccumulation hazard and the potential risk of exposures to elevated chemical concentrations in organisms at high trophic levels., (Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.)