Prioritization Of Chemicals Research Articles

Nontargeted Analysis of Face Masks: Comparison of Manual Curation to Automated GCxGC Processing Tools.

Masks constructed of a variety of materials are in widespread use due to the COVID-19 pandemic, and people are exposed to chemicals inherent in the masks through inhalation. This work aims to survey commonly available mask materials to provide an overview of potential exposure. A total of 19 mask materials were analyzed using a nontargeted analysis two-dimensional gas chromatography (GCxGC)-mass spectrometric (MS) workflow. Traditionally, there has been a lack of GCxGC-MS automated high-throughput screening methods, resulting in trade-offs with throughput and thoroughness. This work addresses the gap by introducing new machine learning software tools for high-throughput screening (Floodlight) and subsequent pattern analysis (Searchlight). A recursive workflow for chemical prioritization suitable for both manual curation and machine learning is introduced as a means of controlling the level of effort and equalizing sample loading while retaining key chemical signatures. Manual curation and machine learning were comparable with the mask materials clustering into three groups. The majority of the chemical signatures could be characterized by chemical class in seven categories: organophosphorus, long chain amides, polyethylene terephthalate oligomers, n-alkanes, olefins, branched alkanes and long-chain organic acids, alcohols, and aldehydes. The olefin, branched alkane, and organophosphorus components were primary contributors to clustering, with the other chemical classes having a significant degree of heterogeneity within the three clusters. Machine learning provided a means of rapidly extracting the key signatures of interest in agreement with the more traditional time-consuming and tedious manual curation process. Some identified signatures associated with plastics and flame retardants are potential toxins, warranting future study to understand the mask exposure route and potential health effects.

Integration of production and use information into an exposure-based screening approach to rank chemicals of emerging Arctic concern for potential to be planetary boundary threats

Planetary boundaries delimit a ‘safe operating space for humanity’ that should not be overstepped to maintain stable Holocene-like conditions on Earth. Some chemical pollutants have the potential to pose a planetary boundary threat to the functioning of vital Earth system processes as so-called ‘novel entities’. Recently, an exposure-based prioritization scheme was developed that uses model-estimated data on persistence and degree of mobility in air and water to identify and prioritise chemical substances that may be planetary boundary threats. As a case study, chemicals of emerging Arctic concern identified by the Arctic Monitoring and Assessment Programme (AMAP) were used to develop the scheme. The exposure-based prioritization scheme cannot address all scenarios for a chemical to pose an unknown planetary boundary threat, but it does allow for prioritization of chemicals according to environmental fate and exposure profiles. A key limitation of the scheme is that the quantity of chemical potentially released to the environment was not considered in the prioritization. Here, we use data on chemical production and use reported under the European chemicals regulation REACH, and an emission scoring system developed by the European Food Safety Authority (EFSA) to attempt to add information about estimated emissions to the exposure-based prioritization scheme. Using REACH data and the EFSA scoring system, we ranked the AMAP substances according to their potential for environmental release and combined that information with the previously reported exposure-based prioritization that considers persistence and long-range transport potential. Our method successfully assigned ‘high priority’ to known ozone-depleting substances (methyl chloride and dichloromethane) and identified chemicals of concern recently under consideration for nomination as persistent organic pollutants under the Stockholm Convention (octamethylcyclotetrasiloxane and decamethylcyclopentasiloxane). The EFSA scoring system offers a useful starting point that provided useful additional information in the case study for chemicals of emerging Arctic concern, but lack of information to estimate potential releases of chemicals was a major limitation.

Assessing Human Exposure to SVOCs in Materials, Products, and Articles: A Modular Mechanistic Framework.

A critical review of the current state of knowledge of chemical emissions from indoor sources, partitioning among indoor compartments, and the ensuing indoor exposure leads to a proposal for a modular mechanistic framework for predicting human exposure to semivolatile organic compounds (SVOCs). Mechanistically consistent source emission categories include solid, soft, frequent contact, applied, sprayed, and high temperature sources. Environmental compartments are the gas phase, airborne particles, settled dust, indoor surfaces, and clothing. Identified research needs are the development of dynamic emission models for several of the source emission categories and of estimation strategies for critical model parameters. The modular structure of the framework facilitates subsequent inclusion of new knowledge, other chemical classes of indoor pollutants, and additional mechanistic processes relevant to human exposure indoors. The framework may serve as the foundation for developing an open-source community model to better support collaborative research and improve access for application by stakeholders. Combining exposure estimates derived using this framework with toxicity data for different end points and toxicokinetic mechanisms will accelerate chemical risk prioritization, advance effective chemical management decisions, and protect public health.

Integrating endocrine-related health effects into comparative human toxicity characterization

Endocrine-disrupting chemicals have the ability to interfere with and alter functions of the hormone system, leading to adverse effects on reproduction, growth and development. Despite growing concerns over their now ubiquitous presence in the environment, endocrine-related human health effects remain largely outside of comparative human toxicity characterization frameworks as applied for example in life cycle impact assessments. In this paper, we propose a new methodological framework to consistently integrate endocrine-related health effects into comparative human toxicity characterization. We present two quantitative and operational approaches for extrapolating towards a common point of departure from both in vivo and dosimetry-adjusted in vitro endocrine-related effect data and deriving effect factors as well as corresponding characterization factors for endocrine-active/endocrine-disrupting chemicals. Following the proposed approaches, we calculated effect factors for 323 chemicals, reflecting their endocrine potency, and related characterization factors for 157 chemicals, expressing their relative endocrine-related human toxicity potential. Developed effect and characterization factors are ready for use in the context of chemical prioritization and substitution as well as life cycle impact assessment and other comparative assessment frameworks. Endocrine-related effect factors were found comparable to existing effect factors for cancer and non-cancer effects, indicating that (1) the chemicals’ endocrine potency is not necessarily higher or lower than other effect potencies and (2) using dosimetry-adjusted effect data to derive effect factors does not consistently overestimate the effect of potential endocrine disruptors. Calculated characterization factors span over 8–11 orders of magnitude for different substances and emission compartments and are dominated by the range in endocrine potencies.

In silico health effect prioritization of environmental chemicals through transcriptomics data exploration from a chemo-centric view

With the explosive growth of synthetic compounds, the health effects caused by exogenous chemical exposure have attracted more and more public attention. The prediction of health effect is a never-ending story. Collective resource of transcriptomics data offers an opportunity to understand and identify the multiple health effects of small molecule. Inspired by the fact that environmental chemicals of high health risk frequently share both similar gene expression profile and common structural feature of certain drugs, we here propose a novel computational effect prioritization method for environmental chemicals through transcriptomics data exploration from a chemo-centric view. Specifically, non-negative matrix factorization (NMF) method has been adopted to get the association network linking structural features with transcriptomics characteristics of drugs with specific effects. The model yields 13 pivotal types of effects, so-called components, that represent drug categories with common chemo- and geno- type features. Moreover, the established model effectively prioritizes potential toxic effects for the external chemicals from the endocrine disruptor screening program (EDSP) for their potential estrogenicity and other verified risks. Even if only the highest priority is set for the estrogenic effect, the precision and recall can reach 0.76 and 0.77 respectively for these chemicals. Our effort provides a successful endeavor as to profile potential toxic effects simultaneously for environmental chemicals using both chemical and omics data.

Systematic Assessment of Exposure Variations on Observed Bioactivity in Zebrafish Chemical Screening.

The embryonic zebrafish is a powerful tool for high-throughput screening of chemicals. While this model has significant potential for use in safety assessments and chemical prioritization, a lack of exposure protocol harmonized across laboratories has limited full model adoption. To assess the potential that exposure protocols alter chemical bioactivity, we screened a set of eight chemicals and one 2D nanomaterial across four different regimens: (1) the current Tanguay laboratory’s standard protocol of dechorionated embryos and static exposure in darkness; (2) exposure with chorion intact; (3) exposure under a 14 h light: 10 h dark cycle; and (4) exposure with daily chemical renewal. The latter three regimens altered the concentrations, resulting in bioactivity of the test agents compared to that observed with the Tanguay laboratory’s standard regimen, though not directionally the same for each chemical. The results of this study indicate that with the exception for the 2D nanomaterial, the screening design did not change the conclusion regarding chemical bioactivity, just the nominal concentrations producing the observed activity. Since the goal of tier one chemical screening often is to differentiate active from non-active chemicals, researchers could consider the trade-offs regarding cost, labor, and sensitivity in their study design without altering hit rates. Taken further, these results suggest that it is reasonably feasible to reach agreement on a standardized exposure regiment, which will promote data sharing without sacrificing data content.

Using chemical structure information to develop predictive models for in vitro toxicokinetic parameters to inform high-throughput risk-assessment

The toxicokinetic (TK) parameters fraction of the chemical unbound to plasma proteins and metabolic clearance are critical for relating exposure and internal dose when building in vitro-based risk assessment models. However, experimental toxicokinetic studies have only been carried out on limited chemicals of environmental interest (~1000 chemicals with TK data relative to tens of thousands of chemicals of interest). This work evaluated the utility of chemical structure information to predict TK parameters in silico; development of cluster-based read-across and quantitative structure–activity relationship models of fraction unbound or fub (regression) and intrinsic clearance or Clint (classification and regression) using a dataset of 1487 chemicals; utilization of predicted TK parameters to estimate uncertainty in steady-state plasma concentration (Css); and subsequent in vitro–in vivo extrapolation analyses to derive bioactivity-exposure ratio (BER) plot to compare human oral equivalent doses and exposure predictions using androgen and estrogen receptor activity data for 233 chemicals as an example dataset. The results demonstrate that fub is structurally more predictable than Clint. The model with the highest observed performance for fub had an external test set RMSE/σ = 0.61 and R2 = 0.57, for Clint classification had an external test set accuracy = 73.2%, and for intrinsic clearance regression had an external test set RMSE/σ = 0.92 and R2 = 0.16. This relatively low performance is in part due to the large uncertainty in the underlying Clint data. We show that Css is relatively insensitive to uncertainty in Clint. The models were benchmarked against the ADMET Predictor software. Finally, the BER analysis allowed identification of 14 out of 136 chemicals for further risk assessment demonstrating the utility of these models in aiding risk-based chemical prioritization.

Screening-Level Estimates of Environmental Release Rates, Predicted Exposures, and Toxic Pressures of Currently Used Chemicals.

We describe a procedure to quantify emissions of chemicals for environmental protection, assessment, and management purposes. The procedure uses production and use volumes from registration dossiers and combines these with Specific Environmental Release Category data. The procedure was applied in a case study. Emission estimations were made for chemicals registered under the European Union chemicals regulations for industrial chemicals (Registration, Evaluation, Authorisation and Restriction of Chemicals [REACH]) and for the active ingredients of medicines and crop protection products. Emissions themselves cannot be validated. Instead, emission estimates were followed by multimedia fate modeling and mixture toxic pressure modeling to arrive at predicted environmental concentrations (PECs) and toxic pressures for a typical European water body at steady state, which were compared with other such data. The results show that screening‐level assessments could be performed, and yielded estimates of emissions, PECs, and mixture toxic pressures of chemicals used in Europe. Steady‐state PECs agreed fairly well with measured concentrations. The mixture toxic pressure at steady state suggests the presence of effects in aquatic species assemblages, whereby few compounds dominate the predicted impact. The study shows that our screening‐level emission estimation procedure is sufficiently accurate and precise to serve as a basis for assessment of chemical pollution in aquatic ecosystems at the scale of river catchments. Given a recognized societal need to develop methods for realistic, cumulative exposures, the emission assessment procedure can assist in the prioritization of chemicals in safety policies (such as the European Union REACH regulation), where “possibility to be used safely” needs to be demonstrated, and environmental quality policies (such as the European Union Water Framework Directive), where “good environmental quality” needs to be reached. Environ Toxicol Chem 2020;39:1839–1851. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Non-target and suspect characterisation of organic contaminants in Arctic air – Part 2: Application of a new tool for identification and prioritisation of chemicals of emerging Arctic concern in air

Abstract. The Norwegian Arctic possesses a unique environment for the detection of new potential chemicals of emerging Arctic concern (CEACs) due to remoteness, sparse population and the low number of local contamination sources. Hence, a contaminant present in Arctic air is still considered a priority indication for its environmental stability and environmental mobility. Today, legacy persistent organic pollutants (POPs) and related conventional environmental pollutants are already well-studied because of their identification as Arctic pollutants in the 1980s. Many of them are implemented and reported in various national and international monitoring activities including the Arctic Monitoring and Assessment Programme (AMAP). These standard monitoring schemes, however, are based on compound-specific quantitative analytical methods. Under such conditions, the possibility for the identification of hitherto unidentified contaminants is limited and random at best. Today, new and advanced technological developments allow a broader, unspecific analytical approach as either targeted multicomponent analysis or suspect and non-target screening strategies. In order to facilitate such a wide range of compounds, a wide-scope sample clean-up method for high-volume air samples based on a combination of adsorbents was applied, followed by comprehensive two-dimensional gas chromatography separation and low-resolution time-of-flight mass spectrometric detection (GC × GC-LRMS). During the study reported here, simultaneous non-target and suspect screening were applied. The detection of over 700 compounds of interest in the particle phase and over 1200 compounds in the gaseous phase is reported. Of those, 62 compounds were confirmed with reference standards and 90 compounds with a probable structure (based upon mass spectrometric interpretation and library spectrum comparison). These included compounds already detected in Arctic matrices and compounds not detected previously (see also Fig. 1). In addition, 241 compounds were assigned a tentative structure or compound class. Hitherto unknown halogenated compounds, which are not listed in the mass spectral libraries used, were also detected and partly identified.

Toward a Computational Ecotoxicity Assay.

Thousands of anthropogenic chemicals are released into the environment each year, posing potential hazards to human and environmental health. Toxic chemicals may cause a variety of adverse health effects, triggering immediate symptoms or delayed effects over longer periods of time. It is thus crucial to develop methods that can rapidly screen and predict the toxicity of chemicals to limit the potential harmful impacts of chemical pollutants. Computational methods are being increasingly used in toxicity predictions. Here, the method of molecular docking is assessed for screening potential toxicity of a variety of xenobiotic compounds, including pesticides, pharmaceuticals, pollutants, and toxins derived from the chemical industry. The method predicts the binding energy of pollutants to a set of carefully selected receptors under the assumption that toxicity in many cases is related to interference with biochemical pathways. The strength of the applied method lies in its rapid generation of interaction maps between potential toxins and the targeted enzymes, which could quickly yield molecular-level information and insight into potential perturbation pathways, aiding in the prioritization of chemicals for further tests. Two scoring functions are compared: Autodock Vina and the machine-learning scoring function RF-Score-VS. The results are promising, although hampered by the accuracy of the scoring functions. The strengths and weaknesses of the docking protocol are discussed, as well as future directions for improving the accuracy for the purpose of toxicity predictions.

Mechanisms of pH-Dependent Uptake of Ionizable Organic Chemicals by Fish from Oil Sands Process-Affected Water (OSPW).

Uptake and effects of ionizable organic chemicals (IOCs) that are weak acids in aqueous solution by fish can differ as a function of pH. While the pH-dependent behavior of select IOCs is well-understood, complex mixtures of IOCs, e.g., from oil sands process-affected water (OSPW), have not yet been studied systematically. Here, we established an in vitro screening method using the rainbow trout gill cell line, RTgill-W1, to investigate pH-dependent cytotoxicity and permeation of IOCs across cultured epithelia using ultra-high-performance liquid chromatography with high-resolution mass spectrometry (UPLC-HRMS). The assay was benchmarked using model chemicals and technical mixtures, and then used to characterize fractions and reconstituted extracts of field-collected OSPW. Significant pH-dependent cytotoxicity of individual IOCs, acidic fractions, and reconstituted extracts of OSPW was observed. In vitro data were in good agreement with data from a 96 h in vivo exposure experiment with juvenile rainbow trout. Permeation of some IOCs from OSPW was mediated by active transport, as revealed by studies in which inhibitors of these active transport mechanisms were applied. We conclude that the RTgill-W1 in vitro assay is useful for the screening of pH-dependent uptake of IOCs in fish, and has applications for in vitro-in vivo extrapolation, and prioritization of chemicals in nontarget screenings.

Evaluation of the Aryl Hydrocarbon Receptor Response in LMH 3D Spheroids.

In the present study, we investigated whether the immortalized chicken hepatocellular carcinoma cell line, leghorn male hepatoma (LMH), had a comparable aryl hydrocarbon receptor (AhR) response to primary chicken embryonic hepatocytes (CEHs) when used in a well-established assay for chemical screening and prioritization. The LMH cells were grown as 2-dimensional (2D) confluent cells and 3D spheroids to determine the optimal cell culture states for chemical screening. Cytochrome P450 1A4 and 1A5 (CYP1A) activity and gene expression were compared between CEHs and LMH cells grown in 2 culture states following exposure to the dioxin-like compound 3,3',4,4',5-pentachlorobiphenyl (PCB-126). The CYP1A activity was measured using the ethoxyresorufin-O-deethylase (EROD) assay, and changes in mRNA expression associated with the AhR pathway were determined using a custom-designed polymerase chain reaction array. Among LMH cell culture states (i.e., 2D vs 3D), EROD induction was observed only in 3D LMH spheroids. Similarly, 3D spheroids had the greatest number of changes in AhR-related genes compared with confluent cells. Overall, these results suggest that LMH cells grown as 3D spheroids have a metabolic and gene expression profile that is comparable to that of CEH, and may represent a suitable animal-free alternative for in vitro screening of chemicals. Environ Toxicol Chem 2020;39:1693-1701. © 2020 SETAC.

Pesticide prioritization approaches and limitations in environmental monitoring studies: From Europe to Latin America and the Caribbean

Assessment and management of issues related to pesticide residues, such as environmental fate, monitoring and toxicity, are complex and, in many cases, require costly studies. The early establishment of a priority list of pesticides that should be monitored and assigned to a restricted-use policy is an important issue of post-registration Risk Assessment (RA). Various pesticide registration approaches have been adopted by different countries with those from Europe and the USA being the most popular, constituting the major prototypes for registration approaches in other countries. Adoption of pesticide registration and monitoring systems developed in Europe or USA by Latin American and Caribbean countries may underestimate factors affecting the environmental fate and toxicity of pesticides in their own countries. Incentive for this short review was the activities undertaken during the three KNOWPEC workshops held in Costa Rica, Argentina and Bolivia where European pesticide experts met Latin American experience in the form of Costa Rica’s exceptional environmental conditions and ecology, Argentina’s and Uruguay’s soyisation and Bolivia’s contrasting climate and agricultural zones. During the parallel activities of the workshop - including scientific presentations, field trips, interviews and meetings among European partners and pesticide stakeholders in Latin America, - the whole pesticide chain (import-export, trade, application, plant protection-efficacy, residues, monitoring, remediation and risk) was studied and clarified. Recently-published chemical prioritization studies were reviewed to consider their use as a tool to support risk assessments. Differences in regional practices are highlighted as regards to the establishment of RA or prioritization strategy in European and Latin American regimes. General guidance of establishing a cost-effective pesticide monitoring scheme in water bodies of Latin America and the Caribbean (LAC) is also proposed. Moreover, we summarize the most important factors that should be taken into consideration for prioritization approaches and categorization used in pesticide environmental monitoring studies. Consideration of current RA approaches and limitations, and pesticide prioritization exercises highlighted in this Commentary could assist in the management of pesticides in Latin America and Caribbean.

Application of the hard and soft, acids and bases (HSAB) theory as a method to predict cumulative neurotoxicity

Xenobiotic electrophiles can form covalent adducts that may impair protein function, damage DNA, and may lead a range of adverse effects. Cumulative neurotoxicity is one adverse effect that has been linked to covalent protein binding as a Molecular Initiating Event (MIE). This paper describes a mechanistic in silico chemical screening approach for neurotoxicity based on Hard and Soft Acids and Bases (HSAB) theory. We evaluated the applicability of HSAB-based electrophilicity screening protocol for neurotoxicity on 19 positive and 19 negative reference chemicals. These reference chemicals were identified from the literature, using available information on mechanisms of neurotoxicity whenever possible. In silico screening was based on structural alerts for protein binding motifs and electrophilicity index in the range of known neurotoxicants. The approach demonstrated both a high positive prediction rate (82–90 %) and specificity (90 %). The overall sensitivity was relatively lower (47 %). However, when predicting the toxicity of chemicals known or suspected of acting via non-specific adduct formation mechanism, the HSAB approach identified 7/8 (sensitivity 88 %) of positive control chemicals correctly. Consequently, the HSAB-based screening is a promising approach of identifying possible neurotoxins with adduct formation molecular initiating events. While the approach must be expanded over time to capture a wider range of MIEs involved in neurotoxicity, the mechanistic nature of the screen allows users to flag chemicals for possible adduct formation MIEs. Thus, the HSAB based toxicity screening is a promising strategy for toxicity assessment and chemical prioritization in neurotoxicology and other health endpoints that involve adduct formation.

Comparison of threshold of toxicological concern (TTC) values to oral reference dose (RfD) values

Thousands of chemicals have limited, or no hazard data readily available to characterize human risk. The threshold of toxicological concern (TTC) constitutes a science-based tool for screening level risk-based prioritization of chemicals with low exposure. Herein we compare TTC values to more rigorously derived reference dose (RfD) values for 288 chemicals in the U.S. Environmental Protection Agency's (US EPA) Integrated Risk Information System (IRIS) database. Using the Cramer decision tree and the Kroes tiered decision tree approaches to determine TTC values, the TCC for the majority of these chemicals were determined to be lower than their corresponding RfD values. The ratio of log10(RfD/TCC) was used to measure the differences between these values and the mean ratio for the substances evaluated was ~0.74 and ~0.79 for the Cramer and Kroes approach, respectively, when considering the Cramer Classes only. These data indicate that the RfD values for Cramer Class III compounds were, on average, ~6-fold higher than their TTC value. These analyses indicate that provisional oral toxicity values might be estimated from TTCs in data-poor or emergency situations; moreover, RfD values that are well below TTC values (e.g., 2 standard deviations below the log10(Ratio)) might be overly conservative and targets for re-evaluation.

Characterizing honey bee exposure and effects from pesticides for chemical prioritization and life cycle assessment

Agricultural pesticides are key contributors to pollinator decline worldwide. However, methods for quantifying impacts associated with pollinator exposure to pesticides are currently missing in comparative risk screening, chemical substitution and prioritization, and life cycle impact assessment methods. To address this gap, we developed a method for quantifying pesticide field exposure and ecotoxicity effects of honey bees as most economically important pollinator species worldwide. We defined bee intake and dermal contact fractions representing respectively oral and dermal exposure per unit mass applied, and tested our model on two pesticides applied to oilseed rape. Our results show that exposure varies between types of forager bees, with highest dermal contact fraction of 59 ppm in nectar foragers for lambda-cyhalothrin (insecticide), and highest oral intake fractions of 32 and 190 ppm in nectar foragers for boscalid (fungicide) and lambda-cyhalothrin, respectively. Hive oral exposure is up to 115 times higher than forager oral exposure. Combining exposure with effect estimates yields impacts, which are three orders of magnitude higher for the insecticide. Overall, nectar foragers are the most affected forager type for both pesticides, dominated by oral exposure. Our framework constitutes an important step toward integrating pollinator impacts in chemical substitution and life cycle impact assessment, and should be expanded to cover all relevant pesticide-crop combinations.

A comprehensive analysis of racial disparities in chemical biomarker concentrations in United States women, 1999–2014

BackgroundStark racial disparities in disease incidence among American women remain a persistent public health challenge. These disparities likely result from complex interactions between genetic, social, lifestyle, and environmental risk factors. The influence of environmental risk factors, such as chemical exposure, however, may be substantial and is poorly understood. ObjectivesWe quantitatively evaluated chemical-exposure disparities by race/ethnicity, life stage, and time in United States (US) women (n = 38,080) by using biomarker data for 143 chemicals from the National Health and Nutrition Examination Survey (NHANES) 1999–2014. MethodsWe applied a series of survey-weighted, generalized linear models using data from the entire NHANES women population along with cycle and age-group stratified subpopulations. The outcome was chemical biomarker concentration, and the main predictor was race/ethnicity with adjustment for age, socioeconomic status, smoking habits, and NHANES cycle. ResultsCompared to non-Hispanic White women, the highest disparities were observed for non-Hispanic Black, Mexican American, Other Hispanic, and Other Race/Multi-Racial women with higher levels of pesticides and their metabolites, including 2,5-dichlorophenol, o,p’-DDE, beta-hexachlorocyclohexane, and 2,4-dichlorophenol, along with personal care and consumer product compounds, including parabens and monoethyl phthalate, as well as several metals, such as mercury and arsenic. Moreover, for Mexican American, Other Hispanic, and non-Hispanic black women, there were several exposure disparities that persisted across age groups, such as higher 2,4- and 2,5-dichlorophenol concentrations. Exposure levels for methyl and propyl parabens, however, were the highest in non-Hispanic black compared to non-Hispanic white children with average differences exceeding 4-fold. Exposure disparities for methyl and propyl parabens are increasing over time in Other Race/Multi-Racial women while fluctuating for non-Hispanic Black, Mexican American, and Other Hispanic. Cotinine levels are among the highest in Non-Hispanic White women compared to Mexican American and Other Hispanic women with disparities plateauing and increasing, respectively. DiscussionWe systematically evaluated differences in chemical exposures across women of various race/ethnic groups and across age groups and time. Our findings could help inform chemical prioritization in designing epidemiological and toxicological studies. In addition, they could help guide public health interventions to reduce environmental and health disparities across populations.

An automated framework for compiling and integrating chemical hazard data.

Comparative chemical hazard assessment, which compares hazards for several endpoints across several chemicals, can be used for a variety of purposes including alternatives assessment and the prioritization of chemicals for further assessment. A new framework was developed to compile and integrate chemical hazard data for several human health and ecotoxicity endpoints from public online sources including hazardous chemical lists, Globally Harmonized System hazard codes (H-codes) or hazard categories from government health agencies, experimental quantitative toxicity values, and predicted values using Quantitative Structure-Activity Relationship (QSAR) models. QSAR model predictions were obtained using EPA's Toxicity Estimation Software Tool. Java programming was used to download hazard data, convert data from each source into a consistent score record format, and store the data in a database. Scoring criteria based on the EPA's Design for the Environment Program Alternatives Assessment Criteria for Hazard Evaluation were used to determine ordinal hazard scores (i.e., low, medium, high, or very high) for each score record. Different methodologies were assessed for integrating data from multiple sources into one score for each hazard endpoint for each chemical. The chemical hazard assessment (CHA) Database developed in this study currently contains more than 990,000 score records for more than 85,000 chemicals. The CHA Database and the methods used in its development may contribute to several cheminformatics, public health, and environmental activities.

Leveraging complementary computational models for prioritizing chemicals of developmental and reproductive toxicity concern: an example of food contact materials

The evaluation of developmental and reproductive toxicity of food contact materials (FCMs) is an important task for food safety. Since traditional experiments are both time-consuming and labor-intensive, only a small number of FCMs have sufficient toxicological data for evaluating their effects on human health. While computational methods such as structural alerts and quantitative structure-activity relationships can serve as first-line tools for the identification of chemicals of high toxicity concern, models with binary outputs and unsatisfied accuracy and coverage prevent the use of computational methods for prioritizing chemicals of high concern. This study proposed a genetic algorithm-based method to develop a weight-of-evidence (WoE) model leveraging complementary methods of structural alerts, quantitative structure-activity relationships and in silico toxicogenomics models for chemical prioritization. The WoE model was applied to evaluate 623 food contact chemicals and identify 26 chemicals of high toxicity concern, where 13 chemicals have been reported to be developmental or reproductive toxic and further experiments are suggested for the remaining 13 chemicals without toxicity data related to developmental and reproductive effects. The proposed WoE model is potentially useful for prioritizing chemicals of high toxicity concern and the methodology may be applied to toxicities other than developmental and reproductive toxicity.

The role of fit-for-purpose assays within tiered testing approaches: A case study evaluating prioritized estrogen-active compounds in an in vitro human uterotrophic assay

Chemical risk assessment relies on toxicity tests that require significant numbers of animals, time and costs. For the >30,000 chemicals in commerce, the current scale of animal testing is insufficient to address chemical safety concerns as regulatory and product stewardship considerations evolve to require more comprehensive understanding of potential biological effects, conditions of use, and associated exposures. We demonstrate the use of a multi-level new approach methodology (NAMs) strategy for hazard- and risk-based prioritization to reduce animal testing. A Level 1/2 chemical prioritization based on estrogen receptor (ER) activity and metabolic activation using ToxCast data was used to select 112 chemicals for testing in a Level 3 human uterine cell estrogen response assay (IKA assay). The Level 3 data were coupled with quantitative in vitro to in vivo extrapolation (Q-IVIVE) to support bioactivity determination (as a surrogate for hazard) in a tissue-specific context. Assay AC50s and Q-IVIVE were used to estimate human equivalent doses (HEDs), and HEDs were compared to rodent uterotrophic assay in vivo-derived points of departure (PODs). For substances active both in vitro and in vivo, IKA assay-derived HEDs were lower or equivalent to in vivo PODs for 19/23 compounds (83%). Activity exposure relationships were calculated, and the IKA assay was as or more protective of human health than the rodent uterotrophic assay for all IKA-positive compounds. This study demonstrates the utility of biologically relevant fit-for-purpose assays and supports the use of a multi-level strategy for chemical risk assessment.