A value of information framework for assessing the trade-offs associated with uncertainty, duration, and cost of chemical toxicity testing.

A number of investigators have explored the use of value of information (VOI) analysis to evaluate alternative information collection procedures in diverse decision-making contexts. This paper presents an analytic framework for determining the value of toxicity information used in risk-based decision making. The framework is specifically designed to explore the trade-offs between cost, timeliness, and uncertainty reduction associated with different toxicity-testing methodologies. The use of the proposed framework is demonstrated by two illustrative applications which, although based on simplified assumptions, show the insights that can be obtained through the use of VOI analysis. Specifically, these results suggest that timeliness of information collection has a significant impact on estimates of the VOI of chemical toxicity tests, even in the presence of smaller reductions in uncertainty. The framework introduces the concept of the expected value of delayed sample information, as an extension to the usual expected value of sample information, to accommodate the reductions in value resulting from delayed decision making. Our analysis also suggests that lower cost and higher throughput testing also may be beneficial in terms of public health benefits by increasing the number of substances that can be evaluated within a given budget. When the relative value is expressed in terms of return-on-investment per testing strategy, the differences can be substantial.

A Framework that Considers the Impacts of Time, Cost, and Uncertainty in the Determination of the Cost Effectiveness of Toxicity-Testing Methodologies.

Regulatory agencies are required to evaluate the impacts of thousands of chemicals. Toxicological tests currently used in such evaluations are time-consuming and resource intensive; however, advances in toxicology and related fields are providing new testing methodologies that reduce the cost and time required for testing. The selection of a preferred methodology is challenging because the new methodologies vary in duration and cost, and the data they generate vary in the level of uncertainty. This article presents a framework for performing cost-effectiveness analyses (CEAs) of toxicity tests that account for cost, duration, and uncertainty. This is achieved by using an output metric-the cost per correct regulatory decision-that reflects the three elements. The framework is demonstrated in two example CEAs, one for a simple decision of risk acceptability and a second, more complex decision, involving the selection of regulatory actions. Each example CEA evaluates five hypothetical toxicity-testing methodologies which differ with respect to cost, time, and uncertainty. The results of the examples indicate that either a fivefold reduction in cost or duration can be a larger driver of the selection of an optimal toxicity-testing methodology than a fivefold reduction in uncertainty. Uncertainty becomes of similar importance to cost and duration when decisionmakers are required to make more complex decisions that require the determination of small differences in risk predictions. The framework presented in this article may provide a useful basis for the identification of cost-effective methods for toxicity testing of large numbers of chemicals.

Accelerating the Pace of Chemical Risk Assessment.

Changes in chemical regulations worldwide have increased the demand for new data on chemical safety. New approach methodologies (NAMs) are defined broadly here as including in silico approaches and in chemico and in vitro assays, as well as the inclusion of information from the exposure of chemicals in the context of hazard [European Chemicals Agency, " New Approach Methodologies in Regulatory Science ", 2016]. NAMs for toxicity testing, including alternatives to animal testing approaches, have shown promise to provide a large amount of data to fill information gaps in both hazard and exposure. In order to increase experience with the new data and to advance the applications of NAM data to evaluate the safety of data-poor chemicals, demonstration case studies have to be developed to build confidence in their usability. Case studies can be used to explore the domains of applicability of the NAM data and identify areas that would benefit from further research, development, and application. To ensure that this science evolves with direct input from and engagement by risk managers and regulatory decision makers, a workshop was convened among senior leaders from international regulatory agencies to identify common barriers for using NAMs and to propose next steps to address them. Central to the workshop were a series of collaborative case studies designed to explore areas where the benefits of NAM data could be demonstrated. These included use of in vitro bioassays data in combination with exposure estimates to derive a quantitative assessment of risk, use of NAMs for updating chemical categorizations, and use of NAMs to increase understanding of exposure and human health toxicity of various chemicals. The case study approach proved effective in building collaborations and engagement with regulatory decision makers and to promote the importance of data and knowledge sharing among international regulatory agencies. The case studies will be continued to explore new ways of describing hazard (i.e., pathway perturbations as a measure of adversity) and new ways of describing risk (i.e., using NAMs to identify protective levels without necessarily being predictive of a specific hazard). Importantly, the case studies also highlighted the need for increased training and communication across the various communities including the risk assessors, regulators, stakeholders (e.g., industry, non-governmental organizations), and the general public. The development and application of NAMs will play an increasing role in filling important data gaps on the safety of chemicals, but confidence in NAMs will only come with learning by doing and sharing in the experience.

Chemical Risk Assessment: Traditional vs Public Health Perspectives.

Preventing adverse health effects of environmental chemical exposure is fundamental to protecting individual and public health. When done efficiently and properly, chemical risk assessment enables risk management actions that minimize the incidence and effects of environmentally induced diseases related to chemical exposure. However, traditional chemical risk assessment is faced with multiple challenges with respect to predicting and preventing disease in human populations, and epidemiological studies increasingly report observations of adverse health effects at exposure levels predicted from animal studies to be safe for humans. This discordance reinforces concerns about the adequacy of contemporary risk assessment practices for protecting public health. It is becoming clear that to protect public health more effectively, future risk assessments will need to use the full range of available data, draw on innovative methods to integrate diverse data streams, and consider health endpoints that also reflect the range of subtle effects and morbidities observed in human populations. Considering these factors, there is a need to reframe chemical risk assessment to be more clearly aligned with the public health goal of minimizing environmental exposures associated with disease.

Comprehensive environmental assessment: a meta-assessment approach.

With growing calls for changes in the field of risk assessment, improved systematic approaches for addressing environmental issues with greater transparency and stakeholder engagement are needed to ensure sustainable trade-offs. Here we describe the comprehensive environmental assessment (CEA) approach as a holistic way to manage complex information and to structure input from diverse stakeholder perspectives to support environmental decision-making for the near- and long-term. We further note how CEA builds upon and incorporates other available tools and approaches, describe its current application at the U.S. Environmental Protection Agency, and point out how it could be extended in evaluating a major issue such as the sustainability of biofuels.

Towards replacement of animal tests with in vitro assays: a gene expression biomarker predicts in vitro and in vivo estrogen receptor activity.

High-throughput transcriptomics (HTTr) has the potential to support efforts to reduce or replace some animal tests. In past studies, we described a computational approach utilizing a gene expression biomarker consisting of 46 genes to predict estrogen receptor (ER) activity after chemical exposure in ER-positive human breast cancer cells including the MCF-7 cell line. We hypothesized that the biomarker model could identify ER activities of chemicals examined by Endocrine Disruptor Screening Program (EDSP) Tier 1 screening assays in which transcript profiles of the same chemicals were examined in MCF-7 cells. For the 62 chemicals examined including 5 chemicals examined in this study using RNA-Seq, the ER biomarker model accuracy was 1) 97% for in vitro reference chemicals, 2) 76-85% for guideline uterotrophic assays, and 3) 87-88% for guideline and nonguideline uterotrophic assays. For the same chemicals, these accuracies were similar or slightly better than those of the ToxCast ER model based on 18 in vitro assays. The performance of the ER biomarker model indicates that HTTr interpreted using the ER biomarker correctly identifies active and inactive ER reference chemicals. As part of the HTTr screening program the approach could rapidly identify chemicals with potential ER bioactivities for additional screening and testing.

A review of the genotoxicity of 1,2-dichloroethane (EDC).

1,2-Dichloroethane (EDC, CAS#107-06-2) is a high production volume halogenated aliphatic hydrocarbon that is used mainly in the manufacture of vinyl chloride. EDC has been found in ambient and residential air samples, as well as in groundwater, surface water and drinking water. EDC has been well-studied in a variety of genotoxicity assays, and appears to involve the metabolic activation of the parent compound. We critically evaluated the genotoxicity data of EDC and its metabolites as part of an evaluation of carcinogenic mechanisms of action of EDC. EDC is genotoxic in multiple test systems via multiple routes of exposure. EDC has been shown to induce DNA adduct formation, gene mutations and chromosomal aberrations in the presence of key activation enzymes (including CYP450s and/or GSTs) in laboratory animal and in vitro studies. EDC was negative for clastogenesis as measured by the micronucleus assay in mice. In general, an increased level of DNA damage is observed related to the GSH-dependent bioactivation of EDC. Increased chromosomal aberrations with increased CYP450 expression were suggestive of a role for the oxidative metabolites of EDC in inducing chromosomal damage. Taken together, these studies demonstrate that EDC exposure, in the presence of key enzymes (including CYP450s and/or GSTs), leads to DNA adduct formation, gene mutations and chromosomal aberrations.

Evaluation of Existing QSAR Models and Structural Alerts and Development of New Ensemble Models for Genotoxicity Using a Newly Compiled Experimental Dataset.

Regulatory agencies world-wide face the challenge of performing risk-based prioritization of thousands of substances in commerce. In this study, a major effort was undertaken to compile a large genotoxicity dataset (54,805 records for 9299 substances) from several public sources (e.g., TOXNET, COSMOS, eChemPortal). The names and outcomes of the different assays were harmonized, and assays were annotated by type: gene mutation in Salmonella bacteria (Ames assay) and chromosome mutation (clastogenicity) in vitro or in vivo (chromosome aberration, micronucleus, and mouse lymphoma Tk +/- assays). This dataset was then evaluated to assess genotoxic potential using a categorization scheme, whereby a substance was considered genotoxic if it was positive in at least one Ames or clastogen study. The categorization dataset comprised 8442 chemicals, of which 2728 chemicals were genotoxic, 5585 were not and 129 were inconclusive. QSAR models (TEST and VEGA) and the OECD Toolbox structural alerts/profilers (e.g., OASIS DNA alerts for Ames and chromosomal aberrations) were used to make in silico predictions of genotoxicity potential. The performance of the individual QSAR tools and structural alerts resulted in balanced accuracies of 57-73%. A Naïve Bayes consensus model was developed using combinations of QSAR models and structural alert predictions. The 'best' consensus model selected had a balanced accuracy of 81.2%, a sensitivity of 87.24% and a specificity of 75.20%. This in silico scheme offers promise as a first step in ranking thousands of substances as part of a prioritization approach for genotoxicity.

Integrating publicly available information to screen potential candidates for chemical prioritization under the Toxic Substances Control Act: A proof of concept case study using genotoxicity and carcinogenicity.

The Toxic Substances Control Act (TSCA) became law in the U.S. in 1976 and was amended in 2016. The amended law requires the U.S. EPA to perform risk-based evaluations of existing chemicals. Here, we developed a tiered approach to screen potential candidates based on their genotoxicity and carcinogenicity information to inform the selection of candidate chemicals for prioritization under TSCA. The approach was underpinned by a large database of carcinogenicity and genotoxicity information that had been compiled from various public sources. Carcinogenicity data included weight-of-evidence human carcinogenicity evaluations and animal cancer data. Genotoxicity data included bacterial gene mutation data from the Salmonella (Ames) and Escherichia coli WP2 assays and chromosomal mutation (clastogenicity) data. Additionally, Ames and clastogenicity outcomes were predicted using the alert schemes within the OECD QSAR Toolbox and the Toxicity Estimation Software Tool (TEST). The evaluation workflows for carcinogenicity and genotoxicity were developed along with associated scoring schemes to make an overall outcome determination. For this case study, two sets of chemicals, the TSCA Active Inventory non-confidential portion list available on the EPA CompTox Chemicals Dashboard (33,364 chemicals, 'TSCA Active List') and a representative proof-of-concept (POC) set of 238 chemicals were profiled through the two workflows to make determinations of carcinogenicity and genotoxicity potential. Of the 33,364 substances on the 'TSCA Active List', overall calls could be made for 20,371 substances. Here 46.67%% (9507) of substances were non-genotoxic, 0.5% (103) were scored as inconclusive, 43.93% (8949) were predicted genotoxic and 8.9% (1812) were genotoxic. Overall calls for genotoxicity could be made for 225 of the 238 POC chemicals. Of these, 40.44% (91) were non-genotoxic, 2.67% (6) were inconclusive, 6.22% (14) were predicted genotoxic, and 50.67% (114) genotoxic. The approach shows promise as a means to identify potential candidates for prioritization from a genotoxicity and carcinogenicity perspective.

Utility of In Vitro Bioactivity as a Lower Bound Estimate of In Vivo Adverse Effect Levels and in Risk-Based Prioritization.

Use of high-throughput, in vitro bioactivity data in setting a point-of-departure (POD) has the potential to accelerate the pace of human health safety evaluation by informing screening-level assessments. The primary objective of this work was to compare PODs based on high-throughput predictions of bioactivity, exposure predictions, and traditional hazard information for 448 chemicals. PODs derived from new approach methodologies (NAMs) were obtained for this comparison using the 50th (PODNAM, 50) and the 95th (PODNAM, 95) percentile credible interval estimates for the steady-state plasma concentration used in in vitro to in vivo extrapolation of administered equivalent doses. Of the 448 substances, 89% had a PODNAM, 95 that was less than the traditional POD (PODtraditional) value. For the 48 substances for which PODtraditional < PODNAM, 95, the PODNAM and PODtraditional were typically within a factor of 10 of each other, and there was an enrichment of chemical structural features associated with organophosphate and carbamate insecticides. When PODtraditional < PODNAM, 95, it did not appear to result from an enrichment of PODtraditional based on a particular study type (eg, developmental, reproductive, and chronic studies). Bioactivity:exposure ratios, useful for identification of substances with potential priority, demonstrated that high-throughput exposure predictions were greater than the PODNAM, 95 for 11 substances. When compared with threshold of toxicological concern (TTC) values, the PODNAM, 95 was greater than the corresponding TTC value 90% of the time. This work demonstrates the feasibility, and continuing challenges, of using in vitro bioactivity as a protective estimate of POD in screening-level assessments via a case study.

The role of p53 in silica-induced cellular and molecular responses associated with carcinogenesis.

Crystalline silica (silica), a suspected human carcinogen, produces an increase in reactive oxygen species (ROS) when fractured using mechanical tools used in several occupations. Although ROS has been linked to apoptosis, DNA damage, and carcinogenesis, the role of enhanced ROS production by silica in silica-induced carcinogenesis is not completely understood. The goal of this study was to compare freshly fractured and aged silica-induced molecular alterations in human immortalized/transformed bronchial epithelial cells (BEAS-IIB) and lung cancer cells with altered (H460) or deficient (H1299) p53 expression. Exposure to freshly fractured or aged silica produced divergent cellular responses in certain downstream cellular events, including ROS production, apoptosis, cell cycle and chromosomal changes, and gene expression. ROS production increased significantly following exposure to freshly fractured silica compared to aged silica in BEAS-IIB and H460 cells. Apoptosis showed a comparable enhanced level of induction with freshly fractured or aged silica in both cancer lines with p53 functional changes. p53 protein was present in the BEAS-IIB and was absent in cancer cell lines after silica exposure. Exposure to freshly fractured silica also resulted in a rise in aneuploidy in cancer cells with a significantly greater increase in p53-deficient cells. Cytogenetic analysis demonstrated increased metaphase spreads, chromosome breakage, rearrangements, and endoreduplication in both cancer cells. These results suggest that altered and deficient p53 affects the cellular response to freshly fractured silica exposure, and thereby enhances susceptibility and augments cell proliferation and lung cancer development.

The Next Generation Blueprint of Computational Toxicology at the U.S. Environmental Protection Agency.

The U.S. Environmental Protection Agency (EPA) is faced with the challenge of efficiently and credibly evaluating chemical safety often with limited or no available toxicity data. The expanding number of chemicals found in commerce and the environment, coupled with time and resource requirements for traditional toxicity testing and exposure characterization, continue to underscore the need for new approaches. In 2005, EPA charted a new course to address this challenge by embracing computational toxicology (CompTox) and investing in the technologies and capabilities to push the field forward. The return on this investment has been demonstrated through results and applications across a range of human and environmental health problems, as well as initial application to regulatory decision-making within programs such as the EPA's Endocrine Disruptor Screening Program. The CompTox initiative at EPA is more than a decade old. This manuscript presents a blueprint to guide the strategic and operational direction over the next 5 years. The primary goal is to obtain broader acceptance of the CompTox approaches for application to higher tier regulatory decisions, such as chemical assessments. To achieve this goal, the blueprint expands and refines the use of high-throughput and computational modeling approaches to transform the components in chemical risk assessment, while systematically addressing key challenges that have hindered progress. In addition, the blueprint outlines additional investments in cross-cutting efforts to characterize uncertainty and variability, develop software and information technology tools, provide outreach and training, and establish scientific confidence for application to different public health and environmental regulatory decisions.

Application of oligonucleotide microarray technology to toxic occupational exposures.

Microarray technology has advanced toward analysis of toxic occupational exposures in biological systems. Microarray analysis is an ideal way to search for biomarkers of exposure, even if no specific gene or pathway has been identified. Analysis may now be performed on thousands of genes simultaneously, as opposed to small numbers of genes as in the past. This ability has been put to use to analyze gene expression profiles of a variety of occupational toxins in animal models to classify toxins into specific categories based on response. Analysis of normal human cell strains allows an extension of this analysis to investigate the role of interindividual variation in response to various toxins. This methodology was used to analyze four occupationally related toxins in our lab: oxythioquinox (OTQ), a quinoxaline pesticide; malathion, an organophosphate pesticide; di-n-butyl phthalate (DBP), a chemical commonly found in personal care and cosmetic items; and benzo[a]pyrene (BaP), an environmental and occupational carcinogen. The results for each exposure highlighted signaling pathways involved in response to these occupational exposures. Both pesticides showed increase in metabolic enzymes, while DBP showed alterations in genes related to fertility. BaP exposure showed alterations in two cytochrome P450s related to carcinogenicity. When used with occupational exposure information, these data may be used to augment risk assessment to make the workplace safer for a greater proportion of the workforce, including individuals susceptible to disease related to exposures.

Epidemiology: a foundation of environmental decision making.

Many epidemiologic studies are designed so they can be drawn upon to provide scientific evidence for evaluating hazards of environmental exposures, conducting quantitative assessments of risk, and informing decisions designed to reduce or eliminate harmful exposures. However, experimental animal studies are often relied upon for environmental and public health policy making despite the expanding body of observational epidemiologic studies that could inform the relationship between actual, as opposed to controlled, exposures and health effects. This paper provides historical examples of how epidemiology has informed decisions at the U.S. Environmental Protection Agency, discusses some challenges with using epidemiology to inform decision making, and highlights advances in the field that may help address these challenges and further the use of epidemiologic studies moving forward.

Gene expression profiling of di-n-butyl phthalate in normal human mammary epithelial cells.

Studies show that female workers in the personal-care industry have an increased risk of developing cancer believed to be the result of increased exposure to toxic and/or carcinogenic chemicals found in cosmetics, hair dyes, and nail polish. One chemical found in multiple personal-care products, di-n-butyl phthalate (DBP), is a known endocrine disruptor and has been found in increased levels in women of childbearing age. The goal of this study was to elucidate mechanisms of phthalate toxicity in normal human cells to provide information concerning interindividual variation and gene-environment interactions. Normal human mammary epithelial cell strains were obtained from discarded tissues following reduction mammoplasty [Cooperative Human Tissue Network (sponsors: NCI/NDRI)]. Gene transcription in each cell strain was analyzed using high-density oligonucleotide DNA microarrays (U133A, Affymetrix) and changes in the expression of selected genes were verified by real-time polymerase chain reaction (PCR) (ABI). DNA microarrays were hybridized with total RNA that was collected after DBP treatment for 5 hr and 10 hr. RNA was harvested from the vehicle control (acetone) at 10 hr. Data Mining Tool software (Affymetrix) was used to separate genes in clusters based on their expression patterns over time. Only 57 genes were found to be altered in all four cell strains following exposure to DBP. These included genes involved in fertility (inhibin, placental growth factor), immune response (tumor necrosis factor induced protein), and antioxidant status (glutathione peroxidase). Data from this study will help clarify the role of DBP in reproductive toxicity, and yield biomarkers of exposure for future epidemiology studies.

Nanoparticles: health effects--pros and cons.

With the advent of nanotechnology, the prospects for using engineered nanomaterials with diameters of < 100 nm in industrial applications, medical imaging, disease diagnoses, drug delivery, cancer treatment, gene therapy, and other areas have progressed rapidly. The potential for nanoparticles (NPs) in these areas is infinite, with novel new applications constantly being explored. The possible toxic health effects of these NPs associated with human exposure are unknown. Many fine particles generally considered "nuisance dusts" are likely to acquire unique surface properties when engineered to nanosize and may exhibit toxic biological effects. Consequently, the nuisance dust may be transported to distant sites and could induce adverse health effects. In addition the beneficial uses of NPs in drug delivery, cancer treatment, and gene therapy may cause unintentional human exposure. Because of our lack of knowledge about the health effects associated with NP exposure, we have an ethical duty to take precautionary measures regarding their use. In this review we highlight the possible toxic human health effects that can result from exposure to ultrafine particles (UFPs) generated by anthropogenic activities and their cardiopulmonary outcomes. The comparability of engineered NPs to UFPs suggests that the human health effects are likely to be similar. Therefore, it is prudent to elucidate their toxicologic effect to minimize occupational and environmental exposure. Highlighting the human health outcomes caused by UFPs is not intended to give a lesser importance to either the unprecedented technologic and industrial rewards of the nanotechnology or their beneficial human uses.

Respiratory burst: role in signal transduction in alveolar macrophages.

Alveolar macrophages play an important role in defense against airborne pathogens and particles. These macrophages respond through both the adaptive and acquired immune responses, and through the activation of a multitude of signaling pathways. One major macrophage defense mechanism is respiratory burst, the production of reactive oxygen species (ROS). While the ROS produced may act directly in pathogen killing, they may also be involved as secondary signaling messengers. This review focuses on the activation of four main signaling pathways following the production of reactive oxygen species. These pathways include the nuclear factor kappa beta (NFkB), activating protein-1 (AP-1), mitogen-activating protein kinase (MAPK), and phosphotidyl inositol-3 kinase (PI3K) pathways. This review also briefly examines the role of ROS in DNA damage, in particular looking at the base excision repair pathway (BER), the main pathway involved in repair of oxidative DNA damage. This review highlights many of the studies in the field of ROS, signal transduction, and DNA damage; however, work still remains to further elucidate the role of ROS in disease.

Transcriptional signatures of normal human mammary epithelial cells in response to benzo[a]pyrene exposure: a comparison of three microarray platforms.

Microarrays are used to study gene expression in a variety of biological systems. A number of different platforms have been developed, but few studies exist that have directly compared the performance of one platform with another. The goal of this study was to determine array variation by analyzing the same RNA samples with three different array platforms. Using gene expression responses to benzo[a]pyrene exposure in normal human mammary epithelial cells (NHMECs), we compared the results of gene expression profiling using three microarray platforms: photolithographic oligonucleotide arrays (Affymetrix), spotted oligonucleotide arrays (Amersham), and spotted cDNA arrays (NCI). While most previous reports comparing microarrays have analyzed pre-existing data from different platforms, this comparison study used the same sample assayed on all three platforms, allowing for analysis of variation from each array platform. In general, poor correlation was found with corresponding measurements from each platform. Each platform yielded different gene expression profiles, suggesting that while microarray analysis is a useful discovery tool, further validation is needed to extrapolate results for broad use of the data. Also, microarray variability needs to be taken into consideration, not only in the data analysis but also in specific probe selection for each array type.

Differential gene expression in normal human mammary epithelial cells treated with malathion monitored by DNA microarrays.

Organophosphate pesticides are a major source of occupational exposure in the United States. Moreover, malathion has been sprayed over major urban populations in an effort to control mosquitoes carrying West Nile virus. Previous research, reviewed by the U.S. Environmental Protection Agency, on the genotoxicity and carcinogenicity of malathion has been inconclusive, although malathion is a known endocrine disruptor. Here, interindividual variations and commonality of gene expression signatures have been studied in normal human mammary epithelial cells from four women undergoing reduction mammoplasty. The cell strains were obtained from the discarded tissues through the Cooperative Human Tissue Network (sponsors: National Cancer Institute and National Disease Research Interchange). Interindividual variation of gene expression patterns in response to malathion was observed in various clustering patterns for the four cell strains. Further clustering identified three genes with increased expression after treatment in all four cell strains. These genes were two aldo-keto reductases (AKR1C1 and AKR1C2) and an estrogen-responsive gene (EBBP). Decreased expression of six RNA species was seen at various time points in all cell strains analyzed: plasminogen activator (PLAT), centromere protein F (CPF), replication factor C (RFC3), thymidylate synthetase (TYMS), a putative mitotic checkpoint kinase (BUB1), and a gene of unknown function (GenBank accession no. AI859865). Expression changes in all these genes, detected by DNA microarrays, have been verified by real-time polymerase chain reaction. Differential changes in expression of these genes may yield biomarkers that provide insight into interindividual variation in malathion toxicity.