Current status and future directions for a neurotoxicity hazard assessment framework that integrates in silico approaches.

Neurotoxicology is the study of adverse effects on the structure or function of the developing or mature adult nervous system following exposure to chemical, biological, or physical agents. The development of more informative alternative methods to assess developmental (DNT) and adult (NT) neurotoxicity induced by xenobiotics is critically needed. The use of such alternative methods including in silico approaches that predict DNT or NT from chemical structure (e.g., statistical-based and expert rule-based systems) is ideally based on a comprehensive understanding of the relevant biological mechanisms. This paper discusses known mechanisms alongside the current state of the art in DNT/NT testing. In silico approaches available today that support the assessment of neurotoxicity based on knowledge of chemical structure are reviewed, and a conceptual framework for the integration of in silico methods with experimental information is presented. Establishing this framework is essential for the development of protocols, namely standardized approaches, to ensure that assessments of NT and DNT based on chemical structures are generated in a transparent, consistent, and defendable manner.

IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making.

During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.

Evaluation of interactions in chemical mixtures containing cyanides.

Cyanides are highly toxic chemicals found indoors and outdoors, in air, water, and soil. Environmental exposures often are to mixtures of cyanides with other environmental pollutants. Interactive toxicology is the study of the toxicity of a chemical when it occurs with other chemicals or stressors. Such interactions can modify the joint toxicity of a given mixture. Several binary mixtures of cyanides have been studied in humans and animals to develop antidotes, and their mechanism of action is well understood. We used this limited binary weight of evidence to evaluate the toxicity of untested mixtures, extended it, and applied it to complex environmental mixtures to advance methods for joint toxicity assessment. Federal agencies and local entities provide guidance to evaluate such exposures in the absence of specific data. The objective of this paper is to illustrate use and applicability of ATSDR's framework for evaluation of environmental mixtures, specifically the use of weight of evidence in Tier III, using cyanide mixtures as examples. The results show, for certain cyanide mixtures for which data are available, interactions can be evaluated with a high degree of confidence. For complex mixtures that contain unidentified components, such as found in fires, similarity-based grouping risk assessment is proposed.

Principles and Procedures for Assessment of Acute Toxicity Incorporating In Silico Methods.

Acute toxicity in silico models are being used to support an increasing number of application areas including (1) product research and development, (2) product approval and registration as well as (3) the transport, storage and handling of chemicals. The adoption of such models is being hindered, in part, because of a lack of guidance describing how to perform and document an in silico analysis. To address this issue, a framework for an acute toxicity hazard assessment is proposed. This framework combines results from different sources including in silico methods and in vitro or in vivo experiments. In silico methods that can assist the prediction of in vivo outcomes (i.e., LD50) are analyzed concluding that predictions obtained using in silico approaches are now well-suited for reliably supporting assessment of LD50-based acute toxicity for the purpose of GHS classification. A general overview is provided of the endpoints from in vitro studies commonly evaluated for predicting acute toxicity (e.g., cytotoxicity/cytolethality as well as assays targeting specific mechanisms). The increased understanding of pathways and key triggering mechanisms underlying toxicity and the increased availability of in vitro data allow for a shift away from assessments solely based on endpoints such as LD50, to mechanism-based endpoints that can be accurately assessed in vitro or by using in silico prediction models. This paper also highlights the importance of an expert review of all available information using weight-of-evidence considerations and illustrates, using a series of diverse practical use cases, how in silico approaches support the assessment of acute toxicity.

Advances in Assessing Hazard and Risk to Emerging Threats and Emergency Response: Comparing and Contrasting Efforts of 3 Federal Agencies.

Federal statutes authorize several agencies to protect human populations from chemical emergencies and provide guidance to evacuate, clean, and reoccupy affected areas. Each of the authorized federal agencies has developed programs to provide managers, public health officials, and regulators, with a rapid assessment of potential hazards and risks associated with chemical emergencies. Emergency responses vary based on exposure scenarios, routes, temporal considerations, and the substance(s) present. Traditional chemical assessments and derivation of toxicity values are time-intensive, typically requiring large amounts of human epidemiological and experimental animal data. When a rapid assessment of health effects is needed, an integrated computational approach of augmenting extant toxicity data with in vitro (new alternative toxicity testing methods) data can provide a quick, evidence-based solution. In so doing, multiple streams of data can be used, including literature searches, hazard, dose-response, physicochemical, environmental fate, transport property data, in vitro cell bioactivity testing, and toxicogenomics. The field of toxicology is moving, towards increased use of this approach as it transforms from observational to predictive science. The challenge is to objectively and transparently derive toxicity values using this approach to protect human health and the environment. Presented here are examples and efforts toward rapid risk assessment that demonstrate unified, parallel, and complementary work to provide timely protection in times of chemical emergency.

In silico approaches in organ toxicity hazard assessment: current status and future needs in predicting liver toxicity.

Hepatotoxicity is one of the most frequently observed adverse effects resulting from exposure to a xenobiotic. For example, in pharmaceutical research and development it is one of the major reasons for drug withdrawals, clinical failures, and discontinuation of drug candidates. The development of faster and cheaper methods to assess hepatotoxicity that are both more sustainable and more informative is critically needed. The biological mechanisms and processes underpinning hepatotoxicity are summarized and experimental approaches to support the prediction of hepatotoxicity are described, including toxicokinetic considerations. The paper describes the increasingly important role of in silico approaches and highlights challenges to the adoption of these methods including the lack of a commonly agreed upon protocol for performing such an assessment and the need for in silico solutions that take dose into consideration. A proposed framework for the integration of in silico and experimental information is provided along with a case study describing how computational methods have been used to successfully respond to a regulatory question concerning non-genotoxic impurities in chemically synthesized pharmaceuticals.

In silico approaches in organ toxicity hazard assessment: Current status and future needs for predicting heart, kidney and lung toxicities.

The kidneys, heart and lungs are vital organ systems evaluated as part of acute or chronic toxicity assessments. New methodologies are being developed to predict these adverse effects based on in vitro and in silico approaches. This paper reviews the current state of the art in predicting these organ toxicities. It outlines the biological basis, processes and endpoints for kidney toxicity, pulmonary toxicity, respiratory irritation and sensitization as well as functional and structural cardiac toxicities. The review also covers current experimental approaches, including off-target panels from secondary pharmacology batteries. Current in silico approaches for prediction of these effects and mechanisms are described as well as obstacles to the use of in silico methods. Ultimately, a commonly accepted protocol for performing such assessment would be a valuable resource to expand the use of such approaches across different regulatory and industrial applications. However, a number of factors impede their widespread deployment including a lack of a comprehensive mechanistic understanding, limited in vitro testing approaches and limited in vivo databases suitable for modeling, a limited understanding of how to incorporate absorption, distribution, metabolism, and excretion (ADME) considerations into the overall process, a lack of in silico models designed to predict a safe dose and an accepted framework for organizing the key characteristics of these organ toxicants.

Exploring Mechanistic Toxicity of Mixtures Using PBPK Modeling and Computational Systems Biology.

Mixtures risk assessment needs an efficient integration of in vivo, in vitro, and in silico data with epidemiology and human studies data. This involves several approaches, some in current use and others under development. This work extends the Agency for Toxic Substances and Disease Registry physiologically based pharmacokinetic (PBPK) toolkit, available for risk assessors, to include a mixture PBPK model of benzene, toluene, ethylbenzene, and xylenes. The recoded model was evaluated and applied to exposure scenarios to evaluate the validity of dose additivity for mixtures. In the second part of this work, we studied toluene, ethylbenzene, and xylene (TEX)-gene-disease associations using Comparative Toxicogenomics Database, pathway analysis and published microarray data from human gene expression changes in blood samples after short- and long-term exposures. Collectively, this information was used to establish hypotheses on potential linkages between TEX exposures and human health. The results show that 236 genes expressed were common between the short- and long-term exposures. These genes could be central for the interconnecting biological pathways potentially stimulated by TEX exposure, likely related to respiratory and neuro diseases. Using publicly available data we propose a conceptual framework to study pathway perturbations leading to toxicity of chemical mixtures. This proposed methodology lends mechanistic insights of the toxicity of mixtures and when experimentally validated will allow data gaps filling for mixtures' toxicity assessment. This work proposes an approach using current knowledge, available multiple stream data and applying computational methods to advance mixtures risk assessment.

Exploring current read-across applications and needs among selected U.S. Federal Agencies.

Read-across is a well-established data gap-filling technique applied for regulatory purposes. In US Environmental Protection Agency's New Chemicals Program under TSCA, read-across has been used extensively for decades, however the extent of application and acceptance of read-across among U.S. federal agencies is less clear. In an effort to build read-across capacity, raise awareness of the state of the science, and work towards a harmonization of read-across approaches across U.S. agencies, a new read-across workgroup was established under the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM). This is one of several ad hoc groups ICCVAM has convened to implement the ICCVAM Strategic Roadmap. In this article, we outline the charge and scope of the workgroup and summarize the current applications, tools used, and needs of the agencies represented on the workgroup for read-across. Of the agencies surveyed, the Environmental Protection Agency had the greatest experience in using read-across whereas other agencies indicated that they would benefit from gaining a perspective of the landscape of the tools and available guidance. Two practical case studies are also described to illustrate how the read-across approaches applied by two agencies vary on account of decision context.

Prevalence and associated demographic characteristics of exposure to multiple metals and their species in human populations: The United States NHANES, 2007-2012.

Lead (Pb), cadmium (Cd), mercury (Hg), and arsenic (As) are among the top 10 pollutants of global health concern. Studies have shown that exposures to these metals produce severe adverse effects. However, the mechanisms underlying these effects, particularly joint toxicities, are poorly understood in humans. The objective of this investigation was to identify and characterize prevalent combinations of these metals and their species in the U.S. NHANES population to provide background data for future studies of potential metal interactions. Exposure was defined as urine or blood levels ≥ medians of the NHANES 2007-2012 participants ≥6 years (n = 7408). Adjusted-odds ratios (adj-OR) and 95% confidence intervals were determined for covariates (age, gender, and race/ethnicity, cotinine and body mass index). Species-specific analysis was also conducted for As and Hg including iAs (urinary arsenous acid and/or arsenic acid), met-iAs (urinary monomethylarsonic acid and/or dimethylarsinic acid), and oHg (blood methyl-mercury and/or ethyl-mercury). For combinations of As and Hg species, age- and gender-specific prevalence was determined among NHANES 2011-2012 participants (n = 2342). Data showed that approximately 49.3% of the population contained a combination of three or more metals. The most prevalent unique specific combinations were Pb/Cd/Hg/As, Pb/Cd/Hg, and Pb/Cd. Age was consistently associated with these combinations: adj-ORs ranged from 10.9 (Pb/Cd) to 11.2 (Pb/Cd/Hg/As). Race/ethnicity was significant for Pb/Cd/Hg/As. Among women of reproductive age, frequency of oHg/iAs/met-iAS and oHg/met-iAs was 22.9 and 40.3%, respectively. These findings may help prioritize efforts to assess joint toxicities and their impact on public health.

Minimal Risk Level Derivation for Cadmium: Acute and Intermediate Duration Exposures.

The Agency for Toxic Substances and Disease Registry (ATSDR) lists cadmium as one of its priority hazardous substances. The agency conducted a comprehensive literature review of cadmium and used the information to develop a toxicological profile that identified the full range of health effects associated with exposure to cadmium. It included an assessment that identified screening levels, termed health guidance values or minimal risk levels (MRLs), below which adverse health effects are not expected. In this paper, we describe how MRLs for cadmium are derived. For the acute inhalation MRL, the traditional no observed adverse effect level or lowest observed adverse effect level (NOAEL/LOAEL) approach is used; for the oral intermediate MRL, the benchmark dose (BMD) approach is used. MRLs were developed for the most sensitive route-specific end points, other than mortality and cancer that were sufficiently supported and justified by the data. These included an acute duration (1-14 day exposure) inhalation MRL of 0.03 µg Cd/m3 for alveolar histiocytic infiltration and focal inflammation in alveolar septa and an intermediate duration (15-365 day exposure) oral MRL of 0.5 µg Cd/kg/day for decreased bone mineral density.

Physiologically based pharmacokinetic toolkit to evaluate environmental exposures: Applications of the dioxin model to study real life exposures.

Chlorinated dibenzo-p-dioxins (CDDs) are a series of mono- to octa-chlorinated homologous chemicals commonly referred to as polychlorinated dioxins. One of the most potent, well-known, and persistent member of this family is 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). As part of translational research to make computerized models accessible to health risk assessors, we present a Berkeley Madonna recoded version of the human physiologically based pharmacokinetic (PBPK) model used by the U.S. Environmental Protection Agency (EPA) in the recent dioxin assessment. This model incorporates CYP1A2 induction, which is an important metabolic vector that drives dioxin distribution in the human body, and it uses a variable elimination half-life that is body burden dependent. To evaluate the model accuracy, the recoded model predictions were compared with those of the original published model. The simulations performed with the recoded model matched well with those of the original model. The recoded model was then applied to available data sets of real life exposure studies. The recoded model can describe acute and chronic exposures and can be useful for interpreting human biomonitoring data as part of an overall dioxin and/or dioxin-like compounds risk assessment.

A Systems Biology Approach Reveals Converging Molecular Mechanisms that Link Different POPs to Common Metabolic Diseases.

BACKGROUND: A number of epidemiological studies have identified statistical associations between persistent organic pollutants (POPs) and metabolic diseases, but testable hypotheses regarding underlying molecular mechanisms to explain these linkages have not been published. OBJECTIVES: We assessed the underlying mechanisms of POPs that have been associated with metabolic diseases; three well-known POPs [2,3,7,8-tetrachlorodibenzodioxin (TCDD), 2,2´,4,4´,5,5´-hexachlorobiphenyl (PCB 153), and 4,4´-dichlorodiphenyldichloroethylene (p,p´-DDE)] were studied. We used advanced database search tools to delineate testable hypotheses and to guide laboratory-based research studies into underlying mechanisms by which this POP mixture could produce or exacerbate metabolic diseases. METHODS: For our searches, we used proprietary systems biology software (MetaCore™/MetaDrug™) to conduct advanced search queries for the underlying interactions database, followed by directional network construction to identify common mechanisms for these POPs within two or fewer interaction steps downstream of their primary targets. These common downstream pathways belong to various cytokine and chemokine families with experimentally well-documented causal associations with type 2 diabetes. CONCLUSIONS: Our systems biology approach allowed identification of converging pathways leading to activation of common downstream targets. To our knowledge, this is the first study to propose an integrated global set of step-by-step molecular mechanisms for a combination of three common POPs using a systems biology approach, which may link POP exposure to diseases. Experimental evaluation of the proposed pathways may lead to development of predictive biomarkers of the effects of POPs, which could translate into disease prevention and effective clinical treatment strategies. CITATION: Ruiz P, Perlina A, Mumtaz M, Fowler BA. 2016. A systems biology approach reveals converging molecular mechanisms that link different POPs to common metabolic diseases. Environ Health Perspect 124:1034-1041; http://dx.doi.org/10.1289/ehp.1510308.

3D QSAR studies of hydroxylated polychlorinated biphenyls as potential xenoestrogens.

Mono-hydroxylated polychlorinated biphenyls (OH-PCBs) are found in human biological samples and lack of data on their potential estrogenic activity has been a source of concern. We have extended our previous in silico 2D QSAR study through the application of advance techniques such as docking and 3D QSAR to gain insights into their estrogen receptor (ERα) binding. The results support our earlier findings that the hydroxyl group is the most important feature on the compounds; its position, orientation and surroundings in the structure are influential for the binding of OH-PCBs to ERα. This study has also revealed the following additional interactions that influence estrogenicity of these chemicals (a) the aromatic interactions of the biphenyl moieties with the receptor, (b) hydrogen bonding interactions of the p-hydroxyl group with key amino acids ARG394 and GLU353, (c) low or no electronegative substitution at para-positions of the p-hydroxyl group, (d) enhanced electrostatic interactions at the meta position on the B ring, and (e) co-planarity of the hydroxyl group on the A ring. In combination the 2D and 3D QSAR approaches have led us to the support conclusion that the hydroxyl group is the most important feature on the OH-PCB influencing the binding to estrogen receptors, and have enhanced our understanding of the mechanistic details of estrogenicity of this class of chemicals. Such in silico computational methods could serve as useful tools in risk assessment of chemicals.

Interspecies uncertainty in molecular responses and toxicity of mixtures.

Most of the experimental toxicity testing data for chemicals are generated through the use of laboratory animals, namely, rodents such as rats and mice or other species. Interspecies extrapolation is needed to nullify the differences between species so as to use such data for human health/risk assessment. Thus, understanding of interspecies differences is important in extrapolating the laboratory results to humans and conducting human risk assessments based on current credible scientific knowledge. Major causes of interspecies differences in anatomy and physiology, toxicokinetics, injury repair, molecular receptors, and signal transduction pathways responsible for variations in responses to toxic chemicals are outlined. In the risk assessment process, uncertainty associated with data gaps in our knowledge is reflected by application of uncertainty factors for interspecies differences. Refinement of the risk assessment methods is the ultimate goal as we strive to realistically evaluate the impact of toxic chemicals on human populations. Using specific examples from current risk assessment practice, this chapter illustrates the integration of interspecies differences in evaluation of individual chemicals and chemical mixtures.

Prediction of acute mammalian toxicity using QSAR methods: a case study of sulfur mustard and its breakdown products.

Predicting toxicity quantitatively, using Quantitative Structure Activity Relationships (QSAR), has matured over recent years to the point that the predictions can be used to help identify missing comparison values in a substance's database. In this manuscript we investigate using the lethal dose that kills fifty percent of a test population (LD50) for determining relative toxicity of a number of substances. In general, the smaller the LD50 value, the more toxic the chemical, and the larger the LD50 value, the lower the toxicity. When systemic toxicity and other specific toxicity data are unavailable for the chemical(s) of interest, during emergency responses, LD50 values may be employed to determine the relative toxicity of a series of chemicals. In the present study, a group of chemical warfare agents and their breakdown products have been evaluated using four available rat oral QSAR LD50 models. The QSAR analysis shows that the breakdown products of Sulfur Mustard (HD) are predicted to be less toxic than the parent compound as well as other known breakdown products that have known toxicities. The QSAR estimated break down products LD50 values ranged from 299 mg/kg to 5,764 mg/kg. This evaluation allows for the ranking and toxicity estimation of compounds for which little toxicity information existed; thus leading to better risk decision making in the field.

Application of physiologically based pharmacokinetic models in chemical risk assessment.

Post-exposure risk assessment of chemical and environmental stressors is a public health challenge. Linking exposure to health outcomes is a 4-step process: exposure assessment, hazard identification, dose response assessment, and risk characterization. This process is increasingly adopting "in silico" tools such as physiologically based pharmacokinetic (PBPK) models to fine-tune exposure assessments and determine internal doses in target organs/tissues. Many excellent PBPK models have been developed. But most, because of their scientific sophistication, have found limited field application-health assessors rarely use them. Over the years, government agencies, stakeholders/partners, and the scientific community have attempted to use these models or their underlying principles in combination with other practical procedures. During the past two decades, through cooperative agreements and contracts at several research and higher education institutions, ATSDR funded translational research has encouraged the use of various types of models. Such collaborative efforts have led to the development and use of transparent and user-friendly models. The "human PBPK model toolkit" is one such project. While not necessarily state of the art, this toolkit is sufficiently accurate for screening purposes. Highlighted in this paper are some selected examples of environmental and occupational exposure assessments of chemicals and their mixtures.

Incorporating nonchemical stressors into cumulative risk assessments.

The role of nonchemical stressors in modulating the human health risk associated with chemical exposures is an area of increasing attention. On 9 March 2011, a workshop titled "Approaches for Incorporating Nonchemical Stressors into Cumulative Risk Assessment" took place during the 50th Anniversary Annual Society of Toxicology Meeting in Washington D.C. Objectives of the workshop included describing the current state of the science from various perspectives (i.e., regulatory, exposure, modeling, and risk assessment) and presenting expert opinions on currently available methods for incorporating nonchemical stressors into cumulative risk assessments. Herein, distinct frameworks for characterizing exposure to, joint effects of, and risk associated with chemical and nonchemical stressors are discussed.

Development of a human Physiologically Based Pharmacokinetic (PBPK) Toolkit for environmental pollutants.

Physiologically Based Pharmacokinetic (PBPK) models can be used to determine the internal dose and strengthen exposure assessment. Many PBPK models are available, but they are not easily accessible for field use. The Agency for Toxic Substances and Disease Registry (ATSDR) has conducted translational research to develop a human PBPK model toolkit by recoding published PBPK models. This toolkit, when fully developed, will provide a platform that consists of a series of priority PBPK models of environmental pollutants. Presented here is work on recoded PBPK models for volatile organic compounds (VOCs) and metals. Good agreement was generally obtained between the original and the recoded models. This toolkit will be available for ATSDR scientists and public health assessors to perform simulations of exposures from contaminated environmental media at sites of concern and to help interpret biomonitoring data. It can be used as screening tools that can provide useful information for the protection of the public.