David J Dix

United States Environmental Protection Agency, Cincinnati, Ohio, United States

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Publications (122)708.67 Total impact

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    ABSTRACT: The U.S. Tox21 program has screened a library of approximately 10,000 (10K) environmental chemicals and drugs in three independent runs for estrogen receptor alpha (ERα) agonist and antagonist activity using two types of ER reporter gene cell lines, one with an endogenous full length ERα (ER-luc; BG1 cell line) and the other with a transfected partial receptor consisting of the ligand binding domain (ER-bla; ERα β-lactamase cell line), in a quantitative high-throughput screening (qHTS) format. The ability of the two assays to correctly identify ERα agonists and antagonists was evaluated using a set of 39 reference compounds with known ERα activity. Although both assays demonstrated adequate (i.e. >80%) predictivity, the ER-luc assay was more sensitive and the ER-bla assay more specific. The qHTS assay results were compared with results from previously published ERα binding assay data and showed >80% consistency. Actives identified from both the ER-bla and ER-luc assays were analyzed for structure-activity relationships (SARs) revealing known and potentially novel ERα active structure classes. The results demonstrate the feasibility of qHTS to identify environmental chemicals with the potential to interact with the ERα signaling pathway and the two different assay formats improve the confidence in correctly identifying these chemicals.
    Scientific Reports 07/2014; 4:5664. DOI:10.1038/srep05664 · 5.58 Impact Factor
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    ABSTRACT: Thousands of environmental chemicals are subject to regulatory review for their potential to be endocrine disruptors (ED). In vitro high-throughput screening (HTS) assays have emerged as a potential tool for prioritizing chemicals for ED-related whole-animal tests. In this study, 1814 chemicals including pesticide active and inert ingredients, industrial chemicals, food additives, and pharmaceuticals were evaluated in a panel of 13 in vitro HTS assays. The panel of in vitro assays interrogated multiple endpoints related to estrogen receptor (ER) signaling, namely binding, agonist, antagonist and cell growth responses. The results from the in vitro assays were used to create an ER Interaction Score. For 36 reference chemicals, an ER Interaction Score > 0 showed 100% sensitivity and 87.5% specificity for classifying potential ER activity. The magnitude of the ER Interaction Score was significantly related to the potency classification of the reference chemicals (p<0.0001). ERα/ERβ selectivity was also evaluated, but relatively few chemicals showed significant selectivity for a specific isoform. When applied to a broader set of chemicals with in vivo uterotrophic data, the ER Interaction Scores showed 91% sensitivity and 65% specificity. Overall, this study provides a novel method for combining in vitro concentration response data from multiple assays, and when applied to a large set of ER data, accurately predicted estrogenic responses and demonstrated its utility for chemical prioritization.
    Environmental Science and Technology 06/2014; 48(15). DOI:10.1021/es502676e · 5.48 Impact Factor
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    ABSTRACT: Addressing the safety aspects of drugs and environmental chemicals has historically been undertaken through animal testing. However, the quantity of chemicals in need of assessment and the challenges of species extrapolation require the development of alternative approaches. Our approach, the US Environmental Protection Agency's ToxCast program, utilizes a large suite of in vitro and model organism assays to interrogate important chemical libraries and computationally analyze bioactivity profiles. Here we evaluated one component of the ToxCast program, the use of primary human cell systems, by screening for chemicals that disrupt physiologically important pathways. Chemical-response signatures for 87 endpoints covering molecular functions relevant to toxic and therapeutic pathways were generated in eight cell systems for 641 environmental chemicals and 135 reference pharmaceuticals and failed drugs. Computational clustering of the profiling data provided insights into the polypharmacology and potential off-target effects for many chemicals that have limited or no toxicity information. The endpoints measured can be closely linked to in vivo outcomes, such as the upregulation of tissue factor in endothelial cell systems by compounds linked to the risk of thrombosis in vivo. Our results demonstrate that assaying complex biological pathways in primary human cells can identify potential chemical targets, toxicological liabilities and mechanisms useful for elucidating adverse outcome pathways.
    Nature Biotechnology 05/2014; 32(6). DOI:10.1038/nbt.2914 · 39.08 Impact Factor
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    ABSTRACT: High-throughput screening (HTS) assays capable of profiling thousands of environmentally relevant chemicals for in vitro biological activity provide useful information on the potential for disrupting endocrine pathways. Disruption of the estrogen signaling pathway has been implicated in a variety of adverse health effects including impaired development, reproduction, and carcinogenesis. The estrogen-responsive human mammary ductal carcinoma cell line T-47D was exposed to 1815 ToxCast chemicals comprising pesticides, industrial chemicals, pharmaceuticals, personal care products, cosmetics, food ingredients, and other chemicals with known or suspected human exposure potential. Cell growth kinetics were evaluated using real-time cell electronic sensing. T-47D cells were exposed to eight concentrations (0.006-100µM) and measurements of cellular impedance were repeatedly recorded for 105 h. Chemical effects were evaluated based on potency (concentration at which response occurs) and efficacy (extent of response). A linear growth response was observed in response to prototypical estrogen receptor agonists (17β-estradiol, genistein, bisphenol-A, nonylphenol, 4-tert-octylphenol). Several compounds, including bisphenol-A and genistein, induced cell growth comparable in efficacy to 17β-estradiol, but with decreased potency. Progestins, androgens, and corticosteroids invoked a biphasic growth response indicative of changes in cell number or cell morphology. Results from this cell growth assay were compared with results from additional estrogen receptor (ER) binding and transactivation assays. Chemicals detected as active in both the cell growth and ER receptor binding assays demonstrated potencies highly correlated with two ER transactivation assays (r = 0.72, r = 0.70). While ER binding assays detected chemicals that were highly potent or efficacious in the T-47D cell growth and transactivation assays, the binding assays lacked sensitivity in detecting weakly active compounds. In conclusion, this cell-based assay rapidly detects chemical effects on T-47D growth and shows potential, in combination with other HTS assays, to detect environmentally relevant chemicals with potential estrogenic activity.
    Chemical Research in Toxicology 05/2013; 26(7). DOI:10.1021/tx400117y · 4.19 Impact Factor
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    ABSTRACT: Understanding potential health risks is a significant challenge due to large numbers of diverse chemicals with poorly characterized exposures and mechanisms of toxicities. The present study analyzes 976 chemicals (including failed pharmaceuticals, alternative plasticizers, food additives, and pesticides) in Phase I and II of the U.S. EPA's ToxCast™ project across 331 cell-free enzymatic and ligand-binding high-throughput screening (HTS) assays. Half-maximal activity concentrations (AC50) were identified for 729 chemicals in 256 assays (7,135 chemical-assay pairs). Some of the most commonly affected assays were CYPs (CYP2C9, CYP2C19), transporters (mitochondrial TSPO, norepinephrine, dopaminergic), and GPCRs (aminergic). Heavy metals, surfactants, and dithiocarbamate fungicides showed promiscuous, but distinctly different patterns of activity whereas many of the pharma compounds showed promiscuous activity across GPCRs. Literature analysis confirmed >50% of the activities for the most potent chemical-assay pairs (56), but also revealed 10 missed interactions. Twenty-two chemicals with known estrogenic activity were correctly identified for the majority (77%), missing only the weaker interactions. In many cases, novel findings for previously unreported chemical-target combinations clustered with known chemical-target interactions. Results from this large inventory of chemical-biological interactions can inform read-across methods as well as to link potential targets to molecular initiating events in adverse outcome pathways for diverse toxicities. This abstract does not necessarily reflect U.S. EPA policy.
    Chemical Research in Toxicology 04/2013; 26(6). DOI:10.1021/tx400021f · 4.19 Impact Factor
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    ABSTRACT: Vascular development is a complex process regulated by dynamic biological networks that vary in topology and state across different tissues and developmental stages. Signals regulating de novo blood vessel formation (vasculogenesis) and remodeling (angiogenesis) come from a variety of biological pathways linked to endothelial cell (EC) behavior, extracellular matrix (ECM) remodeling and the local generation of chemokines and growth factors. Simulating these interactions at a systems level requires sufficient biological detail about the relevant molecular pathways and associated cellular behaviors, and tractable computational models that offset mathematical and biological complexity. Here, we describe a novel multicellular agent-based model of vasculogenesis using the CompuCell3D (http://www.compucell3d.org/) modeling environment supplemented with semi-automatic knowledgebase creation. The model incorporates vascular endothelial growth factor signals, pro- and anti-angiogenic inflammatory chemokine signals, and the plasminogen activating system of enzymes and proteases linked to ECM interactions, to simulate nascent EC organization, growth and remodeling. The model was shown to recapitulate stereotypical capillary plexus formation and structural emergence of non-coded cellular behaviors, such as a heterologous bridging phenomenon linking endothelial tip cells together during formation of polygonal endothelial cords. Molecular targets in the computational model were mapped to signatures of vascular disruption derived from in vitro chemical profiling using the EPA's ToxCast high-throughput screening (HTS) dataset. Simulating the HTS data with the cell-agent based model of vascular development predicted adverse effects of a reference anti-angiogenic thalidomide analog, 5HPP-33, on in vitro angiogenesis with respect to both concentration-response and morphological consequences. These findings support the utility of cell agent-based models for simulating a morphogenetic series of events and for the first time demonstrate the applicability of these models for predictive toxicology.
    PLoS Computational Biology 04/2013; 9(4):e1002996. DOI:10.1371/journal.pcbi.1002996 · 4.83 Impact Factor
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    ABSTRACT: In vitro high-throughput screening (HTS) assays are seeing increasing use in toxicity testing. HTS assays can simultaneously test many chemicals but have seen limited use in the regulatory arena, in part because of the need to undergo rigorous, time-consuming formal validation. Here we discuss streamlining the validation process, specifically for prioritization applications. By prioritization, we mean a process in which less complex, less expensive, and faster assays are used to prioritize which chemicals are subjected first to more complex, expensive, and slower guideline assays. Data from the HTS prioritization assays is intended to provide a priori evidence that certain chemicals have the potential to lead to the types of adverse effects that the guideline tests are assessing. The need for such prioritization approaches is driven by the fact that there are tens of thousands of chemicals to which people are exposed, but the yearly throughput of most guideline assays is small in comparison. The streamlined validation process would continue to ensure the reliability and relevance of assays for this application. We discuss the following practical guidelines: (1) follow current validation practice to the extent possible and practical; (2) make increased use of reference compounds to better demonstrate assay reliability and relevance; (3) de-emphasize the need for cross-laboratory testing; and (4) implement a web-based, transparent, and expedited peer review process.
    01/2013; 30(1):51-6.
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    ABSTRACT: Thousands of untested chemicals in the environment require efficient characterization of carcinogenic potential in humans. A proposed solution is rapid testing of chemicals using in vitro high-throughput screening (HTS) assays for targets in pathways linked to disease processes to build models for priority-setting and further testing. We describe a model for predicting rodent carcinogenicity based on HTS data from 292 chemicals tested in 672 assays mapping to 455 genes. All data come from the EPA ToxCast project. The model was trained on a subset of 232 chemicals with in vivo rodent carcinogenicity data in the Toxicity Reference Database (ToxRefDB). Individual HTS assays strongly associated with rodent cancers in ToxRefDB were linked to genes, pathways and hallmark processes documented to be involved in tumor biology and cancer progression. Rodent liver cancer endpoints were linked to well-documented pathways such as PPAR signaling and TP53 and novel targets such as PDE5A and PLAUR. Cancer hallmark genes associated with rodent thyroid tumors were found to be linked to human thyroid tumors and autoimmune thyroid disease. A model was developed in which these genes/pathways function as hypothetical enhancers or promoters of rat thyroid tumors, acting secondary to the key initiating event of thyroid hormone disruption. A simple scoring function was generated to identify chemicals with significant in vitro evidence that was predictive of in vivo carcinogenicity in different rat tissues and organs. This scoring function was applied to an external test set of 33 compounds with carcinogenicity classifications from the EPA's Office of Pesticide Programs and successfully (p=0.024) differentiated between chemicals classified as "possible"/"probable"/"likely" carcinogens and those designated as "not likely" or with "evidence of non-carcinogenicity". This model represents a chemical carcinogenicity prioritization tool supporting targeted testing and functional validation of cancer pathways.
    Toxicological Sciences 09/2012; 131(1). DOI:10.1093/toxsci/kfs285 · 4.48 Impact Factor
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    ABSTRACT: Background: Over the past 20 years, an increased focus on detecting environmental chemicals that pose a risk of adverse effects due to endocrine disruption has driven the creation of the U.S. Environmental Protection Agency (EPA) Endocrine Disruptor Screening Program (EDSP). Thousands of chemicals are subject to the EDSP; thus, processing these chemicals using current test batteries could require millions of dollars and decades. A need for increased throughput and efficiency motivated the development of methods using in vitro high throughput screening (HTS) assays to prioritize chemicals for EDSP Tier 1 screening (T1S). Objective: In this study we used U.S. EPA ToxCast HTS assays for estrogen, androgen, steroidogenic, and thyroid-disrupting mechanisms to classify compounds and compare ToxCast results to in vitro and in vivo data from EDSP T1S assays. Method: We implemented an iterative model that optimized the ability of endocrine-related HTS assays to predict components of EDSP T1S and related results. Balanced accuracy was used as a measure of model performance. Results: ToxCast estrogen receptor and androgen receptor assays predicted the results of relevant EDSP T1S assays with balanced accuracies of 0.91 (p < 0.001) and 0.92 (p < 0.001), respectively. Uterotrophic and Hershberger assay results were predicted with balanced accuracies of 0.89 (p < 0.001) and 1 (p < 0.001), respectively. Models for steroidogenic and thyroid-related effects could not be developed with the currently published ToxCast data. Conclusions: Overall, results suggest that current ToxCast assays can accurately identify chemicals with potential to interact with the estrogenic and androgenic pathways, and could help prioritize chemicals for EDSP T1S assays.
    Environmental Health Perspectives 09/2012; 121(1). DOI:10.1289/ehp.1205065 · 7.98 Impact Factor
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    ABSTRACT: not applicable.
    Toxicological Sciences 09/2012; 130(2). DOI:10.1093/toxsci/kfs281 · 4.48 Impact Factor
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    ABSTRACT: Background: Over the past 20 years, knowledge of the genome and its function has increased dramatically, but risk assessment methodologies using such knowledge have not advanced accordingly. Objective: This commentary describes a collaborative effort among several federal and state agencies to advance the next generation of risk assessment. The objective of the NexGen program is to begin to incorporate recent progress in molecular and systems biology into risk assessment practice. The ultimate success of this program will be based on the incorporation of new practices that facilitate faster, cheaper, and/or more accurate assessments of public health risks. Methods: We are developing prototype risk assessments that compare the results of traditional, data-rich risk assessments with insights gained from new types of molecular and systems biology data. In this manner, new approaches can be validated, traditional approaches improved, and the value of different types of new scientific information better understood. Discussion and Conclusions: We anticipate that these new approaches will have a variety of applications, such as assessment of new and existing chemicals in commerce and the design of chemical products and processes that reduce or eliminate the use or generation of hazardous substances. Additionally, results of the effort are likely to spur further research and test methods development. Full implementation of new approaches is likely to take 10–20 years.
    Environmental Health Perspectives 08/2012; 120(11). DOI:10.1289/ehp.1104870 · 7.98 Impact Factor
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    ABSTRACT: The field of toxicology is on the cusp of a major transformation in how the safety and hazard of chemicals are evaluated for potential effects on human health and the environment. Brought on by the recognition of the limitations of the current paradigm in terms of cost, time, and throughput, combined with the ever increasing power of modern biological tools to probe mechanisms of chemical-biological interactions at finer and finer resolutions, 21st century toxicology is rapidly taking shape. A key element of the new approach is a focus on the molecular and cellular pathways that are the targets of chemical interactions. By understanding toxicity in this manner, we begin to learn how chemicals cause toxicity, as opposed to merely what diseases or health effects they might cause. This deeper understanding leads to increasing confidence in identifying which populations might be at risk, significant susceptibility factors, and key influences on the shape of the dose-response curve. The U. S. Environmental Protection Agency (EPA) initiated the ToxCast, or "toxicity forecaster", program 5 years ago to gain understanding of the strengths and limitations of the new approach by starting to test relatively large numbers (hundreds) of chemicals against an equally large number of biological assays. Using computational approaches, the EPA is building decision support tools based on ToxCast in vitro screening results to help prioritize chemicals for further investigation, as well as developing predictive models for a number of health outcomes. This perspective provides a summary of the initial, proof of concept, Phase I of ToxCast that has laid the groundwork for the next phases and future directions of the program.
    Chemical Research in Toxicology 04/2012; 25(7):1287-302. DOI:10.1021/tx3000939 · 4.19 Impact Factor
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    Toxicological Sciences 04/2012; 128(1):297-9. DOI:10.1093/toxsci/kfs144 · 4.48 Impact Factor

Publication Stats

7k Citations
708.67 Total Impact Points


  • 1999–2014
    • United States Environmental Protection Agency
      • • National Center for Computational Toxicology
      • • Office of Research and Development
      Cincinnati, Ohio, United States
    • Kyoto University
      • Department of Anatomy and Development Biology
      Kyoto, Kyoto-fu, Japan
  • 2008–2011
    • Computational Toxicology Services LLC
      Maryland, United States
  • 2010
    • University of North Carolina at Chapel Hill
      • Department of Environmental Sciences and Engineering
      North Carolina, United States
  • 2007–2009
    • North Carolina State University
      • Department of Environmental and Molecular Toxicology
      Raleigh, North Carolina, United States
  • 2002–2009
    • The Ohio Environmental Protection Agency
      Columbus, Ohio, United States
  • 2002–2007
    • Wayne State University
      • Department of Obstetrics and Gynecology
      Detroit, MI, United States
  • 2001
    • William Penn University
      Filadelfia, Pennsylvania, United States
  • 1997
    • National Institutes of Health
      • Branch of Reproductive and Developmental Toxicology
      Bethesda, MD, United States