Final Report: Carolina Center for Computational Toxicology: Assays, models and tools for NextGen safety assessments

EPA Grant Number: R835166
Title: Carolina Center for Computational Toxicology: Assays, models and tools for NextGen safety assessments
Investigators: Rusyn, Ivan , Chiu, Weihsueh , Tropsha, Alexander , Wright, Fred A.
Institution: University of North Carolina at Chapel Hill , North Carolina State University , Texas A&M , University of North Carolina at Chapel Hill
EPA Project Officer: Lasat, Mitch
Project Period: July 1, 2012 through June 30, 2016 (Extended to June 30, 2017)
Project Amount: $1,200,000
RFA: Developing High-Throughput Assays for Predictive Modeling of Reproductive and Developmental Toxicity Modulated Through the Endocrine System or Pertinent Pathways in Humans and Species Relevant to Ecological Risk Assessment (2011) RFA Text |  Recipients Lists
Research Category: Computational Toxicology , Health , Ecosystems , Safer Chemicals

Objective:

The long-term objective of our ongoing research program is to advance the science and practice of toxicology by (i) filling critical gaps in our knowledge of the toxicity mechanisms, (ii) incorporating the population-based screening methods into the practice of toxicity testing, (iii) developing reliable computational models and tools that address specific existing challenges in hazard identification, and (iv) engaging with the stakeholders to increase the impact of our work.

Objective 1: Develop a quantitative high-throughput screening (qHTS) approach to probe differential chemical effects in a population-based in vitro system.

Objective 2: Provide the computational toxicology solutions for risk characterization in NexGen assessments with a focus on point-of-departure and population variability.

Objective 3: Develop cheminformatics-based, as well as enhanced chemical-biological, models of in vivo reproductive and developmental toxicity that rely on concomitant exploration of chemical descriptors and population-based screening data.

Summary/Accomplishments (Outputs/Outcomes):

This project was focused on developing solutions for a transition of chemical safety assessments into the 21st century. This effort was informed by recent developments in the fields of toxicology and risk assessment where greater availability of comprehensive non-animal tests is changing the practice of decision-making around the world. In the United States, the Toxic Substances Control Act (TSCA), as amended by the Frank R. Lautenberg Chemical Safety for the 21st Century Act, is calling for a considerable expansion in the use of novel data streams in decision-making. The US EPA is busy at work in rule-making process to define the framework on how and where these novel data may best applied in decision-making. In Europe, the so-called New Approach Methodologies (NAMs) are also a hot topic with respect to the implementation of the read-across mandate under Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) regulations. Regardless of the jurisdiction, new information streams are taken in a broad context and include in silico approaches, in chemico, and in vitro assays, as well as the inclusion of information from the exposure of chemicals in the context of hazard and risk assessment. They also include a variety of new testing tools, such as “high-throughput screening” and “high-content methods” e.g. genomics; proteomics, metabolomics; as well as some “conventional” methods that aim to improve understanding of toxic effects, either through improving toxicokinetic or toxicodynamic knowledge for substances. Thus, the overall goals and objectives of this Center were timely, topical, and have contributed a number of important datasets, conceptual frameworks, novel methods and models, and software tools. Most importantly, the Center investigators have stepped far beyond the methodological and conceptual proposals and have published a number of case studies that demonstrated how novel in silico and in vitro approaches can be used by risk assessors today, hence the contribution to practical solutions for environmental health was both broad and significant.

First, our efforts in developing and promoting in vitro methodology for evaluation of population variability in toxicity of chemicals and mixtures fill a critical gap in the practice of risk assessment. We demonstrated that population variability can be studies in “the dish” and the work with lymphoblast cell lines have paved the way for using human induced pluripotent stem cell (iPSC)-derived organotypic in vitro models to study inter-individual variability. Replacement of default uncertainty factors with scientific data will considerably advance the practice of risk assessment and reduce uncertainties in deriving toxicity values. These data are highly complementary to the larger ToxCast toxicity screening conducted by US EPA and other government agencies as this was the first effort to add a population dimension to high-throughput screening. The importance of these studies to human health is that they have provided a framework and a path to connect in vitro data collection to decision-making. The key elements, which have been largely missing from the in vitro literature, are (i) sufficient toxicodynamic data to estimate population variability and to perform association with genetic variants, (ii) in vitro dosimetry estimates, and (iii) an analytic pipeline to combine the data from disparate sources. As the cost of some types of screening assays drops, we anticipate fruitful follow up to our methods. In addition, a new generations of in vitro assays, including those intended to be organotypic, will also benefit from our novel experimental approaches. We have developed and tested a number of multiplexed assays in iPSC-derived cells that can be used to evaluate organ-specific effects of chemicals, soon in cells derived from multiple individuals. These assays were used to demonstrate that in vitro screening data can be effectively utilized to categorize both individual chemicals and complex substances/mixtures into categories thereby indicating the potential for using these data in support of read-across in regulatory submissions.

Second, our Center pioneered a concept of combining in silico-calculated chemical descriptors and in vitro bioactivity data for read-across applications in hazard and risk assessments. Traditionally, computational chemists and modelers, and biomedical researchers have worked in silos proposing their own ways to address the challenges in biomedical and environmental sciences. Through close integration of the researchers in this Center, a natural extension towards a hybrid approach, chemical-biological read-across has been proposed, tested, and validated. This concept has been taken up rapidly by the field and the use of multiple data streams in combination, rather than individually, is now well accepted and welcomed.

Third, the use of in silico predictive models based on chemical structural descriptors is also a scientific discipline that is ripe for methodological and collaborative work. In this regard our Center has contributed significantly be developing QSAR models for key endocrine disruption pathways, establishing new standards for data curation and best practices for modeling, and development of common data visualization and modeling platforms.

Finally, we have continued building open-source computational tools for processing and visualizing complex datasets that emanate from novel approach methodologies. Programs and online resources like ToxPi, CBRA, HAWC and ToxValue are now used widely by a variety of stakeholders in environmental health. These tools also represent practical solutions that facilitate inclusion of novel data streams, create a new level of transparency to complex datasets, and lower the barriers for communication of these data to decision-makers and other constituents.

Conclusions:

Overall, the data from our studies are not only important for better understanding of how chemicals may cause harm to human health, but also allow greater precision in determining how variable these responses may be, information that is crucial for risk assessment. In addition, our findings also demonstrate how novel computational tools and data can be used for decision-making. The impact of our work has been realized not only the scientific publications in the highest impact journals and numerous citations, but also by the growing use of our methods, tools and computational solutions by the wider scientific community. The IARC Monographs program, multiple reports from the National Academies, and other public forums have endorsed our outputs. The user base for many of the tools developed in this Center now includes international (IARC and HealthCanada), national (NIEHS-NTP and EPA), and state (California EPA, Vermont Department of Public Health, and TCEQ) stakeholders.


Journal Articles on this Report : 38 Displayed | Download in RIS Format

Other project views: All 53 publications 39 publications in selected types All 39 journal articles
Type Citation Project Document Sources
Journal Article Abdo N, Wetmore BA, Chappell GA, Shea D, Wright FA, Rusyn I. In vitro screening for population variability in toxicity of pesticide-containing mixtures. Environment International 2015;85:147-155. R835166 (2016)
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  • Journal Article Abdo N, Xia M, Brown CC, Kosyk O, Huang R, Sakamuru S, Zhou YH, Jack JR, Gallins P, Xia K, Li Y, Chiu WA, Motsinger-Reif AA, Austin CP, Tice RR, Rusyn I, Wright FA. Population-based in vitro hazard and concentration-response assessment of chemicals: the 1000 genomes high-throughput screening study. Environmental Health Perspectives 2015;123(5):458-466. R835166 (2014)
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  • Journal Article Alexander DL, Tropsha A, Winkler DA. Beware of R2: simple, unambiguous assessment of the prediction accuracy of QSAR and QSPR models. Journal of Chemical Information and Modeling 2015 Jul 27;55(7):1316-1322. R835166 (Final)
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  • Journal Article Alves VM, Muratov E, Fourches D, Strickland J, Kleinstreuer N, Andrade CH, Tropsha A. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds. Toxicology and Applied Pharmacology 2015;284(2):262-272. R835166 (Final)
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  • Journal Article Alves VM, Muratov E, Fourches D, Strickland J, Kleinstreuer N, Andrade CH, Tropsha A. Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization. Toxicology and Applied Pharmacology 2015; 284(2):273-280. R835166 (Final)
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  • Journal Article Alves V, Muratov E, Capuzzi S, Politi R, Low Y, Braga R, Zakharov AV, Sedykh A, Mokshyna E, Farag S, Andrade C, Kuz'min V, Fourches D, Tropsha A. Alarms about structural alerts. Green Chemistry 2016;18(16):4348-4360. R835166 (Final)
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  • Journal Article Berggren E, Amcoff P, Benigni R, Blackburn K, Carney E, Cronin M, Deluyker H, Gautier F, Judson RS, Kass GE, Keller D, Knight D, Lilienblum W, Mahony C, Rusyn I, Schultz T, Schwarz M, Schuurmann G, White A, Burton J, Lostia AM, Munn S, Worth A. Chemical safety assessment using read-across: assessing the use of novel testing methods to strengthen the evidence base for decision making. Environmental Health Perspectives 2015;123(12):1232-1240. R835166 (2016)
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  • Journal Article Chappell G, Pogribny IP, Guyton KZ, Rusyn I. Epigenetic alterations induced by genotoxic occupational and environmental human chemical carcinogens: a systematic literature review. Mutation Research. Reviews in Mutation Research 2016;768:27-45. R835166 (Final)
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  • Journal Article Chiu WA, Wright FA, Rusyn I. A tiered, Bayesian approach to estimating population variability for regulatory decision-making. ALTEX 2017;34(3):377-388. R835166 (2016)
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  • Journal Article Cote I, Andersen ME, Ankley GT, Barone S, Birnbaum LS, Boekelheide K, Bois FY, Burgoon LD, Chiu WA, Crawford-Brown D, Crofton KM, DeVito M, Devlin RB, Edwards SW, Guyton KZ, Hattis D, Judson RS, Knight D, Krewski D, Lambert J, Maull EA, Mendrick D, Paoli GM, Patel CJ, Perkins EJ, Poje G, Portier CJ, Rusyn I, Schulte PA, Simeonov A, Smith MT, Thayer KA, Thomas RS, Thomas R, Tice RR, Vandenberg JJ, Villeneuve DL, Wesselkamper S, Whelan M, Whittaker C, White R, Xia M, Yauk C, Zeise L, Zhao J, DeWoskin RS. The next generation of risk assessment multi-year study--highlights of findings, applications to risk assessment, and future directions. Environmental Health Perspectives 2016;124(11):1671-1682. R835166 (Final)
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  • Journal Article Eduati F, Mangravite LM, Wang T, Tang H, Bare JC, Huang R, Norman T, Kellen M, Menden MP, Yang J, Zhan X, Zhong R, Xiao G, Xia M, Abdo N, Kosyk O, NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration, Friend S, Dearry A, Simeonov A, Tice RR, Rusyn I, Wright FA, Stolovitzky G, Xie Y, Saez-Rodriguez J. Prediction of human population responses to toxic compounds by a collaborative competition. Nature Biotechnology 2015;33(9):933-940. R835166 (2016)
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  • Journal Article Fourches D, Tropsha A. Using graph indices for the analysis. Using graph indices for the analysis and comparison of chemial datasets. Molecular Informatics 2013;32(9-10):827-842. R835166 (Final)
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  • Journal Article Fourches D, Muratov E, Tropsha A. Curation of chemogenomics data. Nature Chemical Biology 2015;11(8):535. R835166 (Final)
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  • Journal Article Fourches D, Muratov E, Tropsha A. Trust, but verify II: a practical guide to chemogenomics data curation. Journal of Chemical Information and Modeling 2016;56(7):1243-1252. R835166 (Final)
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  • Journal Article Grimm FA, Iwata Y, Sirenko O, Chappell GA, Wright FA, Reif DM, Braisted J, Gerhold DL, Yeakley JM, Shepard P, Seligmann B, Roy T, Boogaard PJ, Ketelslegers HB, Rohde AM, Rusyn I. A chemical-biological similarity-based grouping of complex substances as a prototype approach for evaluating chemical alternatives. Green Chemistry 2016;18(16):4407-4419. R835166 (Final)
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  • Journal Article Grimm FA, Russell WK, Luo YS, Iwata Y, Chiu WA, Roy T, Boogaard PJ, Ketelslegers HB, Rusyn I. Grouping of petroleum substances as example UVCBs by ion mobility-mass spectrometry to enable chemical composition-based read-across. Environmental Science and Technology 2017;51(12):7197-7207. R835166 (Final)
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  • Journal Article Grimm FA, House JS, Wilson MR, Sirenko O, Iwata Y, Wright FA, Ball N, Rusyn I. Multi-Dimensional in Vitro Bioactivity Profiling for Grouping of Glycol Ethers. Regulatory Toxicology and Pharmacology 2019;101:91-102. R835166 (Final)
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  • Journal Article Iwata Y, Klaren WD, Lebakken CS, Grimm FA, Rusyn I. High-content assay multiplexing for vascular toxicity screening in induced pluripotent stem cell-derived endothelial cells and human umbilical vein endothelial cells. Assay and Drug Development Technologies 2017;15(6):267-279. R835166 (Final)
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  • Journal Article Kushman ME, Kraft AD, Guyton KZ, Chiu WA, Makris SL, Rusyn I. A systematic approach for identifying and presenting mechanistic evidence in human health assessments. Regulatory Toxicology and Pharmacology 2013;67(2):266-277. R835166 (Final)
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  • Journal Article Linkov I, Massey O, Keisler J, Rusyn I, Hartung T. From "weight of evidence" to quantitative data integration using multicriteria decision analysis and Bayesian methods. ALTEX 2015;32(1):3-8. R835166 (Final)
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  • Journal Article Lock EF, Abdo N, Huang R, Xia M, Kosyk O, O'Shea SH, Zhou YH, Sedykh A, Tropsha A, Austin CP, Tice RR, Wright FA, Rusyn I. Quantitative high-throughput screening for chemical toxicity in a population-based in vitro model. Toxicological Sciences 2012;126(2):578-588. R835166 (Final)
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  • Journal Article Low YS, Sedykh AY, Rusyn I, Tropsha A. Integrative approaches for predicting in vivo effects of chemicals from their structural descriptors and the results of short-term biological assays. Current Topics in Medicinal Chemistry 2014;14(11):1356-1364. R835166 (2014)
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  • Journal Article Low Y, Sedykh A, Fourches D, Golbraikh A, Whelan M, Rusyn I, Tropsha A. Integrative chemical-biological read-across approach for chemical hazard classification. Chemical Research in Toxicology 2013;26(8):1199-1208. R835166 (2013)
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  • Journal Article Mansouri K, Abdelaziz A, Rybacka A, Roncaglioni A, Tropsha A, Varnek A, Zakharov A, Worth A, Richard AM, Grulke CM, Trisciuzzi D, Fourches D, Horvath D, Benfenati E, Muratov E, Wedebye EB, Grisoni F, Mangiatordi GF, Incisivo GM, Hong H, Ng HW, Tetko IV, Balabin I, Kancherla J, Shen J, Burton J, Nicklaus M, Cassotti M, Nikolov NG, Nicolotti O, Andersson PL, Zang Q, Politi R, Beger RD, Todeschini R, Huang R, Farag S, Rosenberg SA, Slavov S, Hu X, Judson RS. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project. Environmental Health Perspectives 2016;124(7):1023-1033. R835166 (2016)
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  • Journal Article Politi R, Rusyn I, Tropsha A. Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods. Toxicology and Applied Pharmacology 2014;280(1):177-189. R835166 (2014)
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  • Journal Article Reif DM, Sypa M, Lock EF, Wright FA, Wilson A, Cathey T, Judson RR, Rusyn I. ToxPi GUI: an interactive visualization tool for transparent integration of data from diverse sources of evidence. Bioinformatics 2013;29(3):402-403. R835166 (Final)
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  • Journal Article Rusyn I, Sedykh A, Low Y, Guyton KZ, Tropsha A. Predictive modeling of chemical hazard by integrating numerical descriptors of chemical structures and short-term toxicity assay data. Toxicological Sciences 2012;127(1):1-9. R835166 (Final)
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  • Journal Article Sirenko O, Cromwell EF, Crittenden C, Wignall JA, Wright FA, Rusyn I. Assessment of beating parameters in human induced pluripotent stem cells enables quantitative in vitro screening for cardiotoxicity. Toxicology and Applied Pharmacology 2013;273(3):500-507. R835166 (2013)
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  • Journal Article Sirenko O, Crittenden C, Callamaras N, Hesley J, Chen YW, Funes C, Rusyn I, Anson B, Cromwell EF. Multiparameter in vitro assessment of compound effects on cardiomyocyte physiology using iPSC cells. Journal of Biomolecular Screening 2013;18(1):39-53. R835166 (2013)
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  • Journal Article Sirenko O, Hesley J, Rusyn I, Cromwell EF. High-content assays for hepatotoxicity using induced pluripotent stem cell-derived cells. Assay and Drug Development Technologies 2014;12(1):43-54. R835166 (2013)
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  • Journal Article Sirenko O, Hesley J, Rusyn I, Cromwell E. High-content high-throughput assays for characterizing the viability and morphology of human iPSC-derived neuronal cultures. Assay and Drug Development Technologies 2014;12(9-10):536-547. R835166 (2014)
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  • Journal Article Sirenko O, Grimm FA, Ryan KR, Iwata Y, Chiu WA, Parham F, Wignall JA, Anson B, Cromwell EF, Behl M, Rusyn I, Tice RR. In vitro cardiotoxicity assessment of environmental chemicals using an organotypic human induced pluripotent stem cell-derived model. Toxicology and Applied Pharmacology 2017;322:60-74. R835166 (Final)
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  • Journal Article Smith MT, Guyton KZ, Gibbons CF, Fritz JM, Portier CJ, Rusyn I, DeMarini DM, Caldwell JC, Kavlock RJ, Lambert PF, Hecht SS, Bucher JR, Stewart BW, Baan RA, Cogliano VJ, Straif K. Key characteristics of carcinogens as a basis for organizing data on mechanisms of carcinogenesis. Environmental Health Perspectives 2016;124(6):713-721. R835166 (Final)
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  • Journal Article Wambaugh JF, Wetmore BA, Pearce R, Strope C, Goldsmith R, Sluka JP, Sedykh A, Tropsha A, Bosgra S, Shah I, Judson R, Thomas RS, Setzer RW. Toxicokinetic triage for environmental chemicals. Toxicological Sciences 2015;147(1):55-67. R835166 (2016)
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  • Journal Article Wignall JA, Shapiro AJ, Wright FA, Woodruff TJ, Chiu WA, Guyton KZ, Rusyn I. Standardizing benchmark dose calculations to improve science-based decisions in human health assessments. Environmental Health Perspectives 2014;122(5):499-505. R835166 (2013)
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  • Journal Article Wright FA, Shabalin AA, Rusyn I. Computational tools for discovery and interpretation of expression quantitative trait loci. Pharmacogenomics 2012;13(3):343-352. R835166 (Final)
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  • Journal Article Zeise L, Bois FY, Chiu WA, Hattis D, Rusyn I, Guyton KZ. Addressing human variability in next-generation human health risk assessments of environmental chemicals. Environmental Health Perspectives 2013;121(1):23-31. R835166 (Final)
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  • Journal Article Zhang L, Sedykh A, Tripathi A, Zhu H, Afantitis A, Mouchlis VD, Melagraki G, Rusyn I, Tropsha A. Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches. Toxicology and Applied Pharmacology 2013;272(1):67-76. R835166 (2013)
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  • Supplemental Keywords:

    risk assessment, effects, health effects, human health, vulnerability, sensitive populations, dose-response, carcinogen, population, stressor, genetic pre-disposition, genetic polymorphisms, susceptibility, chemicals, decision making, genetics, toxicology, chemistry

    Relevant Websites:

    ToxPi GUI: http://comptox.unc.edu/toxpi.php

    Conditional Toxicity Value (CTV) Predictor: http://toxvalue.org/

    HAWC (Health Assessment Workspace Collaborative): https://hawcproject.org/

    CBRA Software: https://www.fourches-laboratory.com/software

    Progress and Final Reports:

    Original Abstract
  • 2013 Progress Report
  • 2014 Progress Report
  • 2015
  • 2016 Progress Report