Grantee Research Project Results
Final Report: Cardiotoxicity Adverse Outcome Pathway: Organotypic Culture Model and in vitro-to-in vivo Extrapolation for High-throughput Hazard, Dose-response and Variability Assessments
EPA Grant Number: R835802Center: Organotypic Culture Models For Predictive Toxicology Center
Center Director: Rusyn, Ivan
Title: Cardiotoxicity Adverse Outcome Pathway: Organotypic Culture Model and in vitro-to-in vivo Extrapolation for High-throughput Hazard, Dose-response and Variability Assessments
Investigators: Rusyn, Ivan
Institution: Texas A & M University , North Carolina State University
EPA Project Officer:
Project Period: June 1, 2015 through May 31, 2019 (Extended to May 31, 2022)
Project Amount: $6,000,000
RFA: Organotypic Culture Models for Predictive Toxicology Center (2013) RFA Text | Recipients Lists
Research Category: Chemical Safety for Sustainability
Summary/Accomplishments (Outputs/Outcomes):
Project 1 work was focused on using multi-plexed assays for high-content imaging and high-throughput transcriptomic analyses using iCell cardiomyocyte organotypic culture model and other cell types derived from iPS cells. We have completed testing 140 compounds selected in consultation with FDA, NTP and EPA-NCCT in a population-based in vitro iPSC-derived cell model with iCell cardiomyocytes from 43 normal donors. Several manuscripts detailing the outcomes have been published or are in submission. Using these data from this in vitro screening, and data from human clinical trials, we demonstrated that in vitro human iPSCderived cardiomyocyte model accurately predicts clinical concentration-QTc relationships. This finding confirms our central hypothesis that human induced pluripotent stem cell (iPSC)-derived cardiomyocyte cultures constitute an effective organotypic culture model for predictive toxicity screening. We also showed that iPSC-derived cardiomyocytes are a highly reproducible in vitro model where donor-specific differences in baseline function and drug-induced effects are highly conserved across experiments and batches of cells. We demonstrated the feasibility of using a panel of population-based organotypic cells from healthy donors as an animal replacement experimental model. The results of in vitro iPSC cell-derived cardiomyocyte assays were corrected for protein binding in cell culture media to enable confident comparisons of dose with in vivo human data. Additional experiments are under way to characterize binding parameters of additional compounds that are tested. Finally, we have prepared screening plates with 1000+ chemicals for additional experiments in human iPSC-derived cardiomyocytes from selected donors (5 individuals were selected). These compounds were provided by EPA NCCT and include chemicals of diverse classes with high-throughput toxicokinetic data, established toxicity values and those that are on the TSCA active inventory. The first round of experiments with this library in one iPSC cardiomyocyte cell line was completed.
Project 2 investigators continue to derive iPS from the CC lines. Despite early success in generating robust embryoid bodies from CC derived iPSC, during year 3 most lines began to lose totipotency, and did not form reproducible embryoid bodies. We have spent the last year investigating the source of the culture issues. Surprisingly, a collaborator at the University of Washington whom we had sent several iPSC was not having the same issue, and was getting robust differentiation. After discussing their protocols, which were from out lab, and testing multiple sources of reagents and tracking changes to reagent production that may have contributed, we were able to localize the issue to the source of serum that was being used. Although we had not changed sources from early successful embryoid body generation to the present, the functionality of the serum had changed and caused the iSPC cultures to differentiate into a metastable epiblast stem cell (EpiSC) state that do not readily form embryoid bodies. These cells can be readily reversed to an iPSC state under proper conditions. We have found that by changing how the serum is prepared allows the iPSC to remain totipotent and to revert EpiES back to an iSPC state. Although delayed, the iPSC are back on track to make substantial project over the remaining time of the project. To investigate the in vitro-to-in vivo predictive ability of OCM, we acquired two ECGenie instruments for recording electrocardiograms in vivo. These instruments, along with echocardiography (Echo) using a Vevo High-Frequency Ultrasound have been used to generate ECG and detailed baseline cardiac phenotypes for 31 CC lines using both male and female mice. This is an important foundation for Aim 3. These Echo measures were performed in both conscience and unconscious mice, with substantial strain-specific differences observed in many measurements that are far greater than anticipated. We have also built a web app called gEKGo that allows ECG tracings to be processed to extract relevant phenotypic data that overcomes variation in inter-strain differences in ECG that were challenging for the current commercial software based on C57BL/6 ECG patterns. To evaluate the utility of mouse genetic diversity to model human diversity, two cardiotoxicants from Project 1 (chloroquine and isoproterenol) were evaluated in vivo using 8 CC lines. Exposed mice were evaluated for ECGs using the ECGenie and cardiac function using Echo followed by Spectral Tracking analysis for detailed cardiovascular function.
Project 3 investigators have refined our published improved pipeline for dose-response analysis, applicable to both physiological parameters and to expression data (e.g. the TempOSeq technology). The pipeline includes methods for sequence read counting and numerous flags in order to highlight genes that show evidence of differential expression prior to dose-response analysis. We have had numerous discussion with stakeholders at the U.S. EPA, NIEHS, and other environmental scientists about the implications of our work and high-throughput doseresponse modeling. In addition, down-sampling analyses of the TempoSeq pipeline has been revealing in better understanding the role of replication in high-throughput dose-response modeling, when the total number of assays is held fixed. Some of the results can be counterintuitive compared to standard toxicological design practice. We have made considerable progress in scripting all analyses using R/Markdown, which enhances reproducible research and makes interaction with non-data scientists much more accessible, and easier to make modifications “on the fly.” We have created expression analysis apps using R/Shiny, enabling fast and transparent analyses of high-dimensional datasets and contrast plots easier to run and display. In ToxPi 2.0, we have made publicly available finalized modifications of the software to handle multiple dimensions of prioritization, to handle missing data, and quantify across endpoints with irregular correlation structure. As discussed in previous reports, the ability to cluster samples based on the ToxPi profile, rather than an overall sum of slice values (the ToxPi rank) offers new insights into the data and has been received well by the toxicological community. These features are also already being used in analyses of Projects 1 and 2. Finally, following on the ToxPi clustering methods, we have continued to make progress in evaluating clustering trees in a manner that enables comparison of different trees to each other, and to proposed prior categorization of chemicals. These methods work well with measures of toxicity in profiling of cardiomyocytes, and are important for other Project activity.
Project 1 has shifted focus on screening a larger array of environmental compounds (~1000 chemicals have been selected in consultation with EPA-NCCT) in iPSC-derived cardiomyocytes from 5 donors. The first experiment with this library of 1,000 chemicals in standard CDI donor cells has not been fully successful as we have experienced difficulties handling a large number of plates. Experimental plan will be adjusted to decrease the number of plates that are processed on the same day and the experiment will be repeated in July 2019. In addition, we will be collecting high throughput transcriptomics data on the concentrationresponse effects of these 1000 compounds in one standard iCell cardiomyocyte donor from CDI.
Project 2 altered the procedures to produce iPS cells. The change has had a positive impact on the reproducibility of the product and to enable ramping up of the number of iPS lines generated. Another challenge faced was the interpretation of the in vivo EKG readings among different strains. We have sought assistance from veterinary cardiologists and developed an app to interpret and analyze the waveforms of EKG traces.
For Project 3, the project has pivoted somewhat by focusing on variation in response (transcriptomic or otherwise) across cell lines, rather than identification of specific SNP variants at this stage. The new ToxPi 2.0 has overcome some problems in interpretation of hierarchical clustering by adding new display modes to more seamlessly move from considering overall ToxPi score to considering clustering relationships, which are essential for incorporating transcriptional information.
Conclusions:
Project 1 will continue experiments in 5 donors with 1000 chemicals; collect samples and conduct data analysis for TempO-seq high-throughput transcriptomics on 1000 chemicals in the standard iPSC-cardiomyocyte donor; continue collecting protein binding and other kinetic data to enable in vitro-to-in vivo comparisons; will work closely with Project 3 staff to analyze the data from high-content screening and high-throughput transcriptomics; and will work with project 2 staff to conduct screening of mouse-derived embryoid bodies.
Project 2 will use existing iPS lines with the new media preparation to confirm the reproducibility of embryoid body formation. The eight lines used to screen chloroquine and isoproterenol in vivo will be tested for in vitro effects of cardiomyocyte function in collaboration with Project 1. The graduate student working on this project recently started a summer externship with Amgen in their iPSC program and will be focusing on cardiotoxicity. This opportunity should enhance moving the project forward over the remaining time. Additional staff have also been recruited to focus on iPSC and embryoid body culture studies. This should be completed by the end of summer, after which 8 cell lines, corresponding to the CC lines used in vivo, will be used to screen putative cardiotoxicants identified in Project 1. An additional six chemicals beyond the two already screened will also be screened in vivo using the same 8 CC lines already used. Analysis of baseline cardiac function using both EKG an Echo (conscience and unconscious) will be completed by the fall of 2019. By conclusion of the project, we anticipate having generated detailed baseline cardiac phenotypes for 31 CC lines, performed genetic analysis to identify the genetic architecture underlying cardiac phenotypic variation, tested 8 iPSC and corresponding CC lines for 8 chemicals identified in Project 1 as candidate cardiotoxicants. Although not of the scale original envisioned, the results will still address the original primary goal of the project, are mice predictive of human cardiotoxicity and do in vitro OCM accurately recapitulate in vivo phenotypes.
The Project 3 will be bringing the published TempOSeq dose-response analysis pipeline to a new version, with automatic statistical testing and confidence intervals for Hill parameters, and downsampling analyses to understand the robustness to sample size. We will continue to analyze the data from high-content screening and high-throughput transcriptomics, working closely with Project 1 and 2 personnel. These involve standard statistical methods and tools applied to the cardiomyocyte data. We will integrate information from additional data streams, including high-content screening platforms for neurotoxicological activity, public toxicological databases, and epidemiological studies. The work to explore the impact of clustering techniques into ToxPi will continue, so that best principles and standards can be applied and assessed visualized. Various stakeholders will be engaged in assessing these improvements, with suggestions for further efforts. Finally, we will be implementing the developed protocol for variability analysis across cell lines. These will be used in concert with other developing chemical prioritization schemes, e.g. in ToxPi, and perhaps using these measures as “slices” in ToxPi analyses.
Journal Articles: 44 Displayed | Download in RIS Format
Other center views: | All 149 publications | 44 publications in selected types | All 44 journal articles |
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Auerbach S, Filer D, Reif D, Walker V, Holloway AC, Schlezinger J, Srinivasan S, Svoboda D, Judson R, Bucher JR, Thayer KA. Prioritizing environmental chemicals for obesity and diabetes outcomes research: a screening approach using ToxCastTM high-throughput data. Environmental Health Perspectives 2016;124(8):1141-1154. |
R835802 (2015) R835802 (2016) R835802 (2017) R835802 (2018) R835802C003 (2015) |
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Barton-Maclaren TS, Westphal M, Sarwar E, Mattison D, Chiu WA, Dix D, Kavlock R, Krewski D. Challenges and opportunities in the risk assessment of existing substances in Canada: lessons learned from the international community. International Journal of Risk Assessment and Management 2017;20;(1-3):261-283. |
R835802 (2016) R835802 (2017) R835802 (2018) |
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Blanchette AD, Grimm FA, Dalaijamts C, Hsieh NH, Ferguson K, Luo YS, Anson B, Rusyn I, Chiu WA. Thorough QT/QTc in a dish:An in vitro human model that accurately predicts clinical concentration-QTc relationships. Clinical Pharmacology and Therapeutics 2019;105:1175-1186. |
R835802 (2018) R835802C001 (2018) |
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Blanchette A, Burnett S, Rusyn I, Chiu W. A tiered approach to population-based in vitro testing for cardiotoxicity:Balancing estimates of potency and variability. Journal of Pharmacological and Toxicological Methods 01;119(107154). |
R835802 (2020) |
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Blanchette A, Burnett S, Grimm F, Rusyn I, Chiu W. A Bayesian Method for Population-wide Cardiotoxicity Hazard and Risk Characterization Using an In Vitro Human Model. Toxilogical Sciences 2020;178(2):391-403. |
R835802 (2019) |
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Bokkers BGH, Mengelers MJ, Bakker MI, Chiu WA, Slob W. APROBA-Plus: a probabilistic tool to evaluate and express uncertainty in hazard characterization and exposure assessment of substances. Food and Chemical Toxicology. 2017;110:408-417. |
R835802 (2017) R835802 (2018) |
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Burnett S, Karmakar M, Murphy W, Chiu W, Rusyn I. A new approach method for characterizing inter-species toxicodynamic variability. Journal of Toxicology and Environmental Health, Part A 2021;. |
R835802 (2020) |
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Ceballos D, Luo Y, Chen Z, Blanchette A, Zhou Y, Wright F, Baker E, Chiu W, Rusyn I. Relationships between constituents of energy drinks and beating parameters in human induced pluripotent stem cell (iPSC)-Derived cardiomyocytes. Food and Chemical Toxicology 2021;149:111979. |
R835802 (2019) |
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Chiu WA, Wright FA, Rusyn I. A tiered, Bayesian approach to estimating population variability for regulatory decision-making. ALTEX 2017;34(3):377-388. |
R835802 (2016) R835802 (2017) R835802 (2018) R835166 (2016) R835166 (Final) |
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Chiu WA, Axelrad DA, Dalaijamts C, Dockins C, Shao K, Shapiro AJ, Paoli G. Beyond the RfD:Broad application of a probabilistic approach to improve chemical dose-response assessments for noncancer effects. Environmental Health Perspective 2018;126(6):067009. |
R835802 (2018) R835802C001 (2018) |
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Chiu WA, Guyton KZ, Martin MT, Reif DM, Rusyn I. Use of high-throughput in vitro toxicity screening data in cancer hazard evaluations by IARC Monograph Working Groups. ALTEX 2018;35(1):51-64. |
R835802 (2017) R835802 (2018) R835802C003 (2018) |
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Chiu WA, Rusyn I. Advancing chemical risk assessment decision-making with population variability data: challenges and opportunities. Mammalian Genome 2018;29(1-2):182-189. |
R835802 (2017) R835802 (2018) |
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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. |
R835802 (2015) R835802 (2016) R835802 (2017) R835802 (2018) R835802C001 (2015) R835166 (Final) |
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Fantke P, Aylward L, Bare J, Chiu WA, Dodson R, Dwyer R, Ernstoff A, Howard B, Jantunen M, Jolliet O, Judson R, Kirchhübel N, Li D, Miller A, Paoli G, Price P, Rhomberg L, Shen B, Shin HM, Teeguarden J, Vallero D, Wambaugh J, Wetmore BA, Zaleski R, McKone TE. Advancements in life cycle human exposure and toxicity characterization. Environmetnal Health Perspective 2018;126:125001. |
R835802 (2018) R835802C001 (2018) |
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Garbutt TA, Konneker TI, Konganti K, Hillhouse AE, Swift-Haire F, Jones A, Phelps D, Aylor DL, Threadgill D. Permissiveness to form pluripotent stem cells may be an evolutionarily derived characteristic in Mus musculus. Scientific Reports 2018;8:14706. |
R835802 (2018) R835802C002 (2018) |
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Grimm FA, Iwata Y, Sirenko O, Bittner M, Rusyn I. High-content assay multiplexing for toxicity screening in induced pluripotent stem cell-derived cardiomyocytes and hepatocytes. Assay and Drug Development Technologies 2015;13(9):529-546. |
R835802 (2015) R835802 (2016) R835802 (2017) R835802 (2018) R835802C001 (2015) |
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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. |
R835802 (2015) R835802 (2016) R835802 (2017) R835802 (2018) R835802C001 (2015) R835166 (Final) |
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Grimm FA, Blanchette A, House JS, Ferguson K, Hsieh NH, Dalaijamts C, Wright AA, Anson B, Wright FA, Chiu WA, Rusyn I. A human population-based organotypic in vitro model for cardiotoxicity screening. ALTEX 2018;35:441-452. |
R835802 (2018) R835802C001 (2018) R835802C003 (2018) |
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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. |
R835802 (2018) R835802C001 (2018) R835166 (Final) |
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Grimm FA, Klaren WD, Li X, Lehmler HJ, Karmakar M, Robertson LW, Chiu WA, Rusyn I. Cardiovascular effects of polychlorinated biphenyls and their major metabolites.Environmental Health Perspectives 2020;128(7):077008. |
R835802 (Final) |
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Grondin CJ, Davis AP, Wiegers TC, King BL, Wiegers JA, Reif DM, Hoppin JA, Mattingly CJ. Advancing exposure science through chemical data curation and integration in the Comparative Toxicogenomics Database. Environmental Health Perspectives 2016;124(10):1592-1599. |
R835802 (2015) R835802 (2016) R835802 (2017) R835802 (2018) R835802C003 (2015) |
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Guyton KZ, Rusyn I, Chiu WA, Corpet DE, van den Berg M, Ross MK, Christiani DC, Beland FA, Smith MT. Application of the key characteristics of carcinogens in cancer hazard identification. Carcinogenesis 2018;39(4):614-622. |
R835802 (2017) R835802 (2018) |
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House JS, Grimm FA, Jima DD, Zhou Y-H, Rusyn I, Wright FA. A pipeline for high-throughput concentration response modeling of gene expression for toxicogenomics. Frontiers in Genetics 2017;8:168 (11 pp.). |
R835802 (2017) R835802 (2018) |
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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. |
R835802 (2017) R835802 (2018) R835166 (Final) |
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Judson R, Houck K, Martin M, Richard AM, Knudsen TB, Shah I, Little S, Wambaugh J, Woodrow Setzer R, Kothya P, Phuong J, Filer D, Smith D, Reif D, Rotroff D, Kleinstreuer N, Sipes N, Xia M, Huang R, Crofton K, Thomas RS. Editor's highlight: Analysis of the effects of cell stress and cytotoxicity on in vitro assay activity across a diverse chemical and assay space. Toxicological Sciences 2016;152(2):323-339. |
R835802 (2015) R835802 (2016) R835802 (2017) R835802 (2018) R835802C003 (2015) |
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Konganti K, Ehrlich A, Rusyn I, Threadgill DW. gQTL:a web application for QTL analysis using the collaborative cross mouse genetic reference population. G3:Genes, Genomes, Genetics 2018;8(8):2559-2562 |
R835802 (2017) R835802 (2018) R835802C001 (2018) R835802C002 (2018) |
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Li G, Shabalin AA, Rusyn I, Wright FA, Nobel AB. An empirical Bayes approach for multiple tissue eQTL analysis. Biostatistics 2018;19(3):391-406. |
R835802 (2017) R835802 (2018) |
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LInd L, Araujo J, Barchosky A, Belcher S, Berridge B, Chiamvimonvat N, Chiu W, Cogliano V, Elmore S, Farraj A. Key Characteristics of Cardiovascular Toxicants. Environmental Health Perspectives 2021;129(9). |
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Lu E, Grimm F, Rusyn I, De Saeger S, De Bouvre M, Chiu W. Advancing probabilistic risk assessment by integrating human biomonitoring, new approach methods, and Bayesian modeling:A case study with the mycotoxin deoxynivalenol. ENVIRONMENT INTERNATIONAL 2023;182(108326). |
R835802 (Final) R835166 (Final) |
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Marvel SW, To K, Grimm FA, Wright FA, Rusyn I, Reif DM. ToxPi Graphical User Interface 2.0: dynamic exploration, visualization, and sharing of integrated data models. BMC Bioinformatics 2018;19(1):80 (7 pp.). |
R835802 (2017) R835802 (2018) R835802C001 (2018) R835802C003 (2018) |
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Rusyn I, Greene N. The impact of novel assessment methodologies in toxicology on green chemistry and chemical alternatives. Toxicological Sciences 2018;161(2):276-284. |
R835802 (2017) R835802 (2018) |
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Shah I, Setzer RW, Jack J, Houck KA, Judson RS, Knudsen TB, Liu J, Martin MT, Reif DM, Richard AM, Thomas RS, Crofton KM, Dix DJ, Kavlock RJ. Using ToxCast™ data to reconstruct dynamic cell state trajectories and estimate toxicological points of departure. Environmental Health Perspectives 2016;124(7):910-919. |
R835802 (2015) R835802 (2016) R835802 (2017) R835802 (2018) |
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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. |
R835802 (2016) R835802 (2017) R835802 (2018) R835166 (Final) |
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Tilley SK, Reif DM, Fry RC. Incorporating ToxCast and Tox21 datasets to rank biological activity of chemicals at Superfund sites in North Carolina. Environment International 2017;101:19-26. |
R835802 (2017) R835802 (2018) |
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Wignall JA, Muratov E, Sedykh A, Guyton KZ, Tropsha A, Rusyn I, Chiu WA. Conditional Toxicity Value (CTV) predictor: an in silico approach for generating quantitative risk estimates for chemicals. Environmental Health Perspectives 2018;126(5):057008 (13 pp.). |
R835802 (2017) R835802 (2018) |
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Zhang G, Marvel S, Truong L, Tanguay RL, Reif DM. Aggregate entropy scoring for quantifying activity across endpoints with irregular correlation structure. Reproductive Toxicology 2016;62:92-99. |
R835802 (2015) R835802 (2016) R835802 (2017) R835802 (2018) R835802C003 (2015) R835168 (Final) R835796 (2017) |
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Zhang G, Roell KR, Truong L, Tanguay RL, Reif DM. A data-driven weighting scheme for multivariate phenotypic endpoints recapitulates zebrafish developmental cascades. Toxicology and Applied Pharmacology 2017;314:109-117. |
R835802 (2016) R835802 (2017) R835802 (2018) R835796 (2017) |
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Zhou Y-H, Marron JS, Wright FA. Computation of ancestry scores with mixed families and unrelated individuals. Biometrics 2018;74(1):155-164. |
R835802 (2016) R835802 (2017) R835802 (2018) |
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Kosnik MB, Strickland JD, Marvel SW, Wallis DJ, Wallace K, Richard AM, Reif DM, Shafer TJ. Concentration–response evaluation of ToxCast compounds for multivariate activity patterns of neural network function. ARCHIVES OF TOXICOLOGY 2013;94:469-484. |
R835802 (2019) |
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Li G, Jima D, Wright FA, Nobel AB. HT-eQTL:integrative expression quantitative trait loci analysis in a large number of human tissues. BMC Bioinformatics 2018;19:95. |
R835802 (2018) R835802C003 (2018) |
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Kosnik MB, Reif DM. Determination of chemical-disease risk values to prioritize connections between environmental factors, genetic variants, and human diseases. Toxicology and Applied Pharmacology2019;379:114674. |
R835802C003 (2018) |
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Kosnik MB, Planchart A, Marvel SW, Reif DM, Mattingly CJ. Integration of curated and high-throughput screening data to elucidate environmental influences on disease pathways. Computational Toxicology2019;12:100094. |
R835802C003 (2018) |
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Chen Z, Liu Y, Wright FA, Chiu WA, Rusyn I. Rapid hazard characterization of environmental chemicals using a compendium of human cell lines from different organs. ALTEX-Alternatives to Animal Experimentation 2020; 37(4):623-638 |
R835802 (2019) |
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Hsieh NH, Reisfeld, B, Bois FY, Chiu WA. Applying a global sensitivity analysis workflow to improve the computational efficiencies in physiologically-based pharmacokinetic modeling. Frontiers in Pharmacology 2018 9:588. |
R835802 (2018) R835802C001 (2018) |
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Progress and Final Reports:
Original Abstract Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R835802C001 High-throughput Hazard,Dose-responseandPopulationVariabilityAssessmentofCardiotoxicity in aHumanInducedPluripotentStem Cell(iPSC)-derivedinvitro Culture Model
R835802C002 Linking in vitro-to-in vivoToxicity Testing Using
Genetically-matchedOrganoids and Mice from a Novel Genetic Reference Population
R835802C003 A Pipeline for in vitro-to-in vivo Extrapolation, Population Modeling,
& Prioritization
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.
Project Research Results
- 2020 Progress Report
- 2019 Progress Report
- 2018 Progress Report
- 2017 Progress Report
- 2016 Progress Report
- 2015 Progress Report
- Original Abstract
44 journal articles for this center