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Meier MJ, Harrill J, Johnson K, Thomas RS, Tong W, Rager JE, Yauk CL. Progress in toxicogenomics to protect human health. Nat Rev Genet 2024:10.1038/s41576-024-00767-1. [PMID: 39223311 DOI: 10.1038/s41576-024-00767-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/23/2024] [Indexed: 09/04/2024]
Abstract
Toxicogenomics measures molecular features, such as transcripts, proteins, metabolites and epigenomic modifications, to understand and predict the toxicological effects of environmental and pharmaceutical exposures. Transcriptomics has become an integral tool in contemporary toxicology research owing to innovations in gene expression profiling that can provide mechanistic and quantitative information at scale. These data can be used to predict toxicological hazards through the use of transcriptomic biomarkers, network inference analyses, pattern-matching approaches and artificial intelligence. Furthermore, emerging approaches, such as high-throughput dose-response modelling, can leverage toxicogenomic data for human health protection even in the absence of predicting specific hazards. Finally, single-cell transcriptomics and multi-omics provide detailed insights into toxicological mechanisms. Here, we review the progress since the inception of toxicogenomics in applying transcriptomics towards toxicology testing and highlight advances that are transforming risk assessment.
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Affiliation(s)
- Matthew J Meier
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario, Canada
| | - Joshua Harrill
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, USA
| | - Kamin Johnson
- Predictive Safety Center, Corteva Agriscience, Indianapolis, IN, USA
| | - Russell S Thomas
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, USA
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, AR, USA
- Curriculum in Toxicology & Environmental Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Julia E Rager
- Curriculum in Toxicology & Environmental Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
- The Center for Environmental Medicine, Asthma and Lung Biology, School of Medicine, The University of North Carolina, Chapel Hill, NC, USA
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Carole L Yauk
- Department of Biology, University of Ottawa, Ottawa, Ontario, Canada.
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2
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Tsai HHD, Ford LC, Burnett SD, Dickey AN, Wright FA, Chiu WA, Rusyn I. Informing Hazard Identification and Risk Characterization of Environmental Chemicals by Combining Transcriptomic and Functional Data from Human-Induced Pluripotent Stem-Cell-Derived Cardiomyocytes. Chem Res Toxicol 2024; 37:1428-1444. [PMID: 39046974 DOI: 10.1021/acs.chemrestox.4c00193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2024]
Abstract
Environmental chemicals may contribute to the global burden of cardiovascular disease, but experimental data are lacking to determine which substances pose the greatest risk. Human-induced pluripotent stem cell (iPSC)-derived cardiomyocytes are a high-throughput cardiotoxicity model that is widely used to test drugs and chemicals; however, most studies focus on exploring electro-physiological readouts. Gene expression data may provide additional molecular insights to be used for both mechanistic interpretation and dose-response analyses. Therefore, we hypothesized that both transcriptomic and functional data in human iPSC-derived cardiomyocytes may be used as a comprehensive screening tool to identify potential cardiotoxicity hazards and risks of the chemicals. To test this hypothesis, we performed concentration-response analysis of 464 chemicals from 12 classes, including both pharmaceuticals and nonpharmaceutical substances. Functional effects (beat frequency, QT prolongation, and asystole), cytotoxicity, and whole transcriptome response were evaluated. Points of departure were derived from phenotypic and transcriptomic data, and risk characterization was performed. Overall, 244 (53%) substances were active in at least one phenotype; as expected, pharmaceuticals with known cardiac liabilities were the most active. Positive chronotropy was the functional phenotype activated by the largest number of tested chemicals. No chemical class was particularly prone to pose a potential hazard to cardiomyocytes; a varying proportion (10-44%) of substances in each class had effects on cardiomyocytes. Transcriptomic data showed that 69 (15%) substances elicited significant gene expression changes; most perturbed pathways were highly relevant to known key characteristics of human cardiotoxicants. The bioactivity-to-exposure ratios showed that phenotypic- and transcriptomic-based POD led to similar results for risk characterization. Overall, our findings demonstrate how the integrative use of in vitro transcriptomic and phenotypic data from iPSC-derived cardiomyocytes not only offers a complementary approach for hazard and risk prioritization, but also enables mechanistic interpretation of the in vitro test results to increase confidence in decision-making.
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Affiliation(s)
- Han-Hsuan D Tsai
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas 77843, United States
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas 77843, United States
| | - Lucie C Ford
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas 77843, United States
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas 77843, United States
| | - Sarah D Burnett
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas 77843, United States
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas 77843, United States
| | - Allison N Dickey
- Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27603, United States
| | - Fred A Wright
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas 77843, United States
- Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27603, United States
- Department of Statistics and Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27603, United States
| | - Weihsueh A Chiu
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas 77843, United States
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas 77843, United States
| | - Ivan Rusyn
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas 77843, United States
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas 77843, United States
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3
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Lampi MA, Therkorn JH, Kung MH, Isola AL, Barter RA. Current frameworks for environmental and health assessment of hydrocarbon streams and products are flexible and ready for alternative non crude oil-based feeds. Toxicol Res (Camb) 2024; 13:tfae114. [PMID: 39086642 PMCID: PMC11289309 DOI: 10.1093/toxres/tfae114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 06/19/2024] [Indexed: 08/02/2024] Open
Abstract
Hazard and risk assessment of complex petroleum-derived substances has been in a state of continuous improvement since the 1970s, with the development of approaches that continue to be applied and refined. Alternative feeds are defined here as those coming into a refinery or chemical plant that are not hydrocarbons from oil and gas extraction such as biologically derived oils, pyrolysis oil from biomass or other, and recycled materials. These feeds are increasingly being used for production of liquid hydrocarbon streams, and hence, there is a need to assess these alternatives, subsequent manufacturing and refining processes and end products for potential risk to humans and the environment. Here we propose a tiered, problem formulation-driven framework for assessing the safety of hydrocarbon streams and products derived from alternative feedstocks in use. The scope of this work is only focused on petrochemical safety assessment, though the principles may be applicable to other chemistries. The framework integrates combinations of analytical chemistry, in silico and in vitro tools, and targeted testing together with conservative assumptions/approaches to leverage existing health, environmental, and exposure data, where applicable. The framework enables the identification of scenarios where de novo hazard and/or exposure assessments may be needed and incorporates tiered approaches to do so. It can be applied to enable decisions efficiently and transparently and can encompass a wide range of compositional space in both feedstocks and finished products, with the objective of ensuring safety in manufacturing and use.
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Affiliation(s)
- Mark A Lampi
- ExxonMobil Technology and Engineering Company, ExxonMobil Biomedical Sciences, Inc., 1545 US 22 East, Annandale, NJ 08801, United States
| | - Jennifer H Therkorn
- ExxonMobil Technology and Engineering Company, ExxonMobil Biomedical Sciences, Inc., 1545 US 22 East, Annandale, NJ 08801, United States
| | - Ming H Kung
- ExxonMobil Technology and Engineering Company, ExxonMobil Biomedical Sciences, Inc., 1545 US 22 East, Annandale, NJ 08801, United States
| | - Allison L Isola
- ExxonMobil Product Solutions Company, Product Stewardship & Regulatory Affairs, 22777 Springwoods Village Parkway, Spring, TX 77389, United States
| | - Robert A Barter
- ExxonMobil Technology and Engineering Company, Research Organization, 1545 US 22 East, Annandale, NJ 08801, United States
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4
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Wood A, Breffa C, Chaine C, Cubberley R, Dent M, Eichhorn J, Fayyaz S, Grimm FA, Houghton J, Kiwamoto R, Kukic P, Lee M, Malcomber S, Martin S, Nicol B, Reynolds J, Riley G, Scott S, Smith C, Westmoreland C, Wieland W, Williams M, Wolton K, Zellmann T, Gutsell S. Next generation risk assessment for occupational chemical safety - A real world example with sodium-2-hydroxyethane sulfonate. Toxicology 2024; 506:153835. [PMID: 38857863 DOI: 10.1016/j.tox.2024.153835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 05/07/2024] [Accepted: 05/15/2024] [Indexed: 06/12/2024]
Abstract
Next Generation Risk Assessment (NGRA) is an exposure-led approach to safety assessment that uses New Approach Methodologies (NAMs). Application of NGRA has been largely restricted to assessments of consumer use of cosmetics and is not currently implemented in occupational safety assessments, e.g. under EU REACH. By contrast, a large proportion of regulatory worker safety assessments are underpinned by toxicological studies using experimental animals. Consequently, occupational safety assessment represents an area that would benefit from increasing application of NGRA to safety decision making. Here, a workflow for conducting NGRA under an occupational safety context was developed, which is illustrated with a case study chemical; sodium 2-hydroxyethane sulphonate (sodium isethionate or SI). Exposures were estimated using a standard occupational exposure model following a comprehensive life cycle assessment of SI and considering factory-specific data. Outputs of this model were then used to estimate internal exposures using a Physiologically Based Kinetic (PBK) model, which was constructed with SI specific Absorption, Distribution, Metabolism and Excretion (ADME) data. PBK modelling indicated a worst-case plasma maximum concentration (Cmax) of 0.8 μM across the SI life cycle. SI bioactivity was assessed in a battery of NAMs relevant to systemic, reproductive, and developmental toxicity; a cell stress panel, high throughput transcriptomics in three cell lines (HepG2, HepaRG and MCF-7 cells), pharmacological profiling and specific assays relating to developmental toxicity (Reprotracker and devTOX quickPredict). Points of Departure (PoDs) for SI ranged from 104 to 5044 µM. Cmax values obtained from PBK modelling of occupational exposures to SI were compared with PoDs from the bioactivity assays to derive Bioactivity Exposure Ratios (BERs) which demonstrated the safety for workers exposed to SI under current levels of factory specific risk management. In summary, the tiered and iterative workflow developed here represents an opportunity for integrating non animal approaches for a large subset of substances for which systemic worker safety assessment is required. Such an approach could be followed to ensure that animal testing is only conducted as a "last resort" e.g. under EU REACH.
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Affiliation(s)
- Adam Wood
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK.
| | - Catherine Breffa
- Clariant Produkte (Deutschland) GmbH, Frankfurt am Main, Germany
| | - Caroline Chaine
- Vantage Specialty Chemicals, 3 rue Jules Guesde, Ris Orangis 91130, France
| | - Richard Cubberley
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Matthew Dent
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Joachim Eichhorn
- Clariant Produkte (Deutschland) GmbH, Frankfurt am Main, Germany
| | - Susann Fayyaz
- Clariant Produkte (Deutschland) GmbH, Frankfurt am Main, Germany
| | - Fabian A Grimm
- Clariant Produkte (Deutschland) GmbH, Frankfurt am Main, Germany
| | - Jade Houghton
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Reiko Kiwamoto
- Unilever, Bronland 14, Wageningen 6708 WH, the Netherlands
| | - Predrag Kukic
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - MoungSook Lee
- Clariant Produkte (Deutschland) GmbH, Frankfurt am Main, Germany
| | - Sophie Malcomber
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Suzanne Martin
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Beate Nicol
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Joe Reynolds
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Gordon Riley
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Sharon Scott
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Colin Smith
- ERM Ireland Limited, Ardilaun Court, St Stephen's Green, Dublin, Ireland
| | - Carl Westmoreland
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | | | - Mesha Williams
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Kathryn Wolton
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | | | - Steve Gutsell
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
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5
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Bianchi E, Costa E, Harrill J, Deford P, LaRocca J, Chen W, Sutake Z, Lehman A, Pappas-Garton A, Sherer E, Moreillon C, Sriram S, Dhroso A, Johnson K. Discovery Phase Agrochemical Predictive Safety Assessment Using High Content In Vitro Data to Estimate an In Vivo Toxicity Point of Departure. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024. [PMID: 39033510 DOI: 10.1021/acs.jafc.4c03094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/23/2024]
Abstract
Utilization of in vitro (cellular) techniques, like Cell Painting and transcriptomics, could provide powerful tools for agrochemical candidate sorting and selection in the discovery process. However, using these models generates challenges translating in vitro concentrations to the corresponding in vivo exposures. Physiologically based pharmacokinetic (PBPK) modeling provides a framework for quantitative in vitro to in vivo extrapolation (IVIVE). We tested whether in vivo (rat liver) transcriptomic and apical points of departure (PODs) could be accurately predicted from in vitro (rat hepatocyte or human HepaRG) transcriptomic PODs or HepaRG Cell Painting PODs using PBPK modeling. We compared two PBPK models, the ADMET predictor and the httk R package, and found httk to predict the in vivo PODs more accurately. Our findings suggest that a rat liver apical and transcriptomic POD can be estimated utilizing a combination of in vitro transcriptome-based PODs coupled with PBPK modeling for IVIVE. Thus, high content in vitro data can be translated with modest accuracy to in vivo models of ultimate regulatory importance to help select agrochemical analogs in early stage discovery program.
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Affiliation(s)
- Enrica Bianchi
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | | | - Joshua Harrill
- Center for Computational Toxicology and Exposure, United States Environmental Protection Agency, Research Triangle Park ,North Carolina 27709, United States
| | - Paul Deford
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Jessica LaRocca
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Wei Chen
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Zachary Sutake
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Audrey Lehman
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | | | - Eric Sherer
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | | | | | - Andi Dhroso
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Kamin Johnson
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
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6
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Debad S, Allen D, Bandele O, Bishop C, Blaylock M, Brown P, Bunger MK, Co JY, Crosby L, Daniel AB, Ferguson SS, Ford K, Gamboa da Costa G, Gilchrist KH, Grogg MW, Gwinn M, Hartung T, Hogan SP, Jeong YE, Kass GE, Kenyon E, Kleinstreuer NC, Kujala V, Lundquist P, Matheson J, McCullough SD, Melton-Celsa A, Musser S, Oh I, Oyetade OB, Patil SU, Petersen EJ, Sadrieh N, Sayes CM, Scruggs BS, Tan YM, Thelin B, Nelson MT, Tarazona JV, Wambaugh JF, Yang JY, Yu C, Fitzpatrick S. Trust your gut: Establishing confidence in gastrointestinal models - An overview of the state of the science and contexts of use. ALTEX 2024; 41:402-424. [PMID: 38898799 PMCID: PMC11413798 DOI: 10.14573/altex.2403261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Indexed: 06/21/2024]
Abstract
The webinar series and workshop titled “Trust Your Gut: Establishing Confidence in Gastrointestinal Models – An Overview of the State of the Science and Contexts of Use” was co-organized by NICEATM, NIEHS, FDA, EPA, CPSC, DoD, and the Johns Hopkins Center for Alternatives to Animal Testing (CAAT) and hosted at the National Institutes of Health in Bethesda, MD, USA on October 11-12, 2023. New approach methods (NAMs) for assessing issues of gastrointestinal tract (GIT)- related toxicity offer promise in addressing some of the limitations associated with animal-based assessments. GIT NAMs vary in complexity, from two-dimensional monolayer cell line-based systems to sophisticated 3-dimensional organoid systems derived from human primary cells. Despite advances in GIT NAMs, challenges remain in fully replicating the complex interactions and processes occurring within the human GIT. Presentations and discussions addressed regulatory needs, challenges, and innovations in incorporating NAMs into risk assessment frameworks; explored the state of the science in using NAMs for evaluating systemic toxicity, understanding absorption and pharmacokinetics, evaluating GIT toxicity, and assessing potential allergenicity; and discussed strengths, limitations, and data gaps of GIT NAMs as well as steps needed to establish confidence in these models for use in the regulatory setting.
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Affiliation(s)
| | | | - Omari Bandele
- Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Colin Bishop
- Wake Forest Institute for Regenerative Medicine, Winston Salem, NC, USA
| | | | - Paul Brown
- Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | | | - Julia Y Co
- Complex in vitro Systems, Genentech Inc, South San Francisco, CA, USA
| | - Lynn Crosby
- Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | | | - Steve S Ferguson
- Mechanistic Toxicology Branch, Division of Translational Toxicology, NIEHS, National Institutes of Health, Bethesda, MD, USA
| | - Kevin Ford
- Office of Clinical Pharmacology, US Food and Drug Administration, Silver Spring, MD, USA
| | - Gonçalo Gamboa da Costa
- FDA National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Kristin H Gilchrist
- 4D Bio³ Center for Biotechnology, Uniformed Services University, Bethesda, MD, USA
| | - Matthew W Grogg
- 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson AFB, OH, USA
| | - Maureen Gwinn
- U.S. Environmental Protection Agency, Office of Research and Development, RTP, NC, USA
| | - Thomas Hartung
- Johns Hopkins University, Bloomberg School of Public Health and Whiting School of Engineering, Doerenkamp-Zbinden-Chair for Evidence-based Toxicology, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
- University of Konstanz, CAAT-Europe, Konstanz, Germany
| | - Simon P Hogan
- Mary H. Weiser Food Allergy Center, Department of Pathology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Ye Eun Jeong
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA
| | | | - Elaina Kenyon
- U.S. Environmental Protection Agency, Office of Research and Development, RTP, NC, USA
| | | | | | | | | | | | - Angela Melton-Celsa
- Department of Microbiology and Immunology, Uniformed Services University, Bethesda, MD, USA
| | - Steven Musser
- Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Ilung Oh
- Toxicology Research Division, Ministry of Food and Drug Safety, National Institute of Food and Drug Safety Evaluation, Republic of Korea
| | | | - Sarita U Patil
- Divisions of Allergy and Clinical Immunology, Departments of Medicine and Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Elijah J Petersen
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nakissa Sadrieh
- Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Christie M Sayes
- Department of Environmental Science, Baylor University, Waco, TX, USA
| | | | - Yu-Mei Tan
- U.S. Environmental Protection Agency, Office of Pesticide Programs, Research Triangle Park, NC, USA
| | - Bill Thelin
- Altis Biosystems, Inc. Research Triangle Park, NC, USA
| | - M Tyler Nelson
- 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson AFB, OH, USA
| | - José V Tarazona
- Spanish National Environmental Health Centre, Instituto de Salud Carlos III. Madrid, Spain
| | - John F Wambaugh
- U.S. Environmental Protection Agency, Office of Research and Development, RTP, NC, USA
| | - Jun-Young Yang
- Toxicology Research Division, Ministry of Food and Drug Safety, National Institute of Food and Drug Safety Evaluation, Cheongju, Republic of Korea
| | - Changwoo Yu
- Toxicology Research Division, Ministry of Food and Drug Safety, National Institute of Food and Drug Safety Evaluation, Cheongju, Republic of Korea
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7
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Costa E, Johnson KJ, Walker CA, O’Brien JM. Transcriptomic point of departure determination: a comparison of distribution-based and gene set-based approaches. Front Genet 2024; 15:1374791. [PMID: 38784034 PMCID: PMC11112360 DOI: 10.3389/fgene.2024.1374791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 04/02/2024] [Indexed: 05/25/2024] Open
Abstract
A key step in assessing the potential human and environmental health risks of industrial and agricultural chemicals is to determine the toxicity point of departure (POD), which is the highest dose level that causes no adverse effect. Transcriptomic POD (tPOD) values have been suggested to accurately estimate toxicity POD values. One step in the most common approach for tPOD determination involves mapping genes to annotated gene sets, a process that might lead to substantial information loss particularly in species with poor gene annotation. Alternatively, methods that calculate tPOD values directly from the distribution of individual gene POD values omit this mapping step. Using rat transcriptome data for 79 molecules obtained from Open TG-GATEs (Toxicogenomics Project Genomics Assisted Toxicity Evaluation System), the hypothesis was tested that methods based on the distribution of all individual gene POD values will give a similar tPOD value to that obtained via the gene set-based method. Gene set-based tPOD values using four different gene set structures were compared to tPOD values from five different individual gene distribution methods. Results revealed a high tPOD concordance for all methods tested, especially for molecules with at least 300 dose-responsive probesets: for 90% of those molecules, the tPOD values from all methods were within 4-fold of each other. In addition, random gene sets based upon the structure of biological knowledge-derived gene sets produced tPOD values with a median absolute fold change of 1.3-1.4 when compared to the original biological knowledge-derived gene set counterparts, suggesting that little biological information is used in the gene set-based tPOD generation approach. These findings indicate using individual gene distributions to calculate a tPOD is a viable and parsimonious alternative to using gene sets. Importantly, individual gene distribution-based tPOD methods do not require knowledge of biological organization and can be applied to any species including those with poorly annotated gene sets.
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Affiliation(s)
| | | | | | - Jason M. O’Brien
- Ecotoxicology and Wildlife Health Division, Environment and Climate Change Canada, Ottawa, ON, Canada
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8
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Lee H, Stead JD, Williams A, Cortés Ramírez SA, Atlas E, Mennigen JA, O’Brien JM, Yauk C. Empirical Characterization of False Discovery Rates of Differentially Expressed Genes and Transcriptomic Benchmark Concentrations in Zebrafish Embryos. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:6128-6137. [PMID: 38530926 PMCID: PMC11008580 DOI: 10.1021/acs.est.3c10543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 03/08/2024] [Accepted: 03/11/2024] [Indexed: 03/28/2024]
Abstract
High-throughput transcriptomics (HTTr) is increasingly applied to zebrafish embryos to survey the toxicological effects of environmental chemicals. Before the adoption of this approach in regulatory testing, it is essential to characterize background noise in order to guide experimental designs. We thus empirically quantified the HTTr false discovery rate (FDR) across different embryo pool sizes, sample sizes, and concentration groups for toxicology studies. We exposed zebrafish embryos to 0.1% dimethyl sulfoxide (DMSO) for 5 days. Pools of 1, 5, 10, and 20 embryos were created (n = 24 samples for each pool size). Samples were sequenced on the TempO-Seq platform and then randomly assigned to mock treatment groups before differentially expressed gene (DEG), pathway, and benchmark concentration (BMC) analyses. Given that all samples were treated with DMSO, any significant DEGs, pathways, or BMCs are false positives. As expected, we found decreasing FDRs for DEG and pathway analyses with increasing pool and sample sizes. Similarly, FDRs for BMC analyses decreased with increasing pool size and concentration groups, with more stringent BMC premodel filtering reducing BMC FDRs. Our study provides foundational data for determining appropriate experiment designs for regulatory toxicity testing with HTTr in zebrafish embryos.
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Affiliation(s)
- Hyojin Lee
- Department
of Biology, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
| | - John D.H. Stead
- Department
of Neuroscience, Carleton University, Ottawa, Ontario K1S 5B6, Canada
| | - Andrew Williams
- Environmental
Health Science and Research Bureau, Health
Canada, Ottawa, Ontario K1A 0K9, Canada
| | | | - Ella Atlas
- Environmental
Health Science and Research Bureau, Health
Canada, Ottawa, Ontario K1A 0K9, Canada
| | - Jan A. Mennigen
- Department
of Biology, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
| | - Jason M. O’Brien
- Ecotoxicology
and Wildlife Health Division, Environment
and Climate Change Canada, Ottawa, Ontario K1A 0H3, Canada
| | - Carole Yauk
- Department
of Biology, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
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9
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Browne P, Paul Friedman K, Boekelheide K, Thomas RS. Adverse effects in traditional and alternative toxicity tests. Regul Toxicol Pharmacol 2024; 148:105579. [PMID: 38309424 PMCID: PMC11062625 DOI: 10.1016/j.yrtph.2024.105579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 01/10/2024] [Accepted: 01/31/2024] [Indexed: 02/05/2024]
Abstract
Chemical safety assessment begins with defining the lowest level of chemical that alters one or more measured endpoints. This critical effect level, along with factors to account for uncertainty, is used to derive limits for human exposure. In the absence of data regarding the specific mechanisms or biological pathways affected, non-specific endpoints such as body weight and non-target organ weight changes are used to set critical effect levels. Specific apical endpoints such as impaired reproductive function or altered neurodevelopment have also been used to set chemical safety limits; however, in test guidelines designed for specific apical effect(s), concurrently measured non-specific endpoints may be equally or more sensitive than specific endpoints. This means that rather than predicting a specific toxicological response, animal data are often used to develop protective critical effect levels, without assuming the same change would be observed in humans. This manuscript is intended to encourage a rethinking of how adverse chemical effects are interpreted: non-specific endpoints from in vivo toxicological studies data are often used to derive points of departure for use with safety assessment factors to create recommended exposure levels that are broadly protective but not necessarily target-specific.
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Affiliation(s)
- Patience Browne
- Environment Health and Safety Division Environmental Directorate, Organisation for Economic and Cooperative Development (OECD), 2 rue André Pascal, Paris Cedex 16, 75775, France.
| | - Katie Paul Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Kim Boekelheide
- Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, USA
| | - Russell S Thomas
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
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10
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Hunt PR, Welch B, Camacho J, Bushana PN, Rand H, Sprando RL, Ferguson M. The worm Adult Activity Test (wAAT): A de novo mathematical model for detecting acute chemical effects in Caenorhabditis elegans. J Appl Toxicol 2023; 43:1899-1915. [PMID: 37551865 DOI: 10.1002/jat.4525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 07/05/2023] [Accepted: 07/20/2023] [Indexed: 08/09/2023]
Abstract
We have adapted a semiautomated method for tracking Caenorhabditis elegans spontaneous locomotor activity into a quantifiable assay by developing a sophisticated method for analyzing the time course of measured activity. The 16-h worm Adult Activity Test (wAAT) can be used to measure C. elegans activity levels for efficient screening for pharmacological and toxicity-induced effects. As with any apical endpoint assay, the wAAT is mode of action agnostic, allowing for detection of effects from a broad spectrum of response pathways. With caffeine as a model mild stimulant, the wAAT showed transient hyperactivity followed by reversion to baseline. Mercury chloride (HgCl2 ) produced an early dose-response hyperactivity phase followed by pronounced hypoactivity, a behavior pattern we have termed a toxicant "escape response." Methylmercury chloride (meHgCl) produced a similar pattern to HgCl2 , but at much lower concentrations, a weaker hyperactivity response, and more pronounced hypoactivity. Sodium arsenite (NaAsO2 ) and dimethylarsinic acid (DMA) induced hypoactivity at high concentrations. Acute toxicity, as measured by hypoactivity in C. elegans adults, was ranked: meHgCl > HgCl2 > NaAsO2 = DMA. Caffeine was not toxic with the wAAT at tested concentrations. Methods for conducting the wAAT are described, along with instructions for preparing C. elegans Habitation Medium, a liquid nutrient medium that allows for developmental timing equivalent to that found with C. elegans grown on agar with OP50 Escherichia coli feeder cultures. A de novo mathematical parametric model for adult C. elegans activity and the application of this model in ranking exposure toxicity are presented.
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Affiliation(s)
- Piper Reid Hunt
- Division of Toxicology, Office of Applied Research and Safety Assessment, Center for Food Safety and Applied Nutrition, United States Food and Drug Administration, Laurel, Maryland, USA
| | - Bonnie Welch
- Division of Toxicology, Office of Applied Research and Safety Assessment, Center for Food Safety and Applied Nutrition, United States Food and Drug Administration, Laurel, Maryland, USA
| | - Jessica Camacho
- Division of Toxicology, Office of Applied Research and Safety Assessment, Center for Food Safety and Applied Nutrition, United States Food and Drug Administration, Laurel, Maryland, USA
| | - Priyanka N Bushana
- Department of Translational Medicine and Physiology, Washington State University - Health Science Campus, Pullman, Washington, USA
| | - Hugh Rand
- Biostatistics and Bioinformatics Staff, Office of Analytics and Outreach, Center for Food Safety and Applied Nutrition, United States Food and Drug Administration, College Park, Maryland, USA
| | - Robert L Sprando
- Division of Toxicology, Office of Applied Research and Safety Assessment, Center for Food Safety and Applied Nutrition, United States Food and Drug Administration, Laurel, Maryland, USA
| | - Martine Ferguson
- Biostatistics and Bioinformatics Staff, Office of Analytics and Outreach, Center for Food Safety and Applied Nutrition, United States Food and Drug Administration, College Park, Maryland, USA
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11
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Russo D, Aleksunes LM, Goyak K, Qian H, Zhu H. Integrating Concentration-Dependent Toxicity Data and Toxicokinetics To Inform Hepatotoxicity Response Pathways. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:12291-12301. [PMID: 37566783 PMCID: PMC10448720 DOI: 10.1021/acs.est.3c02792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 07/30/2023] [Accepted: 07/31/2023] [Indexed: 08/13/2023]
Abstract
Failure of animal models to predict hepatotoxicity in humans has created a push to develop biological pathway-based alternatives, such as those that use in vitro assays. Public screening programs (e.g., ToxCast/Tox21 programs) have tested thousands of chemicals using in vitro high-throughput screening (HTS) assays. Developing pathway-based models for simple biological pathways, such as endocrine disruption, has proven successful, but development remains a challenge for complex toxicities like hepatotoxicity, due to the many biological events involved. To this goal, we aimed to develop a computational strategy for developing pathway-based models for complex toxicities. Using a database of 2171 chemicals with human hepatotoxicity classifications, we identified 157 out of 1600+ ToxCast/Tox21 HTS assays to be associated with human hepatotoxicity. Then, a computational framework was used to group these assays by biological target or mechanisms into 52 key event (KE) models of hepatotoxicity. KE model output is a KE score summarizing chemical potency against a hepatotoxicity-relevant biological target or mechanism. Grouping hepatotoxic chemicals based on the chemical structure revealed chemical classes with high KE scores plausibly informing their hepatotoxicity mechanisms. Using KE scores and supervised learning to predict in vivo hepatotoxicity, including toxicokinetic information, improved the predictive performance. This new approach can be a universal computational toxicology strategy for various chemical toxicity evaluations.
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Affiliation(s)
- Daniel
P. Russo
- Department
of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States
| | - Lauren M. Aleksunes
- Department
of Pharmacology and Toxicology, Ernest Mario School of Pharmacy, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Katy Goyak
- ExxonMobil
Biomedical Sciences, Inc., Annandale, New Jersey 08801, United States
| | - Hua Qian
- ExxonMobil
Biomedical Sciences, Inc., Annandale, New Jersey 08801, United States
| | - Hao Zhu
- Department
of Chemistry and Biochemistry, Rowan University, Glassboro, New Jersey 08028, United States
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12
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Schmeisser S, Miccoli A, von Bergen M, Berggren E, Braeuning A, Busch W, Desaintes C, Gourmelon A, Grafström R, Harrill J, Hartung T, Herzler M, Kass GEN, Kleinstreuer N, Leist M, Luijten M, Marx-Stoelting P, Poetz O, van Ravenzwaay B, Roggeband R, Rogiers V, Roth A, Sanders P, Thomas RS, Marie Vinggaard A, Vinken M, van de Water B, Luch A, Tralau T. New approach methodologies in human regulatory toxicology - Not if, but how and when! ENVIRONMENT INTERNATIONAL 2023; 178:108082. [PMID: 37422975 PMCID: PMC10858683 DOI: 10.1016/j.envint.2023.108082] [Citation(s) in RCA: 58] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 06/30/2023] [Accepted: 07/01/2023] [Indexed: 07/11/2023]
Abstract
The predominantly animal-centric approach of chemical safety assessment has increasingly come under pressure. Society is questioning overall performance, sustainability, continued relevance for human health risk assessment and ethics of this system, demanding a change of paradigm. At the same time, the scientific toolbox used for risk assessment is continuously enriched by the development of "New Approach Methodologies" (NAMs). While this term does not define the age or the state of readiness of the innovation, it covers a wide range of methods, including quantitative structure-activity relationship (QSAR) predictions, high-throughput screening (HTS) bioassays, omics applications, cell cultures, organoids, microphysiological systems (MPS), machine learning models and artificial intelligence (AI). In addition to promising faster and more efficient toxicity testing, NAMs have the potential to fundamentally transform today's regulatory work by allowing more human-relevant decision-making in terms of both hazard and exposure assessment. Yet, several obstacles hamper a broader application of NAMs in current regulatory risk assessment. Constraints in addressing repeated-dose toxicity, with particular reference to the chronic toxicity, and hesitance from relevant stakeholders, are major challenges for the implementation of NAMs in a broader context. Moreover, issues regarding predictivity, reproducibility and quantification need to be addressed and regulatory and legislative frameworks need to be adapted to NAMs. The conceptual perspective presented here has its focus on hazard assessment and is grounded on the main findings and conclusions from a symposium and workshop held in Berlin in November 2021. It intends to provide further insights into how NAMs can be gradually integrated into chemical risk assessment aimed at protection of human health, until eventually the current paradigm is replaced by an animal-free "Next Generation Risk Assessment" (NGRA).
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Affiliation(s)
| | - Andrea Miccoli
- German Federal Institute for Risk Assessment (BfR), Berlin, Germany; National Research Council, Ancona, Italy
| | - Martin von Bergen
- Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany; University of Leipzig, Faculty of Life Sciences, Institute of Biochemistry, Leipzig, Germany
| | | | - Albert Braeuning
- German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Wibke Busch
- Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany
| | - Christian Desaintes
- European Commission (EC), Directorate General for Research and Innovation (RTD), Brussels, Belgium
| | - Anne Gourmelon
- Organisation for Economic Cooperation and Development (OECD), Environment Directorate, Paris, France
| | | | - Joshua Harrill
- Center for Computational Toxicology and Exposure (CCTE), United States Environmental Protection Agency (US EPA), Durham, USA
| | - Thomas Hartung
- Center for Alternatives to Animal Testing (CAAT), Johns Hopkins Bloomberg School of Public Health Baltimore MD USA, CAAT-Europe, University of Konstanz, Konstanz, Germany
| | - Matthias Herzler
- German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | | | - Nicole Kleinstreuer
- NTP Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM), National Institute of Environmental Health Sciences (NIEHS), Durham, USA
| | - Marcel Leist
- CAAT‑Europe and Department of Biology, University of Konstanz, Konstanz, Germany
| | - Mirjam Luijten
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | | | - Oliver Poetz
- NMI Natural and Medical Science Institute at the University of Tuebingen, Reutlingen, Germany; SIGNATOPE GmbH, Reutlingen, Germany
| | | | - Rob Roggeband
- European Partnership for Alternative Approaches to Animal Testing (EPAA), Procter and Gamble Services Company NV/SA, Strombeek-Bever, Belgium
| | - Vera Rogiers
- Scientific Committee on Consumer Safety (SCCS), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Adrian Roth
- F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Pascal Sanders
- Fougeres Laboratory, French Agency for Food, Environmental and Occupational Health and Safety (ANSES), Fougères, France France
| | - Russell S Thomas
- Center for Computational Toxicology and Exposure (CCTE), United States Environmental Protection Agency (US EPA), Durham, USA
| | | | | | | | - Andreas Luch
- German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Tewes Tralau
- German Federal Institute for Risk Assessment (BfR), Berlin, Germany
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13
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Reardon AJF, Farmahin R, Williams A, Meier MJ, Addicks GC, Yauk CL, Matteo G, Atlas E, Harrill J, Everett LJ, Shah I, Judson R, Ramaiahgari S, Ferguson SS, Barton-Maclaren TS. From vision toward best practices: Evaluating in vitro transcriptomic points of departure for application in risk assessment using a uniform workflow. FRONTIERS IN TOXICOLOGY 2023; 5:1194895. [PMID: 37288009 PMCID: PMC10242042 DOI: 10.3389/ftox.2023.1194895] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 05/03/2023] [Indexed: 06/09/2023] Open
Abstract
The growing number of chemicals in the current consumer and industrial markets presents a major challenge for regulatory programs faced with the need to assess the potential risks they pose to human and ecological health. The increasing demand for hazard and risk assessment of chemicals currently exceeds the capacity to produce the toxicity data necessary for regulatory decision making, and the applied data is commonly generated using traditional approaches with animal models that have limited context in terms of human relevance. This scenario provides the opportunity to implement novel, more efficient strategies for risk assessment purposes. This study aims to increase confidence in the implementation of new approach methods in a risk assessment context by using a parallel analysis to identify data gaps in current experimental designs, reveal the limitations of common approaches deriving transcriptomic points of departure, and demonstrate the strengths in using high-throughput transcriptomics (HTTr) to derive practical endpoints. A uniform workflow was applied across six curated gene expression datasets from concentration-response studies containing 117 diverse chemicals, three cell types, and a range of exposure durations, to determine tPODs based on gene expression profiles. After benchmark concentration modeling, a range of approaches was used to determine consistent and reliable tPODs. High-throughput toxicokinetics were employed to translate in vitro tPODs (µM) to human-relevant administered equivalent doses (AEDs, mg/kg-bw/day). The tPODs from most chemicals had AEDs that were lower (i.e., more conservative) than apical PODs in the US EPA CompTox chemical dashboard, suggesting in vitro tPODs would be protective of potential effects on human health. An assessment of multiple data points for single chemicals revealed that longer exposure duration and varied cell culture systems (e.g., 3D vs. 2D) lead to a decreased tPOD value that indicated increased chemical potency. Seven chemicals were flagged as outliers when comparing the ratio of tPOD to traditional POD, thus indicating they require further assessment to better understand their hazard potential. Our findings build confidence in the use of tPODs but also reveal data gaps that must be addressed prior to their adoption to support risk assessment applications.
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Affiliation(s)
- Anthony J. F. Reardon
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Reza Farmahin
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Matthew J. Meier
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Gregory C. Addicks
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Carole L. Yauk
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
| | - Geronimo Matteo
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
| | - Ella Atlas
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
- Department of Biochemistry, University of Ottawa, Ottawa, ON, Canada
| | - Joshua Harrill
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Logan J. Everett
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Imran Shah
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Richard Judson
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Sreenivasa Ramaiahgari
- Division of Translational Toxicology, Mechanistic Toxicology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Stephen S. Ferguson
- Division of Translational Toxicology, Mechanistic Toxicology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Tara S. Barton-Maclaren
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
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14
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Rivetti C, Houghton J, Basili D, Hodges G, Campos B. Genes-to-Pathways Species Conservation Analysis: Enabling the Exploration of Conservation of Biological Pathways and Processes Across Species. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2023; 42:1152-1166. [PMID: 36861224 DOI: 10.1002/etc.5600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 06/18/2023]
Abstract
The last two decades have witnessed a strong momentum toward integration of cell-based and computational approaches in safety assessments. This is fueling a global regulatory paradigm shift toward reduction and replacement of the use of animals in toxicity tests while promoting the use of new approach methodologies. The understanding of conservation of molecular targets and pathways provides an opportunity to extrapolate effects across species and ultimately to determine the taxonomic applicability domain of assays and biological effects. Despite the wealth of genome-linked data available, there is a compelling need for improved accessibility, while ensuring that it reflects the underpinning biology. We present the novel pipeline Genes-to-Pathways Species Conservation Analysis (G2P-SCAN) to further support understanding on cross-species extrapolation of biological processes. This R package extracts, synthetizes, and structures the data available from different databases, that is, gene orthologs, protein families, entities, and reactions, linked to human genes and respective pathways across six relevant model species. The use of G2P-SCAN enables the overall analysis of orthology and functional families to substantiate the identification of conservation and susceptibility at the pathway level. In the present study we discuss five case studies, demonstrating the validity of the developed pipeline and its potential use as species extrapolation support. We foresee this pipeline will provide valuable biological insights and create space for the use of mechanistically based data to inform potential species susceptibility for research and safety decision purposes. Environ Toxicol Chem 2023;42:1152-1166. © 2023 UNILEVER GLOBAL IP LTD. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
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Affiliation(s)
- Claudia Rivetti
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Bedfordshire, United Kingdom
| | - Jade Houghton
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Bedfordshire, United Kingdom
| | - Danilo Basili
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Bedfordshire, United Kingdom
| | - Geoff Hodges
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Bedfordshire, United Kingdom
| | - Bruno Campos
- Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Bedfordshire, United Kingdom
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15
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Minucci JM, Purucker ST, Isaacs KK, Wambaugh JF, Phillips KA. A Data-Driven Approach to Estimating Occupational Inhalation Exposure Using Workplace Compliance Data. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:5947-5956. [PMID: 36995295 PMCID: PMC10100548 DOI: 10.1021/acs.est.2c08234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 03/07/2023] [Accepted: 03/08/2023] [Indexed: 06/19/2023]
Abstract
A growing list of chemicals are approved for production and use in the United States and elsewhere, and new approaches are needed to rapidly assess the potential exposure and health hazard posed by these substances. Here, we present a high-throughput, data-driven approach that will aid in estimating occupational exposure using a database of over 1.5 million observations of chemical concentrations in U.S. workplace air samples. We fit a Bayesian hierarchical model that uses industry type and the physicochemical properties of a substance to predict the distribution of workplace air concentrations. This model substantially outperforms a null model when predicting whether a substance will be detected in an air sample, and if so at what concentration, with 75.9% classification accuracy and a root-mean-square error (RMSE) of 1.00 log10 mg m-3 when applied to a held-out test set of substances. This modeling framework can be used to predict air concentration distributions for new substances, which we demonstrate by making predictions for 5587 new substance-by-workplace-type pairs reported in the US EPA's Toxic Substances Control Act (TSCA) Chemical Data Reporting (CDR) industrial use database. It also allows for improved consideration of occupational exposure within the context of high-throughput, risk-based chemical prioritization efforts.
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Affiliation(s)
- Jeffrey M. Minucci
- Center
for Public Health and Environmental Assessment, Office of Research
and Development, US Environmental Protection
Agency, 109 TW Alexander Drive, Durham, North Carolina 27709, United States
| | - S. Thomas Purucker
- Center
for Computational Toxicology and Exposure, Office of Research and
Development, US Environmental Protection
Agency, 109 TW Alexander
Drive, Durham, North Carolina 27709, United States
| | - Kristin K. Isaacs
- Center
for Computational Toxicology and Exposure, Office of Research and
Development, US Environmental Protection
Agency, 109 TW Alexander
Drive, Durham, North Carolina 27709, United States
| | - John F. Wambaugh
- Center
for Computational Toxicology and Exposure, Office of Research and
Development, US Environmental Protection
Agency, 109 TW Alexander
Drive, Durham, North Carolina 27709, United States
| | - Katherine A. Phillips
- Center
for Computational Toxicology and Exposure, Office of Research and
Development, US Environmental Protection
Agency, 109 TW Alexander
Drive, Durham, North Carolina 27709, United States
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16
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Chauhan V, Yu J, Vuong N, Haber LT, Williams A, Auerbach SS, Beaton D, Wang Y, Stainforth R, Wilkins RC, Azzam EI, Richardson RB, Khan MGM, Jadhav A, Burtt JJ, Leblanc J, Randhawa K, Tollefsen KE, Yauk CL. Considerations for application of benchmark dose modeling in radiation research: workshop highlights. Int J Radiat Biol 2023; 99:1320-1331. [PMID: 36881459 DOI: 10.1080/09553002.2023.2181998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 01/18/2023] [Accepted: 02/06/2023] [Indexed: 02/24/2023]
Abstract
BACKGROUND Exposure to different forms of ionizing radiation occurs in diverse occupational, medical, and environmental settings. Improving the accuracy of the estimated health risks associated with exposure is therefore, essential for protecting the public, particularly as it relates to chronic low dose exposures. A key aspect to understanding health risks is precise and accurate modeling of the dose-response relationship. Toward this vision, benchmark dose (BMD) modeling may be a suitable approach for consideration in the radiation field. BMD modeling is already extensively used for chemical hazard assessments and is considered statistically preferable to identifying low and no observed adverse effects levels. BMD modeling involves fitting mathematical models to dose-response data for a relevant biological endpoint and identifying a point of departure (the BMD, or its lower bound). Recent examples in chemical toxicology show that when applied to molecular endpoints (e.g. genotoxic and transcriptional endpoints), BMDs correlate to points of departure for more apical endpoints such as phenotypic changes (e.g. adverse effects) of interest to regulatory decisions. This use of BMD modeling may be valuable to explore in the radiation field, specifically in combination with adverse outcome pathways, and may facilitate better interpretation of relevant in vivo and in vitro dose-response data. To advance this application, a workshop was organized on June 3rd, 2022, in Ottawa, Ontario that brought together BMD experts in chemical toxicology and the radiation scientific community of researchers, regulators, and policy-makers. The workshop's objective was to introduce radiation scientists to BMD modeling and its practical application using case examples from the chemical toxicity field and demonstrate the BMDExpress software using a radiation dataset. Discussions focused on the BMD approach, the importance of experimental design, regulatory applications, its use in supporting the development of adverse outcome pathways, and specific radiation-relevant examples. CONCLUSIONS Although further deliberations are needed to advance the use of BMD modeling in the radiation field, these initial discussions and partnerships highlight some key steps to guide future undertakings related to new experimental work.
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Affiliation(s)
- Vinita Chauhan
- Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Jihang Yu
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
| | - Ngoc Vuong
- Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Lynne T Haber
- Department of Environmental and Public Health Sciences, Risk Science Center, University of Cincinnati, Cincinnati, OH, USA
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Health Science and Research Bureau, Health Canada, Ottawa, Canada
| | - Scott S Auerbach
- National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Danielle Beaton
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
| | - Yi Wang
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Canada
| | | | - Ruth C Wilkins
- Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Edouard I Azzam
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
- Department of Radiology, New Jersey Medical School, Rutgers University, Newark, NJ, USA
| | - Richard B Richardson
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
- Medical Physics Unit, McGill University, Montreal, QC, Canada
| | | | - Ashok Jadhav
- Radiobiology and Health Branch, Canadian Nuclear Laboratories, Chalk River, Canada
| | - Julie J Burtt
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Julie Leblanc
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Kristi Randhawa
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Knut Erik Tollefsen
- Norwegian Institute for Water Research (NIVA), Oslo, Norway
- Norwegian University of Life Sciences (NMBU), Ås, Norway
- Centre for Environmental Radioactivity, Norwegian University of Life Sciences (NMBU), Ås, Norway
| | - Carole L Yauk
- Department of Biology, University of Ottawa, Ottawa, Canada
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17
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Hagiwara S, Paoli GM, Price PS, Gwinn MR, Guiseppi-Elie A, Farrell PJ, Hubbell BJ, Krewski D, Thomas RS. A value of information framework for assessing the trade-offs associated with uncertainty, duration, and cost of chemical toxicity testing. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2023; 43:498-515. [PMID: 35460101 PMCID: PMC10515440 DOI: 10.1111/risa.13931] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
A number of investigators have explored the use of value of information (VOI) analysis to evaluate alternative information collection procedures in diverse decision-making contexts. This paper presents an analytic framework for determining the value of toxicity information used in risk-based decision making. The framework is specifically designed to explore the trade-offs between cost, timeliness, and uncertainty reduction associated with different toxicity-testing methodologies. The use of the proposed framework is demonstrated by two illustrative applications which, although based on simplified assumptions, show the insights that can be obtained through the use of VOI analysis. Specifically, these results suggest that timeliness of information collection has a significant impact on estimates of the VOI of chemical toxicity tests, even in the presence of smaller reductions in uncertainty. The framework introduces the concept of the expected value of delayed sample information, as an extension to the usual expected value of sample information, to accommodate the reductions in value resulting from delayed decision making. Our analysis also suggests that lower cost and higher throughput testing also may be beneficial in terms of public health benefits by increasing the number of substances that can be evaluated within a given budget. When the relative value is expressed in terms of return-on-investment per testing strategy, the differences can be substantial.
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Affiliation(s)
- Shintaro Hagiwara
- Risk Sciences International, Ottawa, Canada
- School of Mathematics and Statistics, Carleton University, Ottawa, Canada
| | | | - Paul S. Price
- Center for Compuational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Maureen R. Gwinn
- Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Annette Guiseppi-Elie
- Center for Compuational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Patrick J. Farrell
- School of Mathematics and Statistics, Carleton University, Ottawa, Canada
| | - Bryan J. Hubbell
- Air, Climate, and Energy Research Program, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Daniel Krewski
- Risk Sciences International, Ottawa, Canada
- McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Canada
| | - Russell S. Thomas
- Center for Compuational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
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18
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Brescia S, Alexander-White C, Li H, Cayley A. Risk assessment in the 21st century: where are we heading? Toxicol Res (Camb) 2023; 12:1-11. [PMID: 36866215 PMCID: PMC9972812 DOI: 10.1093/toxres/tfac087] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/19/2022] [Accepted: 12/22/2022] [Indexed: 01/12/2023] Open
Abstract
Reliance on animal tests for chemical safety assessment is increasingly being challenged, not only because of ethical reasons, but also because they procrastinate regulatory decisions and because of concerns over the transferability of results to humans. New approach methodologies (NAMs) need to be fit for purpose and new thinking is required to reconsider chemical legislation, validation of NAMs and opportunities to move away from animal tests. This article summarizes the presentations from a symposium at the 2022 Annual Congress of the British Toxicology Society on the topic of the future of chemical risk assessment in the 21st century. The symposium included three case-studies where NAMs have been used in safety assessments. The first case illustrated how read-across augmented with some in vitro tests could be used reliably to perform the risk assessment of analogues lacking data. The second case showed how specific bioactivity assays could identify an NAM point of departure (PoD) and how this could be translated through physiologically based kinetic modelling in an in vivo PoD for the risk assessment. The third case showed how adverse-outcome pathway (AOP) information, including molecular-initiating event and key events with their underlying data, established for certain chemicals could be used to produce an in silico model that is able to associate chemical features of an unstudied substance with specific AOPs or AOP networks. The manuscript presents the discussions that took place regarding the limitations and benefits of these new approaches, and what are the barriers and the opportunities for their increased use in regulatory decision making.
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Affiliation(s)
- Susy Brescia
- Health & Safety Executive, Chemicals Regulation Division, Redgrave Court, Merton Road, Bootle, Merseyside L20 7HS, UK
| | | | - Hequn Li
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Alex Cayley
- Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds LS11, 5PS, UK
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Lambert JC. Adverse Outcome Pathway 'Footprinting': A Novel Approach to the Integration of 21st Century Toxicology Information into Chemical Mixtures Risk Assessment. TOXICS 2022; 11:37. [PMID: 36668763 PMCID: PMC9860797 DOI: 10.3390/toxics11010037] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 12/23/2022] [Accepted: 12/28/2022] [Indexed: 06/17/2023]
Abstract
For over a decade, New Approach Methodologies (NAMs) such as structure-activity/read-across, -omics technologies, and Adverse Outcome Pathway (AOP), have been considered within regulatory communities as alternative sources of chemical and biological information potentially relevant to human health risk assessment. Integration of NAMs into applications such as chemical mixtures risk assessment has been limited due to the lack of validation of qualitative and quantitative application to adverse health outcomes in vivo, and acceptance by risk assessors. However, leveraging existent hazard and dose-response information, including NAM-based data, for mixture component chemicals across one or more levels of biological organization using novel approaches such as AOP 'footprinting' proposed herein, may significantly advance mixtures risk assessment. AOP footprinting entails the systematic stepwise profiling and comparison of all known or suspected AOPs involved in a toxicological effect at the level of key event (KE). The goal is to identify key event(s) most proximal to an adverse outcome within each AOP suspected of contributing to a given health outcome at which similarity between mixture chemicals can be confidently determined. These key events are identified as the 'footprint' for a given AOP. This work presents the general concept, and a hypothetical example application, of AOP footprinting as a key methodology for the integration of NAM data into mixtures risk assessment.
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Affiliation(s)
- Jason C Lambert
- United States Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Cincinnati, OH 45268, USA
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20
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Becker RA, Bianchi E, LaRocca J, Marty MS, Mehta V. Identifying the landscape of developmental toxicity new approach methodologies. Birth Defects Res 2022; 114:1123-1137. [PMID: 36205106 DOI: 10.1002/bdr2.2075] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 07/08/2022] [Accepted: 07/21/2022] [Indexed: 01/07/2023]
Abstract
BACKGROUND The dynamics and complexities of in utero fetal development create significant challenges in transitioning from lab animal-centric developmental toxicity testing methods to assessment strategies based on new approach methodologies (NAMs). Nevertheless, considerable progress is being made, stimulated by increased research investments and scientific advances, such as induced pluripotent stem cell-derived models. To help identify developmental toxicity NAMs for toxicity screening and potential funding through the American Chemistry Council's Long-Range Research Initiative, a systematic literature review was conducted to better understand the current landscape of developmental toxicity NAMs. METHODS Scoping review tools were used to systematically survey the literature (2010-2021; ~18,000 references identified), results and metadata were then extracted, and a user-friendly interactive dashboard was created. RESULTS The data visualization dashboard, developed using Tableau® software, is provided as a free, open-access web tool. This dashboard enables straightforward interactive queries and visualizations to identify trends and to distinguish and understand areas or NAMs where research has been most, or least focused. CONCLUSIONS Herein, we describe the approach and methods used, summarize the benefits and challenges of applying the systematic-review techniques, and highlight the types of questions and answers for which the dashboard can be used to explore the many different facets of developmental toxicity NAMs.
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Affiliation(s)
- Richard A Becker
- American Chemistry Council, Washington, District of Columbia, USA
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21
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Nicolas CI, Linakis MW, Minto MS, Mansouri K, Clewell RA, Yoon M, Wambaugh JF, Patlewicz G, McMullen PD, Andersen ME, Clewell III HJ. Estimating provisional margins of exposure for data-poor chemicals using high-throughput computational methods. Front Pharmacol 2022; 13:980747. [PMID: 36278238 PMCID: PMC9586287 DOI: 10.3389/fphar.2022.980747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
Current computational technologies hold promise for prioritizing the testing of the thousands of chemicals in commerce. Here, a case study is presented demonstrating comparative risk-prioritization approaches based on the ratio of surrogate hazard and exposure data, called margins of exposure (MoEs). Exposures were estimated using a U.S. EPA’s ExpoCast predictive model (SEEM3) results and estimates of bioactivity were predicted using: 1) Oral equivalent doses (OEDs) derived from U.S. EPA’s ToxCast high-throughput screening program, together with in vitro to in vivo extrapolation and 2) thresholds of toxicological concern (TTCs) determined using a structure-based decision-tree using the Toxtree open source software. To ground-truth these computational approaches, we compared the MoEs based on predicted noncancer TTC and OED values to those derived using the traditional method of deriving points of departure from no-observed adverse effect levels (NOAELs) from in vivo oral exposures in rodents. TTC-based MoEs were lower than NOAEL-based MoEs for 520 out of 522 (99.6%) compounds in this smaller overlapping dataset, but were relatively well correlated with the same (r2 = 0.59). TTC-based MoEs were also lower than OED-based MoEs for 590 (83.2%) of the 709 evaluated chemicals, indicating that TTCs may serve as a conservative surrogate in the absence of chemical-specific experimental data. The TTC-based MoE prioritization process was then applied to over 45,000 curated environmental chemical structures as a proof-of-concept for high-throughput prioritization using TTC-based MoEs. This study demonstrates the utility of exploiting existing computational methods at the pre-assessment phase of a tiered risk-based approach to quickly, and conservatively, prioritize thousands of untested chemicals for further study.
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Affiliation(s)
- Chantel I. Nicolas
- Office of Chemical Safety and Pollution Prevention, US EPA, Washington, DC, United States
| | | | | | - Kamel Mansouri
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Research Triangle Park, NC, United States
| | | | | | - John F. Wambaugh
- Center for Computational Toxicology and Exposure Office of Research and Development, US EPA, Research Triangle Park, NC, United States
| | - Grace Patlewicz
- Center for Computational Toxicology and Exposure Office of Research and Development, US EPA, Research Triangle Park, NC, United States
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22
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Kapraun DF, Sfeir M, Pearce RG, Davidson-Fritz SE, Lumen A, Dallmann A, Judson RS, Wambaugh JF. Evaluation of a rapid, generic human gestational dose model. Reprod Toxicol 2022; 113:172-188. [PMID: 36122840 PMCID: PMC9761697 DOI: 10.1016/j.reprotox.2022.09.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Revised: 08/30/2022] [Accepted: 09/14/2022] [Indexed: 10/14/2022]
Abstract
Chemical risk assessment considers potentially susceptible populations including pregnant women and developing fetuses. Humans encounter thousands of chemicals in their environments, few of which have been fully characterized. Toxicokinetic (TK) information is needed to relate chemical exposure to potentially bioactive tissue concentrations. Observational data describing human gestational exposures are unavailable for most chemicals, but physiologically based TK (PBTK) models estimate such exposures. Development of chemical-specific PBTK models requires considerable time and resources. As an alternative, generic PBTK approaches describe a standardized physiology and characterize chemicals with a set of standard physical and TK descriptors - primarily plasma protein binding and hepatic clearance. Here we report and evaluate a generic PBTK model of a human mother and developing fetus. We used a published set of formulas describing the major anatomical and physiological changes that occur during pregnancy to augment the High-Throughput Toxicokinetics (httk) software package. We simulated the ratio of concentrations in maternal and fetal plasma and compared to literature in vivo measurements. We evaluated the model with literature in vivo time-course measurements of maternal plasma concentrations in pregnant and non-pregnant women. Finally, we prioritized chemicals measured in maternal serum based on predicted fetal brain concentrations. This new model can be used for TK simulations of 859 chemicals with existing human-specific in vitro TK data as well as any new chemicals for which such data become available. This gestational model may allow for in vitro to in vivo extrapolation of point of departure doses relevant to reproductive and developmental toxicity.
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Affiliation(s)
- Dustin F Kapraun
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Mark Sfeir
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA; Oak Ridge Institute for Science and Education, Oak Ridge, TN 37831, USA
| | - Robert G Pearce
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA; Oak Ridge Institute for Science and Education, Oak Ridge, TN 37831, USA
| | - Sarah E Davidson-Fritz
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Annie Lumen
- National Center for Toxicological Research, US Food and Drug Administration, USA
| | - André Dallmann
- Pharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
| | - Richard S Judson
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - John F Wambaugh
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
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23
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Krewski D, Saunders-Hastings P, Baan RA, Barton-Maclaren TS, Browne P, Chiu WA, Gwinn M, Hartung T, Kraft AD, Lam J, Lewis RJ, Sanaa M, Morgan RL, Paoli G, Rhomberg L, Rooney A, Sand S, Schünemann HJ, Straif K, Thayer KA, Tsaioun K. Development of an Evidence-Based Risk Assessment Framework. ALTEX 2022; 39:667-693. [PMID: 36098377 PMCID: PMC10080579 DOI: 10.14573/altex.2004041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 06/29/2021] [Indexed: 11/23/2022]
Abstract
Assessment of potential human health risks associated with environmental and other agents requires careful evaluation of all available and relevant evidence for the agent of interest, including both data-rich and data-poor agents. With the advent of new approach methodologies in toxicological risk assessment, guidance on integrating evidence from mul-tiple evidence streams is needed to ensure that all available data is given due consideration in both qualitative and quantitative risk assessment. The present report summarizes the discussions among academic, government, and private sector participants from North America and Europe in an international workshop convened to explore the development of an evidence-based risk assessment framework, taking into account all available evidence in an appropriate manner in order to arrive at the best possible characterization of potential human health risks and associated uncertainty. Although consensus among workshop participants was not a specific goal, there was general agreement on the key consider-ations involved in evidence-based risk assessment incorporating 21st century science into human health risk assessment. These considerations have been embodied into an overarching prototype framework for evidence integration that will be explored in more depth in a follow-up meeting.
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Affiliation(s)
- Daniel Krewski
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
- McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Canada
- Risk Sciences International, Ottawa, Canada
| | | | - Robert A. Baan
- The IARC Monographs Programme, International Agency for Research on Cancer, Lyon, France (retired)
| | | | - Patience Browne
- Organization for Economic Cooperation and Development, Paris, France
| | - Weihsueh A. Chiu
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas, USA
| | - Maureen Gwinn
- Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, USA
| | - Thomas Hartung
- Chair for Evidence-based Toxicology and Center for Alternatives to Animal Testing (CAAT), Johns Hopkins University, Baltimore, USA
- CAAT-Europe, University of Konstanz, Konstanz, Germany
| | - Andrew D. Kraft
- Center for Public Health and Environmental Assessment, Chemical & Pollutant Assessment Division, US EPA, DC, USA
| | - Juleen Lam
- Department of Public Health at California State University, East Bay, USA
| | - R. Jeffrey Lewis
- ExxonMobil Biomedical Sciences, Annandale, New Jersey, USA (retired)
| | - Moez Sanaa
- Agence Nationale Sécurité Sanitaire Alimentaire Nationale, Paris, France
| | | | - Greg Paoli
- Risk Sciences International, Ottawa, Canada
| | | | - Andrew Rooney
- Integrative Health Assessments Branch, National Toxicology Program, US National Institute of Environmental Health Sciences, Research Triangle Park, USA
| | - Salomon Sand
- Department of Risk and Benefit Assessment, Swedish Food Agency, Uppsala, Sweden
| | | | - Kurt Straif
- The IARC Monographs Programme, International Agency for Research on Cancer, Lyon, France (retired)
| | - Kristina A Thayer
- Center for Public Health and Environmental Assessment, Chemical & Pollutant Assessment Division, US EPA, NC, USA
| | - Katya Tsaioun
- Boston College, Chestnut Hill, MA, USA ISGlobal, Barcelona, Spain
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24
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Adam N, Vuong NQ, Adams H, Kuo B, Beheshti A, Yauk C, Wilkins R, Chauhan V. Evaluating the Influences of Confounding Variables on Benchmark Dose using a Case Study in the Field of Ionizing Radiation. Int J Radiat Biol 2022; 98:1845-1855. [PMID: 35939396 DOI: 10.1080/09553002.2022.2110303] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Purpose A vast amount of data regarding the effects of radiation stressors on transcriptional changes has been produced over the past few decades. These data have shown remarkable consistency across platforms and experimental design, enabling increased understanding of early molecular effects of radiation exposure. However, the value of transcriptomic data in the context of risk assessment is not clear and represents a gap that is worthy of further consideration. Recently, benchmark dose (BMD) modeling has shown promise in correlating a transcriptional point of departure (POD) to that derived using phenotypic outcomes relevant to human health risk assessment. Although frequently applied in chemical toxicity evaluation, our group has recently demonstrated application within the field of radiation research. This approach allows the possibility to quantitatively compare radiation-induced gene and pathway alterations across various datasets using BMD values and derive meaningful biological effects. However, before BMD modeling can confidently be used, an understanding of the impact of confounding variables on BMD outputs is needed. Methods: To this end, BMD modeling was applied to a publicly available microarray dataset (Gene Expression Omnibus #GSE23515) that used peripheral blood ex-vivo gamma-irradiated at 0.82 Gy/min, at doses of 0, 0.1, 0.5 or 2 Gy, and assessed 6 hours post-exposure. The dataset comprised six female smokers (F-S), six female non-smokers (F-NS), six male smokers (M-S), and six male non-smokers (M-NS). Results: A combined total of 412 genes were fit to models and the BMD distribution was noted to be bi-modal across the four groups. A total of 74, 41, 62 and 62 genes were unique to the F-NS, M-NS, F-S and M-S groups. Sixty-two BMD modeled genes and nine pathways were common across all four groups. There were no differential sensitivity of responses in the robust common genes and pathways. Conclusion: For radiation-responsive genes and pathways common across the study groups, the BMD distribution of transcriptional activity was unaltered by sex and smoking status. Although further validation of the data is needed, these initial findings suggest BMD values for radiation relevant genes and pathways are robust and could be explored further in future studies.
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Affiliation(s)
- Nadine Adam
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Ngoc Q Vuong
- Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Hailey Adams
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Byron Kuo
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Afshin Beheshti
- KBR, Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, 94035, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Carole Yauk
- University of Ottawa, Ottawa, Ontario K1N 6N5, Canada
| | - Ruth Wilkins
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Vinita Chauhan
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
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25
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Amano Y, Yamane M, Honda H. RAID: Regression Analysis–Based Inductive DNA Microarray for Precise Read-Across. Front Pharmacol 2022; 13:879907. [PMID: 35935858 PMCID: PMC9354856 DOI: 10.3389/fphar.2022.879907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 05/30/2022] [Indexed: 12/02/2022] Open
Abstract
Chemical structure-based read-across represents a promising method for chemical toxicity evaluation without the need for animal testing; however, a chemical structure is not necessarily related to toxicity. Therefore, in vitro studies were often used for read-across reliability refinement; however, their external validity has been hindered by the gap between in vitro and in vivo conditions. Thus, we developed a virtual DNA microarray, regression analysis–based inductive DNA microarray (RAID), which quantitatively predicts in vivo gene expression profiles based on the chemical structure and/or in vitro transcriptome data. For each gene, elastic-net models were constructed using chemical descriptors and in vitro transcriptome data to predict in vivo data from in vitro data (in vitro to in vivo extrapolation; IVIVE). In feature selection, useful genes for assessing the quantitative structure–activity relationship (QSAR) and IVIVE were identified. Predicted transcriptome data derived from the RAID system reflected the in vivo gene expression profiles of characteristic hepatotoxic substances. Moreover, gene ontology and pathway analysis indicated that nuclear receptor-mediated xenobiotic response and metabolic activation are related to these gene expressions. The identified IVIVE-related genes were associated with fatty acid, xenobiotic, and drug metabolisms, indicating that in vitro studies were effective in evaluating these key events. Furthermore, validation studies revealed that chemical substances associated with these key events could be detected as hepatotoxic biosimilar substances. These results indicated that the RAID system could represent an alternative screening test for a repeated-dose toxicity test and toxicogenomics analyses. Our technology provides a critical solution for IVIVE-based read-across by considering the mode of action and chemical structures.
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26
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Kuo B, Beal MA, Wills JW, White PA, Marchetti F, Nong A, Barton-Maclaren TS, Houck K, Yauk CL. Comprehensive interpretation of in vitro micronucleus test results for 292 chemicals: from hazard identification to risk assessment application. Arch Toxicol 2022; 96:2067-2085. [PMID: 35445829 PMCID: PMC9151546 DOI: 10.1007/s00204-022-03286-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 02/23/2022] [Indexed: 11/08/2022]
Abstract
Risk assessments are increasingly reliant on information from in vitro assays. The in vitro micronucleus test (MNvit) is a genotoxicity test that detects chromosomal abnormalities, including chromosome breakage (clastogenicity) and/or whole chromosome loss (aneugenicity). In this study, MNvit datasets for 292 chemicals, generated by the US EPA's ToxCast program, were evaluated using a decision tree-based pipeline for hazard identification. Chemicals were tested with 19 concentrations (n = 1) up to 200 µM, in the presence and absence of Aroclor 1254-induced rat liver S9. To identify clastogenic chemicals, %MN values at each concentration were compared to a distribution of batch-specific solvent controls; this was followed by cytotoxicity assessment and benchmark concentration (BMC) analyses. The approach classified 157 substances as positives, 25 as negatives, and 110 as inconclusive. Using the approach described in Bryce et al. (Environ Mol Mutagen 52:280-286, 2011), we identified 15 (5%) aneugens. IVIVE (in vitro to in vivo extrapolation) was employed to convert BMCs into administered equivalent doses (AEDs). Where possible, AEDs were compared to points of departure (PODs) for traditional genotoxicity endpoints; AEDs were generally lower than PODs based on in vivo endpoints. To facilitate interpretation of in vitro MN assay concentration-response data for risk assessment, exposure estimates were utilized to calculate bioactivity exposure ratio (BER) values. BERs for 50 clastogens and two aneugens had AEDs that approached exposure estimates (i.e., BER < 100); these chemicals might be considered priorities for additional testing. This work provides a framework for the use of high-throughput in vitro genotoxicity testing for priority setting and chemical risk assessment.
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Affiliation(s)
- Byron Kuo
- Environmental Health Science and Research Bureau, Environmental and Radiation Health Sciences Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Marc A Beal
- Bureau of Chemical Safety, Food Directorate, Health Products and Food Branch, Health Canada, Ottawa, ON, Canada
| | - John W Wills
- Environmental Health Science and Research Bureau, Environmental and Radiation Health Sciences Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
- Biominerals Research, Department of Veterinary Medicine, University of Cambridge, Cambridge, CB3 0ES, UK
| | - Paul A White
- Environmental Health Science and Research Bureau, Environmental and Radiation Health Sciences Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Francesco Marchetti
- Environmental Health Science and Research Bureau, Environmental and Radiation Health Sciences Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Andy Nong
- Environmental Health Science and Research Bureau, Environmental and Radiation Health Sciences Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Tara S Barton-Maclaren
- Existing Substances Risk Assessment Bureau, Safe Environments Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Keith Houck
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Carole L Yauk
- Environmental Health Science and Research Bureau, Environmental and Radiation Health Sciences Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada.
- Department of Biology, University of Ottawa, 30 Marie Curie Private, Room 269, Ottawa, ON, K1N 6N5, Canada.
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27
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Bus JS, Gollapudi BB, Hard GC. Methyl-tert-butyl ether (MTBE): integration of rat and mouse carcinogenicity data with mode of action and human and rodent bioassay dosimetry and toxicokinetics indicates MTBE is not a plausible human carcinogen. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. PART B, CRITICAL REVIEWS 2022; 25:135-161. [PMID: 35291916 DOI: 10.1080/10937404.2022.2041516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Methyl-tert-butyl ether (MTBE) is a fuel oxygenate used in non-United States geographies. Multiple health reviews conclude that MTBE is not a human-relevant carcinogen, and this review provides updated mode of action (MOA), exposure, dosimetry and risk perspectives supporting those conclusions. MTBE is non-genotoxic and has large margins of exposure between blood concentrations at the overall rat 400 ppm inhalation NOAEL and blood concentrations in typical workplace or general population exposures. Non-cancer and threshold cancer hazard quotients range from a high of 0.046 for fuel-pump gasoline station attendants and are 100-1,000-fold lower for general population exposures. Cancer risks conservatively assuming genotoxicity for these same scenarios are all less than 1 × 10-6. The onset of MTBE nonlinear toxicokinetics (TK) in rats at inhalation exposures less than 3,000 ppm, a dose that is also not practically achievable in fuel-use scenarios, indicates that high-dose specific male rat kidney and testes (3,000 and 8,000 ppm) and female mouse liver tumors (8000 ppm) are not quantitatively relevant to humans. Mode of action analyses also indicate MTBE male rat kidney tumors, and lesser so female mouse liver tumors, are not qualitatively relevant to humans. Thus, an integrated analysis of the toxicology, exposure/dosimetry, TK, and MOA data indicates that MTBE presents minimal human cancer and non-cancer risks.
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Affiliation(s)
- James S Bus
- Toxicology and Mechanistic Biology, Exponent Inc, Apex, NC, USA
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28
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Crofton KM, Bassan A, Behl M, Chushak YG, Fritsche E, Gearhart JM, Marty MS, Mumtaz M, Pavan M, Ruiz P, Sachana M, Selvam R, Shafer TJ, Stavitskaya L, Szabo DT, Szabo ST, Tice RR, Wilson D, Woolley D, Myatt GJ. Current status and future directions for a neurotoxicity hazard assessment framework that integrates in silico approaches. COMPUTATIONAL TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2022; 22:100223. [PMID: 35844258 PMCID: PMC9281386 DOI: 10.1016/j.comtox.2022.100223] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/27/2023]
Abstract
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.
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Affiliation(s)
| | - Arianna Bassan
- Innovatune srl, Via Giulio Zanon 130/D, 35129 Padova,
Italy
| | - Mamta Behl
- Division of the National Toxicology Program, National
Institutes of Environmental Health Sciences, Durham, NC 27709, USA
| | - Yaroslav G. Chushak
- Henry M Jackson Foundation for the Advancement of Military
Medicine, Wright-Patterson AFB, OH 45433, USA
| | - Ellen Fritsche
- IUF – Leibniz Research Institute for Environmental
Medicine & Medical Faculty Heinrich-Heine-University, Düsseldorf,
Germany
| | - Jeffery M. Gearhart
- Henry M Jackson Foundation for the Advancement of Military
Medicine, Wright-Patterson AFB, OH 45433, USA
| | | | - Moiz Mumtaz
- Agency for Toxic Substances and Disease Registry, US
Department of Health and Human Services, Atlanta, GA, USA
| | - Manuela Pavan
- Innovatune srl, Via Giulio Zanon 130/D, 35129 Padova,
Italy
| | - Patricia Ruiz
- Agency for Toxic Substances and Disease Registry, US
Department of Health and Human Services, Atlanta, GA, USA
| | - Magdalini Sachana
- Environment Health and Safety Division, Environment
Directorate, Organisation for Economic Co-Operation and Development (OECD), 75775
Paris Cedex 16, France
| | - Rajamani Selvam
- Office of Clinical Pharmacology, Office of Translational
Sciences, Center for Drug Evaluation and Research (CDER), U.S. Food and Drug
Administration (FDA), Silver Spring, MD 20993, USA
| | - Timothy J. Shafer
- Biomolecular and Computational Toxicology Division, Center
for Computational Toxicology and Exposure, US EPA, Research Triangle Park, NC,
USA
| | - Lidiya Stavitskaya
- Office of Clinical Pharmacology, Office of Translational
Sciences, Center for Drug Evaluation and Research (CDER), U.S. Food and Drug
Administration (FDA), Silver Spring, MD 20993, USA
| | | | | | | | - Dan Wilson
- The Dow Chemical Company, Midland, MI 48667, USA
| | | | - Glenn J. Myatt
- Instem, Columbus, OH 43215, USA
- Corresponding author.
(G.J. Myatt)
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Price PS, Hubbell BJ, Hagiwara S, Paoli GM, Krewski D, Guiseppi‐Elie A, Gwinn MR, Adkins NL, Thomas RS. A Framework that Considers the Impacts of Time, Cost, and Uncertainty in the Determination of the Cost Effectiveness of Toxicity-Testing Methodologies. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2022; 42:707-729. [PMID: 34490933 PMCID: PMC9290960 DOI: 10.1111/risa.13810] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 07/06/2021] [Accepted: 07/28/2021] [Indexed: 06/13/2023]
Abstract
Regulatory agencies are required to evaluate the impacts of thousands of chemicals. Toxicological tests currently used in such evaluations are time-consuming and resource intensive; however, advances in toxicology and related fields are providing new testing methodologies that reduce the cost and time required for testing. The selection of a preferred methodology is challenging because the new methodologies vary in duration and cost, and the data they generate vary in the level of uncertainty. This article presents a framework for performing cost-effectiveness analyses (CEAs) of toxicity tests that account for cost, duration, and uncertainty. This is achieved by using an output metric-the cost per correct regulatory decision-that reflects the three elements. The framework is demonstrated in two example CEAs, one for a simple decision of risk acceptability and a second, more complex decision, involving the selection of regulatory actions. Each example CEA evaluates five hypothetical toxicity-testing methodologies which differ with respect to cost, time, and uncertainty. The results of the examples indicate that either a fivefold reduction in cost or duration can be a larger driver of the selection of an optimal toxicity-testing methodology than a fivefold reduction in uncertainty. Uncertainty becomes of similar importance to cost and duration when decisionmakers are required to make more complex decisions that require the determination of small differences in risk predictions. The framework presented in this article may provide a useful basis for the identification of cost-effective methods for toxicity testing of large numbers of chemicals.
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Affiliation(s)
- Paul S. Price
- Center for Computational Toxicology and ExposureUS Environmental Protection Agency, Research Triangle ParkDurhamNCUSA
| | - Bryan J. Hubbell
- Air, Climate, and Energy Research ProgramUS Environmental Protection Agency, Research Triangle ParkDurhamNCUSA
| | - Shintaro Hagiwara
- School of Mathematics and StatisticsCarleton UniversityOttawaCanada
- Risk Sciences InternationalOttawaCanada
| | | | - Daniel Krewski
- McLaughlin Centre for Population Health Risk AssessmentUniversity of OttawaOttawaCanada
| | - Annette Guiseppi‐Elie
- Center for Computational Toxicology and ExposureUS Environmental Protection Agency, Research Triangle ParkDurhamNCUSA
| | - Maureen R. Gwinn
- Sustainable and Healthy Communities Research ProgramUS Environmental Protection Agency, Research Triangle ParkNCUSA
| | - Norman L. Adkins
- Center for Computational Toxicology and ExposureUS Environmental Protection Agency, Research Triangle ParkDurhamNCUSA
| | - Russell S. Thomas
- Center for Computational Toxicology and ExposureUS Environmental Protection Agency, Research Triangle ParkDurhamNCUSA
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30
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Hilton GM, Adcock C, Akerman G, Baldassari J, Battalora M, Casey W, Clippinger AJ, Cope R, Goetz A, Hayes AW, Papineni S, Peffer RC, Ramsingh D, Williamson Riffle B, Sanches da Rocha M, Ryan N, Scollon E, Visconti N, Wolf DC, Yan Z, Lowit A. Rethinking chronic toxicity and carcinogenicity assessment for agrochemicals project (ReCAAP): A reporting framework to support a weight of evidence safety assessment without long-term rodent bioassays. Regul Toxicol Pharmacol 2022; 131:105160. [PMID: 35311659 DOI: 10.1016/j.yrtph.2022.105160] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 03/07/2022] [Accepted: 03/14/2022] [Indexed: 11/17/2022]
Abstract
Rodent cancer bioassays have been long-required studies for regulatory assessment of human cancer hazard and risk. These studies use hundreds of animals, are resource intensive, and certain aspects of these studies have limited human relevance. The past 10 years have seen an exponential growth of new technologies with the potential to effectively evaluate human cancer hazard and risk while reducing, refining, or replacing animal use. To streamline and facilitate uptake of new technologies, a workgroup comprised of scientists from government, academia, non-governmental organizations, and industry stakeholders developed a framework for waiver rationales of rodent cancer bioassays for consideration in agrochemical safety assessment. The workgroup used an iterative approach, incorporating regulatory agency feedback, and identifying critical information to be considered in a risk assessment-based weight of evidence determination of the need for rodent cancer bioassays. The reporting framework described herein was developed to support a chronic toxicity and carcinogenicity study waiver rationale, which includes information on use pattern(s), exposure scenario(s), pesticidal mode-of-action, physicochemical properties, metabolism, toxicokinetics, toxicological data including mechanistic data, and chemical read-across from similar registered pesticides. The framework could also be applied to endpoints other than chronic toxicity and carcinogenicity, and for chemicals other than agrochemicals.
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Affiliation(s)
- Gina M Hilton
- PETA Science Consortium International e.V., Stuttgart, Germany.
| | - Catherine Adcock
- Health Canada, Pest Management Regulatory Agency, Ottawa, Ontario, Canada
| | - Gregory Akerman
- United States Environmental Protection Agency, Office of Pesticide Programs, Washington DC, USA
| | | | | | - Warren Casey
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | | | - Rhian Cope
- Australian Pesticides and Veterinary Medicines Authority, Armidale, New South Wales, Australia
| | - Amber Goetz
- Syngenta Crop Protection, LLC, Greensboro, NC, USA
| | - A Wallace Hayes
- University of South Florida College of Public Health, Tampa, FL, USA
| | | | | | - Deborah Ramsingh
- Health Canada, Pest Management Regulatory Agency, Ottawa, Ontario, Canada
| | | | | | - Natalia Ryan
- Syngenta Crop Protection, LLC, Greensboro, NC, USA
| | | | | | | | | | - Anna Lowit
- United States Environmental Protection Agency, Office of Pesticide Programs, Washington DC, USA
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Rajagopal R, Baltazar MT, Carmichael PL, Dent MP, Head J, Li H, Muller I, Reynolds J, Sadh K, Simpson W, Spriggs S, White A, Kukic P. Beyond AOPs: A Mechanistic Evaluation of NAMs in DART Testing. FRONTIERS IN TOXICOLOGY 2022; 4:838466. [PMID: 35295212 PMCID: PMC8915803 DOI: 10.3389/ftox.2022.838466] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 01/31/2022] [Indexed: 12/22/2022] Open
Abstract
New Approach Methodologies (NAMs) promise to offer a unique opportunity to enable human-relevant safety decisions to be made without the need for animal testing in the context of exposure-driven Next Generation Risk Assessment (NGRA). Protecting human health against the potential effects a chemical may have on embryo-foetal development and/or aspects of reproductive biology using NGRA is particularly challenging. These are not single endpoint or health effects and risk assessments have traditionally relied on data from Developmental and Reproductive Toxicity (DART) tests in animals. There are numerous Adverse Outcome Pathways (AOPs) that can lead to DART, which means defining and developing strict testing strategies for every AOP, to predict apical outcomes, is neither a tenable goal nor a necessity to ensure NAM-based safety assessments are fit-for-purpose. Instead, a pragmatic approach is needed that uses the available knowledge and data to ensure NAM-based exposure-led safety assessments are sufficiently protective. To this end, the mechanistic and biological coverage of existing NAMs for DART were assessed and gaps to be addressed were identified, allowing the development of an approach that relies on generating data relevant to the overall mechanisms involved in human reproduction and embryo-foetal development. Using the knowledge of cellular processes and signalling pathways underlying the key stages in reproduction and development, we have developed a broad outline of endpoints informative of DART. When the existing NAMs were compared against this outline to determine whether they provide comprehensive coverage when integrated in a framework, we found them to generally cover the reproductive and developmental processes underlying the traditionally evaluated apical endpoint studies. The application of this safety assessment framework is illustrated using an exposure-led case study.
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Affiliation(s)
- Ramya Rajagopal
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, United Kingdom
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32
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Firman JW, Cronin MTD, Rowe PH, Semenova E, Doe JE. The use of Bayesian methodology in the development and validation of a tiered assessment approach towards prediction of rat acute oral toxicity. Arch Toxicol 2022; 96:817-830. [PMID: 35034154 PMCID: PMC8850222 DOI: 10.1007/s00204-021-03205-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 12/09/2021] [Indexed: 11/16/2022]
Abstract
There exists consensus that the traditional means by which safety of chemicals is assessed-namely through reliance upon apical outcomes obtained following in vivo testing-is increasingly unfit for purpose. Whilst efforts in development of suitable alternatives continue, few have achieved levels of robustness required for regulatory acceptance. An array of "new approach methodologies" (NAM) for determining toxic effect, spanning in vitro and in silico spheres, have by now emerged. It has been suggested, intuitively, that combining data obtained from across these sources might serve to enhance overall confidence in derived judgment. This concept may be formalised in the "tiered assessment" approach, whereby evidence gathered through a sequential NAM testing strategy is exploited so to infer the properties of a compound of interest. Our intention has been to provide an illustration of how such a scheme might be developed and applied within a practical setting-adopting for this purpose the endpoint of rat acute oral lethality. Bayesian statistical inference is drawn upon to enable quantification of degree of confidence that a substance might ultimately belong to one of five LD50-associated toxicity categories. Informing this is evidence acquired both from existing in silico and in vitro resources, alongside a purposely-constructed random forest model and structural alert set. Results indicate that the combination of in silico methodologies provides moderately conservative estimations of hazard, conducive for application in safety assessment, and for which levels of certainty are defined. Accordingly, scope for potential extension of approach to further toxicological endpoints is demonstrated.
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Affiliation(s)
- James W Firman
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, UK.
| | - Mark T D Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, UK
| | - Philip H Rowe
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, UK
| | | | - John E Doe
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, UK
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ALOHA: Aggregated local extrema splines for high-throughput dose-response analysis. COMPUTATIONAL TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2022; 21:100196. [PMID: 35083394 PMCID: PMC8785973 DOI: 10.1016/j.comtox.2021.100196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Computational methods for genomic dose-response integrate dose-response modeling with bioinformatics tools to evaluate changes in molecular and cellular functions related to pathogenic processes. These methods use parametric models to describe each gene's dose-response, but such models may not adequately capture expression changes. Additionally, current approaches do not consider gene co-expression networks. When assessing co-expression networks, one typically does not consider the dose-response relationship, resulting in 'co-regulated' gene sets containing genes having different dose-response patterns. To avoid these limitations, we develop an analysis pipeline called Aggregated Local Extrema Splines for High-throughput Analysis (ALOHA), which computes individual genomic dose-response functions using a flexible class Bayesian shape constrained splines and clusters gene co-regulation based upon these fits. Using splines, we reduce information loss due to parametric lack-of-fit issues, and because we cluster on dose-response relationships, we better identify co-regulation clusters for genes that have co-expressed dose-response patterns from chemical exposure. The clustered pathways can then be used to estimate a dose associated with a pre-specified biological response, i.e., the benchmark dose (BMD), and approximate a point of departure dose corresponding to minimal adverse response in the whole tissue/organism. We compare our approach to current parametric methods and our biologically enriched gene sets to cluster on normalized expression data. Using this methodology, we can more effectively extract the underlying structure leading to more cohesive estimates of gene set potency.
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34
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Felter SP, Bhat VS, Botham PA, Bussard DA, Casey W, Hayes AW, Hilton GM, Magurany KA, Sauer UG, Ohanian EV. Assessing chemical carcinogenicity: hazard identification, classification, and risk assessment. Insight from a Toxicology Forum state-of-the-science workshop. Crit Rev Toxicol 2022; 51:653-694. [DOI: 10.1080/10408444.2021.2003295] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
| | | | | | - David A. Bussard
- U.S. Environmental Protection Agency, Office of the Science Advisor, Policy and Engagement, Washington, DC, USA
| | - Warren Casey
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - A. Wallace Hayes
- University of South Florida College of Public Health, Tampa, FL, USA
| | - Gina M. Hilton
- PETA Science Consortium International e.V., Stuttgart, Germany
| | | | | | - Edward V. Ohanian
- United States Environmental Protection Agency, Office of Water, Washington, DC, USA
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35
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Beal MA, Gagne M, Kulkarni SA, Patlewicz G, Thomas RS, Barton-Maclaren TS. Implementing in vitro bioactivity data to modernize priority setting of chemical inventories. ALTEX 2022; 39:123-139. [PMID: 34818430 PMCID: PMC8973434 DOI: 10.14573/altex.2106171] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 11/22/2021] [Indexed: 01/03/2023]
Abstract
Internationally, there are thousands of existing and newly introduced chemicals in commerce, highlighting the ongoing importance of innovative approaches to identify emerging chemicals of concern. For many chemicals, there is a paucity of hazard and exposure data. Thus, there is a crucial need for efficient and robust approaches to address data gaps and support risk-based prioritization. Several studies have demonstrated the utility of in vitro bioactivity data from the ToxCast program in deriving points of departure (PODs). ToxCast contains data for nearly 1,400 endpoints per chemical, and the bioactivity concentrations, indicative of potential adverse outcomes, can be converted to human-equivalent PODs using high-throughput toxicokinetics (HTTK) modeling. However, data gaps need to be addressed for broader application: the limited chemical space of HTTK and quantitative high-throughput screening data. Here we explore the applicability of in silico models to address these data needs. Specifically, we used ADMET predictor for HTTK predictions and a generalized read-across approach to predict ToxCast bioactivity potency. We applied these models to profile 5,801 chemicals on Canada’s Domestic Substances List (DSL). To evaluate the approach’s performance, bioactivity PODs were compared with in vivo results from the EPA Toxicity Values database for 1,042 DSL chemicals. Comparisons demonstrated that the bioactivity PODs, based on ToxCast data or read-across, were conservative for 95% of the chemicals. Comparing bioactivity PODs to human exposure estimates supports the identification of chemicals of potential interest for further work. The bioactivity workflow shows promise as a powerful screening tool to support effective triaging of chemical inventories.
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Affiliation(s)
- Marc A. Beal
- Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Matthew Gagne
- Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Sunil A. Kulkarni
- Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Grace Patlewicz
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Russell S. Thomas
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
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36
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Bauer B, Mally A, Liedtke D. Zebrafish Embryos and Larvae as Alternative Animal Models for Toxicity Testing. Int J Mol Sci 2021; 22:13417. [PMID: 34948215 PMCID: PMC8707050 DOI: 10.3390/ijms222413417] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Revised: 12/07/2021] [Accepted: 12/10/2021] [Indexed: 02/07/2023] Open
Abstract
Prerequisite to any biological laboratory assay employing living animals is consideration about its necessity, feasibility, ethics and the potential harm caused during an experiment. The imperative of these thoughts has led to the formulation of the 3R-principle, which today is a pivotal scientific standard of animal experimentation worldwide. The rising amount of laboratory investigations utilizing living animals throughout the last decades, either for regulatory concerns or for basic science, demands the development of alternative methods in accordance with 3R to help reduce experiments in mammals. This demand has resulted in investigation of additional vertebrate species displaying favourable biological properties. One prominent species among these is the zebrafish (Danio rerio), as these small laboratory ray-finned fish are well established in science today and feature outstanding biological characteristics. In this review, we highlight the advantages and general prerequisites of zebrafish embryos and larvae before free-feeding stages for toxicological testing, with a particular focus on cardio-, neuro, hepato- and nephrotoxicity. Furthermore, we discuss toxicokinetics, current advances in utilizing zebrafish for organ toxicity testing and highlight how advanced laboratory methods (such as automation, advanced imaging and genetic techniques) can refine future toxicological studies in this species.
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Affiliation(s)
- Benedikt Bauer
- Institute of Pharmacology and Toxicology, Julius-Maximilians-University, 97078 Würzburg, Germany; (B.B.); (A.M.)
| | - Angela Mally
- Institute of Pharmacology and Toxicology, Julius-Maximilians-University, 97078 Würzburg, Germany; (B.B.); (A.M.)
| | - Daniel Liedtke
- Institute of Human Genetics, Julius-Maximilians-University, 97074 Würzburg, Germany
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Integrating toxicokinetics into toxicology studies and the human health risk assessment process for chemicals: Reduced uncertainty, better health protection. Regul Toxicol Pharmacol 2021; 128:105092. [PMID: 34863906 DOI: 10.1016/j.yrtph.2021.105092] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 11/23/2021] [Accepted: 11/29/2021] [Indexed: 01/16/2023]
Abstract
The database of practical examples where toxicokinetic (TK) data has benefitted all stages of the human health risk assessment process are increasingly being published and accepted. This review aimed to highlight and summarise notable examples and to describe the "state of the art" in this field. The overall recommendation is that for any in vivo animal study conducted, measurements of TK should be very carefully considered for inclusion as the numerous benefits this brings continues to grow, particularly during the current march towards animal free toxicology testing and ambitions to eventually conduct human health risk assessments entirely based upon non-animal methods.
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38
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Borgert CJ, Fuentes C, Burgoon LD. Principles of dose-setting in toxicology studies: the importance of kinetics for ensuring human safety. Arch Toxicol 2021; 95:3651-3664. [PMID: 34623454 PMCID: PMC8536606 DOI: 10.1007/s00204-021-03155-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 09/02/2021] [Indexed: 01/11/2023]
Abstract
Regulatory toxicology seeks to ensure that exposures to chemicals encountered in the environment, in the workplace, or in products pose no significant hazards and produce no harm to humans or other organisms, i.e., that chemicals are used safely. The most practical and direct means of ensuring that hazards and harms are avoided is to identify the doses and conditions under which chemical toxicity does not occur so that chemical concentrations and exposures can be appropriately limited. Modern advancements in pharmacology and toxicology have revealed that the rates and mechanisms by which organisms absorb, distribute, metabolize and eliminate chemicals-i.e., the field of kinetics-often determine the doses and conditions under which hazard, and harm, are absent, i.e., the safe dose range. Since kinetics, like chemical hazard and toxicity, are extensive properties that depend on the amount of the chemical encountered, it is possible to identify the maximum dose under which organisms can efficiently metabolize and eliminate the chemicals to which they are exposed, a dose that has been referred to as the kinetic maximum dose, or KMD. This review explains the rationale that compels regulatory toxicology to embrace the advancements made possible by kinetics, why understanding the kinetic relationship between the blood level produced and the administered dose of a chemical is essential for identifying the safe dose range, and why dose-setting in regulatory toxicology studies should be informed by estimates of the KMD rather than rely on the flawed concept of maximum-tolerated toxic dose, or MTD.
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Affiliation(s)
- C J Borgert
- Applied Pharmacology and Toxicology, Inc., Gainesville, FL, USA.
- Center for Environmental and Human Toxicology (CEHT), Department of Physiological Sciences, University of Florida College of Veterinary Medicine, Gainesville, FL, USA.
| | - C Fuentes
- Department of Statistics, Oregon State University, Corvallis, OR, USA
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39
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Chauhan V, Leblanc J, Sadi B, Burtt J, Sauvé K, Lane R, Randhawa K, Wilkins R, Quayle D. COHERE - strengthening cooperation within the Canadian government on radiation research. Int J Radiat Biol 2021; 97:1153-1165. [PMID: 34133252 DOI: 10.1080/09553002.2021.1941379] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 05/16/2021] [Accepted: 06/03/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE Canadian Organization on Health Effects from Radiation Exposure (COHERE) is a government initiative to better understand biological and human health risks from ionizing radiation exposures relevant to occupational and environmental settings (<100 mGy, <6 mGy/h). It is currently a partnership between two federal agencies, Health Canada (HC) and the Canadian Nuclear Safety Commission (CNSC). COHERE's vision is to contribute knowledge to reduce scientific uncertainties from low dose and dose-rate exposures. COHERE will advance our understanding by bridging the knowledge gap between human health risks and linkages to molecular- and cellular-level responses to radiation. Research focuses on identifying sensitive, early, and key molecular events of relevance to risk assessment. CONCLUSIONS The initiative will address questions of relevance to better apprize Canadians, including radiation workers and members of the public and Indigenous peoples, on health risks from low dose radiation exposure and inform radiation protection frameworks at a national and international level. Furthermore, it will support global efforts to conduct collaborative undertakings and better coordinate research. Here, we describe a historical overview of the research conducted, the strategic research agenda that outlines the scientific framework, stakeholders, opportunities to harmonize internationally, and how research outcomes will better inform communication of risk to Canadians.
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Affiliation(s)
- Vinita Chauhan
- Radiation Protection Bureau, Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Julie Leblanc
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Baki Sadi
- Radiation Protection Bureau, Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Julie Burtt
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Kiza Sauvé
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Rachel Lane
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Kristi Randhawa
- Directorate of Environmental and Radiation Protection and Assessment, Canadian Nuclear Safety Commission, Ottawa, Canada
| | - Ruth Wilkins
- Radiation Protection Bureau, Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
| | - Debora Quayle
- Radiation Protection Bureau, Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Canada
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40
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Valdiviezo A, Luo YS, Chen Z, Chiu WA, Rusyn I. Quantitative in Vitro-to-in Vivo Extrapolation for Mixtures: A Case Study of Superfund Priority List Pesticides. Toxicol Sci 2021; 183:60-69. [PMID: 34142158 DOI: 10.1093/toxsci/kfab076] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
In vitro cell-based toxicity testing methods generate large amounts of data informative for risk-based evaluations. To allow extrapolation of the quantitative outputs from cell-based tests to the equivalent exposure levels in humans, reverse toxicokinetic (RTK) modeling is used to conduct in vitro-to-in vivo extrapolation (IVIVE) from in vitro effective concentrations to in vivo oral dose equivalents. IVIVE modeling approaches for individual chemicals are well-established; however, the potential implications of chemical-to-chemical interactions in mixture settings on IVIVE remains largely unexplored. We hypothesized that chemical co-exposures could modulate both protein binding efficiency and hepatocyte clearance of the chemicals in a mixture, which would in turn affect the quantitative IVIVE toxicokinetic parameters. To test this hypothesis, we used 20 pesticides from the Agency for Toxic Substances and Disease Registry (ATSDR) Substance Priority List, both individually and as equimolar mixtures, and investigated the concentration-dependent effects of chemical interactions on in vitro toxicokinetic parameters. Plasma protein binding efficiency was determined by using ultracentrifugation, and hepatocyte clearance was estimated in suspensions of cryopreserved primary human hepatocytes. We found that for single chemicals, the protein binding efficiencies were similar at different test concentrations. In a mixture, however, both protein binding efficiency and hepatocyte clearance were affected. When IVIVE was conducted using mixture-derived toxicokinetic data, more conservative estimates of Activity-to-Exposure Ratios (AERs) were produced as compared to using data from single chemical experiments. Because humans are exposed to mixtures of chemicals, this study is significant as it demonstrates the importance of incorporating mixture-derived parameters into IVIVE for in vitro bioactivity data in order to accurately prioritize risks and facilitate science-based decision-making.
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Affiliation(s)
- Alan Valdiviezo
- Interdisciplinary Faculty of Toxicology and Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843
| | - Yu-Syuan Luo
- Interdisciplinary Faculty of Toxicology and Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843
| | - Zunwei Chen
- Interdisciplinary Faculty of Toxicology and Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843
| | - Weihsueh A Chiu
- Interdisciplinary Faculty of Toxicology and Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843
| | - Ivan Rusyn
- Interdisciplinary Faculty of Toxicology and Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843
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Crizer DM, Ramaiahgari SC, Ferguson SS, Rice JR, Dunlap PE, Sipes NS, Auerbach SS, Merrick BA, DeVito MJ. Benchmark Concentrations for Untargeted Metabolomics Versus Transcriptomics for Liver Injury Compounds in In Vitro Liver Models. Toxicol Sci 2021; 181:175-186. [PMID: 33749773 PMCID: PMC8163038 DOI: 10.1093/toxsci/kfab036] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Interpretation of untargeted metabolomics data from both in vivo and physiologically relevant in vitro model systems continues to be a significant challenge for toxicology research. Potency-based modeling of toxicological responses has served as a pillar of interpretive context and translation of testing data. In this study, we leverage the resolving power of concentration-response modeling through benchmark concentration (BMC) analysis to interpret untargeted metabolomics data from differentiated cultures of HepaRG cells exposed to a panel of reference compounds and integrate data in a potency-aligned framework with matched transcriptomic data. For this work, we characterized biological responses to classical human liver injury compounds and comparator compounds, known to not cause liver injury in humans, at 10 exposure concentrations in spent culture media by untargeted liquid chromatography-mass spectrometry analysis. The analyte features observed (with limited metabolites identified) were analyzed using BMC modeling to derive compound-induced points of departure. The results revealed liver injury compounds produced concentration-related increases in metabolomic response compared to those rarely associated with liver injury (ie, sucrose, potassium chloride). Moreover, the distributions of altered metabolomic features were largely comparable with those observed using high throughput transcriptomics, which were further extended to investigate the potential for in vitro observed biological responses to be observed in humans with exposures at therapeutic doses. These results demonstrate the utility of BMC modeling of untargeted metabolomics data as a sensitive and quantitative indicator of human liver injury potential.
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Affiliation(s)
- David M Crizer
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Sreenivasa C Ramaiahgari
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Stephen S Ferguson
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Julie R Rice
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Paul E Dunlap
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Nisha S Sipes
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Scott S Auerbach
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Bruce Alex Merrick
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
| | - Michael J DeVito
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina 27709, USA
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42
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Paul Friedman K, Gagne M, Loo LH, Karamertzanis P, Netzeva T, Sobanski T, Franzosa JA, Richard AM, Lougee RR, Gissi A, Lee JYJ, Angrish M, Dorne JL, Foster S, Raffaele K, Bahadori T, Gwinn MR, Lambert J, Whelan M, Rasenberg M, Barton-Maclaren T, Thomas RS. Utility of In Vitro Bioactivity as a Lower Bound Estimate of In Vivo Adverse Effect Levels and in Risk-Based Prioritization. Toxicol Sci 2021; 173:202-225. [PMID: 31532525 DOI: 10.1093/toxsci/kfz201] [Citation(s) in RCA: 135] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Use of high-throughput, in vitro bioactivity data in setting a point-of-departure (POD) has the potential to accelerate the pace of human health safety evaluation by informing screening-level assessments. The primary objective of this work was to compare PODs based on high-throughput predictions of bioactivity, exposure predictions, and traditional hazard information for 448 chemicals. PODs derived from new approach methodologies (NAMs) were obtained for this comparison using the 50th (PODNAM, 50) and the 95th (PODNAM, 95) percentile credible interval estimates for the steady-state plasma concentration used in in vitro to in vivo extrapolation of administered equivalent doses. Of the 448 substances, 89% had a PODNAM, 95 that was less than the traditional POD (PODtraditional) value. For the 48 substances for which PODtraditional < PODNAM, 95, the PODNAM and PODtraditional were typically within a factor of 10 of each other, and there was an enrichment of chemical structural features associated with organophosphate and carbamate insecticides. When PODtraditional < PODNAM, 95, it did not appear to result from an enrichment of PODtraditional based on a particular study type (eg, developmental, reproductive, and chronic studies). Bioactivity:exposure ratios, useful for identification of substances with potential priority, demonstrated that high-throughput exposure predictions were greater than the PODNAM, 95 for 11 substances. When compared with threshold of toxicological concern (TTC) values, the PODNAM, 95 was greater than the corresponding TTC value 90% of the time. This work demonstrates the feasibility, and continuing challenges, of using in vitro bioactivity as a protective estimate of POD in screening-level assessments via a case study.
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Affiliation(s)
- Katie Paul Friedman
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711
| | - Matthew Gagne
- Healthy Environments and Consumer Safety Branch, Health Canada, Government of Canada, Ottawa, Ontario, Canada, K1A0K9
| | - Lit-Hsin Loo
- Innovations in Food and Chemical Safety Programme and Bioinformatics Institute, Agency for Science, Technology and Research, Singapore, 138671, Singapore
| | - Panagiotis Karamertzanis
- Computational Assessment Unit, European Chemicals Agency, European Chemicals Agency Annankatu 18, P.O. Box 400, FI-00121 Helsinki, Uusimaa, Finland
| | - Tatiana Netzeva
- Computational Assessment Unit, European Chemicals Agency, European Chemicals Agency Annankatu 18, P.O. Box 400, FI-00121 Helsinki, Uusimaa, Finland
| | - Tomasz Sobanski
- Computational Assessment Unit, European Chemicals Agency, European Chemicals Agency Annankatu 18, P.O. Box 400, FI-00121 Helsinki, Uusimaa, Finland
| | - Jill A Franzosa
- National Health and Environmental Effects Research Laboratory, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711
| | - Ann M Richard
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711
| | - Ryan R Lougee
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711.,Oak Ridge Institute for Science and Education, U.S. Department of Energy, Oak Ridge, TN 37831, USA
| | - Andrea Gissi
- Computational Assessment Unit, European Chemicals Agency, European Chemicals Agency Annankatu 18, P.O. Box 400, FI-00121 Helsinki, Uusimaa, Finland
| | - Jia-Ying Joey Lee
- Innovations in Food and Chemical Safety Programme and Bioinformatics Institute, Agency for Science, Technology and Research, Singapore, 138671, Singapore
| | - Michelle Angrish
- National Center for Environmental Assessment, Office of Research and Development, US Environmental Protection Agency, Washington, DC, 20004 and Research Triangle Park, NC 27711
| | - Jean Lou Dorne
- Scientific Committee and Emerging Risks Unit Department of Risk Assessment and Scientific Assistance, Via Carlo Magno 1A, 43126 Parma, Italy
| | - Stiven Foster
- Office of Land and Emergency Management, U.S. Environmental Protection Agency, Washington, DC, 20004
| | - Kathleen Raffaele
- Office of Land and Emergency Management, U.S. Environmental Protection Agency, Washington, DC, 20004
| | - Tina Bahadori
- Oak Ridge Institute for Science and Education, U.S. Department of Energy, Oak Ridge, TN 37831, USA
| | - Maureen R Gwinn
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711
| | - Jason Lambert
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711
| | - Maurice Whelan
- European Commission, Joint Research Centre (JRC), Via Enrico Fermi, 2749, I - 21027 Ispra, Italy
| | - Mike Rasenberg
- Computational Assessment Unit, European Chemicals Agency, European Chemicals Agency Annankatu 18, P.O. Box 400, FI-00121 Helsinki, Uusimaa, Finland
| | - Tara Barton-Maclaren
- Healthy Environments and Consumer Safety Branch, Health Canada, Government of Canada, Ottawa, Ontario, Canada, K1A0K9
| | - Russell S Thomas
- National Center for Computational Toxicology, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC, 27711
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Dawson D, Ingle BL, Phillips KA, Nichols JW, Wambaugh JF, Tornero-Velez R. Designing QSARs for Parameters of High-Throughput Toxicokinetic Models Using Open-Source Descriptors. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:6505-6517. [PMID: 33856768 PMCID: PMC8548983 DOI: 10.1021/acs.est.0c06117] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
The intrinsic metabolic clearance rate (Clint) and the fraction of the chemical unbound in plasma (fup) serve as important parameters for high-throughput toxicokinetic (TK) models, but experimental data are limited for many chemicals. Open-source quantitative structure-activity relationship (QSAR) models for both parameters were developed to offer reliable in silico predictions for a diverse set of chemicals regulated under the U.S. law, including pharmaceuticals, pesticides, and industrial chemicals. As a case study to demonstrate their utility, model predictions served as inputs to the TK component of a risk-based prioritization approach based on bioactivity/exposure ratios (BERs), in which a BER < 1 indicates that exposures are predicted to exceed a biological activity threshold. When applied to a subset of the Tox21 screening library (6484 chemicals), we found that the proportion of chemicals with BER <1 was similar using either in silico (1133/6484; 17.5%) or in vitro (148/848; 17.5%) parameters. Further, when considering only the chemicals in the Tox21 set with in vitro data, there was a high concordance of chemicals classified with either BER <1 or >1 using either in silico or in vitro parameters (767/848, 90.4%). Thus, the presented QSARs may be suitable for prioritizing the risk posed by many chemicals for which measured in vitro TK data are lacking.
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Affiliation(s)
- Daniel Dawson
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709
| | - Brandall L. Ingle
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709
| | - Katherine A. Phillips
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709
| | - John W. Nichols
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709
| | - John F. Wambaugh
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709
| | - Rogelio Tornero-Velez
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709
- Corresponding Author Address correspondence to Rogelio Tornero-Velez at 109 T.W. Alexander Drive, Mail Code E205-01, Research Triangle Park, NC, 27709;
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44
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Evaluation of Quantitative Structure Property Relationship Algorithms for Predicting Plasma Protein Binding in Humans. ACTA ACUST UNITED AC 2021; 17:100142. [PMID: 34017929 DOI: 10.1016/j.comtox.2020.100142] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The extent of plasma protein binding is an important compound-specific property that influences a compound's pharmacokinetic behavior and is a critical input parameter for predicting exposure in physiologically based pharmacokinetic (PBPK) modeling. When experimentally determined fraction unbound in plasma (fup) data are not available, quantitative structure-property relationship (QSPR) models can be used for prediction. Because available QSPR models were developed based on training sets containing pharmaceutical-like compounds, we compared their prediction accuracy for environmentally relevant and pharmaceutical compounds. Fup values were calculated using Ingle et al., Watanabe et al. and ADMET Predictor (Simulation Plus). The test set included 818 pharmaceutical and environmentally relevant compounds with fup values ranging from 0.01 to 1. Overall, the three QSPR models resulted in over-prediction of fup for highly binding compounds and under-prediction for low or moderately binding compounds. For highly binding compounds (0.01≤ fup ≤ 0.25), Watanabe et al. performed better with a lower mean absolute error (MAE) of 6.7% and a lower mean absolute relative prediction error (RPE) of 171.7 % than other methods. For low to moderately binding compounds, both Ingle et al. and ADMET Predictor performed better than Watanabe et al. with superior MAE and RPE values. The positive polar surface area, the number of basic functional groups and lipophilicity were the most important chemical descriptors for predicting fup. This study demonstrated that the prediction of fup was the most uncertain for highly binding compounds. This suggested that QSPR-predicted fup values should be used with caution in PBPK modeling.
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45
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Luijten M, Wackers PFK, Rorije E, Pennings JLA, Heusinkveld HJ. Relevance of In Vitro Transcriptomics for In Vivo Mode of Action Assessment. Chem Res Toxicol 2020; 34:452-459. [PMID: 33378166 DOI: 10.1021/acs.chemrestox.0c00313] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Recently, we reported an in vitro toxicogenomics comparison approach to categorize chemical substances according to similarities in their proposed toxicological modes of action. Use of such an approach for regulatory purposes requires, among others, insight into the extent of biological concordance between in vitro and in vivo findings. To that end, we applied the comparison approach to transcriptomics data from the Open TG-GATEs database for 137 substances with diverging modes of action and evaluated the outcomes obtained for rat primary hepatocytes and for rat liver. The results showed that a relatively small number of matches observed in vitro were also observed in vivo, whereas quite a large number of matches between substances were found to be relevant solely in vivo or in vitro. The latter could not be explained by physicochemical properties, leading to insufficient bioavailability or poor water solubility. Nevertheless, pathway analyses indicated that for relevant matches the mechanisms perturbed in vitro are consistent with those perturbed in vivo. These findings support the utility of the comparison approach as tool in mechanism-based risk assessment.
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Affiliation(s)
- Mirjam Luijten
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), 3720 BA Bilthoven, The Netherlands
| | - Paul F K Wackers
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), 3720 BA Bilthoven, The Netherlands
| | - Emiel Rorije
- Centre for Safety of Substances and Products, National Institute for Public Health and the Environment (RIVM), 3720 BA Bilthoven, The Netherlands
| | - Jeroen L A Pennings
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), 3720 BA Bilthoven, The Netherlands
| | - Harm J Heusinkveld
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), 3720 BA Bilthoven, The Netherlands
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46
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Pradeep P, Patlewicz G, Pearce R, Wambaugh J, Wetmore B, Judson R. Using Chemical Structure Information to Develop Predictive Models for In Vitro Toxicokinetic Parameters to Inform High-throughput Risk-assessment. ACTA ACUST UNITED AC 2020; 16. [PMID: 34124416 DOI: 10.1016/j.comtox.2020.100136] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The toxicokinetic (TK) parameters fraction of the chemical unbound to plasma proteins and metabolic clearance are critical for relating exposure and internal dose when building in vitro-based risk assessment models. However, experimental toxicokinetic studies have only been carried out on limited chemicals of environmental interest (~1000 chemicals with TK data relative to tens of thousands of chemicals of interest). This work evaluated the utility of chemical structure information to predict TK parameters in silico; development of cluster-based read-across and quantitative structure-activity relationship models of fraction unbound or fub (regression) and intrinsic clearance or Clint (classification and regression) using a dataset of 1487 chemicals; utilization of predicted TK parameters to estimate uncertainty in steady-state plasma concentration (Css); and subsequent in vitro-in vivo extrapolation analyses to derive bioactivity-exposure ratio (BER) plot to compare human oral equivalent doses and exposure predictions using androgen and estrogen receptor activity data for 233 chemicals as an example dataset. The results demonstrate that fub is structurally more predictable than Clint. The model with the highest observed performance for fub had an external test set RMSE/σ=0.62 and R2=0.61, for Clint classification had an external test set accuracy = 65.9%, and for intrinsic clearance regression had an external test set RMSE/σ=0.90 and R2=0.20. This relatively low performance is in part due to the large uncertainty in the underlying Clint data. We show that Css is relatively insensitive to uncertainty in Clint. The models were benchmarked against the ADMET Predictor software. Finally, the BER analysis allowed identification of 14 out of 136 chemicals for further risk assessment demonstrating the utility of these models in aiding risk-based chemical prioritization.
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Affiliation(s)
- Prachi Pradeep
- Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee.,Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
| | - Grace Patlewicz
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
| | - Robert Pearce
- Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee.,Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
| | - John Wambaugh
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
| | - Barbara Wetmore
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
| | - Richard Judson
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
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47
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Lewis RW, Hill T, Corton JC. A set of six Gene expression biomarkers and their thresholds identify rat liver tumorigens in short-term assays. Toxicology 2020; 443:152547. [PMID: 32755643 PMCID: PMC10439517 DOI: 10.1016/j.tox.2020.152547] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 07/23/2020] [Accepted: 07/28/2020] [Indexed: 02/01/2023]
Abstract
Traditional methods for cancer risk assessment are retrospective, resource-intensive, and not feasible for the vast majority of environmental chemicals. In earlier studies, we used a set of six biomarkers to accurately identify liver tumorigens in transcript profiles derived from chemically-treated rats using either a Toxicological Priority Index (ToxPi) approach or using derived biomarker thresholds for cancer. The biomarkers consisting of 7-113 genes are used to predict the most common liver cancer molecular initiating events: genotoxicity, cytotoxicity and activation of the xenobiotic receptors AhR, CAR, ER, and PPARα. In the present study, we apply and evaluate the performance of these methods for cancer prediction in an independent rat liver study of 44 chemicals (6 h-7d exposures) examined by Affymetrix arrays. In the first approach, ToxPi ranking of biomarker scores consistently gave the highest scores to tumorigenic chemical-dose pairs; balanced accuracies for identification of liver tumorigenic chemicals were up to 89 %. The second approach used tumorigenic thresholds derived in the present study or from our earlier study that were set at the maximum value for chemical-dose exposures without detectable liver tumor outcomes. Using these thresholds, balanced accuracies were up to 90 %. Both approaches identified all tumorigenic chemicals. Almost all of the tumorigenic chemicals activated more than one MIE. We also compared biomarker responses between two types of profiling platforms (Affymetrix full-genome array, TempO-Seq 1500+ array containing ∼2600 genes) and found that the lack of the full set of biomarker genes on the 1500+ array resulted in decreased ability to identify chemicals that activate the MIEs. Overall, these results demonstrate that predictive approaches based on the 6 biomarkers could be used in short-term assays to identify chemicals and their doses that induce liver tumors, the most common endpoint in rodent bioassays.
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Affiliation(s)
- Robert W Lewis
- Center for Computational Toxicology and Exposure, U.S. EPA, Research Triangle Park, NC, United States.
| | - Thomas Hill
- Center for Computational Toxicology and Exposure, U.S. EPA, Research Triangle Park, NC, United States; Oak Ridge Institute for Science and Education (ORISE) fellow Office of Research and Development, U.S. Environmental Protection Agency (EPA), Research Triangle Park, NC, United States.
| | - J Christopher Corton
- Center for Computational Toxicology and Exposure, U.S. EPA, Research Triangle Park, NC, United States.
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48
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Hill T, Rooney J, Abedini J, El-Masri H, Wood CE, Corton JC. Gene Expression Thresholds Derived From Short-term Exposures Identify Rat Liver Tumorigens. Toxicol Sci 2020; 177:41-59. [PMID: 32603419 DOI: 10.1093/toxsci/kfaa102] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Traditional methods for cancer risk assessment are resource-intensive, retrospective, and not feasible for the vast majority of environmental chemicals. In this study, we investigated whether quantitative genomic data from short-term studies may be used to set protective thresholds for potential tumorigenic effects. We hypothesized that gene expression biomarkers measuring activation of the key early events in established pathways for rodent liver cancer exhibit cross-chemical thresholds for tumorigenesis predictive for liver cancer risk. We defined biomarker thresholds for 6 major liver cancer pathways using training sets of chemicals with short-term genomic data (3-29 days of exposure) from the TG-GATES (n = 77 chemicals) and DrugMatrix (n = 86 chemicals) databases and then tested these thresholds within and between datasets. The 6 pathway biomarkers represented genotoxicity, cytotoxicity, and activation of xenobiotic, steroid, and lipid receptors (aryl hydrocarbon receptor, constitutive activated receptor, estrogen receptor, and peroxisome proliferator-activated receptor α). Thresholds were calculated as the maximum values derived from exposures without detectable liver tumor outcomes. We identified clear response values that were consistent across training and test sets. Thresholds derived from the TG-GATES training set were highly predictive (97%) in a test set of independent chemicals, whereas thresholds derived from the DrugMatrix study were 96%-97% predictive for the TG-GATES study. Threshold values derived from an abridged gene list (2/biomarker) also exhibited high predictive accuracy (91%-94%). These findings support the idea that early genomic changes can be used to establish threshold estimates or "molecular tipping points" that are predictive of later-life health outcomes.
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Affiliation(s)
- Thomas Hill
- Center for Computational Toxicology and Exposure.,Oak Ridge Institute for Science and Education (ORISE), NHEERL, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711
| | - John Rooney
- Center for Computational Toxicology and Exposure.,Oak Ridge Institute for Science and Education (ORISE), NHEERL, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711.,Integrated Laboratory Systems, Morrisville, North Carolina
| | - Jaleh Abedini
- Center for Computational Toxicology and Exposure.,Integrated Laboratory Systems, Morrisville, NC
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Chauhan V, Adam N, Kuo B, Williams A, Yauk CL, Wilkins R, Stainforth R. Meta-analysis of transcriptomic datasets using benchmark dose modeling shows value in supporting radiation risk assessment. Int J Radiat Biol 2020; 97:31-49. [PMID: 32687419 DOI: 10.1080/09553002.2020.1798543] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
PURPOSE Benchmark dose (BMD) modeling is used to determine the dose of a stressor at which a predefined increase in any biological effect above background occurs (e.g. 10% increase from control values). BMD analytical tools have the capacity to model transcriptional dose-response data to derive BMDs for genes, pathways and gene ontologies. We recently demonstrated the value of this approach to support various areas of radiation research using predominately 'in-house' generated datasets. MATERIALS AND METHODS As a continuation of this work, transcriptomic studies of relevance to ionizing radiation were retrieved through the Gene Expression Omnibus (GEO). The datasets were compiled and filtered, then analyzed using BMDExpress. The objective was to determine the reproducibility of BMD values in relation to pathways and genes across different exposure scenarios and compare to those derived using cytogenetic endpoints. A number of graphic visualization approaches were used to determine if BMD outputs could be correlated to parameters such as dose-rate, radiation quality and cell type. RESULTS Curated studies were diverse and derived from experiments with varied design and intent. Despite this, common genes and pathways were identified with low and high dose thresholds. The higher BMD values were associated with immune response and cell death, while transcripts with lower BMD values were generally related to the classic DNA damage response/repair processes, centered on TP53 signaling. Analysis of datasets with relatively similar dose-ranges under comparable experimental conditions showed a bi-modal distribution with a high degree of consistency in BMD values across shared genes and pathways, particularly for those below the 25th percentile of total distribution by dose. The median BMD values were noted to be approximately 0.5 Gy for genes/pathways that comprised mode 1. Furthermore, transcriptional BMD values derived from a subset of genes using in vivo and in vitro datasets were in accord to those using cytogenetic endpoints. CONCLUSION Overall, the results from this work highlight the value of the BMD methodology to derive meaningful outputs that are consistent across different models, provided the studies are conducted using a similar dose-range.
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Affiliation(s)
- Vinita Chauhan
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Nadine Adam
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Byron Kuo
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Carole L Yauk
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Ruth Wilkins
- Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
| | - Robert Stainforth
- Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada
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Escher BI, Henneberger L, König M, Schlichting R, Fischer FC. Cytotoxicity Burst? Differentiating Specific from Nonspecific Effects in Tox21 in Vitro Reporter Gene Assays. ENVIRONMENTAL HEALTH PERSPECTIVES 2020; 128:77007. [PMID: 32700975 PMCID: PMC7377237 DOI: 10.1289/ehp6664] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 06/16/2020] [Accepted: 07/02/2020] [Indexed: 05/03/2023]
Abstract
BACKGROUND High-throughput screening of chemicals with in vitro reporter gene assays in Tox21 has produced a large database on cytotoxicity and specific modes of action. However, the validity of some of the reported activities is questionable due to the "cytotoxicity burst," which refers to the supposition that many stress responses are activated in a nonspecific way at concentrations close to cell death. OBJECTIVES We propose a pragmatic method to identify whether reporter gene activation is specific or cytotoxicity-triggered by comparing the measured effects with baseline toxicity. METHODS Baseline toxicity, also termed narcosis, is the minimal toxicity any chemical causes. Quantitative structure-activity relationships (QSARs) developed for baseline toxicity in mammalian reporter gene cell lines served as anchors to define the chemical-specific threshold for the cytotoxicity burst and to evaluate the degree of specificity of the reporter gene activation. Measured 10% effect concentrations were related to measured or QSAR-predicted 10% cytotoxicity concentrations yielding specificity ratios (SR). We applied this approach to our own experimental data and to ∼ 8,000 chemicals that were tested in six of the high-throughput Tox21 reporter gene assays. RESULTS Confirmed baseline toxicants activated reporter gene activity around cytotoxic concentrations triggered by the cytotoxicity burst. In six Tox21 assays, 37%-87% of the active hits were presumably caused by the cytotoxicity burst (SR < 1 ) and only 2%-14% were specific with SR ≥ 10 against experimental cytotoxicity but 75%-97% were specific against baseline toxicity. This difference was caused by a large fraction of chemicals showing excess cytotoxicity. CONCLUSIONS The specificity analysis for measured in vitro effects identified whether a cytotoxicity burst had likely occurred. The SR-analysis not only prevented false positives, but it may also serve as measure for relative effect potency and can be used for quantitative in vitro-in vivo extrapolation and risk assessment of chemicals. https://doi.org/10.1289/EHP6664.
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Affiliation(s)
- Beate I. Escher
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
- Environmental Toxicology, Center for Applied Geoscience, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Luise Henneberger
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
| | - Maria König
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
| | - Rita Schlichting
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
| | - Fabian C. Fischer
- Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
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