1
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Bishop PL, Mansouri K, Eckel WP, Lowit MB, Allen D, Blankinship A, Lowit AB, Harwood DE, Johnson T, Kleinstreuer NC. Evaluation of in silico model predictions for mammalian acute oral toxicity and regulatory application in pesticide hazard and risk assessment. Regul Toxicol Pharmacol 2024; 149:105614. [PMID: 38574841 DOI: 10.1016/j.yrtph.2024.105614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 01/29/2024] [Accepted: 03/27/2024] [Indexed: 04/06/2024]
Abstract
The United States Environmental Protection Agency (USEPA) uses the lethal dose 50% (LD50) value from in vivo rat acute oral toxicity studies for pesticide product label precautionary statements and environmental risk assessment (RA). The Collaborative Acute Toxicity Modeling Suite (CATMoS) is a quantitative structure-activity relationship (QSAR)-based in silico approach to predict rat acute oral toxicity that has the potential to reduce animal use when registering a new pesticide technical grade active ingredient (TGAI). This analysis compared LD50 values predicted by CATMoS to empirical values from in vivo studies for the TGAIs of 177 conventional pesticides. The accuracy and reliability of the model predictions were assessed relative to the empirical data in terms of USEPA acute oral toxicity categories and discrete LD50 values for each chemical. CATMoS was most reliable at placing pesticide TGAIs in acute toxicity categories III (>500-5000 mg/kg) and IV (>5000 mg/kg), with 88% categorical concordance for 165 chemicals with empirical in vivo LD50 values ≥ 500 mg/kg. When considering an LD50 for RA, CATMoS predictions of 2000 mg/kg and higher were found to agree with empirical values from limit tests (i.e., single, high-dose tests) or definitive results over 2000 mg/kg with few exceptions.
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Affiliation(s)
- Patricia L Bishop
- Animal Research Issues, The Humane Society of the United States, Washington, DC, USA.
| | - Kamel Mansouri
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - William P Eckel
- US Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, USA
| | - Michael B Lowit
- US Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, USA
| | - David Allen
- Predictive Toxicology and Information Sciences Group, Discovery and Safety Assessment Division, Inotiv, Morrisville, NC, USA
| | - Amy Blankinship
- US Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, USA
| | - Anna B Lowit
- US Environmental Protection Agency, Office of Pollution Prevention and Toxics, Washington, DC, USA
| | - D Ethan Harwood
- US Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, USA
| | - Tamara Johnson
- US Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, USA
| | - Nicole C Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
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2
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van der Zalm AJ, Daniel AB, Raabe HA, Choksi N, Flint Silva T, Breeden-Alemi J, O'Dell L, Kleinstreuer NC, Lowit AB, Allen DG, Clippinger AJ. Defined approaches to classify agrochemical formulations into EPA hazard categories developed using EpiOcular TM reconstructed human corneal epithelium and bovine corneal opacity and permeability assays. Cutan Ocul Toxicol 2024; 43:58-68. [PMID: 37905558 DOI: 10.1080/15569527.2023.2275029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 10/20/2023] [Indexed: 11/02/2023]
Abstract
Many sectors have seen complete replacement of the in vivo rabbit eye test with reproducible and relevant in vitro and ex vivo methods to assess the eye corrosion/irritation potential of chemicals. However, the in vivo rabbit eye test remains the standard test used for agrochemical formulations in some countries. Therefore, two defined approaches (DAs) for assessing conventional agrochemical formulations were developed, using the EpiOcularTM Eye Irritation Test (EIT) [Organisation for Economic Co-operation and Development (OECD) test guideline (TG) 492] and the Bovine Corneal Opacity and Permeability (OECD TG 437; BCOP) test with histopathology. Presented here are the results from testing 29 agrochemical formulations, which were evaluated against the United States Environmental Protection Agency's (EPA) pesticide classification system, and assessed using orthogonal validation, rather than direct concordance analysis with the historical in vivo rabbit eye data. Scientific confidence was established by evaluating the methods and testing results using an established framework that considers fitness for purpose, human biological relevance, technical characterisation, data integrity and transparency, and independent review. The in vitro and ex vivo methods used in the DAs were demonstrated to be as or more fit for purpose, reliable and relevant than the in vivo rabbit eye test. Overall, there is high scientific confidence in the use of these DAs for assessing the eye corrosion/irritation potential of agrochemical formulations.
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Affiliation(s)
| | | | - Hans A Raabe
- Institute for In Vitro Sciences, Inc, Gaithersburg, MD, USA
| | | | - Tara Flint Silva
- US Environmental Protection Agency Office of Pesticide Programs, Washington, DC, USA
| | - Julie Breeden-Alemi
- US Environmental Protection Agency Office of Pesticide Programs, Washington, DC, USA
| | - Lindsay O'Dell
- US Environmental Protection Agency Office of Pollution Prevention and Toxics, Washington, DC, USA
| | - Nicole C Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, NC, USA
| | - Anna B Lowit
- US Environmental Protection Agency Office of Pollution Prevention and Toxics, Washington, DC, USA
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3
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Mansouri K, Moreira-Filho JT, Lowe CN, Charest N, Martin T, Tkachenko V, Judson R, Conway M, Kleinstreuer NC, Williams AJ. Free and open-source QSAR-ready workflow for automated standardization of chemical structures in support of QSAR modeling. J Cheminform 2024; 16:19. [PMID: 38378618 PMCID: PMC10880251 DOI: 10.1186/s13321-024-00814-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 02/10/2024] [Indexed: 02/22/2024] Open
Abstract
The rapid increase of publicly available chemical structures and associated experimental data presents a valuable opportunity to build robust QSAR models for applications in different fields. However, the common concern is the quality of both the chemical structure information and associated experimental data. This is especially true when those data are collected from multiple sources as chemical substance mappings can contain many duplicate structures and molecular inconsistencies. Such issues can impact the resulting molecular descriptors and their mappings to experimental data and, subsequently, the quality of the derived models in terms of accuracy, repeatability, and reliability. Herein we describe the development of an automated workflow to standardize chemical structures according to a set of standard rules and generate two and/or three-dimensional "QSAR-ready" forms prior to the calculation of molecular descriptors. The workflow was designed in the KNIME workflow environment and consists of three high-level steps. First, a structure encoding is read, and then the resulting in-memory representation is cross-referenced with any existing identifiers for consistency. Finally, the structure is standardized using a series of operations including desalting, stripping of stereochemistry (for two-dimensional structures), standardization of tautomers and nitro groups, valence correction, neutralization when possible, and then removal of duplicates. This workflow was initially developed to support collaborative modeling QSAR projects to ensure consistency of the results from the different participants. It was then updated and generalized for other modeling applications. This included modification of the "QSAR-ready" workflow to generate "MS-ready structures" to support the generation of substance mappings and searches for software applications related to non-targeted analysis mass spectrometry. Both QSAR and MS-ready workflows are freely available in KNIME, via standalone versions on GitHub, and as docker container resources for the scientific community. Scientific contribution: This work pioneers an automated workflow in KNIME, systematically standardizing chemical structures to ensure their readiness for QSAR modeling and broader scientific applications. By addressing data quality concerns through desalting, stereochemistry stripping, and normalization, it optimizes molecular descriptors' accuracy and reliability. The freely available resources in KNIME, GitHub, and docker containers democratize access, benefiting collaborative research and advancing diverse modeling endeavors in chemistry and mass spectrometry.
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Affiliation(s)
- Kamel Mansouri
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, USA.
| | - José T Moreira-Filho
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, USA
| | - Charles N Lowe
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Nathaniel Charest
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Todd Martin
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | | | - Richard Judson
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Mike Conway
- National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, USA
| | - Nicole C Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, USA
| | - Antony J Williams
- 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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4
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Balls M, Bass R, Curren R, Fentem J, Goldberg A, Hartung T, Herrmann K, Kleinstreuer NC, Libowitz L, Parascandola J, Rowan A, Spielmann H, Stephens ML, Thomas RS, Tsaioun K. 60 Years of the 3Rs symposium: Lessons learned and the road ahead. ALTEX 2024; 41:179-201. [PMID: 38629803 DOI: 10.14573/altex.2403061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Indexed: 04/19/2024]
Abstract
When The Principles of Humane Experimental Technique was published in 1959, authors William Russell and Rex Burch had a modest goal: to make researchers think about what they were doing in the laboratory - and to do it more humanely. Sixty years later, their groundbreaking book was celebrated for inspiring a revolution in science and launching a new field: The 3Rs of alternatives to animal experimentation. On November 22, 2019, some pioneering and leading scientists and researchers in the field gathered at the Johns Hopkins Bloomberg School of Public Health in Bal-timore for the 60 Years of the 3Rs Symposium: Lessons Learned and the Road Ahead. The event was sponsored by the Johns Hopkins Center for Alternatives to Animal Testing (CAAT), the Foundation for Chemistry Research and Initiatives, the Alternative Research & Development Foundation (ARDF), the American Cleaning Institute (ACI), the International Fragrance Association (IFRA), the Institute for In Vitro Sciences (IIVS), John "Jack" R. Fowle III, and the Society of Toxicology (SoT). Fourteen pres-entations shared the history behind the groundbreaking publication, international efforts to achieve its aims, stumbling blocks to progress, as well as remarkable achievements. The day was a tribute to Russell and Burch, and a testament to what is possible when people from many walks of life - science, government, and industry - work toward a common goal.
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Affiliation(s)
- Michael Balls
- Faculty of Medicine and Health Sciences, University of Nottingham, Medical School, Queen's Medical Centre, Nottingham, UK
| | - Rolf Bass
- Charité - University Medicine, Berlin, Germany
| | - Rodger Curren
- Institute for In Vitro Sciences, Gaithersburg, MD, USA
| | - Julia Fentem
- Unilever Safety and Environmental Assurance Centre (SEAC), Colworth Science Park, Bedfordshire, UK
| | - Alan Goldberg
- Center for Alternatives to Animal Testing (CAAT), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Thomas Hartung
- Center for Alternatives to Animal Testing (CAAT), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
- Doerenkamp-Zbinden-Chair for Evidence-based Toxicology, Baltimore, MD, USA
- CAAT-Europe, University of Konstanz, Konstanz, Germany
| | - Kathrin Herrmann
- Center for Alternatives to Animal Testing (CAAT), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Nicole C Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | | | | | | | - Horst Spielmann
- Institut für Pharmazie, Freie Universität Berlin, Berlin, Germany
| | - Martin L Stephens
- Center for Alternatives to Animal Testing (CAAT), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Russell S Thomas
- Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Katya Tsaioun
- Center for Alternatives to Animal Testing (CAAT), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
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5
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Strickland J, Abedini J, Allen DG, Gordon J, Hull V, Kleinstreuer NC, Ko HS, Matheson J, Thierse HJ, Truax J, Vanselow JT, Herzler M. A database of human predictive patch test data for skin sensitization. Arch Toxicol 2023; 97:2825-2837. [PMID: 37615678 PMCID: PMC10504114 DOI: 10.1007/s00204-023-03530-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 05/24/2023] [Indexed: 08/25/2023]
Abstract
Critical to the evaluation of non-animal tests are reference data with which to assess their relevance. Animal data are typically used because they are generally standardized and available. However, when regulatory agencies aim to protect human health, human reference data provide the benefit of not having to account for possible interspecies variability. To support the evaluation of non-animal approaches for skin sensitization assessment, we collected data from 2277 human predictive patch tests (HPPTs), i.e., human repeat insult patch tests and human maximization tests, for skin sensitization from 1555 publications. We recorded protocol elements and positive or negative outcomes, developed a scoring system to evaluate each test for reliability, and calculated traditional and non-traditional dose metrics. We also traced each test result back to its original report to remove duplicates. The resulting database, which contains information for 1366 unique substances, was characterized for physicochemical properties, chemical structure categories, and protein binding mechanisms. This database is publicly available on the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods website and in the Integrated Chemical Environment to serve as a resource for additional evaluation of alternative methods and development of new approach methodologies for skin sensitization assessments.
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Affiliation(s)
| | | | | | - John Gordon
- United States Consumer Product Safety Commission, Bethesda, MD, USA
| | | | - Nicole C Kleinstreuer
- National Institutes of Health, National Institute of Environmental Health Sciences, Division of Translational Toxicology, National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Research Triangle Park, NC, USA
| | - Hon-Sum Ko
- United States Food and Drug Administration, Silver Spring, MD, USA
| | - Joanna Matheson
- United States Consumer Product Safety Commission, Bethesda, MD, USA
| | | | | | - Jens T Vanselow
- German Federal Institute for Risk Assessment (BfR), Berlin, Germany
| | - Matthias Herzler
- German Federal Institute for Risk Assessment (BfR), Berlin, Germany
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6
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Jordan R, Ford-Scheimer SL, Alarcon RM, Atala A, Borenstein JT, Brimacombe KR, Cherry S, Clevers H, Davis MI, Funnell SGP, Gehrke L, Griffith LG, Grossman AC, Hartung T, Ingber DE, Kleinstreuer NC, Kuo CJ, Lee EM, Mummery CL, Pickett TE, Ramani S, Rosado-Olivieri EA, Struble EB, Wan Z, Williams MS, Hall MD, Ferrer M, Markossian S. Report of the Assay Guidance Workshop on 3-Dimensional Tissue Models for Antiviral Drug Development. J Infect Dis 2023; 228:S337-S354. [PMID: 37669225 PMCID: PMC10547463 DOI: 10.1093/infdis/jiad334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/07/2023] Open
Abstract
The National Center for Advancing Translational Sciences (NCATS) Assay Guidance Manual (AGM) Workshop on 3D Tissue Models for Antiviral Drug Development, held virtually on 7-8 June 2022, provided comprehensive coverage of critical concepts intended to help scientists establish robust, reproducible, and scalable 3D tissue models to study viruses with pandemic potential. This workshop was organized by NCATS, the National Institute of Allergy and Infectious Diseases, and the Bill and Melinda Gates Foundation. During the workshop, scientific experts from academia, industry, and government provided an overview of 3D tissue models' utility and limitations, use of existing 3D tissue models for antiviral drug development, practical advice, best practices, and case studies about the application of available 3D tissue models to infectious disease modeling. This report includes a summary of each workshop session as well as a discussion of perspectives and challenges related to the use of 3D tissues in antiviral drug discovery.
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Affiliation(s)
- Robert Jordan
- Bill and Melinda Gates Foundation, Seattle, Washington, USA
| | - Stephanie L Ford-Scheimer
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Rodolfo M Alarcon
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Anthony Atala
- Wake Forest Institute for Regenerative Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | | | - Kyle R Brimacombe
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Sara Cherry
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - Mindy I Davis
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Simon G P Funnell
- UK Health Security Agency, Salisbury, United Kingdom
- Quadram Institute Bioscience, Norwich, United Kingdom
| | - Lee Gehrke
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Linda G Griffith
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Abigail C Grossman
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Thomas Hartung
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Donald E Ingber
- Harvard Medical School, Boston, Massachusetts, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA
- Harvard School of Engineering and Applied Sciences, Cambridge, Massachusetts, USA
- Boston Children's Hospital, Boston, Massachusetts, USA
| | - Nicole C Kleinstreuer
- National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle, North Carolina, USA
| | - Calvin J Kuo
- Department of Medicine, Division of Hematology, Stanford University School of Medicine, Stanford, California, USA
| | - Emily M Lee
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | | | - Thames E Pickett
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Sasirekha Ramani
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas, USA
| | | | - Evi B Struble
- US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Zhengpeng Wan
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Mark S Williams
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Matthew D Hall
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Marc Ferrer
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Sarine Markossian
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
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7
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Salminen AT, Davis KJ, Felton RP, Nischal N, VonTungeln LS, Beland FA, Derr K, Brown PC, Ferrer M, Katz LM, Kleinstreuer NC, Leshin J, Manga P, Sadrieh N, Xia M, Fitzpatrick SC, Camacho L. Parallel evaluation of alternative skin barrier models and excised human skin for dermal absorption studies in vitro. Toxicol In Vitro 2023; 91:105630. [PMID: 37315744 PMCID: PMC10527924 DOI: 10.1016/j.tiv.2023.105630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 05/24/2023] [Accepted: 06/09/2023] [Indexed: 06/16/2023]
Abstract
Skin permeation is a primary consideration in the safety assessment of cosmetic ingredients, topical drugs, and human users handling veterinary medicinal products. While excised human skin (EHS) remains the 'gold standard' for in vitro permeation testing (IVPT) studies, unreliable supply and high cost motivate the search for alternative skin barrier models. In this study, a standardized dermal absorption testing protocol was developed to evaluate the suitability of alternative skin barrier models to predict skin absorption in humans. Under this protocol, side-by-side assessments of a commercially available reconstructed human epidermis (RhE) model (EpiDerm-200-X, MatTek), a synthetic barrier membrane (Strat-M, Sigma-Aldrich), and EHS were performed. The skin barrier models were mounted on Franz diffusion cells and the permeation of caffeine, salicylic acid, and testosterone was quantified. Transepidermal water loss (TEWL) and histology of the biological models were also compared. EpiDerm-200-X exhibited native human epidermis-like morphology, including a characteristic stratum corneum, but had an elevated TEWL as compared to EHS. The mean 6 h cumulative permeation of a finite dose (6 nmol/cm2) of caffeine and testosterone was highest in EpiDerm-200-X, followed by EHS and Strat-M. Salicylic acid permeated most in EHS, followed by EpiDerm-200-X and Strat-M. Overall, evaluating novel alternative skin barrier models in the manner outlined herein has the potential to reduce the time from basic science discovery to regulatory impact.
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Affiliation(s)
- Alec T Salminen
- Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
| | - Kelly J Davis
- Toxicologic Pathology Associates, Jefferson, AR, USA
| | - Robert P Felton
- Office of Scientific Coordination, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
| | - Nathania Nischal
- Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
| | - Linda S VonTungeln
- Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
| | - Frederick A Beland
- Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA
| | - Kristy Derr
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, USA
| | - Paul C Brown
- Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA
| | - Marc Ferrer
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, USA
| | - Linda M Katz
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, College Park, MD, USA
| | - Nicole C Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Jonathan Leshin
- Center for Veterinary Medicine, U.S. Food and Drug Administration, Rockville, MD, USA
| | - Prashiela Manga
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, College Park, MD, USA
| | - Nakissa Sadrieh
- Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA
| | - Menghang Xia
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, USA
| | - Suzanne C Fitzpatrick
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, College Park, MD, USA
| | - Luísa Camacho
- Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, USA.
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8
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Strickland J, Haugabrooks E, Allen DG, Balottin LB, Hirabayashi Y, Kleinstreuer NC, Kojima H, Nishizawa C, Prieto P, Ratzlaff DE, Jeong J, Lee J, Yang Y, Lin P, Sullivan K, Casey W. International regulatory uses of acute systemic toxicity data and integration of new approach methodologies. Crit Rev Toxicol 2023; 53:385-411. [PMID: 37646804 PMCID: PMC10592330 DOI: 10.1080/10408444.2023.2240852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/17/2023] [Accepted: 07/17/2023] [Indexed: 09/01/2023]
Abstract
Chemical regulatory authorities around the world require systemic toxicity data from acute exposures via the oral, dermal, and inhalation routes for human health risk assessment. To identify opportunities for regulatory uses of non-animal replacements for these tests, we reviewed acute systemic toxicity testing requirements for jurisdictions that participate in the International Cooperation on Alternative Test Methods (ICATM): Brazil, Canada, China, the European Union, Japan, South Korea, Taiwan, and the USA. The chemical sectors included in our review of each jurisdiction were cosmetics, consumer products, industrial chemicals, pharmaceuticals, medical devices, and pesticides. We found acute systemic toxicity data were most often required for hazard assessment, classification, and labeling, and to a lesser extent quantitative risk assessment. Where animal methods were required, animal reduction methods were typically recommended. For many jurisdictions and chemical sectors, non-animal alternatives are not accepted, but several jurisdictions provide guidance to support the use of test waivers to reduce animal use for specific applications. An understanding of international regulatory requirements for acute systemic toxicity testing will inform ICATM's strategy for the development, acceptance, and implementation of non-animal alternatives to assess the health hazards and risks associated with acute toxicity.
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Affiliation(s)
- Judy Strickland
- Inotiv, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA
| | - Esther Haugabrooks
- Physicians Committee for Responsible Medicine, 5100 Wisconsin Ave., NW, Suite 400, Washington, DC 20016, USA
| | - David G. Allen
- Inotiv, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA
| | - Luciene B. Balottin
- National Institute of Metrology, Quality and Technology (INMETRO), Av. Nossa Senhora das Graças, no. 50, 22250-020, Duque de Caxias, RJ, Brazil
| | - Yoko Hirabayashi
- Center for Biological Safety and Research, National Institute of Health Sciences, 3-25-26 Tonomachi, Kawasaki-ku, Kawasaki 210-9501, Japan
| | - Nicole C. Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Division of Translational Toxicology, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, USA
| | - Hajime Kojima
- Japanese Center for the Validation of Alternative Methods, National Institute of Health Sciences, 3-25-26 Tonomachi, Kawasaki-ku, Kawasaki 210-9501, Japan
| | - Claudio Nishizawa
- Brazilian Health Regulatory Agency (ANVISA), Setor de Indústria e Abastecimento (SIA) - Trecho 5, Área Especial 57, Lote 200, 71205-050 - Brasilia /DF, Brazil
| | - Pilar Prieto
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Deborah E. Ratzlaff
- New Substances Assessment and Control Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, K1A 0K9 Canada
| | - Jayoung Jeong
- Toxicological Evaluation and Research Department, National Institute of Food and Drug Safety Evaluation, 187 Osongsaengmyeong 2(i)-ro, Osong-eup, Heungdoek-gu, Cheongju-si, Chungcheongbuk-do, 28159, Korea
| | - JinHee Lee
- Toxicological Evaluation and Research Department, National Institute of Food and Drug Safety Evaluation, 187 Osongsaengmyeong 2(i)-ro, Osong-eup, Heungdoek-gu, Cheongju-si, Chungcheongbuk-do, 28159, Korea
| | - Ying Yang
- Guangdong Provincial Center for Disease Control and Prevention, Qunxian Road 160, Panyu strict, Guangzhou, China 510430
| | - Pinpin Lin
- National Health Research Institutes, No. 35, Keyan Road, Zhunan Town, Miaoli County 350, Taiwan
| | - Kristie Sullivan
- Physicians Committee for Responsible Medicine, 5100 Wisconsin Ave., NW, Suite 400, Washington, DC 20016, USA
| | - Warren Casey
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Division of Translational Toxicology, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, USA
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9
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Borrel A, Conway M, Nolte SZ, Unnikrishnan A, Schmitt CP, Kleinstreuer NC. ChemMaps.com v2.0: exploring the environmental chemical universe. Nucleic Acids Res 2023:7167306. [PMID: 37194699 DOI: 10.1093/nar/gkad380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 04/24/2023] [Accepted: 05/01/2023] [Indexed: 05/18/2023] Open
Abstract
Access to computationally based visualization tools to navigate chemical space has become more important due to the increasing size and diversity of publicly accessible databases, associated compendiums of high-throughput screening (HTS) results, and other descriptor and effects data. However, application of these techniques requires advanced programming skills that are beyond the capabilities of many stakeholders. Here we report the development of the second version of the ChemMaps.com webserver (https://sandbox.ntp.niehs.nih.gov/chemmaps/) focused on environmental chemical space. The chemical space of ChemMaps.com v2.0, released in 2022, now includes approximately one million environmental chemicals from the EPA Distributed Structure-Searchable Toxicity (DSSTox) inventory. ChemMaps.com v2.0 incorporates mapping of HTS assay data from the U.S. federal Tox21 research collaboration program, which includes results from around 2000 assays tested on up to 10 000 chemicals. As a case example, we showcased chemical space navigation for Perfluorooctanoic Acid (PFOA), part of the Per- and polyfluoroalkyl substances (PFAS) chemical family, which are of significant concern for their potential effects on human health and the environment.
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10
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Eccles KM, Karmaus AL, Kleinstreuer NC, Parham F, Rider CV, Wambaugh JF, Messier KP. A geospatial modeling approach to quantifying the risk of exposure to environmental chemical mixtures via a common molecular target. Sci Total Environ 2023; 855:158905. [PMID: 36152849 PMCID: PMC9979101 DOI: 10.1016/j.scitotenv.2022.158905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 09/09/2022] [Accepted: 09/17/2022] [Indexed: 05/14/2023]
Abstract
In the real world, individuals are exposed to chemicals from sources that vary over space and time. However, traditional risk assessments based on in vivo animal studies typically use a chemical-by-chemical approach and apical disease endpoints. New approach methodologies (NAMs) in toxicology, such as in vitro high-throughput (HTS) assays generated in Tox21 and ToxCast, can more readily provide mechanistic chemical hazard information for chemicals with no existing data than in vivo methods. In this paper, we establish a workflow to assess the joint action of 41 modeled ambient chemical exposures in the air from the USA-wide National Air Toxics Assessment by integrating human exposures with hazard data from curated HTS (cHTS) assays to identify counties where exposure to the local chemical mixture may perturb a common biological target. We exemplify this proof-of-concept using CYP1A1 mRNA up-regulation. We first estimate internal exposure and then convert the inhaled concentration to a steady state plasma concentration using physiologically based toxicokinetic modeling parameterized with county-specific information on ages and body weights. We then use the estimated blood plasma concentration and the concentration-response curve from the in vitro cHTS assay to determine the chemical-specific effects of the mixture components. Three mixture modeling methods were used to estimate the joint effect from exposure to the chemical mixture on the activity levels, which were geospatially mapped. Finally, a Monte Carlo uncertainty analysis was performed to quantify the influence of each parameter on the combined effects. This workflow demonstrates how NAMs can be used to predict early-stage biological perturbations that can lead to adverse health outcomes that result from exposure to chemical mixtures. As a result, this work will advance mixture risk assessment and other early events in the effects of chemicals.
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Affiliation(s)
- Kristin M Eccles
- National Institute of Environmental Health Science, Division of the Translational Toxicology, Durham, USA
| | - Agnes L Karmaus
- Integrated Laboratory Systems, an Inotiv Company, Morrisville, NC, USA
| | - Nicole C Kleinstreuer
- National Institute of Environmental Health Science, Division of the Translational Toxicology, Durham, USA
| | - Fred Parham
- National Institute of Environmental Health Science, Division of the Translational Toxicology, Durham, USA
| | - Cynthia V Rider
- National Institute of Environmental Health Science, Division of the Translational Toxicology, Durham, USA
| | - John F Wambaugh
- United States Environmental Protection Agency, Center for Computational Toxicology and Exposure, Durham, USA
| | - Kyle P Messier
- National Institute of Environmental Health Science, Division of the Translational Toxicology, Durham, USA.
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11
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Pierro JD, Ahir BK, Baker NC, Kleinstreuer NC, Xia M, Knudsen TB. Computational model for fetal skeletal defects potentially linked to disruption of retinoic acid signaling. Front Pharmacol 2022; 13:971296. [PMID: 36172177 PMCID: PMC9511990 DOI: 10.3389/fphar.2022.971296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 07/21/2022] [Indexed: 11/13/2022] Open
Abstract
All-trans retinoic acid (ATRA) gradients determine skeletal patterning morphogenesis and can be disrupted by diverse genetic or environmental factors during pregnancy, leading to fetal skeleton defects. Adverse Outcome Pathway (AOP) frameworks for ATRA metabolism, signaling, and homeostasis allow for the development of new approach methods (NAMs) for predictive toxicology with less reliance on animal testing. Here, a data-driven model was constructed to identify chemicals associated with both ATRA pathway bioactivity and prenatal skeletal defects. The phenotype data was culled from ToxRefDB prenatal developmental toxicity studies and produced a list of 363 ToxRefDB chemicals with altered skeletal observations. Defects were classified regionally as cranial, post-cranial axial, appendicular, and other (unspecified) features based on ToxRefDB descriptors. To build a multivariate statistical model, high-throughput screening bioactivity data from >8,070 chemicals in ToxCast/Tox21 across 10 in vitro assays relevant to the retinoid signaling system were evaluated and compared to literature-based candidate reference chemicals in the dataset. There were 48 chemicals identified for effects on both in vivo skeletal defects and in vitro ATRA pathway targets for computational modeling. The list included 28 chemicals with prior evidence of skeletal defects linked to retinoid toxicity and 20 chemicals without prior evidence. The combination of thoracic cage defects and DR5 (direct repeats of 5 nucleotides for RAR/RXR transactivation) disruption was the most frequently occurring phenotypic and target disturbance, respectively. This data model provides valuable AOP elucidation and validates current mechanistic understanding. These findings also shed light on potential avenues for new mechanistic discoveries related to ATRA pathway disruption and associated skeletal dysmorphogenesis due to environmental exposures.
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Affiliation(s)
- Jocylin D. Pierro
- Center for Computational Toxicology and Exposure (CCTE), Computational Toxicology and Bioinformatics Branch (CTBB), Office of Research and Development (ORD), U.S. Environmental Protection Agency (USEPA), Research Triangle Park, NC, United States
| | - Bhavesh K. Ahir
- Eurofins Medical Device Testing, Lancaster, PA, United States
| | - Nancy C. Baker
- Scientific Computing and Data Curation Division (SCDCD), Leidos Contractor, Center for Computational Toxicology and Exposure (CCTE), USEPA/ORD, Research Triangle Park, NC, United States
| | - Nicole C. Kleinstreuer
- Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM), National Toxicology Program, National Institutes of Health, Research Triangle Park, NC, United States
| | - Menghang Xia
- Division for Pre-Clinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, United States
| | - Thomas B. Knudsen
- Center for Computational Toxicology and Exposure (CCTE), Computational Toxicology and Bioinformatics Branch (CTBB), Office of Research and Development (ORD), U.S. Environmental Protection Agency (USEPA), Research Triangle Park, NC, United States
- *Correspondence: Thomas B. Knudsen, , orcid.org/0000-0002-5036-596x
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12
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van der Zalm AJ, Barroso J, Browne P, Casey W, Gordon J, Henry TR, Kleinstreuer NC, Lowit AB, Perron M, Clippinger AJ. A framework for establishing scientific confidence in new approach methodologies. Arch Toxicol 2022; 96:2865-2879. [PMID: 35987941 PMCID: PMC9525335 DOI: 10.1007/s00204-022-03365-4] [Citation(s) in RCA: 55] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 08/11/2022] [Indexed: 12/28/2022]
Abstract
Robust and efficient processes are needed to establish scientific confidence in new approach methodologies (NAMs) if they are to be considered for regulatory applications. NAMs need to be fit for purpose, reliable and, for the assessment of human health effects, provide information relevant to human biology. They must also be independently reviewed and transparently communicated. Ideally, NAM developers should communicate with stakeholders such as regulators and industry to identify the question(s), and specified purpose that the NAM is intended to address, and the context in which it will be used. Assessment of the biological relevance of the NAM should focus on its alignment with human biology, mechanistic understanding, and ability to provide information that leads to health protective decisions, rather than solely comparing NAM-based chemical testing results with those from traditional animal test methods. However, when NAM results are compared to historical animal test results, the variability observed within animal test method results should be used to inform performance benchmarks. Building on previous efforts, this paper proposes a framework comprising five essential elements to establish scientific confidence in NAMs for regulatory use: fitness for purpose, human biological relevance, technical characterization, data integrity and transparency, and independent review. Universal uptake of this framework would facilitate the timely development and use of NAMs by the international community. While this paper focuses on NAMs for assessing human health effects of pesticides and industrial chemicals, many of the suggested elements are expected to apply to other types of chemicals and to ecotoxicological effect assessments.
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Affiliation(s)
| | - João Barroso
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Patience Browne
- Organisation for Economic Co-Operation and Development, Hazard Assessment and Pesticides Programmes, Environmental Directorate, Paris, France
| | - Warren Casey
- National Institutes of Health, Division of the National Toxicology Program, National Institutes of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - John Gordon
- U.S. Consumer Product Safety Commission, Directorate for Health Sciences, Rockville, MD, USA
| | - Tala R Henry
- U.S. Environmental Protection Agency, Office of Pollution Prevention and Toxics, Washington, DC, USA
| | - Nicole C Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Research Triangle Park, NC, USA
| | - Anna B Lowit
- U.S. Environmental Protection Agency, Office of Pollution Prevention and Toxics, Washington, DC, USA
| | - Monique Perron
- U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, USA
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13
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Petersen EJ, Elliott JT, Gordon J, Kleinstreuer NC, Reinke E, Roesslein M, Toman B. Technical framework for enabling high quality measurements in new approach methodologies (NAMs). ALTEX 2022; 40:174-186. [PMID: 35867862 DOI: 10.14573/altex.2205081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 07/12/2022] [Indexed: 01/20/2023]
Abstract
New approach methodologies (NAMs) are in vitro, in chemico, and in silico or computational approaches that can potentially be used to reduce animal testing. For NAMs that require laboratory experiments, it is critical that they provide consistent and reliable results. While guidance has been provided on improving the reproducibility of NAMs that require laboratory experiments, there is not yet an overarching technical framework that details how to add measurement quality features into a protocol. In this manuscript, we discuss such a framework and provide a step-by-step process describing how to refine a protocol using basic quality tools. The steps in this framework include 1) conceptual analysis of sources of technical variability in the assay, 2) within-laboratory evaluation of assay performance, 3) statistical data analysis, and 4) determination of method transferability (if needed). While each of these steps has discrete components, they are all inter-related, and insights from any step can influence the others. Following the steps in this framework can help reveal the advantages and limitations of different choices during the design of an assay such as which in-process control measurements to include and how many replicates to use for each control measurement and for each test substance. Overall, the use of this technical framework can support optimizing NAM reproducibility, thereby supporting meeting research and regulatory needs.
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Affiliation(s)
- Elijah J Petersen
- National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA
| | - John T Elliott
- National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA
| | - John Gordon
- US Consumer Product Safety Commission, Rockville, MD, USA.
| | - Nicole C Kleinstreuer
- National Institute of Environmental Health Sciences, National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Research Triangle Park, NC, USA
| | - Emily Reinke
- U.S. Army Public Health Center, Aberdeen Proving Ground, MD, USA
| | - Mattias Roesslein
- Empa, Swiss Federal Laboratories for Material Testing and Research, Particles-Biology Interactions Laboratory, St. Gallen, Switzerland
| | - Blaza Toman
- National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA
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14
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Sedykh A, Choksi NY, Allen DG, Casey WM, Shah R, Kleinstreuer NC. Mixtures-Inclusive In Silico Models of Ocular Toxicity Based on United States and International Hazard Categories. Chem Res Toxicol 2022; 35:992-1000. [PMID: 35549170 DOI: 10.1021/acs.chemrestox.1c00443] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Computational modeling grounded in reliable experimental data can help design effective non-animal approaches to predict the eye irritation and corrosion potential of chemicals. The National Toxicology Program (NTP) Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM) has compiled and curated a database of in vivo eye irritation studies from the scientific literature and from stakeholder-provided data. The database contains 810 annotated records of 593 unique substances, including mixtures, categorized according to UN GHS and US EPA hazard classifications. This study reports a set of in silico models to predict EPA and GHS hazard classifications for chemicals and mixtures, accounting for purity by setting thresholds of 100% and 10% concentration. We used two approaches to predict classification of mixtures: conventional and mixture-based. Conventional models evaluated substances based on the chemical structure of its major component. These models achieved balanced accuracy in the range of 68-80% and 87-96% for the 100% and 10% test concentration thresholds, respectively. Mixture-based models, which accounted for all known components in the substance by weighted feature averaging, showed similar or slightly higher accuracy of 72-79% and 89-94% for the respective thresholds. We also noted a strong trend between the pH feature metric calculated for each substance and its activity. Across all the models, the calculated pH of inactive substances was within one log10 unit of neutral pH, on average, while for active substances, pH varied from neutral by at least 2 log10 units. This pH dependency is especially important for complex mixtures. Additional evaluation on an external test set of 673 substances obtained from ECHA dossiers achieved balanced accuracies of 64-71%, which suggests that these models can be useful in screening compounds for ocular irritation potential. Negative predictive value was particularly high and indicates the potential application of these models in a bottom-up approach to identify nonirritant substances.
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Affiliation(s)
- Alexander Sedykh
- Sciome LLC, 1920 E NC 54 Hwy, Suite 510, Durham, North Carolina 27713, United States
| | - Neepa Y Choksi
- Integrated Laboratory Systems Inc, 601 Keystone Park Drive, Suite 200, Morrisville, North Carolina 27560, United States
| | - David G Allen
- Integrated Laboratory Systems Inc, 601 Keystone Park Drive, Suite 200, Morrisville, North Carolina 27560, United States
| | - Warren M Casey
- NIH/NIEHS/DNTP/NICEATM, 530 Davis Drive, Morrisville, North Carolina 27560, United States
| | - Ruchir Shah
- Sciome LLC, 1920 E NC 54 Hwy, Suite 510, Durham, North Carolina 27713, United States
| | - Nicole C Kleinstreuer
- NIH/NIEHS/DNTP/NICEATM, 530 Davis Drive, Morrisville, North Carolina 27560, United States
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15
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Carlson JM, Janulewicz PA, Kleinstreuer NC, Heiger-Bernays W. Impact of High-Throughput Model Parameterization and Data Uncertainty on Thyroid-Based Toxicological Estimates for Pesticide Chemicals. Environ Sci Technol 2022; 56:5620-5631. [PMID: 35446564 PMCID: PMC9070357 DOI: 10.1021/acs.est.1c07143] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 03/30/2022] [Accepted: 03/31/2022] [Indexed: 05/23/2023]
Abstract
Chemical-induced alteration of maternal thyroid hormone levels may increase the risk of adverse neurodevelopmental outcomes in offspring. US federal risk assessments rely almost exclusively on apical endpoints in animal models for deriving points of departure (PODs). New approach methodologies (NAMs) such as high-throughput screening (HTS) and mechanistically informative in vitro human cell-based systems, combined with in vitro to in vivo extrapolation (IVIVE), supplement in vivo studies and provide an alternative approach to calculate/determine PODs. We examine how parameterization of IVIVE models impacts the comparison between IVIVE-derived equivalent administered doses (EADs) from thyroid-relevant in vitro assays and the POD values that serve as the basis for risk assessments. Pesticide chemicals with thyroid-based in vitro bioactivity data from the US Tox21 HTS program were included (n = 45). Depending on the model structure used for IVIVE analysis, up to 35 chemicals produced EAD values lower than the POD. A total of 10 chemicals produced EAD values higher than the POD regardless of the model structure. The relationship between IVIVE-derived EAD values and the in vivo-derived POD values is highly dependent on model parameterization. Here, we derive a range of potentially thyroid-relevant doses that incorporate uncertainty in modeling choices and in vitro assay data.
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Affiliation(s)
- Jeffrey M. Carlson
- Environmental
Health Department, Boston University School
of Public Health, 715 Albany Street, Boston, Massachusetts 02118, United States
| | - Patricia A. Janulewicz
- Environmental
Health Department, Boston University School
of Public Health, 715 Albany Street, Boston, Massachusetts 02118, United States
| | - Nicole C. Kleinstreuer
- Division
of Intramural Research, Biostatistics and Computational Biology Branch,
and National Toxicology Program Interagency Center for the Evaluation
of Alternative Toxicological Methods, National
Institute of Environmental Health Sciences, 111 T.W. Alexander Drive, Durham, North Carolina 27709, United States
| | - Wendy Heiger-Bernays
- Environmental
Health Department, Boston University School
of Public Health, 715 Albany Street, Boston, Massachusetts 02118, United States
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16
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Chang X, Tan YM, Allen DG, Bell S, Brown PC, Browning L, Ceger P, Gearhart J, Hakkinen PJ, Kabadi SV, Kleinstreuer NC, Lumen A, Matheson J, Paini A, Pangburn HA, Petersen EJ, Reinke EN, Ribeiro AJS, Sipes N, Sweeney LM, Wambaugh JF, Wange R, Wetmore BA, Mumtaz M. IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making. Toxics 2022; 10:232. [PMID: 35622645 PMCID: PMC9143724 DOI: 10.3390/toxics10050232] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 04/24/2022] [Indexed: 02/04/2023]
Abstract
During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.
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Affiliation(s)
- Xiaoqing Chang
- Inotiv-RTP, 601 Keystone Park Drive, Suite 200, Morrisville, NC 27560, USA; (X.C.); (D.G.A.); (S.B.); (L.B.); (P.C.)
| | - Yu-Mei Tan
- U.S. Environmental Protection Agency, Office of Pesticide Programs, 109 T.W. Alexander Drive, Durham, NC 27709, USA;
| | - David G. Allen
- Inotiv-RTP, 601 Keystone Park Drive, Suite 200, Morrisville, NC 27560, USA; (X.C.); (D.G.A.); (S.B.); (L.B.); (P.C.)
| | - Shannon Bell
- Inotiv-RTP, 601 Keystone Park Drive, Suite 200, Morrisville, NC 27560, USA; (X.C.); (D.G.A.); (S.B.); (L.B.); (P.C.)
| | - Paul C. Brown
- U.S. Food and Drug Administration, Center for Drug Evaluation and Research, 10903 New Hampshire Avenue, Silver Spring, MD 20903, USA; (P.C.B.); (A.J.S.R.); (R.W.)
| | - Lauren Browning
- Inotiv-RTP, 601 Keystone Park Drive, Suite 200, Morrisville, NC 27560, USA; (X.C.); (D.G.A.); (S.B.); (L.B.); (P.C.)
| | - Patricia Ceger
- Inotiv-RTP, 601 Keystone Park Drive, Suite 200, Morrisville, NC 27560, USA; (X.C.); (D.G.A.); (S.B.); (L.B.); (P.C.)
| | - Jeffery Gearhart
- The Henry M. Jackson Foundation, Air Force Research Laboratory, 711 Human Performance Wing, Wright-Patterson Air Force Base, OH 45433, USA;
| | - Pertti J. Hakkinen
- National Library of Medicine, National Center for Biotechnology Information, 8600 Rockville Pike, Bethesda, MD 20894, USA;
| | - Shruti V. Kabadi
- U.S. Food and Drug Administration, Center for Food Safety and Applied Nutrition, Office of Food Additive Safety, 5001 Campus Drive, HFS-275, College Park, MD 20740, USA;
| | - Nicole C. Kleinstreuer
- National Institute of Environmental Health Sciences, National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, P.O. Box 12233, Research Triangle Park, NC 27709, USA;
| | - Annie Lumen
- U.S. Food and Drug Administration, National Center for Toxicological Research, 3900 NCTR Road, Jefferson, AR 72079, USA;
| | - Joanna Matheson
- U.S. Consumer Product Safety Commission, Division of Toxicology and Risk Assessment, 5 Research Place, Rockville, MD 20850, USA;
| | - Alicia Paini
- European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy;
| | - Heather A. Pangburn
- Air Force Research Laboratory, 711 Human Performance Wing, 2729 R Street, Area B, Building 837, Wright-Patterson Air Force Base, OH 45433, USA;
| | - Elijah J. Petersen
- U.S. Department of Commerce, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD 20899, USA;
| | - Emily N. Reinke
- U.S. Army Public Health Center, 8252 Blackhawk Rd., Aberdeen Proving Ground, MD 21010, USA;
| | - Alexandre J. S. Ribeiro
- U.S. Food and Drug Administration, Center for Drug Evaluation and Research, 10903 New Hampshire Avenue, Silver Spring, MD 20903, USA; (P.C.B.); (A.J.S.R.); (R.W.)
| | - Nisha Sipes
- U.S. Environmental Protection Agency, Center for Computational Toxicology and Exposure, 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA; (N.S.); (J.F.W.); (B.A.W.)
| | - Lisa M. Sweeney
- UES, Inc., 4401 Dayton-Xenia Road, Beavercreek, OH 45432, Assigned to Air Force Research Laboratory, 711 Human Performance Wing, Wright-Patterson Air Force Base, OH 45433, USA;
| | - John F. Wambaugh
- U.S. Environmental Protection Agency, Center for Computational Toxicology and Exposure, 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA; (N.S.); (J.F.W.); (B.A.W.)
| | - Ronald Wange
- U.S. Food and Drug Administration, Center for Drug Evaluation and Research, 10903 New Hampshire Avenue, Silver Spring, MD 20903, USA; (P.C.B.); (A.J.S.R.); (R.W.)
| | - Barbara A. Wetmore
- U.S. Environmental Protection Agency, Center for Computational Toxicology and Exposure, 109 TW Alexander Dr., Research Triangle Park, NC 27711, USA; (N.S.); (J.F.W.); (B.A.W.)
| | - Moiz Mumtaz
- Agency for Toxic Substances and Disease Registry, Office of the Associate Director for Science, 1600 Clifton Road, S102-2, Atlanta, GA 30333, USA
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17
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Petersen EJ, Ceger P, Allen DG, Coyle J, Derk R, Garcia-Reyero N, Gordon J, Kleinstreuer NC, Matheson J, McShan D, Nelson BC, Patri AK, Rice P, Rojanasakul L, Sasidharan A, Scarano L, Chang X. U.S. Federal Agency interests and key considerations for new approach methodologies for nanomaterials. ALTEX 2022; 39:183–206. [PMID: 34874455 PMCID: PMC9115850 DOI: 10.14573/altex.2105041] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 12/02/2021] [Indexed: 12/22/2022]
Abstract
Engineered nanomaterials (ENMs) come in a wide array of shapes, sizes, surface coatings, and compositions, and often possess novel or enhanced properties compared to larger sized particles of the same elemental composition. To ensure the safe commercialization of products containing ENMs, it is important to thoroughly understand their potential risks. Given that ENMs can be created in an almost infinite number of variations, it is not feasible to conduct in vivo testing on each type of ENM. Instead, new approach methodologies (NAMs) such as in vitro or in chemico test methods may be needed, given their capacity for higher throughput testing, lower cost, and ability to provide information on toxicological mechanisms. However, the different behaviors of ENMs compared to dissolved chemicals may challenge safety testing of ENMs using NAMs. In this study, member agencies within the Interagency Coordinating Committee on the Validation of Alternative Methods were queried about what types of ENMs are of agency interest and whether there is agency-specific guidance for ENM toxicity testing. To support the ability of NAMs to provide robust results in ENM testing, two key issues in the usage of NAMs, namely dosimetry and interference/bias controls, are thoroughly discussed.
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Affiliation(s)
- Elijah J Petersen
- U.S. Department of Commerce, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Patricia Ceger
- Integrated Laboratory Systems, LLC, P.O. Box 13501, Research Triangle Park, NC 27709, USA
| | - David G Allen
- Integrated Laboratory Systems, LLC, P.O. Box 13501, Research Triangle Park, NC 27709, USA
| | - Jayme Coyle
- National Institute for Occupational Safety and Health, Health Effects Laboratory Division, Morgantown, WV, USA.,Current affiliation: UES, Inc., Dayton, OH, USA
| | - Raymond Derk
- National Institute for Occupational Safety and Health, Health Effects Laboratory Division, Morgantown, WV, USA
| | | | - John Gordon
- U.S. Consumer Product Safety Commission, Bethesda, MD, USA
| | - Nicole C Kleinstreuer
- National Institute of Environmental Health Sciences, National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Research Triangle Park, NC, USA
| | | | - Danielle McShan
- U.S. Environmental Protection Agency, Office of Pesticide Programs, Washington, DC, USA
| | - Bryant C Nelson
- U.S. Department of Commerce, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Anil K Patri
- U.S. Food and Drug Administration, National Center for Toxicological Research, Jefferson, AR, USA
| | - Penelope Rice
- U.S. Food and Drug Administration, Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Liying Rojanasakul
- National Institute for Occupational Safety and Health, Health Effects Laboratory Division, Morgantown, WV, USA
| | - Abhilash Sasidharan
- U.S. Environmental Protection Agency, Office of Pollution Prevention and Toxics, Washington, DC, USA
| | - Louis Scarano
- U.S. Environmental Protection Agency, Office of Pollution Prevention and Toxics, Washington, DC, USA
| | - Xiaoqing Chang
- Integrated Laboratory Systems, LLC, P.O. Box 13501, Research Triangle Park, NC 27709, USA
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18
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Petersen EJ, Elliott JT, Bancos S, Caldwell B, Khajotia SS, Kleinstreuer NC, Margerrison E, Pfeifer C. Predictive alternative methods for assessing biocompatibility of dental materials: A NIST-NIDCR workshop report. ALTEX 2022; 39:522-524. [PMID: 35871505 DOI: 10.14573/altex.2206241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 06/30/2022] [Indexed: 06/15/2023]
Affiliation(s)
- Elijah J Petersen
- Biosystems and Biomaterials Division, National Institute of Standards and Technology (NIST), Gaithersburg, MD, United States
| | - John T Elliott
- Biosystems and Biomaterials Division, National Institute of Standards and Technology (NIST), Gaithersburg, MD, United States
| | - Simona Bancos
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD, United States
| | - Brittany Caldwell
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD, United States
| | - Sharukh S Khajotia
- Department of Restorative Sciences, Division of Dental Biomaterials, College of Dentistry, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Nicole C Kleinstreuer
- National Institute of Environmental Health Sciences, National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Research Triangle Park, NC, United States
| | - Edward Margerrison
- Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD, United States
| | - Carmem Pfeifer
- Biomaterials and Biomechanics, Department of Restorative Dentistry, Oregon Health & Science University, Portland, OR, USA
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19
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Kang I, Smirnova L, Kuhn JH, Hogberg HT, Kleinstreuer NC, Hartung T. COVID-19 - prime time for microphysiological systems, as illustrated for the brain. ALTEX 2021; 38:535-549. [PMID: 34698363 DOI: 10.14573/altex.2110131] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Indexed: 11/23/2022]
Abstract
The development of therapies for and preventions against infectious diseases depends on the availability of disease models. Bioengineering of human organoids and organs-on-chips is one extremely promising avenue of research. These miniature, laboratory-grown organ systems have been broadly used during the ongoing, unprecedented coronavirus 2019 (COVID-19) pandemic to show the many effects of the etiologic agent, severe acute respiratory coronavirus 2 (SARS-CoV-2) on human organs. In contrast, exposure of most animals either did not result in infection or caused mild clinical signs - not the severe course of the infection suffered by many humans. This article illuminates the opportunities of microphysiological systems (MPS) to study COVID-19 in vitro, with a focus on brain cell infection and its translational rel-evance to COVID-19 effects on the human brain. Neurovirulence of SARS-CoV-2 has been reproduced in different types of human brain organoids by 10 groups, consistently showing infection of a small portion of brain cells accompanied by limited viral replication. This mirrors increasingly recognized neurological manifestations in COVID-19 patients (evidence of virus infection and brain-specific antibody formation in brain tissue and cerebrospinal fluid). The pathogenesis of neuro-logical signs, their long-term consequences, and possible interventions remain unclear, but future MPS technologies offer prospects to address these open questions.
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Affiliation(s)
- Ian Kang
- Center for Alternatives to Animal Testing (CAAT), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Lena Smirnova
- Center for Alternatives to Animal Testing (CAAT), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jens H Kuhn
- Integrated Research Facility at Fort Detrick (IRF-Frederick), National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Fort Detrick, Frederick, MD, USA
| | - Helena T Hogberg
- Center for Alternatives to Animal Testing (CAAT), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Nicole C Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM), National Institute of Environmental Health Sciences (NIEHS), National Institutes of Health, RTP, NC, 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
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20
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Mansouri K, Karmaus AL, Fitzpatrick J, Patlewicz G, Pradeep P, Alberga D, Alepee N, Allen TEH, Allen D, Alves VM, Andrade CH, Auernhammer TR, Ballabio D, Bell S, Benfenati E, Bhattacharya S, Bastos JV, Boyd S, Brown JB, Capuzzi SJ, Chushak Y, Ciallella H, Clark AM, Consonni V, Daga PR, Ekins S, Farag S, Fedorov M, Fourches D, Gadaleta D, Gao F, Gearhart JM, Goh G, Goodman JM, Grisoni F, Grulke CM, Hartung T, Hirn M, Karpov P, Korotcov A, Lavado GJ, Lawless M, Li X, Luechtefeld T, Lunghini F, Mangiatordi GF, Marcou G, Marsh D, Martin T, Mauri A, Muratov EN, Myatt GJ, Nguyen DT, Nicolotti O, Note R, Pande P, Parks AK, Peryea T, Polash AH, Rallo R, Roncaglioni A, Rowlands C, Ruiz P, Russo DP, Sayed A, Sayre R, Sheils T, Siegel C, Silva AC, Simeonov A, Sosnin S, Southall N, Strickland J, Tang Y, Teppen B, Tetko IV, Thomas D, Tkachenko V, Todeschini R, Toma C, Tripodi I, Trisciuzzi D, Tropsha A, Varnek A, Vukovic K, Wang Z, Wang L, Waters KM, Wedlake AJ, Wijeyesakere SJ, Wilson D, Xiao Z, Yang H, Zahoranszky-Kohalmi G, Zakharov AV, Zhang FF, Zhang Z, Zhao T, Zhu H, Zorn KM, Casey W, Kleinstreuer NC. Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite. Environ Health Perspect 2021; 129:109001. [PMID: 34647794 PMCID: PMC8516060 DOI: 10.1289/ehp10369] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 09/24/2021] [Indexed: 05/21/2023]
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21
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Hagstrom AL, Anastas P, Boissevain A, Borrel A, Deziel NC, Fenton SE, Fields C, Fortner JD, Franceschi-Hofmann N, Frigon R, Jin L, Kim JH, Kleinstreuer NC, Koelmel J, Lei Y, Liew Z, Ma X, Mathieu L, Nason SL, Organtini K, Oulhote Y, Pociu S, Godri Pollitt KJ, Saiers J, Thompson DC, Toal B, Weiner EJ, Whirledge S, Zhang Y, Vasiliou V. Yale School of Public Health Symposium: An overview of the challenges and opportunities associated with per- and polyfluoroalkyl substances (PFAS). Sci Total Environ 2021; 778:146192. [PMID: 33714836 DOI: 10.1016/j.scitotenv.2021.146192] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 02/22/2021] [Accepted: 02/24/2021] [Indexed: 06/12/2023]
Abstract
On December 13, 2019, the Yale School of Public Health hosted a symposium titled "Per- and Polyfluoroalkyl Substances (PFAS): Challenges and Opportunities" in New Haven, Connecticut. The meeting focused on the current state of the science on these chemicals, highlighted the challenges unique to PFAS, and explored promising opportunities for addressing them. It brought together participants from Yale University, the National Institute of Environmental Health Sciences, the University of Massachusetts Amherst, the University of Connecticut, the Connecticut Agricultural Experiment Station, the Connecticut Departments of Public Health and Energy and Environmental Protection, and the public and private sectors. Presentations during the symposium centered around several primary themes. The first reviewed the current state of the science on the health effects associated with PFAS exposure and noted key areas that warranted future research. As research in this field relies on specialized laboratory analyses, the second theme considered commercially available methods for PFAS analysis as well as several emerging analytical approaches that support health studies and facilitate the investigation of a broader range of PFAS. Since mitigation of PFAS exposure requires prevention and cleanup of contamination, the third theme highlighted new nanotechnology-enabled PFAS remediation technologies and explored the potential of green chemistry to develop safer alternatives to PFAS. The fourth theme covered collaborative efforts to assess the vulnerability of in-state private wells and small public water supplies to PFAS contamination by adjacent landfills, and the fifth focused on strategies that promote successful community engagement. This symposium supported a unique interdisciplinary coalition established during the development of Connecticut's PFAS Action Plan, and discussions occurring throughout the symposium revealed opportunities for collaborations among Connecticut scientists, state and local officials, and community advocates. In doing so, it bolstered the State of Connecticut's efforts to implement the ambitious initiatives that its PFAS Action Plan recommends.
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Affiliation(s)
- Anna L Hagstrom
- Connecticut Department of Energy and Environmental Protection, Hartford, CT, USA; Connecticut Academy of Science and Engineering, Rocky Hill, CT, USA
| | - Paul Anastas
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA; Yale School of the Environment, New Haven, CT, USA
| | - Andrea Boissevain
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA; Stratford Health Department, Stratford, CT, USA
| | - Alexandre Borrel
- NIH/NIEHS/DIR Biostatistics & Computational Biology Branch, Research Triangle Park, NC, USA
| | - Nicole C Deziel
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
| | - Suzanne E Fenton
- NIH/NIEHS Division of the National Toxicology Program, NTP Laboratory, Research Triangle Park, NC, USA
| | - Cheryl Fields
- Connecticut Department of Public Health, Hartford, CT, USA
| | - John D Fortner
- Department of Chemical and Environmental Engineering, Yale University, New Haven, CT, USA
| | | | - Raymond Frigon
- Connecticut Department of Energy and Environmental Protection, Hartford, CT, USA
| | - Lan Jin
- Department of Surgery, Yale School of Medicine, New Haven, CT, USA
| | - Jae-Hong Kim
- Department of Chemical and Environmental Engineering, Yale University, New Haven, CT, USA
| | - Nicole C Kleinstreuer
- NIH/NIEHS/DIR Biostatistics & Computational Biology Branch, Research Triangle Park, NC, USA; NIH/NIEHS Division of the National Toxicology Program, NTP Interagency Center for the Evaluation of Alternative Toxicological Methods, Research Triangle Park, NC, USA
| | - Jeremy Koelmel
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
| | - Yu Lei
- Department of Chemical and Biomolecular Engineering, School of Engineering, University of Connecticut, Storrs, CT, USA
| | - Zeyan Liew
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
| | - Xiuqi Ma
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
| | - Lori Mathieu
- Connecticut Department of Public Health, Hartford, CT, USA
| | - Sara L Nason
- Connecticut Agricultural Experiment Station, New Haven, CT, USA
| | | | - Youssef Oulhote
- School of Public Health & Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA
| | - Shannon Pociu
- Connecticut Department of Energy and Environmental Protection, Hartford, CT, USA
| | - Krystal J Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
| | - James Saiers
- Yale School of the Environment, New Haven, CT, USA
| | - David C Thompson
- Department of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Aurora, CO, USA
| | - Brian Toal
- Connecticut Department of Public Health, Hartford, CT, USA
| | - Eric J Weiner
- Clean Water Task Force at Windsor Climate Action, Windsor, CT, USA
| | - Shannon Whirledge
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA; Department of Obstetrics, Gynecology, and Reproductive Sciences, Yale School of Medicine, New Haven, CT, USA
| | - Yawei Zhang
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
| | - Vasilis Vasiliou
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA.
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22
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Mansouri K, Karmaus A, Fitzpatrick J, Patlewicz G, Pradeep P, Alberga D, Alepee N, Allen TEH, Allen D, Alves VM, Andrade CH, Auernhammer TR, Ballabio D, Bell S, Benfenati E, Bhattacharya S, Bastos JV, Boyd S, Brown JB, Capuzzi SJ, Chushak Y, Ciallella H, Clark AM, Consonni V, Daga PR, Ekins S, Farag S, Fedorov M, Fourches D, Gadaleta D, Gao F, Gearhart JM, Goh G, Goodman JM, Grisoni F, Grulke CM, Hartung T, Hirn M, Karpov P, Korotcov A, Lavado GJ, Lawless M, Li X, Luechtefeld T, Lunghini F, Mangiatordi GF, Marcou G, Marsh D, Martin T, Mauri A, Muratov EN, Myatt GJ, Nguyen DT, Nicolotti O, Note R, Pande P, Parks AK, Peryea T, Polash A, Rallo R, Roncaglioni A, Rowlands C, Ruiz P, Russo D, Sayed A, Sayre R, Sheils T, Siegel C, Silva AC, Simeonov A, Sosnin S, Southall N, Strickland J, Tang Y, Teppen B, Tetko IV, Thomas D, Tkachenko V, Todeschini R, Toma C, Tripodi I, Trisciuzzi D, Tropsha A, Varnek A, Vukovic K, Wang Z, Wang L, Waters KM, Wedlake AJ, Wijeyesakere SJ, Wilson D, Xiao Z, Yang H, Zahoranszky-Kohalmi G, Zakharov AV, Zhang FF, Zhang Z, Zhao T, Zhu H, Zorn KM, Casey W, Kleinstreuer NC. Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite. Environ Health Perspect 2021; 129:79001. [PMID: 34242083 PMCID: PMC8270350 DOI: 10.1289/ehp9883] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 06/28/2021] [Indexed: 05/28/2023]
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23
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Clippinger AJ, Raabe HA, Allen DG, Choksi NY, van der Zalm AJ, Kleinstreuer NC, Barroso J, Lowit AB. Human-relevant approaches to assess eye corrosion/irritation potential of agrochemical formulations. Cutan Ocul Toxicol 2021; 40:145-167. [PMID: 33830843 DOI: 10.1080/15569527.2021.1910291] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
There are multiple in vitro and ex vivo eye irritation and corrosion test methods that are available as internationally harmonized test guidelines for regulatory use. Despite their demonstrated usefulness to a broad range of substances through inter-laboratory validation studies, they have not been widely adopted for testing agrochemical formulations due to a lack of concordance with parallel results from the traditional regulatory test method for this endpoint, the rabbit eye test. The inherent variability of the rabbit test, differences in the anatomy of the rabbit and human eyes, and differences in modelling exposures in rabbit eyes relative to human eyes contribute to this lack of concordance. Ultimately, the regulatory purpose for these tests is protection of human health, and, thus, there is a need for a testing approach based on human biology. This paper reviews the available in vivo, in vitro and ex vivo test methods with respect to their relevance to human ocular anatomy, anticipated exposure scenarios, and the mechanisms of eye irritation/corrosion in humans. Each of the in vitro and ex vivo methods described is generally appropriate for identifying non-irritants. To discriminate among eye irritants, the human three-dimensional epithelial and full thickness corneal models provide the most detailed information about the severity of irritation. Consideration of the mechanisms of eye irritation, and the strengths and limitations of the in vivo, in vitro and ex vivo test methods, show that the in vitro/ex vivo methods are as or more reflective of human biology and less variable than the currently used rabbit approach. Suggestions are made for further optimizing the most promising methods to distinguish between severe (corrosive), moderate, mild and non-irritants and provide information about the reversibility of effects. Also considered is the utility of including additional information (e.g. physical chemical properties), consistent with the Organization for Economic Cooperation and Development's guidance document on an integrated approach to testing and assessment of potential eye irritation. Combining structural and functional information about a test substance with test results from human-relevant methods will ensure the best protection of humans following accidental eye exposure to agrochemicals.
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Affiliation(s)
| | - Hans A Raabe
- Institute for In Vitro Sciences, Inc., Gaithersburg, MD, USA
| | - David G Allen
- Integrated Laboratory Systems, LLC, Research Triangle Park, NC, USA
| | - Neepa Y Choksi
- Integrated Laboratory Systems, LLC, Research Triangle Park, NC, USA
| | | | - Nicole C Kleinstreuer
- National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - João Barroso
- European Commission, Joint Research Centre (JRC), Ispra, VA, Italy
| | - Anna B Lowit
- US Environmental Protection Agency Office of Pesticide Programs, Washington, DC, USA
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24
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Knudsen TB, Fitzpatrick SC, De Abrew KN, Birnbaum LS, Chappelle A, Daston GP, Dolinoy DC, Elder A, Euling S, Faustman EM, Fedinick KP, Franzosa JA, Haggard DE, Haws L, Kleinstreuer NC, Buck Louis GM, Mendrick DL, Rudel R, Saili KS, Schug TT, Tanguay RL, Turley AE, Wetmore BA, White KW, Zurlinden TJ. FutureTox IV Workshop Summary: Predictive Toxicology for Healthy Children. Toxicol Sci 2021; 180:198-211. [PMID: 33555348 PMCID: PMC8041457 DOI: 10.1093/toxsci/kfab013] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
FutureTox IV, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in November 2018. Building upon FutureTox I, II, and III, this conference focused on the latest science and technology for in vitro profiling and in silico modeling as it relates to predictive developmental and reproductive toxicity (DART). Publicly available high-throughput screening data sets are now available for broad in vitro profiling of bioactivities across large inventories of chemicals. Coupling this vast amount of mechanistic data with a deeper understanding of molecular embryology and post-natal development lays the groundwork for using new approach methodologies (NAMs) to evaluate chemical toxicity, drug efficacy, and safety assessment for embryo-fetal development. NAM is a term recently adopted in reference to any technology, methodology, approach, or combination thereof that can be used to provide information on chemical hazard and risk assessment to avoid the use of intact animals (U.S. Environmental Protection Agency [EPA], Strategic plan to promote the development and implementation of alternative test methods within the tsca program, 2018, https://www.epa.gov/sites/production/files/2018-06/documents/epa_alt_strat_plan_6-20-18_clean_final.pdf). There are challenges to implementing NAMs to evaluate chemicals for developmental toxicity compared with adult toxicity. This forum article reviews the 2018 workshop activities, highlighting challenges and opportunities for applying NAMs for adverse pregnancy outcomes (eg, preterm labor, malformations, low birth weight) as well as disorders manifesting postnatally (eg, neurodevelopmental impairment, breast cancer, cardiovascular disease, fertility). DART is an important concern for different regulatory statutes and test guidelines. Leveraging advancements in such approaches and the accompanying efficiencies to detecting potential hazards to human development are the unifying concepts toward implementing NAMs in DART testing. Although use of NAMs for higher level regulatory decision making is still on the horizon, the conference highlighted novel testing platforms and computational models that cover multiple levels of biological organization, with the unique temporal dynamics of embryonic development, and novel approaches for estimating toxicokinetic parameters essential in supporting in vitro to in vivo extrapolation.
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Affiliation(s)
- Thomas B Knudsen
- U.S. Environmental Protection Agency, ORD, Research Triangle Park, North Carolina, USA
| | | | | | - Linda S Birnbaum
- National Institute of Environmental Health Science, NIH, Research Triangle Park, North Carolina, USA
| | - Anne Chappelle
- Chappelle Toxicology Consulting, LLC, Chadds Ford, Pennsylvania, USA
| | | | | | - Alison Elder
- University of Rochester, Rochester, New York, USA
| | - Susan Euling
- U.S. Environmental Protection Agency, Office of Children’s Health Protection, Washington, District of Columbia, USA
| | | | | | - Jill A Franzosa
- U.S. Environmental Protection Agency, ORD, Research Triangle Park, North Carolina, USA
| | - Derik E Haggard
- U.S. Environmental Protection Agency, ORD, Research Triangle Park, North Carolina, USA
- Oak Ridge Institute for Science and Education (ORISE);, Texas, USA
| | | | | | | | - Donna L Mendrick
- U.S. Food and Drug Administration, NCTR, Silver Spring, Maryland, USA
| | | | - Katerine S Saili
- U.S. Environmental Protection Agency, ORD, Research Triangle Park, North Carolina, USA
| | - Thaddeus T Schug
- National Institute of Environmental Health Science, NIH, Research Triangle Park, North Carolina, USA
| | | | | | - Barbara A Wetmore
- U.S. Environmental Protection Agency, ORD, Research Triangle Park, North Carolina, USA
| | - Kimberly W White
- American Chemistry Council, Washington, District of Columbia, USA
| | - Todd J Zurlinden
- U.S. Environmental Protection Agency, ORD, Research Triangle Park, North Carolina, USA
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25
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Mansouri K, Karmaus AL, Fitzpatrick J, Patlewicz G, Pradeep P, Alberga D, Alepee N, Allen TE, Allen D, Alves VM, Andrade CH, Auernhammer TR, Ballabio D, Bell S, Benfenati E, Bhattacharya S, Bastos JV, Boyd S, Brown J, Capuzzi SJ, Chushak Y, Ciallella H, Clark AM, Consonni V, Daga PR, Ekins S, Farag S, Fedorov M, Fourches D, Gadaleta D, Gao F, Gearhart JM, Goh G, Goodman JM, Grisoni F, Grulke CM, Hartung T, Hirn M, Karpov P, Korotcov A, Lavado GJ, Lawless M, Li X, Luechtefeld T, Lunghini F, Mangiatordi GF, Marcou G, Marsh D, Martin T, Mauri A, Muratov EN, Myatt GJ, Nguyen DT, Nicolotti O, Note R, Pande P, Parks AK, Peryea T, Polash AH, Rallo R, Roncaglioni A, Rowlands C, Ruiz P, Russo DP, Sayed A, Sayre R, Sheils T, Siegel C, Silva AC, Simeonov A, Sosnin S, Southall N, Strickland J, Tang Y, Teppen B, Tetko IV, Thomas D, Tkachenko V, Todeschini R, Toma C, Tripodi I, Trisciuzzi D, Tropsha A, Varnek A, Vukovic K, Wang Z, Wang L, Waters KM, Wedlake AJ, Wijeyesakere SJ, Wilson D, Xiao Z, Yang H, Zahoranszky-Kohalmi G, Zakharov AV, Zhang FF, Zhang Z, Zhao T, Zhu H, Zorn KM, Casey W, Kleinstreuer NC. CATMoS: Collaborative Acute Toxicity Modeling Suite. Environ Health Perspect 2021; 129:47013. [PMID: 33929906 PMCID: PMC8086800 DOI: 10.1289/ehp8495] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
BACKGROUND Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. OBJECTIVES The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50≤50mg/kg)], and nontoxic chemicals (LD50>2,000mg/kg). METHODS An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. RESULTS The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in vivo results. DISCUSSION CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemicals have been made available via the National Toxicology Program's Integrated Chemical Environment tools and data sets (ice.ntp.niehs.nih.gov). The models are also implemented in a free, standalone, open-source tool, OPERA, which allows predictions of new and untested chemicals to be made. https://doi.org/10.1289/EHP8495.
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Affiliation(s)
- Kamel Mansouri
- Integrated Laboratory Systems, LLC, Morrisville, North Carolina, USA
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Research Triangle Park, North Carolina, USA
| | - Agnes L. Karmaus
- Integrated Laboratory Systems, LLC, Morrisville, North Carolina, USA
| | | | - Grace Patlewicz
- Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Prachi Pradeep
- Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
- Oak Ridge Institute for Science and Education (ORISE) Research Participation Program, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Domenico Alberga
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, Bari, Italy
| | | | - Timothy E.H. Allen
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Cambridge, UK
| | - Dave Allen
- Integrated Laboratory Systems, LLC, Morrisville, North Carolina, USA
| | - Vinicius M. Alves
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina, USA
- Laboratory for Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiania, Brazil
| | - Carolina H. Andrade
- Laboratory for Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiania, Brazil
| | | | - Davide Ballabio
- Milano Chemometrics & QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
| | - Shannon Bell
- Integrated Laboratory Systems, LLC, Morrisville, North Carolina, USA
| | - Emilio Benfenati
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Sudin Bhattacharya
- Institute for Quantitative Health Science and Engineering, Department of Biomedical Engineering, Michigan State University, East Lansing, Michigan, USA
| | - Joyce V. Bastos
- Laboratory for Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiania, Brazil
| | - Stephen Boyd
- Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, Michigan, USA
| | - J.B. Brown
- Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Stephen J. Capuzzi
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Yaroslav Chushak
- Aeromedical Research Department, Force Health Protection, USAFSAM, Dayton, Ohio, USA
- Henry M Jackson Foundation for the Advancement of Military Medicine, Dayton, Ohio, USA
| | - Heather Ciallella
- Center for Computational and Integrative Biology, Rutgers University, Camden, New Jersey, USA
| | - Alex M. Clark
- Collaborations Pharmaceuticals, Inc., Raleigh, North Carolina, USA
| | - Viviana Consonni
- Milano Chemometrics & QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
| | | | - Sean Ekins
- Collaborations Pharmaceuticals, Inc., Raleigh, North Carolina, USA
| | - Sherif Farag
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Maxim Fedorov
- Skoltech, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Denis Fourches
- Department of Chemistry, North Carolina State University, Raleigh, North Carolina, USA
- Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina, USA
| | - Domenico Gadaleta
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Feng Gao
- Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, Michigan, USA
| | - Jeffery M. Gearhart
- Aeromedical Research Department, Force Health Protection, USAFSAM, Dayton, Ohio, USA
- Henry M Jackson Foundation for the Advancement of Military Medicine, Dayton, Ohio, USA
| | - Garett Goh
- Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Jonathan M. Goodman
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Cambridge, UK
| | - Francesca Grisoni
- Milano Chemometrics & QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
| | - Christopher M. Grulke
- Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | | | - Matthew Hirn
- Department of Computational Mathematics, Science & Engineering, Department of Mathematics, Michigan State University, East Lansing, Michigan, USA
| | - Pavel Karpov
- Institute of Structural Biology, Helmholtz Zentrum München (GmbH), Neuherberg, Germany
| | | | - Giovanna J. Lavado
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | | | - Xinhao Li
- Department of Chemistry, North Carolina State University, Raleigh, North Carolina, USA
| | | | - Filippo Lunghini
- Laboratoire de Chemoinformatique, URM7140, Université de Strasbourg, Strasbourg, France
| | - Giuseppe F. Mangiatordi
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, Bari, Italy
| | - Gilles Marcou
- Laboratoire de Chemoinformatique, URM7140, Université de Strasbourg, Strasbourg, France
| | - Dan Marsh
- Underwriters Laboratories, Northbrook, Illinois, USA
| | - Todd Martin
- Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Cincinnati, Ohio, USA
| | | | - Eugene N. Muratov
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina, USA
- Laboratory for Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiania, Brazil
| | | | - Dac-Trung Nguyen
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Orazio Nicolotti
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, Bari, Italy
| | - Reine Note
- L’Oréal Research & Innovation, Aulnay-sous-Bois, France
| | - Paritosh Pande
- Pacific Northwest National Laboratory, Richland, Washington, USA
| | | | - Tyler Peryea
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | | | - Robert Rallo
- Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Alessandra Roncaglioni
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | | | - Patricia Ruiz
- Office of Innovation and Analytics, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Daniel P. Russo
- Center for Computational and Integrative Biology, Rutgers University, Camden, New Jersey, USA
| | - Ahmed Sayed
- Rosettastein Consulting UG, Freising, Germany
| | - Risa Sayre
- Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
- Oak Ridge Institute for Science and Education (ORISE) Research Participation Program, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Timothy Sheils
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Charles Siegel
- Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Arthur C. Silva
- Laboratory for Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiania, Brazil
| | - Anton Simeonov
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Sergey Sosnin
- Skoltech, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Noel Southall
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Judy Strickland
- Integrated Laboratory Systems, LLC, Morrisville, North Carolina, USA
| | - Yun Tang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Brian Teppen
- Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, Michigan, USA
| | - Igor V. Tetko
- Institute of Structural Biology, Helmholtz Zentrum München (GmbH), Neuherberg, Germany
- BIGCHEM GmbH, Unterschleissheim, Germany
| | - Dennis Thomas
- Pacific Northwest National Laboratory, Richland, Washington, USA
| | | | - Roberto Todeschini
- Milano Chemometrics & QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
| | - Cosimo Toma
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Ignacio Tripodi
- Computer Science/Interdisciplinary Quantitative Biology, University of Colorado, Boulder, Colorado, USA
| | - Daniela Trisciuzzi
- Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, Bari, Italy
| | - Alexander Tropsha
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Alexandre Varnek
- Laboratoire de Chemoinformatique, URM7140, Université de Strasbourg, Strasbourg, France
| | - Kristijan Vukovic
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Zhongyu Wang
- School of Environmental Sciences and Technology, Dalian University of Technology; Dalian, Liaoning, China
| | - Liguo Wang
- School of Environmental Sciences and Technology, Dalian University of Technology; Dalian, Liaoning, China
| | | | - Andrew J. Wedlake
- Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Cambridge, UK
| | | | - Dan Wilson
- The Dow Chemical Company, Midland, Michigan, USA
| | - Zijun Xiao
- School of Environmental Sciences and Technology, Dalian University of Technology; Dalian, Liaoning, China
| | - Hongbin Yang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China
| | - Gergely Zahoranszky-Kohalmi
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Alexey V. Zakharov
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | | | - Zhen Zhang
- Dow Agrosciences, Indianapolis, Indiana, USA
| | - Tongan Zhao
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland, USA
| | - Hao Zhu
- Center for Computational and Integrative Biology, Rutgers University, Camden, New Jersey, USA
| | | | - Warren Casey
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Research Triangle Park, North Carolina, USA
| | - Nicole C. Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, Research Triangle Park, North Carolina, USA
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Sedykh AY, Shah RR, Kleinstreuer NC, Auerbach SS, Gombar VK. Saagar-A New, Extensible Set of Molecular Substructures for QSAR/QSPR and Read-Across Predictions. Chem Res Toxicol 2020; 34:634-640. [PMID: 33356152 DOI: 10.1021/acs.chemrestox.0c00464] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Molecular structure-based predictive models provide a proven alternative to costly and inefficient animal testing. However, due to a lack of interpretability of predictive models built with abstract molecular descriptors they have earned the notoriety of being black boxes. Interpretable models require interpretable descriptors to provide chemistry-backed predictive reasoning and facilitate intelligent molecular design. We developed a novel set of extensible chemistry-aware substructures, Saagar, to support interpretable predictive models and read-across protocols. Performance of Saagar in chemical characterization and search for structurally similar actives for read-across applications was compared with four publicly available fingerprint sets (MACCS (166), PubChem (881), ECFP4 (1024), ToxPrint (729)) in three benchmark sets (MUV, ULS, and Tox21) spanning ∼145 000 compounds and 78 molecular targets at 1%, 2%, 5%, and 10% false discovery rates. In 18 of the 20 comparisons, interpretable Saagar features performed better than the publicly available, but less interpretable and fixed-bit length, fingerprints. Examples are provided to show the enhanced capability of Saagar in extracting compounds with higher scaffold similarity. Saagar features are interpretable and efficiently characterize diverse chemical collections, thus making them a better choice for building interpretable predictive in silico models and read-across protocols.
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Affiliation(s)
| | - Ruchir R Shah
- Sciome LLC, Research Triangle Park, North Carolina 27709, United States
| | - Nicole C Kleinstreuer
- National Institute of Environmental Health Sciences (NIEHS), National Toxicology Program (NTP), Research Triangle Park, North Carolina 27709, United States
| | - Scott S Auerbach
- National Institute of Environmental Health Sciences (NIEHS), National Toxicology Program (NTP), Research Triangle Park, North Carolina 27709, United States
| | - Vijay K Gombar
- Sciome LLC, Research Triangle Park, North Carolina 27709, United States
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Borrel A, Mansouri K, Nolte S, Saddler T, Conway M, Schmitt C, Kleinstreuer NC. InterPred: a webtool to predict chemical autofluorescence and luminescence interference. Nucleic Acids Res 2020; 48:W586-W590. [PMID: 32421835 DOI: 10.1093/nar/gkaa378] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 04/10/2020] [Accepted: 04/29/2020] [Indexed: 02/07/2023] Open
Abstract
High-throughput screening (HTS) research programs for drug development or chemical hazard assessment are designed to screen thousands of molecules across hundreds of biological targets or pathways. Most HTS platforms use fluorescence and luminescence technologies, representing more than 70% of the assays in the US Tox21 research consortium. These technologies are subject to interferent signals largely explained by chemicals interacting with light spectrum. This phenomenon results in up to 5-10% of false positive results, depending on the chemical library used. Here, we present the InterPred webserver (version 1.0), a platform to predict such interference chemicals based on the first large-scale chemical screening effort to directly characterize chemical-assay interference, using assays in the Tox21 portfolio specifically designed to measure autofluorescence and luciferase inhibition. InterPred combines 17 quantitative structure activity relationship (QSAR) models built using optimized machine learning techniques and allows users to predict the probability that a new chemical will interfere with different combinations of cellular and technology conditions. InterPred models have been applied to the entire Distributed Structure-Searchable Toxicity (DSSTox) Database (∼800,000 chemicals). The InterPred webserver is available at https://sandbox.ntp.niehs.nih.gov/interferences/.
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Borrel A, Auerbach SS, Houck KA, Kleinstreuer NC. Tox21BodyMap: a webtool to map chemical effects on the human body. Nucleic Acids Res 2020; 48:W472-W476. [PMID: 32491175 PMCID: PMC7319561 DOI: 10.1093/nar/gkaa433] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 04/21/2020] [Accepted: 05/11/2020] [Indexed: 09/29/2023] Open
Abstract
To support rapid chemical toxicity assessment and mechanistic hypothesis generation, here we present an intuitive webtool allowing a user to identify target organs in the human body where a substance is estimated to be more likely to produce effects. This tool, called Tox21BodyMap, incorporates results of 9,270 chemicals tested in the United States federal Tox21 research consortium in 971 high-throughput screening (HTS) assays whose targets were mapped onto human organs using organ-specific gene expression data. Via Tox21BodyMap's interactive tools, users can visualize chemical target specificity by organ system, and implement different filtering criteria by changing gene expression thresholds and activity concentration parameters. Dynamic network representations, data tables, and plots with comprehensive activity summaries across all Tox21 HTS assay targets provide an overall picture of chemical bioactivity. Tox21BodyMap webserver is available at https://sandbox.ntp.niehs.nih.gov/bodymap/.
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Parish ST, Aschner M, Casey W, Corvaro M, Embry MR, Fitzpatrick S, Kidd D, Kleinstreuer NC, Lima BS, Settivari RS, Wolf DC, Yamazaki D, Boobis A. An evaluation framework for new approach methodologies (NAMs) for human health safety assessment. Regul Toxicol Pharmacol 2020; 112:104592. [DOI: 10.1016/j.yrtph.2020.104592] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 01/15/2020] [Accepted: 01/27/2020] [Indexed: 10/25/2022]
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Affiliation(s)
- Nicole C Kleinstreuer
- National Institute of Environmental Health Sciences (NIEHS), NTP Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM), 530 Davis Drive, Research Triangle Park, North Carolina 27560, United States
| | - Weida Tong
- National Center for Toxicological Research, 3900 NCTR Road, Jefferson, Arkansas 72079, United States
| | - Igor V Tetko
- Institute of Structural Biology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany
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Wei Z, Liu X, Ooka M, Zhang L, Song MJ, Huang R, Kleinstreuer NC, Simeonov A, Xia M, Ferrer M. Two-Dimensional Cellular and Three-Dimensional Bio-Printed Skin Models to Screen Topical-Use Compounds for Irritation Potential. Front Bioeng Biotechnol 2020; 8:109. [PMID: 32154236 PMCID: PMC7046801 DOI: 10.3389/fbioe.2020.00109] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Accepted: 02/03/2020] [Indexed: 11/22/2022] Open
Abstract
Assessing skin irritation potential is critical for the safety evaluation of topical drugs and other consumer products such as cosmetics. The use of advanced cellular models, as an alternative to replace animal testing in the safety evaluation for both consumer products and ingredients, is already mandated by law in the European Union (EU) and other countries. However, there has not yet been a large-scale comparison of the effects of topical-use compounds in different cellular skin models. This study assesses the irritation potential of topical-use compounds in different cellular models of the skin that are compatible with high throughput screening (HTS) platforms. A set of 451 topical-use compounds were first tested for cytotoxic effects using two-dimensional (2D) monolayer models of primary neonatal keratinocytes and immortalized human keratinocytes. Forty-six toxic compounds identified from the initial screen with the monolayer culture systems were further tested for skin irritation potential on reconstructed human epidermis (RhE) and full thickness skin (FTS) three-dimensional (3D) tissue model constructs. Skin irritation potential of the compounds was assessed by measuring tissue viability, trans-epithelial electrical resistance (TEER), and secretion of cytokines interleukin 1 alpha (IL-1α) and interleukin 18 (IL-18). Among known irritants, high concentrations of methyl violet and methylrosaniline decreased viability, lowered TEER, and increased IL-1α secretion in both RhE and FTS models, consistent with irritant properties. However, at low concentrations, these two compounds increased IL-18 secretion without affecting levels of secreted IL-1α, and did not reduce tissue viability and TEER, in either RhE or FTS models. This result suggests that at low concentrations, methyl violet and methylrosaniline have an allergic potential without causing irritation. Using both HTS-compatible 2D cellular and 3D tissue skin models, together with irritation relevant activity endpoints, we obtained data to help assess the irritation effects of topical-use compounds and identify potential dermal hazards.
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Affiliation(s)
- Zhengxi Wei
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, United States
| | - Xue Liu
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, United States
| | - Masato Ooka
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, United States
| | - Li Zhang
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, United States
| | - Min Jae Song
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, United States
- 3D Bioprinting Core, National Eye Institute, Bethesda, MD, United States
| | - Ruili Huang
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, United States
| | - Nicole C. Kleinstreuer
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, United States
| | - Anton Simeonov
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, United States
| | - Menghang Xia
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, United States
| | - Marc Ferrer
- Division of Pre-Clinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, United States
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Li X, Kleinstreuer NC, Fourches D. Hierarchical Quantitative Structure–Activity Relationship Modeling Approach for Integrating Binary, Multiclass, and Regression Models of Acute Oral Systemic Toxicity. Chem Res Toxicol 2020; 33:353-366. [DOI: 10.1021/acs.chemrestox.9b00259] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Xinhao Li
- Department of Chemistry, Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Nicole C. Kleinstreuer
- Division of Intramural Research/Biostatistics and Computational Biology Branch, NIEHS, Research Triangle
Park, Durham, North Carolina 27709, United States
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, NIEHS, Research Triangle Park, Durham, North Carolina 27709, United States
| | - Denis Fourches
- Department of Chemistry, Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27695, United States
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Wei Z, Sakamuru S, Zhang L, Zhao J, Huang R, Kleinstreuer NC, Chen Y, Shu Y, Knudsen TB, Xia M. Identification and Profiling of Environmental Chemicals That Inhibit the TGFβ/SMAD Signaling Pathway. Chem Res Toxicol 2019; 32:2433-2444. [PMID: 31652400 PMCID: PMC7341485 DOI: 10.1021/acs.chemrestox.9b00228] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The transforming growth factor beta (TGFβ) superfamily of secreted signaling molecules and their cognate receptors regulate cell fate and behaviors relevant to many developmental and disease processes. Disruption of TGFβ signaling during embryonic development can, for example, affect morphogenesis and differentiation through complex pathways that may be SMAD (Small Mothers Against Decapentaplegic) dependent or SMAD independent. In the present study, the SMAD Binding Element (SBE)-beta lactamase (bla) HEK 293T cell line, which responds to the activation of the SMAD2/3/4 complex, was used in a quantitative high-throughput screening (qHTS) assay to identify potential TGFβ disruptors in the Tox21 10K compound library. From the primary screening we identified several kinase inhibitors, organometallic compounds, and dithiocarbamates (DTCs) that inhibited TGFβ1-induced SMAD signaling of reporter gene activation independent of cytotoxicity. Counterscreen of SBE antagonists on human embryonic neural stem cells demonstrated cytotoxicity, providing additional evidence to support evaluation of these compounds for developmental toxicity. We profiled the inhibitory patterns of putative SBE antagonists toward other developmental signaling pathways, including wingless-related integration site (WNT), retinoic acid α receptor (RAR), and sonic hedgehog (SHH). The profiling results from SBE-bla assay identify chemicals that disrupt TGFβ/SMAD signaling as part of an integrated qHTS approach for prioritizing putative developmental toxicants.
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Affiliation(s)
- Zhengxi Wei
- National Center for Advancing Translational Sciences, National Institutes of Health, MD, USA
| | - Srilatha Sakamuru
- National Center for Advancing Translational Sciences, National Institutes of Health, MD, USA
| | - Li Zhang
- National Center for Advancing Translational Sciences, National Institutes of Health, MD, USA
| | - Jinghua Zhao
- National Center for Advancing Translational Sciences, National Institutes of Health, MD, USA
| | - Ruili Huang
- National Center for Advancing Translational Sciences, National Institutes of Health, MD, USA
| | - Nicole C. Kleinstreuer
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Yanling Chen
- Division of Molecular Biology, Office of Applied Research and Safety Assessment, Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, Laurel, MD, USA
| | - Yan Shu
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, Baltimore, Maryland 21201, USA
| | - Thomas B. Knudsen
- National Center for Computational Toxicology, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Menghang Xia
- National Center for Advancing Translational Sciences, National Institutes of Health, MD, USA
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Abstract
Motivation Easily navigating chemical space has become more important due to the increasing size and diversity of publicly-accessible databases such as DrugBank, ChEMBL or Tox21. To do so, modelers typically rely on complex projection techniques using molecular descriptors computed for all the chemicals to be visualized. However, the multiple cheminformatics steps required to prepare, characterize, compute and explore those molecules, are technical, typically necessitate scripting skills, and thus represent a real obstacle for non-specialists. Results We developed the ChemMaps.com webserver to easily browse, navigate and mine chemical space. The first version of ChemMaps.com features more than 8000 approved, in development, and rejected drugs, as well as over 47 000 environmental chemicals. Availability and implementation The webserver is freely available at http://www.chemmaps.com.
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Affiliation(s)
- Alexandre Borrel
- Department of Chemistry, Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA.,Division of Intramural Research/Biostatistics and Computational Biology Branch
| | - Nicole C Kleinstreuer
- Division of Intramural Research/Biostatistics and Computational Biology Branch.,National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, NIEHS, RTP, Research Triangle, NC, USA
| | - Denis Fourches
- Department of Chemistry, Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
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Corton JC, Kleinstreuer NC, Judson RS. Identification of potential endocrine disrupting chemicals using gene expression biomarkers. Toxicol Appl Pharmacol 2019; 380:114683. [DOI: 10.1016/j.taap.2019.114683] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Revised: 07/05/2019] [Accepted: 07/15/2019] [Indexed: 02/07/2023]
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Mansouri K, Cariello NF, Korotcov A, Tkachenko V, Grulke CM, Sprankle CS, Allen D, Casey WM, Kleinstreuer NC, Williams AJ. Open-source QSAR models for pKa prediction using multiple machine learning approaches. J Cheminform 2019; 11:60. [PMID: 33430972 PMCID: PMC6749653 DOI: 10.1186/s13321-019-0384-1] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Accepted: 09/03/2019] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The logarithmic acid dissociation constant pKa reflects the ionization of a chemical, which affects lipophilicity, solubility, protein binding, and ability to pass through the plasma membrane. Thus, pKa affects chemical absorption, distribution, metabolism, excretion, and toxicity properties. Multiple proprietary software packages exist for the prediction of pKa, but to the best of our knowledge no free and open-source programs exist for this purpose. Using a freely available data set and three machine learning approaches, we developed open-source models for pKa prediction. METHODS The experimental strongest acidic and strongest basic pKa values in water for 7912 chemicals were obtained from DataWarrior, a freely available software package. Chemical structures were curated and standardized for quantitative structure-activity relationship (QSAR) modeling using KNIME, and a subset comprising 79% of the initial set was used for modeling. To evaluate different approaches to modeling, several datasets were constructed based on different processing of chemical structures with acidic and/or basic pKas. Continuous molecular descriptors, binary fingerprints, and fragment counts were generated using PaDEL, and pKa prediction models were created using three machine learning methods, (1) support vector machines (SVM) combined with k-nearest neighbors (kNN), (2) extreme gradient boosting (XGB) and (3) deep neural networks (DNN). RESULTS The three methods delivered comparable performances on the training and test sets with a root-mean-squared error (RMSE) around 1.5 and a coefficient of determination (R2) around 0.80. Two commercial pKa predictors from ACD/Labs and ChemAxon were used to benchmark the three best models developed in this work, and performance of our models compared favorably to the commercial products. CONCLUSIONS This work provides multiple QSAR models to predict the strongest acidic and strongest basic pKas of chemicals, built using publicly available data, and provided as free and open-source software on GitHub.
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Affiliation(s)
- Kamel Mansouri
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709 USA
| | - Neal F. Cariello
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709 USA
| | - Alexandru Korotcov
- Science Data Software LLC, 14914 Bradwill Court, Rockville, MD 20850 USA
| | - Valery Tkachenko
- Science Data Software LLC, 14914 Bradwill Court, Rockville, MD 20850 USA
| | - Chris M. Grulke
- National Center for Computational Toxicology, U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Mail Code D143-02, Research Triangle Park, NC 27709 USA
| | - Catherine S. Sprankle
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709 USA
| | - David Allen
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709 USA
| | - Warren M. Casey
- National Institute of Environmental Health Sciences, P.O. Box 12233, Mail Stop K2-16, Research Triangle Park, NC 27709 USA
| | - Nicole C. Kleinstreuer
- National Institute of Environmental Health Sciences, P.O. Box 12233, Mail Stop K2-16, Research Triangle Park, NC 27709 USA
| | - Antony J. Williams
- National Center for Computational Toxicology, U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Mail Code D143-02, Research Triangle Park, NC 27709 USA
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Gadaleta D, Vuković K, Toma C, Lavado GJ, Karmaus AL, Mansouri K, Kleinstreuer NC, Benfenati E, Roncaglioni A. SAR and QSAR modeling of a large collection of LD 50 rat acute oral toxicity data. J Cheminform 2019; 11:58. [PMID: 33430989 PMCID: PMC6717335 DOI: 10.1186/s13321-019-0383-2] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Accepted: 08/13/2019] [Indexed: 11/10/2022] Open
Abstract
The median lethal dose for rodent oral acute toxicity (LD50) is a standard piece of information required to categorize chemicals in terms of the potential hazard posed to human health after acute exposure. The exclusive use of in vivo testing is limited by the time and costs required for performing experiments and by the need to sacrifice a number of animals. (Quantitative) structure-activity relationships [(Q)SAR] proved a valid alternative to reduce and assist in vivo assays for assessing acute toxicological hazard. In the framework of a new international collaborative project, the NTP Interagency Center for the Evaluation of Alternative Toxicological Methods and the U.S. Environmental Protection Agency's National Center for Computational Toxicology compiled a large database of rat acute oral LD50 data, with the aim of supporting the development of new computational models for predicting five regulatory relevant acute toxicity endpoints. In this article, a series of regression and classification computational models were developed by employing different statistical and knowledge-based methodologies. External validation was performed to demonstrate the real-life predictability of models. Integrated modeling was then applied to improve performance of single models. Statistical results confirmed the relevance of developed models in regulatory frameworks, and confirmed the effectiveness of integrated modeling. The best integrated strategies reached RMSEs lower than 0.50 and the best classification models reached balanced accuracies over 0.70 for multi-class and over 0.80 for binary endpoints. Computed predictions will be hosted on the EPA's Chemistry Dashboard and made freely available to the scientific community.
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Affiliation(s)
- Domenico Gadaleta
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy.
| | - Kristijan Vuković
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy
| | - Cosimo Toma
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy
- Institute for Risk Assessment Sciences, Utrecht University, PO Box 80177, 3508 TD, Utrecht, The Netherlands
| | - Giovanna J Lavado
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy
| | - Agnes L Karmaus
- Integrated Laboratory Systems, Research Triangle Park, NC, 27560, USA
| | - Kamel Mansouri
- Integrated Laboratory Systems, Research Triangle Park, NC, 27560, USA
| | - Nicole C Kleinstreuer
- NTP Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27560, USA
| | - Emilio Benfenati
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy
| | - Alessandra Roncaglioni
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156, Milan, Italy
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Judson RS, Thomas RS, Baker N, Simha A, Howey XM, Marable C, Kleinstreuer NC, Houck KA. Workflow for defining reference chemicals for assessing performance of in vitro assays. ALTEX 2018; 36:261-276. [PMID: 30570668 DOI: 10.14573/altex.1809281] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Accepted: 12/06/2018] [Indexed: 12/19/2022]
Abstract
Instilling confidence in use of in vitro assays for predictive toxicology requires evaluation of assay performance. Performance is typically assessed using reference chemicals--compounds with defined activity against the test system target. However, developing reference chemical lists has historically been very resource-intensive. We developed a semi-automated process for selecting and annotating reference chemicals across many targets in a standardized format and demonstrate the workflow here. A series of required fields defines the potential reference chemical: the in vitro molecular target, pathway, or phenotype affected; and the chemical's mode (e.g. agonist, antagonist, inhibitor). Activity information was computationally extracted into a database from multiple public sources including non-curated scientific literature and curated chemical-biological databases, resulting in the identification of chemical activity in 2995 biological targets. Sample data from literature sources covering 54 molecular targets ranging from data-poor to data-rich was manually checked for accuracy. Precision rates were 82.7% from curated data sources and 39.5% from automated literature extraction. We applied the final reference chemical lists to evaluating performance of EPA's ToxCast program in vitro bioassays. The level of support, i.e. the number of independent reports in the database linking a chemical to a target, was found to strongly correlate with likelihood of positive results in the ToxCast assays, although individual assay performance had considerable variation. This overall approach allows rapid development of candidate reference chemical lists for a wide variety of targets that can facilitate performance evaluation of in vitro assays as a critical step in imparting confidence in alternative approaches.
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Affiliation(s)
- Richard S Judson
- US EPA, National Center for Computational Toxicology, Research Triangle Park, NC, USA
| | - Russell S Thomas
- US EPA, National Center for Computational Toxicology, Research Triangle Park, NC, USA
| | - Nancy Baker
- Leidos, Inc., Research Triangle Park, NC, USA
| | - Anita Simha
- ORAU, contractor to U.S. Environmental Protection Agency through the National Student Services Contract, Research Triangle Park, NC, USA
| | - Xia Meng Howey
- ORAU, contractor to U.S. Environmental Protection Agency through the National Student Services Contract, Research Triangle Park, NC, USA
| | - Carmen Marable
- ORAU, contractor to U.S. Environmental Protection Agency through the National Student Services Contract, Research Triangle Park, NC, USA
| | - Nicole C Kleinstreuer
- National Toxicology Program, Interagency Center for the Evaluation of Alternative Toxicological Methods, Research Triangle Park, NC, USA
| | - Keith A Houck
- US EPA, National Center for Computational Toxicology, Research Triangle Park, NC, USA
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40
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Kolanjiyil AV, Kleinstreuer C, Kleinstreuer NC, Pham W, Sadikot RT. Mice-to-men comparison of inhaled drug-aerosol deposition and clearance. Respir Physiol Neurobiol 2018; 260:82-94. [PMID: 30445230 DOI: 10.1016/j.resp.2018.11.003] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 11/07/2018] [Accepted: 11/10/2018] [Indexed: 01/17/2023]
Abstract
Part of the effective prediction of the pharmacokinetics of drugs (or toxic particles) requires extrapolation of experimental data sets from animal studies to humans. As the respiratory tracts of rodents and humans are anatomically very different, there is a need to study airflow and drug-aerosol deposition patterns in lung airways of these laboratory animals and compare them to those of human lungs. As a first step, interspecies computational comparison modeling of inhaled nano-to-micron size drugs (50 nm < d<15μm) was performed using mouse and human upper airway models under realistic breathing conditions. Critical species-specific differences in lung physiology of the upper airways and subsequently in local drug deposition were simulated and analyzed. In addition, a hybrid modeling methodology, combining Computational Fluid-Particle Dynamics (CF-PD) simulations with deterministic lung deposition models, was developed and predicted total and regional drug-aerosol depositions in lung airways of both mouse and man were compared, accounting for the geometric, kinematic and dynamic differences. Interestingly, our results indicate that the total particle deposition fractions, especially for submicron particles, are comparable in rodent and human respiratory models for corresponding breathing conditions. However, care must be taken when extrapolating a given dosage as considerable differences were noted in the regional particle deposition pattern. Combined with the deposition model, the particle retention and clearance kinetics of deposited nanoparticles indicates that the clearance rate from the mouse lung is higher than that in the human lung. In summary, the presented computer simulation models provide detailed fluid-particle dynamics results for upper lung airways of representative human and mouse models with a comparative analysis of particle lung deposition data, including a novel mice-to-men correlation as well as a particle-clearance analysis both useful for pharmacokinetic and toxicokinetic studies.
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Affiliation(s)
- Arun V Kolanjiyil
- Department of Mechanical & Aerospace Engineering, North Carolina State University, Raleigh, NC 27695-7910, United States
| | - Clement Kleinstreuer
- Department of Mechanical & Aerospace Engineering, North Carolina State University, Raleigh, NC 27695-7910, United States; Joint UNC-NCSU Department of Biomedical Engineering, North Carolina State University, Raleigh, NC 27695-7910, United States.
| | - Nicole C Kleinstreuer
- National Institute of Environmental Health Sciences (NIEHS), National Toxicology Program Interagency Center for Evaluation of Alternative Toxicological, Methods (NICEATM), United States
| | - Wellington Pham
- Department of Radiology and Radiological Sciences, Vanderbilt University, Institute of Imaging Science, United States
| | - Ruxana T Sadikot
- Division of Pulmonary, Allergy and Critical Care Medicine, Emory University, School of Medicine, United States; Department of Veterans Affairs, Atlanta VAMC, United States
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Kleinstreuer NC, Karmaus A, Mansouri K, Allen DG, Fitzpatrick JM, Patlewicz G. Predictive Models for Acute Oral Systemic Toxicity: A Workshop to Bridge the Gap from Research to Regulation. ACTA ACUST UNITED AC 2018; 8:21-24. [PMID: 30320239 DOI: 10.1016/j.comtox.2018.08.002] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
In early 2018, the Interagency Coordinating Committee for the Validation of Alternative Methods (ICCVAM) published the "Strategic Roadmap for Establishing New Approaches to Evaluate the Safety of Chemicals and Medical Products in the United States" (ICCVAM 2018). Cross-agency federal workgroups have been established to implement this roadmap for various toxicological testing endpoints, with an initial focus on acute toxicity testing. The ICCVAM acute toxicity workgroup (ATWG) helped organize a global collaboration to build predictive in silico models for acute oral systemic toxicity, based on a large dataset of rodent studies and targeted towards regulatory needs identified across federal agencies. Thirty-two international groups across government, industry, and academia participated in the project, culminating in a workshop in April 2018 held at the National Institutes of Health (NIH). At the workshop, computational modelers and regulatory decision makers met to discuss the feasibility of using predictive model outputs for regulatory use in lieu of acute oral systemic toxicity testing. The models were combined to yield consensus predictions which demonstrated excellent performance when compared to the animal data, and workshop outcomes and follow-up activities to make these tools available and put them into practice are discussed here.
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Affiliation(s)
- Nicole C Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
| | - Agnes Karmaus
- Integrated Laboratory Systems, Inc., Research Triangle Park, North Carolina 27560, United States
| | - Kamel Mansouri
- Integrated Laboratory Systems, Inc., Research Triangle Park, North Carolina 27560, United States
| | - David G Allen
- Integrated Laboratory Systems, Inc., Research Triangle Park, North Carolina 27560, United States
| | - Jeremy M Fitzpatrick
- National Center for Computational Toxicology (NCCT), Office of Research and Development, US Environmental Protection Agency, 109 TW Alexander Dr, Research Triangle Park (RTP), NC 27711, USA
| | - Grace Patlewicz
- National Center for Computational Toxicology (NCCT), Office of Research and Development, US Environmental Protection Agency, 109 TW Alexander Dr, Research Triangle Park (RTP), NC 27711, USA
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Kleinstreuer NC, Browne P, Chang X, Judson R, Casey W, Ceger P, Deisenroth C, Baker N, Markey K, Thomas RS. Evaluation of androgen assay results using a curated Hershberger database. Reprod Toxicol 2018; 81:272-280. [PMID: 30205137 PMCID: PMC7171594 DOI: 10.1016/j.reprotox.2018.08.017] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Revised: 07/25/2018] [Accepted: 08/23/2018] [Indexed: 12/18/2022]
Abstract
A set of 39 reference chemicals with reproducible androgen pathway effects in vivo, identified in the companion manuscript [1], were used to interrogate the performance of the ToxCast/Tox 21 androgen receptor (AR) model based on 11 high throughput assays. Cytotoxicity data and specificity confirmation assays were used to distinguish assay loss-of-function from true antagonistic signaling suppression. Overall agreement was 66% (19/29), with ten additional inconclusive chemicals. Most discrepancies were explained using in vitro to in vivo extrapolation to estimate equivalent administered doses. The AR model had 100% positive predictive value for the in vivo response, i.e. there were no false positives, and chemicals with conclusive AR model results (agonist or antagonist) were consistently positive in vivo. Considering the lack of reproducibility of the in vivo Hershberger assay, the in vitro AR model may better predict specific AR interaction and can rapidly and cost-effectively screen thousands of chemicals without using animals.
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43
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Browne P, Kleinstreuer NC, Ceger P, Deisenroth C, Baker N, Markey K, Thomas RS, Judson RJ, Casey W. Development of a curated Hershberger database. Reprod Toxicol 2018; 81:259-271. [PMID: 30205136 DOI: 10.1016/j.reprotox.2018.08.016] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Revised: 07/20/2018] [Accepted: 08/23/2018] [Indexed: 01/17/2023]
Abstract
A systematic literature review was conducted to identify Hershberger bioassays for ∼3200 chemicals including those used to validate the OECD/US EPA guideline assay, US EPA's chemicals screened for endocrine activity, and the library of chemicals run in US EPA 's ToxCast in vitro assays. For 134 chemicals that met pre-defined criteria, experimental results were extracted into a database used to characterize uncertainty in results and evaluate the concordance of the Hershberger assay with other in vivo rodent studies that measure androgen-responsive endpoints. Of 25 chemicals tested in >1 Hershberger study, 28% had disagreements between studies (i.e. ≥1 positive and ≥1 negative study), and of the 65 chemicals tested in Hershberger studies and other in vivo studies with androgen-responsive endpoints, 43% indicated disagreements, though in some cases these may be explained by differences in study designs or physiology of the animal model. Ultimately, 49 chemicals were identified with reproducible androgen pathway responses confirmed in ≥2 in vivo rodent studies that could be considered reference chemicals useful for validating alternative methods.
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Affiliation(s)
| | | | | | | | | | | | | | | | - W Casey
- NIH/NIEHS/DNTP/NICEATM, RTP, NC, USA
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44
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Casey WM, Chang X, Allen DG, Ceger PC, Choksi NY, Hsieh JH, Wetmore BA, Ferguson SS, DeVito MJ, Sprankle CS, Kleinstreuer NC. Evaluation and Optimization of Pharmacokinetic Models for in Vitro to in Vivo Extrapolation of Estrogenic Activity for Environmental Chemicals. Environ Health Perspect 2018; 126:97001. [PMID: 30192161 PMCID: PMC6375436 DOI: 10.1289/ehp1655] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
BACKGROUND To effectively incorporate in vitro data into regulatory use, confidence must be established in the quantitative extrapolation of in vitro activity to relevant end points in animals or humans. OBJECTIVE Our goal was to evaluate and optimize in vitro to in vivo extrapolation (IVIVE) approaches using in vitro estrogen receptor (ER) activity to predict estrogenic effects measured in rodent uterotrophic studies. METHODS We evaluated three pharmacokinetic (PK) models with varying complexities to extrapolate in vitro to in vivo dosimetry for a group of 29 ER agonists, using data from validated in vitro [U.S. Environmental Protection Agency (U.S. EPA) ToxCast™ ER model] and in vivo (uterotrophic) methods. In vitro activity values were adjusted using mass-balance equations to estimate intracellular exposure via an enrichment factor (EF), and steady-state model calculations were adjusted using fraction of unbound chemical in the plasma ([Formula: see text]) to approximate bioavailability. Accuracy of each model-adjustment combination was assessed by comparing model predictions with lowest effect levels (LELs) from guideline uterotrophic studies. RESULTS We found little difference in model predictive performance based on complexity or route-specific modifications. Simple adjustments, applied to account for in vitro intracellular exposure (EF) or chemical bioavailability ([Formula: see text]), resulted in significant improvements in the predictive performance of all models. CONCLUSION Computational IVIVE approaches accurately estimate chemical exposure levels that elicit positive responses in the rodent uterotrophic bioassay. The simplest model had the best overall performance for predicting both oral (PPK_EF) and injection (PPK_[Formula: see text]) LELs from guideline uterotrophic studies, is freely available, and can be parameterized entirely using freely available in silico tools. https://doi.org/10.1289/EHP1655.
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Affiliation(s)
- Warren M Casey
- National Toxicology Program Division, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina, USA
| | - Xiaoqing Chang
- Integrated Laboratory Systems, Inc., Morrisville, North Carolina, USA
| | - David G Allen
- Integrated Laboratory Systems, Inc., Morrisville, North Carolina, USA
| | - Patricia C Ceger
- Integrated Laboratory Systems, Inc., Morrisville, North Carolina, USA
| | - Neepa Y Choksi
- Integrated Laboratory Systems, Inc., Morrisville, North Carolina, USA
| | - Jui-Hua Hsieh
- Kelly Government Solutions, Research Triangle Park, North Carolina, USA
| | | | - Stephen S Ferguson
- National Toxicology Program Division, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina, USA
| | - Michael J DeVito
- National Toxicology Program Division, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina, USA
| | | | - Nicole C Kleinstreuer
- National Toxicology Program Division, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina, USA
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45
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Judson RS, Paul Friedman K, Houck K, Mansouri K, Browne P, Kleinstreuer NC. New approach methods for testing chemicals for endocrine disruption potential. Current Opinion in Toxicology 2018. [DOI: 10.1016/j.cotox.2018.10.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Kleinstreuer NC, Hoffmann S, Alépée N, Allen D, Ashikaga T, Casey W, Clouet E, Cluzel M, Desprez B, Gellatly N, Göbel C, Kern PS, Klaric M, Kühnl J, Martinozzi-Teissier S, Mewes K, Miyazawa M, Strickland J, van Vliet E, Zang Q, Petersohn D. Non-animal methods to predict skin sensitization (II): an assessment of defined approaches *. Crit Rev Toxicol 2018; 48:359-374. [PMID: 29474122 PMCID: PMC7393691 DOI: 10.1080/10408444.2018.1429386] [Citation(s) in RCA: 115] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Revised: 12/11/2017] [Accepted: 01/03/2018] [Indexed: 10/18/2022]
Abstract
Skin sensitization is a toxicity endpoint of widespread concern, for which the mechanistic understanding and concurrent necessity for non-animal testing approaches have evolved to a critical juncture, with many available options for predicting sensitization without using animals. Cosmetics Europe and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods collaborated to analyze the performance of multiple non-animal data integration approaches for the skin sensitization safety assessment of cosmetics ingredients. The Cosmetics Europe Skin Tolerance Task Force (STTF) collected and generated data on 128 substances in multiple in vitro and in chemico skin sensitization assays selected based on a systematic assessment by the STTF. These assays, together with certain in silico predictions, are key components of various non-animal testing strategies that have been submitted to the Organization for Economic Cooperation and Development as case studies for skin sensitization. Curated murine local lymph node assay (LLNA) and human skin sensitization data were used to evaluate the performance of six defined approaches, comprising eight non-animal testing strategies, for both hazard and potency characterization. Defined approaches examined included consensus methods, artificial neural networks, support vector machine models, Bayesian networks, and decision trees, most of which were reproduced using open source software tools. Multiple non-animal testing strategies incorporating in vitro, in chemico, and in silico inputs demonstrated equivalent or superior performance to the LLNA when compared to both animal and human data for skin sensitization.
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Affiliation(s)
- Nicole C. Kleinstreuer
- NIH/NIEHS/DNTP/NICEATM, P.O. Box 12233, Mail Stop K2-16, Research Triangle Park, NC, 27709, USA; NK, 1-919-541-7997,; WC, 1-919-316-4729,
| | - Sebastian Hoffmann
- seh consulting + services, Stembergring 15, 33106 Paderborn, Germany; +4952518700566;
| | - Nathalie Alépée
- L’Oréal Research & Innovation, Aulnay-sous-Bois, France; NA, ; SM-T,
| | - David Allen
- ILS, P.O. Box 13501, Research Triangle Park, NC, 27709, USA, 1-919-281-1110; DA, ; JS, ; QZ,
| | - Takao Ashikaga
- Shiseido, 2-2-1, Hayabuchi, Tsuzuki-ku, Yokohama-shi, Kanagawa 224-8558, Japan. Current Address: Japanese Center for the Validation of Alternative Methods (JaCVAM), National Institute of Health Sciences (NIHS) 1-18-1 Kamiyoga, Setagaya, Tokyo, Japan;
| | - Warren Casey
- NIH/NIEHS/DNTP/NICEATM, P.O. Box 12233, Mail Stop K2-16, Research Triangle Park, NC, 27709, USA; NK, 1-919-541-7997,; WC, 1-919-316-4729,
| | - Elodie Clouet
- Pierre Fabre, 3 Avenue Hubert Curien, 31100 Toulouse, France;
| | - Magalie Cluzel
- LVMH, 185 avenue de Verdun, 45804 St Jean de Braye, France;
| | - Bertrand Desprez
- Cosmetics Europe, Avenue Herrmann Debroux 40, 1160 Brussels, Belgium; BD, ; MK,
| | - Nichola Gellatly
- Unilever, Colworth Science Park, Bedford, United Kingdom. Current address: NC3Rs, Gibbs Building, 215 Euston Road, London NW1 2BE, United Kingdom;
| | | | - Petra S. Kern
- Procter & Gamble Services Company NV, Temselaan 100, 1853 Strombeek-Bever, Belgium;
| | - Martina Klaric
- Cosmetics Europe, Avenue Herrmann Debroux 40, 1160 Brussels, Belgium; BD, ; MK,
| | - Jochen Kühnl
- Beiersdorf AG, Unnastraße 48, 20245 Hamburg, Germany;
| | | | - Karsten Mewes
- Henkel AG & Co. KGaA, Henkelstraße 67, 40589 Düsseldorf, Germany; KM, ; DP,
| | - Masaaki Miyazawa
- Kao Corporation, 2606 Akabane, Ichikai, Haga, Tochigi, 321-3497, Japan;
| | - Judy Strickland
- ILS, P.O. Box 13501, Research Triangle Park, NC, 27709, USA, 1-919-281-1110; DA, ; JS, ; QZ,
| | - Erwin van Vliet
- Services & Consultations on Alternative Methods (SeCAM), Via Campagnora 1, 6983, Magliaso, Switzerland;
| | - Qingda Zang
- ILS, P.O. Box 13501, Research Triangle Park, NC, 27709, USA, 1-919-281-1110; DA, ; JS, ; QZ,
| | - Dirk Petersohn
- Henkel AG & Co. KGaA, Henkelstraße 67, 40589 Düsseldorf, Germany; KM, ; DP,
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Bell SM, Chang X, Wambaugh JF, Allen DG, Bartels M, Brouwer KLR, Casey WM, Choksi N, Ferguson SS, Fraczkiewicz G, Jarabek AM, Ke A, Lumen A, Lynn SG, Paini A, Price PS, Ring C, Simon TW, Sipes NS, Sprankle CS, Strickland J, Troutman J, Wetmore BA, Kleinstreuer NC. In vitro to in vivo extrapolation for high throughput prioritization and decision making. Toxicol In Vitro 2017; 47:213-227. [PMID: 29203341 DOI: 10.1016/j.tiv.2017.11.016] [Citation(s) in RCA: 138] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2017] [Revised: 11/28/2017] [Accepted: 11/30/2017] [Indexed: 01/10/2023]
Abstract
In vitro chemical safety testing methods offer the potential for efficient and economical tools to provide relevant assessments of human health risk. To realize this potential, methods are needed to relate in vitro effects to in vivo responses, i.e., in vitro to in vivo extrapolation (IVIVE). Currently available IVIVE approaches need to be refined before they can be utilized for regulatory decision-making. To explore the capabilities and limitations of IVIVE within this context, the U.S. Environmental Protection Agency Office of Research and Development and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods co-organized a workshop and webinar series. Here, we integrate content from the webinars and workshop to discuss activities and resources that would promote inclusion of IVIVE in regulatory decision-making. We discuss properties of models that successfully generate predictions of in vivo doses from effective in vitro concentration, including the experimental systems that provide input parameters for these models, areas of success, and areas for improvement to reduce model uncertainty. Finally, we provide case studies on the uses of IVIVE in safety assessments, which highlight the respective differences, information requirements, and outcomes across various approaches when applied for decision-making.
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Affiliation(s)
- Shannon M Bell
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA.
| | - Xiaoqing Chang
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA.
| | - John F Wambaugh
- U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Research Triangle Park, NC 27709, USA.
| | - David G Allen
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA.
| | | | - Kim L R Brouwer
- UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Campus Box 7569, Chapel Hill, NC 27599, USA.
| | - Warren M Casey
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, USA.
| | - Neepa Choksi
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA.
| | - Stephen S Ferguson
- National Toxicology Program, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, USA.
| | | | - Annie M Jarabek
- U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Research Triangle Park, NC 27709, USA.
| | - Alice Ke
- Simcyp Limited (a Certara company), John Street, Sheffield, S2 4SU, United Kingdom.
| | - Annie Lumen
- National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079, USA.
| | - Scott G Lynn
- U.S. Environmental Protection Agency, William Jefferson Clinton Building, 1200 Pennsylvania Ave. NW, Washington, DC 20460, USA.
| | - Alicia Paini
- European Commission, Joint Research Centre, Directorate Health, Consumers and Reference Materials, Chemical Safety and Alternative Methods Unit incorporating EURL ECVAM, Via E. Fermi 2749, Ispra, Varese 20127, Italy.
| | - Paul S Price
- U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Research Triangle Park, NC 27709, USA.
| | - Caroline Ring
- Oak Ridge Institute for Science and Education, P.O. Box 2008, Oak Ridge, TN 37831, USA.
| | - Ted W Simon
- Ted Simon LLC, 4184 Johnston Road, Winston, GA 30187, USA.
| | - Nisha S Sipes
- National Toxicology Program, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, USA.
| | - Catherine S Sprankle
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA.
| | - Judy Strickland
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA.
| | - John Troutman
- Central Product Safety, The Procter & Gamble Company, Cincinnati, OH 45202, USA.
| | - Barbara A Wetmore
- ScitoVation LLC, 6 Davis Drive, Research Triangle Park, NC 27709, USA.
| | - Nicole C Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, USA.
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48
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Lynch C, Sakamuru S, Huang R, Stavreva DA, Varticovski L, Hager GL, Judson RS, Houck KA, Kleinstreuer NC, Casey W, Paules RS, Simeonov A, Xia M. Identifying environmental chemicals as agonists of the androgen receptor by using a quantitative high-throughput screening platform. Toxicology 2017; 385:48-58. [PMID: 28478275 PMCID: PMC6135100 DOI: 10.1016/j.tox.2017.05.001] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2016] [Revised: 03/27/2017] [Accepted: 05/03/2017] [Indexed: 01/08/2023]
Abstract
The androgen receptor (AR, NR3C4) is a nuclear receptor whose main function is acting as a transcription factor regulating gene expression for male sexual development and maintaining accessory sexual organ function. It is also a necessary component of female fertility by affecting the functionality of ovarian follicles and ovulation. Pathological processes involving AR include Kennedy's disease and Klinefelter's syndrome, as well as prostate, ovarian, and testicular cancer. Strict regulation of sex hormone signaling is required for normal reproductive organ development and function. Therefore, testing small molecules for their ability to modulate AR is a first step in identifying potential endocrine disruptors. We screened the Tox21 10K compound library in a quantitative high-throughput format to identify activators of AR using two reporter gene cell lines, AR β-lactamase (AR-bla) and AR-luciferase (AR-luc). Seventy-five compounds identified through the primary assay were characterized as potential agonists or inactives through confirmation screens and secondary assays. Biochemical binding and AR nuclear translocation assays were performed to confirm direct binding and activation of AR from these compounds. The top seventeen compounds identified were found to bind to AR, and sixteen of them translocated AR from the cytoplasm into the nucleus. Five potentially novel or not well-characterized AR agonists were discovered through primary and follow-up studies. We have identified multiple AR activators, including known AR agonists such as testosterone, as well as novel/not well-known compounds such as prulifloxacin. The information gained from the current study can be directly used to prioritize compounds for further in-depth toxicological evaluations, as well as their potential to disrupt the endocrine system via AR activation.
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Affiliation(s)
- Caitlin Lynch
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
| | - Srilatha Sakamuru
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
| | - Ruili Huang
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
| | - Diana A Stavreva
- Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lyuba Varticovski
- Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Gordon L Hager
- Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Richard S Judson
- National Center for Computational Toxicology, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Keith A Houck
- National Center for Computational Toxicology, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Nicole C Kleinstreuer
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health,Research Triangle Park, NC, USA
| | - Warren Casey
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health,Research Triangle Park, NC, USA
| | - Richard S Paules
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health,Research Triangle Park, NC, USA
| | - Anton Simeonov
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
| | - Menghang Xia
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA.
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49
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Bell SM, Phillips J, Sedykh A, Tandon A, Sprankle C, Morefield SQ, Shapiro A, Allen D, Shah R, Maull EA, Casey WM, Kleinstreuer NC. An Integrated Chemical Environment to Support 21st-Century Toxicology. Environ Health Perspect 2017; 125:054501. [PMID: 28557712 PMCID: PMC5644972 DOI: 10.1289/ehp1759] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 02/10/2017] [Accepted: 02/12/2017] [Indexed: 05/06/2023]
Abstract
SUMMARY: Access to high-quality reference data is essential for the development, validation, and implementation of in vitro and in silico approaches that reduce and replace the use of animals in toxicity testing. Currently, these data must often be pooled from a variety of disparate sources to efficiently link a set of assay responses and model predictions to an outcome or hazard classification. To provide a central access point for these purposes, the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods developed the Integrated Chemical Environment (ICE) web resource. The ICE data integrator allows users to retrieve and combine data sets and to develop hypotheses through data exploration. Open-source computational workflows and models will be available for download and application to local data. ICE currently includes curated in vivo test data, reference chemical information, in vitro assay data (including Tox21TM/ToxCast™ high-throughput screening data), and in silico model predictions. Users can query these data collections focusing on end points of interest such as acute systemic toxicity, endocrine disruption, skin sensitization, and many others. ICE is publicly accessible at https://ice.ntp.niehs.nih.gov. https://doi.org/10.1289/EHP1759.
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Affiliation(s)
- Shannon M Bell
- Integrated Laboratory Systems, Inc. (ILS), Research Triangle Park, North Carolina, USA
| | | | | | - Arpit Tandon
- Sciome, Research Triangle Park, North Carolina, USA
| | - Catherine Sprankle
- Integrated Laboratory Systems, Inc. (ILS), Research Triangle Park, North Carolina, USA
| | - Stephen Q Morefield
- Integrated Laboratory Systems, Inc. (ILS), Research Triangle Park, North Carolina, USA
| | - Andy Shapiro
- Program Operations Branch, National Toxicology Program (NTP), National Institute of Environmental Health Sciences (NIEHS), National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Research Triangle Park, North Carolina, USA
| | - David Allen
- Integrated Laboratory Systems, Inc. (ILS), Research Triangle Park, North Carolina, USA
| | - Ruchir Shah
- Sciome, Research Triangle Park, North Carolina, USA
| | - Elizabeth A Maull
- NTP Interagency Center for the Evaluation of Alternative Toxicological Methods, NTP, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, USA
| | - Warren M Casey
- NTP Interagency Center for the Evaluation of Alternative Toxicological Methods, NTP, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, USA
| | - Nicole C Kleinstreuer
- NTP Interagency Center for the Evaluation of Alternative Toxicological Methods, NTP, NIEHS, NIH, DHHS, Research Triangle Park, North Carolina, USA
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50
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Zang Q, Mansouri K, Williams AJ, Judson RS, Allen DG, Casey WM, Kleinstreuer NC. In Silico Prediction of Physicochemical Properties of Environmental Chemicals Using Molecular Fingerprints and Machine Learning. J Chem Inf Model 2017; 57:36-49. [PMID: 28006899 PMCID: PMC6131700 DOI: 10.1021/acs.jcim.6b00625] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
There are little available toxicity data on the vast majority of chemicals in commerce. High-throughput screening (HTS) studies, such as those being carried out by the U.S. Environmental Protection Agency (EPA) ToxCast program in partnership with the federal Tox21 research program, can generate biological data to inform models for predicting potential toxicity. However, physicochemical properties are also needed to model environmental fate and transport, as well as exposure potential. The purpose of the present study was to generate an open-source quantitative structure-property relationship (QSPR) workflow to predict a variety of physicochemical properties that would have cross-platform compatibility to integrate into existing cheminformatics workflows. In this effort, decades-old experimental property data sets available within the EPA EPI Suite were reanalyzed using modern cheminformatics workflows to develop updated QSPR models capable of supplying computationally efficient, open, and transparent HTS property predictions in support of environmental modeling efforts. Models were built using updated EPI Suite data sets for the prediction of six physicochemical properties: octanol-water partition coefficient (logP), water solubility (logS), boiling point (BP), melting point (MP), vapor pressure (logVP), and bioconcentration factor (logBCF). The coefficient of determination (R2) between the estimated values and experimental data for the six predicted properties ranged from 0.826 (MP) to 0.965 (BP), with model performance for five of the six properties exceeding those from the original EPI Suite models. The newly derived models can be employed for rapid estimation of physicochemical properties within an open-source HTS workflow to inform fate and toxicity prediction models of environmental chemicals.
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Affiliation(s)
- Qingda Zang
- Integrated Laboratory Systems, Inc., Research Triangle Park, NC 27709, USA
| | - Kamel Mansouri
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Antony J. Williams
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Richard S. Judson
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - David G. Allen
- Integrated Laboratory Systems, Inc., Research Triangle Park, NC 27709, USA
| | - Warren M. Casey
- National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
| | - Nicole C. Kleinstreuer
- National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA
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