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Najjar A, Lange D, Géniès C, Kuehnl J, Zifle A, Jacques C, Fabian E, Hewitt N, Schepky A. Development and validation of PBPK models for genistein and daidzein for use in a next-generation risk assessment. Front Pharmacol 2024; 15:1421650. [PMID: 39421667 PMCID: PMC11483610 DOI: 10.3389/fphar.2024.1421650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 08/30/2024] [Indexed: 10/19/2024] Open
Abstract
Introduction All cosmetic ingredients must be evaluated for their safety to consumers. In the absence of in vivo data, systemic concentrations of ingredients can be predicted using Physiologically based Pharmacokinetic (PBPK) models. However, more examples are needed to demonstrate how they can be validated and applied in Next-Generation Risk Assessments (NGRA) of cosmetic ingredients. We used a bottom-up approach to develop human PBPK models for genistein and daidzein for a read-across NGRA, whereby genistein was the source chemical for the target chemical, daidzein. Methods An oral rat PBPK model for genistein was built using PK-Sim® and in vitro ADME input data. This formed the basis of the daidzein oral rat PBPK model, for which chemical-specific input parameters were used. Rat PBPK models were then converted to human models using human-specific physiological parameters and human in vitro ADME data. In vitro skin metabolism and penetration data were used to build the dermal module to represent the major route of exposure to cosmetics. Results The initial oral rat model for genistein was qualified since it predicted values within 2-fold of measured in vivo PK values. This was used to predict plasma concentrations from the in vivo NOAEL for genistein to set test concentrations in bioassays. Intrinsic hepatic clearance and unbound fractions in plasma were identified as sensitive parameters impacting the predicted Cmax values. Sensitivity and uncertainty analyses indicated the developed PBPK models had a moderate level of confidence. An important aspect of the development of the dermal module was the implementation of first-pass metabolism, which was extensive for both chemicals. The final human PBPK model for daidzein was used to convert the in vitro PoD of 33 nM (from an estrogen receptor transactivation assay) to an external dose of 0.2% in a body lotion formulation. Conclusion PBPK models for genistein and daidzein were developed as a central component of an NGRA read-across case study. This will help to gain regulatory confidence in the use of PBPK models, especially for cosmetic ingredients.
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Affiliation(s)
| | | | - C. Géniès
- Pierre Fabre Dermo-Cosmétique and Personal Care, Toulouse, France
| | | | - A. Zifle
- Kao Germany GmbH, Darmstadt, Germany
| | - C. Jacques
- Pierre Fabre Dermo-Cosmétique and Personal Care, Toulouse, France
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Crizer DM, Rice JR, Smeltz MG, Lavrich KS, Ravindra K, Wambaugh JF, DeVito M, Wetmore BA. In Vitro Hepatic Clearance Evaluations of Per- and Polyfluoroalkyl Substances (PFAS) across Multiple Structural Categories. TOXICS 2024; 12:672. [PMID: 39330600 PMCID: PMC11435625 DOI: 10.3390/toxics12090672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2024] [Revised: 09/06/2024] [Accepted: 09/10/2024] [Indexed: 09/28/2024]
Abstract
Toxicokinetic (TK) assays and in vitro-in vivo extrapolation (IVIVE) models are New Approach Methods (NAMs) used to translate in vitro points of departure to exposure estimates required to reach equivalent blood concentrations. Per- and polyfluoroalkyl substances (PFAS) are a large chemical class with wide-ranging industrial applications for which only limited toxicity data are available for human health evaluation. To address the lack of TK data, a pooled primary human hepatocyte suspension model was used with targeted liquid chromatography-mass spectrometry to investigate substrate depletion for 54 PFAS. A median value of 4.52 μL/(min x million cells) was observed across those that showed significant clearance, with 35 displaying no substrate depletion. Bayesian modeling propagated uncertainty around clearance values for use in IVIVE models. Structural evaluations showed the fluorotelomer carboxylic acids were the only PFAS carboxylates showing appreciable clearance, and per- and polyfluorosulfonamides were more readily metabolized than other PFAS sulfonates. Biotransformation product prediction, using the chemical transformation simulator, suggested hydrolysis of PFAS sulfonamides to more stable sulfonic acids, which is an important consideration for exposure modeling. This effort greatly expands the PFAS in vitro toxicokinetic dataset, enabling refined TK modeling, in silico tool development, and NAM-based human health evaluations across this important set of emerging contaminants.
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Affiliation(s)
- David M Crizer
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27711, USA
| | - Julie R Rice
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27711, USA
| | - Marci G Smeltz
- Center for Public Health and Environmental Assessment, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Katelyn S Lavrich
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27711, USA
| | | | - John F Wambaugh
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Michael DeVito
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Barbara A Wetmore
- Center for Computational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
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Wang S, Zhang Z, Saunders LJ, Li D, Li L. Understanding the Impacts of Presystemic Metabolism on the Human Oral Bioavailability of Chemicals. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024. [PMID: 39083806 DOI: 10.1021/acs.est.4c03344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
Animal-free new approach methods promote chemical assessments based on the comparison between in vitro bioactivity and human internal concentrations, which necessitates a dependable knowledge of human oral bioavailability, i.e., the fraction of an orally ingested chemical that escapes from presystemic ("first-pass") metabolic processes and eventually enters systemic circulation. Using a physiologically based toxicokinetic model, we show how human oral bioavailability is impacted by presystemic metabolism within the gut lumen, gut wall, and liver and how this impact differs among chemicals with various permeability and stability properties. Our results highlight the gut lumen as a primary site of presystemic metabolism of certain chemicals, such as di-2-ethylhexyl phthalate (DEHP), for which the gut lumen may even exceed the liver in importance of presystemic metabolism due to these metabolic processes occurring in sequence. For chemicals with low transmembrane permeability and low stability, metabolism within the gut lumen is the most remarkable of the three presystemic metabolic processes. Notably, for chemicals that undergo substantial metabolism within the gut lumen, where the metabolites have high permeability, there is a notable discrepancy between the "theoretical bioavailability" (bioavailability of the unchanged parent compound) and the "apparent bioavailability" in measurement practices (bioavailability inferred from measured metabolites). Our work highlights the importance of considering presystemic metabolism, notably within the gut lumen, in human exposure and toxicokinetic modeling.
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Affiliation(s)
- Shenghong Wang
- School of Public Health, University of Nevada, Reno, 1664 North Virginia Street, Reno, Nevada 89557-274, United States
| | - Zhizhen Zhang
- School of Public Health, University of Nevada, Reno, 1664 North Virginia Street, Reno, Nevada 89557-274, United States
| | - Leslie J Saunders
- Department of Physical and Environmental Sciences, University of Toronto Scarborough, 1265 Military Trail, Toronto, Ontario M1C 1A4, Canada
| | - Dingsheng Li
- School of Public Health, University of Nevada, Reno, 1664 North Virginia Street, Reno, Nevada 89557-274, United States
| | - Li Li
- School of Public Health, University of Nevada, Reno, 1664 North Virginia Street, Reno, Nevada 89557-274, United States
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4
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Bianchi E, Costa E, Harrill J, Deford P, LaRocca J, Chen W, Sutake Z, Lehman A, Pappas-Garton A, Sherer E, Moreillon C, Sriram S, Dhroso A, Johnson K. Discovery Phase Agrochemical Predictive Safety Assessment Using High Content In Vitro Data to Estimate an In Vivo Toxicity Point of Departure. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024. [PMID: 39033510 DOI: 10.1021/acs.jafc.4c03094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/23/2024]
Abstract
Utilization of in vitro (cellular) techniques, like Cell Painting and transcriptomics, could provide powerful tools for agrochemical candidate sorting and selection in the discovery process. However, using these models generates challenges translating in vitro concentrations to the corresponding in vivo exposures. Physiologically based pharmacokinetic (PBPK) modeling provides a framework for quantitative in vitro to in vivo extrapolation (IVIVE). We tested whether in vivo (rat liver) transcriptomic and apical points of departure (PODs) could be accurately predicted from in vitro (rat hepatocyte or human HepaRG) transcriptomic PODs or HepaRG Cell Painting PODs using PBPK modeling. We compared two PBPK models, the ADMET predictor and the httk R package, and found httk to predict the in vivo PODs more accurately. Our findings suggest that a rat liver apical and transcriptomic POD can be estimated utilizing a combination of in vitro transcriptome-based PODs coupled with PBPK modeling for IVIVE. Thus, high content in vitro data can be translated with modest accuracy to in vivo models of ultimate regulatory importance to help select agrochemical analogs in early stage discovery program.
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Affiliation(s)
- Enrica Bianchi
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | | | - Joshua Harrill
- Center for Computational Toxicology and Exposure, United States Environmental Protection Agency, Research Triangle Park ,North Carolina 27709, United States
| | - Paul Deford
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Jessica LaRocca
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Wei Chen
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Zachary Sutake
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Audrey Lehman
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | | | - Eric Sherer
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | | | | | - Andi Dhroso
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
| | - Kamin Johnson
- Corteva Agriscience, Indianapolis ,Indiana 46268, United States
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Azizah RN, Verheyen GR, Shkedy Z, Van Miert S. Overview of in vitro-in vivo extrapolation approaches for the risk assessment of nanomaterial toxicity. NANOIMPACT 2024; 35:100524. [PMID: 39059748 DOI: 10.1016/j.impact.2024.100524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 06/23/2024] [Accepted: 07/21/2024] [Indexed: 07/28/2024]
Abstract
Nanomaterials are increasingly used in many applications due to their enhanced properties. To ensure their safety for humans and the environment, nanomaterials need to be evaluated for their potential risk. The risk assessment analysis on the nanomaterials based on animal or in vivo studies is accompanied by several concerns, including animal welfare, time and cost needed for the studies. Therefore, incorporating in vitro studies in the risk assessment process is increasingly considered. To be able to analyze the potential risk of nanomaterial to human health, there are factors to take into account. Utilizing in vitro data in the risk assessment analysis requires methods that can be used to translate in vitro data to predict in vivo phenomena (in vitro-in vivo extrapolation (IVIVE) methods) to be incorporated, to obtain a more accurate result. Apart from the experiments and species conversion (for example, translation between the cell culture, animal and human), the challenge also includes the unique properties of nanomaterials that might cause them to behave differently compared to the same materials in a bulk form. This overview presents the IVIVE techniques that are developed to extrapolate pharmacokinetics data or doses. A brief example of the IVIVE methods for chemicals is provided, followed by a more detailed summary of available IVIVE methods applied to nanomaterials. The IVIVE techniques discussed include the comparison between in vitro and in vivo studies, methods to rene the dose metric or the in vitro models, allometric approach, mechanistic modeling, Multiple-Path Particle Dosimetry (MPPD), methods using organ burden data and also approaches that are currently being developed.
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Affiliation(s)
- Rahmasari Nur Azizah
- Thomas More University of Applied Sciences, Geel, Belgium; Data Science Institute, CenStat, I-BioStat, Hasselt University, Diepenbeek, Belgium.
| | | | - Ziv Shkedy
- Data Science Institute, CenStat, I-BioStat, Hasselt University, Diepenbeek, Belgium
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Liu S, Yan J, Xu B, Huang X, Qin H, Zhao J, Xia C, Yan S, Liu G. Fates and models for exposure pathways of pyrethroid pesticide residues: A review. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 277:116342. [PMID: 38657457 DOI: 10.1016/j.ecoenv.2024.116342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 04/04/2024] [Accepted: 04/15/2024] [Indexed: 04/26/2024]
Abstract
Pyrethroids (PYs) are widely applied pesticides whose residues pose potential health risks. This review describes current knowledge on PY chemical properties, usage patterns, environmental and food contamination, and human exposure models. It evaluates life cycle assessment (LCA), chemical alternatives assessment (CAA), and high-throughput screening (HTS) as tools for pesticide policy. Despite efforts to mitigate PY presence, their pervasive residues in the environment and food persist. And the highest concentrations ranged from 54,360 to 80,500 ng/L in water samples from agricultural fields. Food processing techniques variably reduce PY levels, yet no method guarantees complete elimination. This review provides insights into the fates and exposure pathways of PY residues in agriculture and food, and highlights the necessity for improved PY management and alternative practices to safeguard health and environment.
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Affiliation(s)
- Shan Liu
- Key Laboratory of Land Resources Evaluation and Monitoring in Southwest (Sichuan Normal University), Ministry of Education, Chengdu, Sichuan 610101, PR China; College of Life Science, Sichuan Normal University, Chengdu, Sichuan 610101, PR China
| | - Jisha Yan
- Key Laboratory of Land Resources Evaluation and Monitoring in Southwest (Sichuan Normal University), Ministry of Education, Chengdu, Sichuan 610101, PR China; College of Life Science, Sichuan Normal University, Chengdu, Sichuan 610101, PR China
| | - Bowen Xu
- Key Laboratory of Land Resources Evaluation and Monitoring in Southwest (Sichuan Normal University), Ministry of Education, Chengdu, Sichuan 610101, PR China; College of Life Science, Sichuan Normal University, Chengdu, Sichuan 610101, PR China
| | - Xinyi Huang
- Key Laboratory of Land Resources Evaluation and Monitoring in Southwest (Sichuan Normal University), Ministry of Education, Chengdu, Sichuan 610101, PR China; College of Life Science, Sichuan Normal University, Chengdu, Sichuan 610101, PR China
| | - Haixiong Qin
- College of Life Science, Sichuan Normal University, Chengdu, Sichuan 610101, PR China
| | - Jiayuan Zhao
- Key Laboratory of Land Resources Evaluation and Monitoring in Southwest (Sichuan Normal University), Ministry of Education, Chengdu, Sichuan 610101, PR China; College of Life Science, Sichuan Normal University, Chengdu, Sichuan 610101, PR China.
| | - Chen Xia
- Institute of Agro-Products Processing Science and Technology, Sichuan Academy of Agricultural Science, Chengdu, Sichuan 610066, PR China
| | - Shen Yan
- Staff Development Institute of China National Tobacco Corporation, Zhengzhou, Henan 450000, PR China
| | - Gang Liu
- Key Laboratory of Land Resources Evaluation and Monitoring in Southwest (Sichuan Normal University), Ministry of Education, Chengdu, Sichuan 610101, PR China; College of Life Science, Sichuan Normal University, Chengdu, Sichuan 610101, PR China.
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7
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Nicol B, Vandenbossche-Goddard E, Thorpe C, Newman R, Patel H, Yates D. A workflow to practically apply true dose considerations to in vitro testing for next generation risk assessment. Toxicology 2024; 505:153826. [PMID: 38719068 DOI: 10.1016/j.tox.2024.153826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 04/22/2024] [Accepted: 05/01/2024] [Indexed: 05/14/2024]
Abstract
With the move away from safety testing assessment based on data generated in experimental animals the concept of Next Generation Risk Assessment (NGRA) has arisen which instead uses data from in silico and in vitro models. A key uncertainty in risk assessment is the actual dose of test chemical at the target site, and therefore surrogate dose metrics, such as nominal concentration in test media are used to describe in vitro effect (or no-effect) doses. The reliability and accuracy of the risk assessment therefore depends largely on our ability to understand and characterise the relationship between the dose metrics used and the actual biologically effective dose at the target site. The objective of this publication is to use 40 case study chemicals to illustrate how in vitro dose considerations can be applied to characterise the "true dose" and build confidence in the understanding of the biologically effective dose in in vitro test systems for the determination e.g. points of departure (PoDs) for NGRA. We propose a workflow that can be applied to assess whether the nominal test concentration can be considered a conservative dose metric for use in NGRA. The workflow examines the implications of volatility, stability, hydrophobicity, binding to plastic and serum, solubility, and the potential use of in silico models for some of these parameters. For the majority of the case study chemicals we found that the use of nominal concentrations in risk assessment would result in conservative decision making. However, for serval chemicals a potential for underestimation of the risk in humans in vivo based on in vitro nominal effect concentrations was identified, and approaches for refinement by characterisation of the actual effect concentration are proposed.
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Affiliation(s)
- Beate Nicol
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedford, Bedfordshire MK44 1LQ, UK
| | - Evita Vandenbossche-Goddard
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedford, Bedfordshire MK44 1LQ, UK.
| | - Charlotte Thorpe
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedford, Bedfordshire MK44 1LQ, UK
| | | | - Hiral Patel
- Charles River Laboratories, Cambridgeshire CB10 1XL, UK
| | - Dawn Yates
- Charles River Laboratories, Cambridgeshire CB10 1XL, UK
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8
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Debad S, Allen D, Bandele O, Bishop C, Blaylock M, Brown P, Bunger MK, Co JY, Crosby L, Daniel AB, Ferguson SS, Ford K, Gamboa da Costa G, Gilchrist KH, Grogg MW, Gwinn M, Hartung T, Hogan SP, Jeong YE, Kass GE, Kenyon E, Kleinstreuer NC, Kujala V, Lundquist P, Matheson J, McCullough SD, Melton-Celsa A, Musser S, Oh I, Oyetade OB, Patil SU, Petersen EJ, Sadrieh N, Sayes CM, Scruggs BS, Tan YM, Thelin B, Nelson MT, Tarazona JV, Wambaugh JF, Yang JY, Yu C, Fitzpatrick S. Trust your gut: Establishing confidence in gastrointestinal models - An overview of the state of the science and contexts of use. ALTEX 2024; 41:402-424. [PMID: 38898799 PMCID: PMC11413798 DOI: 10.14573/altex.2403261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Indexed: 06/21/2024]
Abstract
The webinar series and workshop titled “Trust Your Gut: Establishing Confidence in Gastrointestinal Models – An Overview of the State of the Science and Contexts of Use” was co-organized by NICEATM, NIEHS, FDA, EPA, CPSC, DoD, and the Johns Hopkins Center for Alternatives to Animal Testing (CAAT) and hosted at the National Institutes of Health in Bethesda, MD, USA on October 11-12, 2023. New approach methods (NAMs) for assessing issues of gastrointestinal tract (GIT)- related toxicity offer promise in addressing some of the limitations associated with animal-based assessments. GIT NAMs vary in complexity, from two-dimensional monolayer cell line-based systems to sophisticated 3-dimensional organoid systems derived from human primary cells. Despite advances in GIT NAMs, challenges remain in fully replicating the complex interactions and processes occurring within the human GIT. Presentations and discussions addressed regulatory needs, challenges, and innovations in incorporating NAMs into risk assessment frameworks; explored the state of the science in using NAMs for evaluating systemic toxicity, understanding absorption and pharmacokinetics, evaluating GIT toxicity, and assessing potential allergenicity; and discussed strengths, limitations, and data gaps of GIT NAMs as well as steps needed to establish confidence in these models for use in the regulatory setting.
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Affiliation(s)
| | | | - Omari Bandele
- Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Colin Bishop
- Wake Forest Institute for Regenerative Medicine, Winston Salem, NC, USA
| | | | - Paul Brown
- Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | | | - Julia Y Co
- Complex in vitro Systems, Genentech Inc, South San Francisco, CA, USA
| | - Lynn Crosby
- Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | | | - Steve S Ferguson
- Mechanistic Toxicology Branch, Division of Translational Toxicology, NIEHS, National Institutes of Health, Bethesda, MD, USA
| | - Kevin Ford
- Office of Clinical Pharmacology, US Food and Drug Administration, Silver Spring, MD, USA
| | - Gonçalo Gamboa da Costa
- FDA National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA
| | - Kristin H Gilchrist
- 4D Bio³ Center for Biotechnology, Uniformed Services University, Bethesda, MD, USA
| | - Matthew W Grogg
- 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson AFB, OH, USA
| | - Maureen Gwinn
- U.S. Environmental Protection Agency, Office of Research and Development, RTP, NC, USA
| | - Thomas Hartung
- Johns Hopkins University, Bloomberg School of Public Health and Whiting School of Engineering, Doerenkamp-Zbinden-Chair for Evidence-based Toxicology, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
- University of Konstanz, CAAT-Europe, Konstanz, Germany
| | - Simon P Hogan
- Mary H. Weiser Food Allergy Center, Department of Pathology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Ye Eun Jeong
- Division of Applied Regulatory Science, Office of Clinical Pharmacology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA
| | | | - Elaina Kenyon
- U.S. Environmental Protection Agency, Office of Research and Development, RTP, NC, USA
| | | | | | | | | | | | - Angela Melton-Celsa
- Department of Microbiology and Immunology, Uniformed Services University, Bethesda, MD, USA
| | - Steven Musser
- Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Ilung Oh
- Toxicology Research Division, Ministry of Food and Drug Safety, National Institute of Food and Drug Safety Evaluation, Republic of Korea
| | | | - Sarita U Patil
- Divisions of Allergy and Clinical Immunology, Departments of Medicine and Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Elijah J Petersen
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nakissa Sadrieh
- Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Christie M Sayes
- Department of Environmental Science, Baylor University, Waco, TX, USA
| | | | - Yu-Mei Tan
- U.S. Environmental Protection Agency, Office of Pesticide Programs, Research Triangle Park, NC, USA
| | - Bill Thelin
- Altis Biosystems, Inc. Research Triangle Park, NC, USA
| | - M Tyler Nelson
- 711th Human Performance Wing, Air Force Research Laboratory, Wright-Patterson AFB, OH, USA
| | - José V Tarazona
- Spanish National Environmental Health Centre, Instituto de Salud Carlos III. Madrid, Spain
| | - John F Wambaugh
- U.S. Environmental Protection Agency, Office of Research and Development, RTP, NC, USA
| | - Jun-Young Yang
- Toxicology Research Division, Ministry of Food and Drug Safety, National Institute of Food and Drug Safety Evaluation, Cheongju, Republic of Korea
| | - Changwoo Yu
- Toxicology Research Division, Ministry of Food and Drug Safety, National Institute of Food and Drug Safety Evaluation, Cheongju, Republic of Korea
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Tsai HHD, Ford LC, Chen Z, Dickey AN, Wright FA, Rusyn I. Risk-based prioritization of PFAS using phenotypic and transcriptomic data from human induced pluripotent stem cell-derived hepatocytes and cardiomyocytes. ALTEX 2024; 41:363-381. [PMID: 38429992 PMCID: PMC11305846 DOI: 10.14573/altex.2311031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 02/20/2024] [Indexed: 03/03/2024]
Abstract
Per- and polyfluoroalkyl substances (PFAS) are chemicals with important applications; they are persistent in the environment and may pose human health hazards. Regulatory agencies are considering restrictions and bans of PFAS; however, little data exists for informed decisions. Several prioritization strategies were proposed for evaluation of potential hazards of PFAS. Structure-based grouping could expedite the selection of PFAS for testing; still, the hypothesis that structure-effect relationships exist for PFAS requires confirmation. We tested 26 structurally diverse PFAS from 8 groups using human induced pluripotent stem cell-derived hepatocytes and cardiomyocytes, and tested concentration-response effects on cell function and gene expression. Few phenotypic effects were observed in hepatocytes, but negative chronotropy was observed in cardiomyocytes for 8 PFAS. Substance- and cell type-dependent transcriptomic changes were more prominent but lacked substantial group-specific effects. In hepatocytes, we found upregulation of stress-related and extracellular matrix organization pathways, and down-regulation of fat metabolism. In cardiomyocytes, contractility-related pathways were most affected. We derived phenotypic and transcriptomic points of departure and compared them to predicted PFAS exposures. Conservative estimates for bioactivity and exposure were used to derive a bioactivity-to-exposure ratio (BER) for each PFAS; 23 of 26 PFAS had BER > 1. Overall, these data suggest that structure-based PFAS grouping may not be sufficient to predict their biological effects. Testing of individual PFAS may be needed for scientifically-supported decision-making. Our proposed strategy of using two human cell types and considering phenotypic and transcriptomic effects, combined with dose-response analysis and calculation of BER, may be used for PFAS prioritization.
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Affiliation(s)
- Han-Hsuan D Tsai
- Interdisciplinary Faculty of Toxicology, College Station, TX, USA
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX, USA
| | - Lucie C Ford
- Interdisciplinary Faculty of Toxicology, College Station, TX, USA
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX, USA
| | - Zunwei Chen
- Interdisciplinary Faculty of Toxicology, College Station, TX, USA
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX, USA
- Current address: Program in Molecular and Integrative Physiological Sciences, Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Allison N Dickey
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
| | - Fred A Wright
- Interdisciplinary Faculty of Toxicology, College Station, TX, USA
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
- Department of Statistics and Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
| | - Ivan Rusyn
- Interdisciplinary Faculty of Toxicology, College Station, TX, USA
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX, USA
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10
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Isaacs KK, Wall JT, Paul Friedman K, Franzosa JA, Goeden H, Williams AJ, Dionisio KL, Lambert JC, Linnenbrink M, Singh A, Wambaugh JF, Bogdan AR, Greene C. Screening for drinking water contaminants of concern using an automated exposure-focused workflow. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2024; 34:136-147. [PMID: 37193773 PMCID: PMC11131037 DOI: 10.1038/s41370-023-00552-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 04/17/2023] [Accepted: 04/18/2023] [Indexed: 05/18/2023]
Abstract
BACKGROUND The number of chemicals present in the environment exceeds the capacity of government bodies to characterize risk. Therefore, data-informed and reproducible processes are needed for identifying chemicals for further assessment. The Minnesota Department of Health (MDH), under its Contaminants of Emerging Concern (CEC) initiative, uses a standardized process to screen potential drinking water contaminants based on toxicity and exposure potential. OBJECTIVE Recently, MDH partnered with the U.S. Environmental Protection Agency (EPA) Office of Research and Development (ORD) to accelerate the screening process via development of an automated workflow accessing relevant exposure data, including exposure new approach methodologies (NAMs) from ORD's ExpoCast project. METHODS The workflow incorporated information from 27 data sources related to persistence and fate, release potential, water occurrence, and exposure potential, making use of ORD tools for harmonization of chemical names and identifiers. The workflow also incorporated data and criteria specific to Minnesota and MDH's regulatory authority. The collected data were used to score chemicals using quantitative algorithms developed by MDH. The workflow was applied to 1867 case study chemicals, including 82 chemicals that were previously manually evaluated by MDH. RESULTS Evaluation of the automated and manual results for these 82 chemicals indicated reasonable agreement between the scores although agreement depended on data availability; automated scores were lower than manual scores for chemicals with fewer available data. Case study chemicals with high exposure scores included disinfection by-products, pharmaceuticals, consumer product chemicals, per- and polyfluoroalkyl substances, pesticides, and metals. Scores were integrated with in vitro bioactivity data to assess the feasibility of using NAMs for further risk prioritization. SIGNIFICANCE This workflow will allow MDH to accelerate exposure screening and expand the number of chemicals examined, freeing resources for in-depth assessments. The workflow will be useful in screening large libraries of chemicals for candidates for the CEC program.
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Affiliation(s)
- Kristin K Isaacs
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, Durham, NC, 27711, USA.
| | - Jonathan T Wall
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, Durham, NC, 27711, USA
| | - Katie Paul Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, Durham, NC, 27711, USA
| | - Jill A Franzosa
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, Durham, NC, 27711, USA
| | - Helen Goeden
- Minnesota Department of Health, 625 Robert St. N, St. Paul, MN, 55155, USA
| | - Antony J Williams
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, Durham, NC, 27711, USA
| | - Kathie L Dionisio
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, Durham, NC, 27711, USA
| | - Jason C Lambert
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, Durham, NC, 27711, USA
| | - Monica Linnenbrink
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, Durham, NC, 27711, USA
| | - Amar Singh
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, Durham, NC, 27711, USA
| | - John F Wambaugh
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, 109 TW Alexander Drive, Research Triangle Park, Durham, NC, 27711, USA
| | - Alexander R Bogdan
- Minnesota Department of Health, 625 Robert St. N, St. Paul, MN, 55155, USA
| | - Christopher Greene
- Minnesota Department of Health, 625 Robert St. N, St. Paul, MN, 55155, USA
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11
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Flannery BM, Turley AE, Anyangwe N, Mattia A, Whiteside C, Hermansky S, Schaefer HR, Tyler T, Fitzpatrick SC. Retrospective analysis of dog study data from food and color additive petitions. Regul Toxicol Pharmacol 2023; 145:105523. [PMID: 37956767 DOI: 10.1016/j.yrtph.2023.105523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 11/01/2023] [Indexed: 11/15/2023]
Abstract
As part of the US FDA CFSAN's efforts to explore alternatives to animal testing, we retrospectively analyzed a sample of food additive (FAP) and color additive petitions (CAP) submitted to the FDA for the utility of dog study data in safety assessment. FAPs and CAPs containing dog studies (161 petitions) were classified as decisive (38%), supportive (27%), supplemental (29%) or undermined (6%) based on the impact the dog study data had on the final safety decision. Petitions classified as decisive were further categorized based on if the dog study data were used to a) address a safety concern (35/61); b) calculate an acceptable daily intake (ADI) (11/61); c) withdraw a petition (4/61); d) the effect was unique to the dog (2/61); or e) unclear (9/61). Of 11 petitions where the dog study was used to set an ADI, 7 contained studies where the points of departure (POD) from the dog studies were within an 8-fold range of the rodent with differences in study design likely contributing to the difference in PODs. Future research should include the development and use of qualified alternative studies to replace the use of animal testing for food and color additive safety assessment while ensuring human safety.
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Affiliation(s)
- Brenna M Flannery
- Office of Analytics and Outreach, Center for Food Safety and Applied Nutrition (CFSAN), United States (US) Food and Drug Administration (FDA), College Park, MD, USA.
| | | | | | | | | | | | - Heather R Schaefer
- Office of Analytics and Outreach, Center for Food Safety and Applied Nutrition (CFSAN), United States (US) Food and Drug Administration (FDA), College Park, MD, USA
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12
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Wang X, Rowan-Carroll A, Meier MJ, Williams A, Yauk CL, Hales BF, Robaire B. Toxicological Mechanisms and Potencies of Organophosphate Esters in KGN Human Ovarian Granulosa Cells as Revealed by High-throughput Transcriptomics. Toxicol Sci 2023; 197:kfad114. [PMID: 37941476 PMCID: PMC10823774 DOI: 10.1093/toxsci/kfad114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023] Open
Abstract
Despite the growing number of studies reporting potential risks associated with exposure to organophosphate esters (OPEs), their molecular mechanisms of action remain poorly defined. We used the high-throughput TempO-Seq™ platform to investigate the effects of frequently detected OPEs on the expression of ∼3000 environmentally responsive genes in KGN human ovarian granulosa cells. Cells were exposed for 48 h to one of five OPEs (0.1 to 50 μM): tris(methylphenyl) phosphate (TMPP), isopropylated triphenyl phosphate (IPPP), tert-butylphenyl diphenyl phosphate (BPDP), triphenyl phosphate (TPHP), or tris(2-butoxyethyl) phosphate (TBOEP). The sequencing data indicate that four OPEs induced transcriptional changes, whereas TBOEP had no effect within the concentration range tested. Multiple pathway databases were used to predict alterations in biological processes based on differentially expressed genes. At lower concentrations, inhibition of the cholesterol biosynthetic pathway was the predominant effect of OPEs; this was likely a consequence of intracellular cholesterol accumulation. At higher concentrations, BPDP and TPHP had distinct effects, primarily affecting pathways involved in cell cycle progression and other stress responses. Benchmark concentration (BMC) modelling revealed that BPDP had the lowest transcriptomic point of departure. However, in vitro to in vivo extrapolation modeling indicated that TMPP was bioactive at lower concentrations than the other OPEs. We conclude that these new approach methodologies provide information on the mechanism(s) underlying the effects of data-poor compounds and assist in the derivation of protective points of departure for use in chemical read-across and decision-making.
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Affiliation(s)
- Xiaotong Wang
- Department of Pharmacology and Therapeutics, McGill University, Montréal, Québec H3G 1Y6, Canada
| | - Andrea Rowan-Carroll
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario K2K 0K9, Canada
| | - Matthew J Meier
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario K2K 0K9, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario K2K 0K9, Canada
| | - Carole L Yauk
- Department of Biology, University of Ottawa, Ottawa, Ontario K1N 9A7, Canada
| | - Barbara F Hales
- Department of Pharmacology and Therapeutics, McGill University, Montréal, Québec H3G 1Y6, Canada
| | - Bernard Robaire
- Department of Pharmacology and Therapeutics, McGill University, Montréal, Québec H3G 1Y6, Canada
- Department of Obstetrics and Gynecology, McGill University, Montréal, Québec H3G 1Y6, Canada
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13
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Dorne JLCM, Cortiñas‐Abrahantes J, Spyropoulos F, Darney K, Lautz L, Louisse J, Kass GEN, Carnesecchi E, Liem AKD, Tarazona JV, Billat P, Beaudoin R, Zeman F, Bodin C, Smith A, Nathanail A, Di Nicola MR, Kleiner J, Terron A, Parra‐Morte JM, Verloo D, Robinson T. TKPlate 1.0: An Open-access platform for toxicokinetic and toxicodynamic modelling of chemicals to implement new approach methodologies in chemical risk assessment. EFSA J 2023; 21:e211101. [PMID: 38027439 PMCID: PMC10644227 DOI: 10.2903/j.efsa.2023.e211101] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2023] Open
Abstract
This publication is linked to the following EFSA Supporting Publications articles: http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2023.EN-8441/full, http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2023.EN-8440/full, http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2023.EN-8437/full.
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14
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Feshuk M, Kolaczkowski L, Dunham K, Davidson-Fritz SE, Carstens KE, Brown J, Judson RS, Paul Friedman K. The ToxCast pipeline: updates to curve-fitting approaches and database structure. FRONTIERS IN TOXICOLOGY 2023; 5:1275980. [PMID: 37808181 PMCID: PMC10552852 DOI: 10.3389/ftox.2023.1275980] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 09/08/2023] [Indexed: 10/10/2023] Open
Abstract
Introduction: The US Environmental Protection Agency Toxicity Forecaster (ToxCast) program makes in vitro medium- and high-throughput screening assay data publicly available for prioritization and hazard characterization of thousands of chemicals. The assays employ a variety of technologies to evaluate the effects of chemical exposure on diverse biological targets, from distinct proteins to more complex cellular processes like mitochondrial toxicity, nuclear receptor signaling, immune responses, and developmental toxicity. The ToxCast data pipeline (tcpl) is an open-source R package that stores, manages, curve-fits, and visualizes ToxCast data and populates the linked MySQL Database, invitrodb. Methods: Herein we describe major updates to tcpl and invitrodb to accommodate a new curve-fitting approach. The original tcpl curve-fitting models (constant, Hill, and gain-loss models) have been expanded to include Polynomial 1 (Linear), Polynomial 2 (Quadratic), Power, Exponential 2, Exponential 3, Exponential 4, and Exponential 5 based on BMDExpress and encoded by the R package dependency, tcplfit2. Inclusion of these models impacted invitrodb (beta version v4.0) and tcpl v3 in several ways: (1) long-format storage of generic modeling parameters to permit additional curve-fitting models; (2) updated logic for winning model selection; (3) continuous hit calling logic; and (4) removal of redundant endpoints as a result of bidirectional fitting. Results and discussion: Overall, the hit call and potency estimates were largely consistent between invitrodb v3.5 and 4.0. Tcpl and invitrodb provide a standard for consistent and reproducible curve-fitting and data management for diverse, targeted in vitro assay data with readily available documentation, thus enabling sharing and use of these data in myriad toxicology applications. The software and database updates described herein promote comparability across multiple tiers of data within the US Environmental Protection Agency CompTox Blueprint.
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Affiliation(s)
- M. Feshuk
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - L. Kolaczkowski
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
- National Student Services Contractor, Oak Ridge Associated Universities, Oak Ridge, TN, United States
| | - K. Dunham
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
- National Student Services Contractor, Oak Ridge Associated Universities, Oak Ridge, TN, United States
| | - S. E. Davidson-Fritz
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - K. E. Carstens
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - J. Brown
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - R. S. Judson
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - K. Paul Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
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15
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Buckley TJ, Egeghy PP, Isaacs K, Richard AM, Ring C, Sayre RR, Sobus JR, Thomas RS, Ulrich EM, Wambaugh JF, Williams AJ. Cutting-edge computational chemical exposure research at the U.S. Environmental Protection Agency. ENVIRONMENT INTERNATIONAL 2023; 178:108097. [PMID: 37478680 PMCID: PMC10588682 DOI: 10.1016/j.envint.2023.108097] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 06/05/2023] [Accepted: 07/12/2023] [Indexed: 07/23/2023]
Abstract
Exposure science is evolving from its traditional "after the fact" and "one chemical at a time" approach to forecasting chemical exposures rapidly enough to keep pace with the constantly expanding landscape of chemicals and exposures. In this article, we provide an overview of the approaches, accomplishments, and plans for advancing computational exposure science within the U.S. Environmental Protection Agency's Office of Research and Development (EPA/ORD). First, to characterize the universe of chemicals in commerce and the environment, a carefully curated, web-accessible chemical resource has been created. This DSSTox database unambiguously identifies >1.2 million unique substances reflecting potential environmental and human exposures and includes computationally accessible links to each compound's corresponding data resources. Next, EPA is developing, applying, and evaluating predictive exposure models. These models increasingly rely on data, computational tools like quantitative structure activity relationship (QSAR) models, and machine learning/artificial intelligence to provide timely and efficient prediction of chemical exposure (and associated uncertainty) for thousands of chemicals at a time. Integral to this modeling effort, EPA is developing data resources across the exposure continuum that includes application of high-resolution mass spectrometry (HRMS) non-targeted analysis (NTA) methods providing measurement capability at scale with the number of chemicals in commerce. These research efforts are integrated and well-tailored to support population exposure assessment to prioritize chemicals for exposure as a critical input to risk management. In addition, the exposure forecasts will allow a wide variety of stakeholders to explore sustainable initiatives like green chemistry to achieve economic, social, and environmental prosperity and protection of future generations.
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Affiliation(s)
- Timothy J Buckley
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States.
| | - Peter P Egeghy
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Kristin Isaacs
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Ann M Richard
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Caroline Ring
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Risa R Sayre
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Jon R Sobus
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Russell S Thomas
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Elin M Ulrich
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - John F Wambaugh
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Antony J Williams
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), 109 TW Alexander Drive, Research Triangle Park, NC 27711, United States
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16
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Smeltz M, Wambaugh JF, Wetmore BA. Plasma Protein Binding Evaluations of Per- and Polyfluoroalkyl Substances for Category-Based Toxicokinetic Assessment. Chem Res Toxicol 2023; 36:870-881. [PMID: 37184865 PMCID: PMC10506455 DOI: 10.1021/acs.chemrestox.3c00003] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
New approach methodologies (NAMs) that make use of in vitro screening and in silico approaches to inform chemical evaluations rely on in vitro toxicokinetic (TK) data to translate in vitro bioactive concentrations to exposure metrics reflective of administered dose. With 1364 per- and polyfluoroalkyl substances (PFAS) identified as of interest under Section 8 of the U.S. Toxic Substances Control Act (TSCA) and concern over the lack of knowledge regarding environmental persistence, human health, and ecological effects, the utility of NAMs to understand potential toxicities and toxicokinetics across these data-poor compounds is being evaluated. To address the TK data deficiency, 71 PFAS selected to span a wide range of functional groups and physico-chemical properties were evaluated for in vitro human plasma protein binding (PPB) by ultracentrifugation with liquid chromatography-mass spectrometry analysis. For the 67 PFAS successfully evaluated by ultracentrifugation, fraction unbound in plasma (fup) ranged from less than 0.0001 (pentadecafluorooctanoyl chloride) to 0.7302 (tetrafluorosuccinic acid), with over half of the PFAS showing PPB exceeding 99.5% (fup < 0.005). Category-based evaluations revealed that perfluoroalkanoyl chlorides and perfluorinated carboxylates (PFCAs) with 6-10 carbons were the highest bound, with similar median values for alkyl, ether, and polyether PFCAs. Interestingly, binding was lower for the PFCAs with a carbon chain length of ≥11. Lower binding also was noted for fluorotelomer carboxylic acids when compared to their carbon-equivalent perfluoroalkyl acids. Comparisons of the fup value derived using two PPB methods, ultracentrifugation or rapid equilibrium dialysis (RED), revealed RED failure for a subset of PFAS of high mass and/or predicted octanol-water partition coefficients exceeding 4 due to failure to achieve equilibrium. Bayesian modeling was used to provide uncertainty bounds around fup point estimates for incorporation into TK modeling. This PFAS PPB evaluation and grouping exercise across 67 structures greatly expand our current knowledge and will aid in PFAS NAM development.
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Affiliation(s)
- Marci Smeltz
- Center for Computational Toxicology and Exposure, US EPA Office of Research and Development, Research Triangle Park, NC 27711, USA
- Current Affiliation: Center for Environmental Measurement and Modeling; Research Triangle Park, NC, 27711, USA
| | - John F. Wambaugh
- Center for Computational Toxicology and Exposure, US EPA Office of Research and Development, Research Triangle Park, NC 27711, USA
| | - Barbara A. Wetmore
- Center for Computational Toxicology and Exposure, US EPA Office of Research and Development, Research Triangle Park, NC 27711, USA
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17
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van Tongeren TCA, Wang S, Carmichael PL, Rietjens IMCM, Li H. Next generation risk assessment of human exposure to estrogens using safe comparator compound values based on in vitro bioactivity assays. Arch Toxicol 2023; 97:1547-1575. [PMID: 37087486 PMCID: PMC10182946 DOI: 10.1007/s00204-023-03480-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 03/02/2023] [Indexed: 04/24/2023]
Abstract
In next generation risk assessment (NGRA), the Dietary Comparator Ratio (DCR) can be used to assess the safety of chemical exposures to humans in a 3R compliant approach. The DCR compares the Exposure Activity Ratio (EAR) for exposure to a compound of interest (EARtest) to the EAR for an established safe exposure level to a comparator compound (EARcomparator), acting by the same mode of action. It can be concluded that the exposure to a test compound is safe at a corresponding DCR ≤ 1. In this study, genistein (GEN) was selected as a comparator compound by comparison of reported safe internal exposures to GEN to its BMCL05, as no effect level, the latter determined in the in vitro estrogenic MCF7/Bos proliferation, T47D ER-CALUX, and U2OS ERα-CALUX assay. The EARcomparator was defined using the BMCL05 and EC50 values from the 3 in vitro assays and subsequently used to calculate the DCRs for exposures to 14 test compounds, predicting the (absence of) estrogenicity. The predictions were evaluated by comparison to reported in vivo estrogenicity in humans for these exposures. The results obtained support in the DCR approach as an important animal-free new approach methodology (NAM) in NGRA and show how in vitro assays can be used to define DCR values.
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Affiliation(s)
- Tessa C A van Tongeren
- Division of Toxicology, Wageningen University and Research, 6700 EA, Wageningen, The Netherlands.
| | - Si Wang
- Division of Toxicology, Wageningen University and Research, 6700 EA, Wageningen, The Netherlands
| | - Paul L Carmichael
- Unilever Safety and Environmental Assurance Centre, Sharnbrook, Bedfordshire, MK44 1LQ, UK
| | - Ivonne M C M Rietjens
- Division of Toxicology, Wageningen University and Research, 6700 EA, Wageningen, The Netherlands
| | - Hequn Li
- Unilever Safety and Environmental Assurance Centre, Sharnbrook, Bedfordshire, MK44 1LQ, UK
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18
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Reardon AJF, Farmahin R, Williams A, Meier MJ, Addicks GC, Yauk CL, Matteo G, Atlas E, Harrill J, Everett LJ, Shah I, Judson R, Ramaiahgari S, Ferguson SS, Barton-Maclaren TS. From vision toward best practices: Evaluating in vitro transcriptomic points of departure for application in risk assessment using a uniform workflow. FRONTIERS IN TOXICOLOGY 2023; 5:1194895. [PMID: 37288009 PMCID: PMC10242042 DOI: 10.3389/ftox.2023.1194895] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 05/03/2023] [Indexed: 06/09/2023] Open
Abstract
The growing number of chemicals in the current consumer and industrial markets presents a major challenge for regulatory programs faced with the need to assess the potential risks they pose to human and ecological health. The increasing demand for hazard and risk assessment of chemicals currently exceeds the capacity to produce the toxicity data necessary for regulatory decision making, and the applied data is commonly generated using traditional approaches with animal models that have limited context in terms of human relevance. This scenario provides the opportunity to implement novel, more efficient strategies for risk assessment purposes. This study aims to increase confidence in the implementation of new approach methods in a risk assessment context by using a parallel analysis to identify data gaps in current experimental designs, reveal the limitations of common approaches deriving transcriptomic points of departure, and demonstrate the strengths in using high-throughput transcriptomics (HTTr) to derive practical endpoints. A uniform workflow was applied across six curated gene expression datasets from concentration-response studies containing 117 diverse chemicals, three cell types, and a range of exposure durations, to determine tPODs based on gene expression profiles. After benchmark concentration modeling, a range of approaches was used to determine consistent and reliable tPODs. High-throughput toxicokinetics were employed to translate in vitro tPODs (µM) to human-relevant administered equivalent doses (AEDs, mg/kg-bw/day). The tPODs from most chemicals had AEDs that were lower (i.e., more conservative) than apical PODs in the US EPA CompTox chemical dashboard, suggesting in vitro tPODs would be protective of potential effects on human health. An assessment of multiple data points for single chemicals revealed that longer exposure duration and varied cell culture systems (e.g., 3D vs. 2D) lead to a decreased tPOD value that indicated increased chemical potency. Seven chemicals were flagged as outliers when comparing the ratio of tPOD to traditional POD, thus indicating they require further assessment to better understand their hazard potential. Our findings build confidence in the use of tPODs but also reveal data gaps that must be addressed prior to their adoption to support risk assessment applications.
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Affiliation(s)
- Anthony J. F. Reardon
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Reza Farmahin
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Matthew J. Meier
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Gregory C. Addicks
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Carole L. Yauk
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
| | - Geronimo Matteo
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
| | - Ella Atlas
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
- Department of Biochemistry, University of Ottawa, Ottawa, ON, Canada
| | - Joshua Harrill
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Logan J. Everett
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Imran Shah
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Richard Judson
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Durham, NC, United States
| | - Sreenivasa Ramaiahgari
- Division of Translational Toxicology, Mechanistic Toxicology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Stephen S. Ferguson
- Division of Translational Toxicology, Mechanistic Toxicology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, United States
| | - Tara S. Barton-Maclaren
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
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19
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Kreutz A, Clifton MS, Henderson WM, Smeltz MG, Phillips M, Wambaugh JF, Wetmore BA. Category-Based Toxicokinetic Evaluations of Data-Poor Per- and Polyfluoroalkyl Substances (PFAS) using Gas Chromatography Coupled with Mass Spectrometry. TOXICS 2023; 11:toxics11050463. [PMID: 37235277 DOI: 10.3390/toxics11050463] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 04/28/2023] [Accepted: 05/08/2023] [Indexed: 05/28/2023]
Abstract
Concern over per- and polyfluoroalkyl substances (PFAS) has increased as more is learned about their environmental presence, persistence, and bioaccumulative potential. The limited monitoring, toxicokinetic (TK), and toxicologic data available are inadequate to inform risk across this diverse domain. Here, 73 PFAS were selected for in vitro TK evaluation to expand knowledge across lesser-studied PFAS alcohols, amides, and acrylates. Targeted methods developed using gas chromatography-tandem mass spectrometry (GC-MS/MS) were used to measure human plasma protein binding and hepatocyte clearance. Forty-three PFAS were successfully evaluated in plasma, with fraction unbound (fup) values ranging from 0.004 to 1. With a median fup of 0.09 (i.e., 91% bound), these PFAS are highly bound but exhibit 10-fold lower binding than legacy perfluoroalkyl acids recently evaluated. Thirty PFAS evaluated in the hepatocyte clearance assay showed abiotic loss, with many exceeding 60% loss within 60 min. Metabolic clearance was noted for 11 of the 13 that were successfully evaluated, with rates up to 49.9 μL/(min × million cells). The chemical transformation simulator revealed potential (bio)transformation products to consider. This effort provides critical information to evaluate PFAS for which volatility, metabolism, and other routes of transformation are likely to modulate their environmental fates.
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Affiliation(s)
- Anna Kreutz
- Oak Ridge Institute for Science and Education, 1299 Bethel Valley Road, Oak Ridge, TN 37830, USA
| | - Matthew S Clifton
- US Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement and Modeling, Research Triangle Park, NC 27711, USA
| | - W Matthew Henderson
- US Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement and Modeling, Athens, GA 30605, USA
| | - Marci G Smeltz
- US Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement and Modeling, Research Triangle Park, NC 27711, USA
- US Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711, USA
| | - Matthew Phillips
- Oak Ridge Associated Universities, 100 ORAU Way, Oak Ridge, TN 37830, USA
| | - John F Wambaugh
- US Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711, USA
| | - Barbara A Wetmore
- US Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711, USA
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20
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Lin HC, Chiu WA. Development of physiologically-based gut absorption model for probabilistic prediction of environmental chemical bioavailability. ALTEX 2023; 40:471-484. [PMID: 37158362 PMCID: PMC10898273 DOI: 10.14573/altex.2210031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 05/02/2023] [Indexed: 05/10/2023]
Abstract
Absorption in the gastrointestinal tract is a key factor determining the bioavailability of chemicals after oral exposure but is frequently assumed to have a conservative value of 100% for environmental chemicals, particularly in the context of high-throughput toxicokinetics for in vitro-to-in vivo extrapolation (IVIVE). For pharmaceutical compounds, the physiologically based advanced compartmental absorption and transit (ACAT) model has been used extensively to predict gut absorption but has not generally been applied to environmental chemicals. Here we develop a probabilistic environmental compartmental absorption and transit (PECAT) model, adapting the ACAT model to environmental chemicals. We calibrated the model parameters to human in vivo, ex vivo, and in vitro datasets of drug permeability and fractional absorption by considering two key factors: (1) differences between permeability in Caco-2 cells and in vivo permeability in the jejunum, and (2) differences in in vivo permeability across different gut segments. Incorporating these factors probabilistically, we found that given Caco-2 permeability measurements, predictions of the PECAT model are consistent with the (limited) available gut absorption data for environmental chemicals. However, the substantial chemical-to-chemical variability observed in the calibration data often led to wide probabilistic confidence bounds in the predicted fraction absorbed and resulting steady state blood concentration. Thus, while the PECAT model provides a statistically rigorous, physiologically based approach for incorporating in vitro data on gut absorption into toxicokinetic modeling and IVIVE, it also highlights the need for more accurate in vitro models and data for measuring gut segment-specific in vivo permeability of environmental chemicals.
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Affiliation(s)
- Hsing-Chieh Lin
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
| | - Weihsueh A. Chiu
- Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA
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21
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Müller FA, Stamou M, Englert FH, Frenzel O, Diedrich S, Suter-Dick L, Wambaugh JF, Sturla SJ. In vitro to in vivo extrapolation and high-content imaging for simultaneous characterization of chemically induced liver steatosis and markers of hepatotoxicity. Arch Toxicol 2023; 97:1701-1721. [PMID: 37046073 PMCID: PMC10182956 DOI: 10.1007/s00204-023-03490-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 03/21/2023] [Indexed: 04/14/2023]
Abstract
Chemically induced steatosis is characterized by lipid accumulation associated with mitochondrial dysfunction, oxidative stress and nucleus distortion. New approach methods integrating in vitro and in silico models are needed to identify chemicals that may induce these cellular events as potential risk factors for steatosis and associated hepatotoxicity. In this study we used high-content imaging for the simultaneous quantification of four cellular markers as sentinels for hepatotoxicity and steatosis in chemically exposed human liver cells in vitro. Furthermore, we evaluated the results with a computational model for the extrapolation of human oral equivalent doses (OED). First, we tested 16 reference chemicals with known capacities to induce cellular alterations in nuclear morphology, lipid accumulation, mitochondrial membrane potential and oxidative stress. Then, using physiologically based pharmacokinetic modeling and reverse dosimetry, OEDs were extrapolated from data of any stimulated individual sentinel response. The extrapolated OEDs were confirmed to be within biologically relevant exposure ranges for the reference chemicals. Next, we tested 14 chemicals found in food, selected from thousands of putative chemicals on the basis of structure-based prediction for nuclear receptor activation. Amongst these, orotic acid had an extrapolated OED overlapping with realistic exposure ranges. Thus, we were able to characterize known steatosis-inducing chemicals as well as data-scarce food-related chemicals, amongst which we confirmed orotic acid to induce hepatotoxicity. This strategy addresses needs of next generation risk assessment and can be used as a first chemical prioritization hazard screening step in a tiered approach to identify chemical risk factors for steatosis and hepatotoxicity-associated events.
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Affiliation(s)
- Fabrice A Müller
- Department of Health Sciences and Technology, ETH Zurich, Schmelzbergstrasse 9, 8092, Zurich, Switzerland
| | - Marianna Stamou
- Department of Health Sciences and Technology, ETH Zurich, Schmelzbergstrasse 9, 8092, Zurich, Switzerland
| | - Felix H Englert
- Department of Health Sciences and Technology, ETH Zurich, Schmelzbergstrasse 9, 8092, Zurich, Switzerland
| | - Ole Frenzel
- Department of Health Sciences and Technology, ETH Zurich, Schmelzbergstrasse 9, 8092, Zurich, Switzerland
| | - Sabine Diedrich
- Department of Health Sciences and Technology, ETH Zurich, Schmelzbergstrasse 9, 8092, Zurich, Switzerland
| | - Laura Suter-Dick
- School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, 4132, Muttenz, Switzerland
- Swiss Centre for Applied Human Toxicology (SCAHT), 4001, Basel, Switzerland
| | - John F Wambaugh
- Center for Computational Toxicology and Exposure, Office of Research and Development, United States Environmental Protection Agency, Research Triangle Park, Durham, NC, 27711, USA
| | - Shana J Sturla
- Department of Health Sciences and Technology, ETH Zurich, Schmelzbergstrasse 9, 8092, Zurich, Switzerland.
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22
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Zhao F, Li L, Lin P, Chen Y, Xing S, Du H, Wang Z, Yang J, Huan T, Long C, Zhang L, Wang B, Fang M. HExpPredict: In Vivo Exposure Prediction of Human Blood Exposome Using a Random Forest Model and Its Application in Chemical Risk Prioritization. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:37009. [PMID: 36913238 PMCID: PMC10010393 DOI: 10.1289/ehp11305] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 12/15/2022] [Accepted: 02/14/2023] [Indexed: 06/01/2023]
Abstract
BACKGROUND Due to many substances in the human exposome, there is a dearth of exposure and toxicity information available to assess potential health risks. Quantification of all trace organics in the biological fluids seems impossible and costly, regardless of the high individual exposure variability. We hypothesized that the blood concentration (CB) of organic pollutants could be predicted via their exposure and chemical properties. Developing a prediction model on the annotation of chemicals in human blood can provide new insight into the distribution and extent of exposures to a wide range of chemicals in humans. OBJECTIVES Our objective was to develop a machine learning (ML) model to predict blood concentrations (CBs) of chemicals and prioritize chemicals of health concern. METHODS We curated the CBs of compounds mostly measured at population levels and developed an ML model for chemical CB predictions by considering chemical daily exposure (DE) and exposure pathway indicators (δij), half-lives (t1/2), and volume of distribution (Vd). Three ML models, including random forest (RF), artificial neural network (ANN) and support vector regression (SVR) were compared. The toxicity potential or prioritization of each chemical was represented as a bioanalytical equivalency (BEQ) and its percentage (BEQ%) estimated based on the predicted CB and ToxCast bioactivity data. We also retrieved the top 25 most active chemicals in each assay to further observe changes in the BEQ% after the exclusion of the drugs and endogenous substances. RESULTS We curated the CBs of 216 compounds primarily measured at population levels. RF outperformed the ANN and SVF models with the root mean square error (RMSE) of 1.66 and 2.07μM, the mean absolute error (MAE) values of 1.28 and 1.56μM, the mean absolute percentage error (MAPE) of 0.29 and 0.23, and R2 of 0.80 and 0.72 across test and testing sets. Subsequently, the human CBs of 7,858 ToxCast chemicals were successfully predicted, ranging from 1.29×10-6 to 1.79×10-2 μM. The predicted CBs were then combined with ToxCast in vitro bioassays to prioritize the ToxCast chemicals across 12 in vitro assays with important toxicological end points. It is interesting that we found the most active compounds to be food additives and pesticides rather than widely monitored environmental pollutants. DISCUSSION We have shown that the accurate prediction of "internal exposure" from "external exposure" is possible, and this result can be quite useful in the risk prioritization. https://doi.org/10.1289/EHP11305.
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Affiliation(s)
- Fanrong Zhao
- Department of Environmental Science and Engineering, Fudan University, Shanghai, P.R. China
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
- School of Civil and Environmental Engineering, Nanyang Technological University, Singapore
| | - Li Li
- School of Community Health Sciences, University of Nevada, Reno, Reno, Nevada, USA
| | - Penghui Lin
- School of Civil and Environmental Engineering, Nanyang Technological University, Singapore
| | - Yue Chen
- School of Computer Science and Engineering, Nanyang Technological University, Singapore
| | - Shipei Xing
- Department of Chemistry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Huili Du
- School of Civil and Environmental Engineering, Nanyang Technological University, Singapore
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, P.R. China
| | - Zheng Wang
- School of Computer Science and Engineering, Nanyang Technological University, Singapore
| | - Junjie Yang
- School of Civil and Environmental Engineering, Nanyang Technological University, Singapore
| | - Tao Huan
- Department of Chemistry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cheng Long
- School of Computer Science and Engineering, Nanyang Technological University, Singapore
| | - Limao Zhang
- School of Civil and Environmental Engineering, Nanyang Technological University, Singapore
| | - Bin Wang
- Institute of Reproductive and Child Health, Peking University/Key Laboratory of Reproductive Health, National Health Commission of the People’s Republic of China, Beijing, P.R. China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, P.R. China
| | - Mingliang Fang
- Department of Environmental Science and Engineering, Fudan University, Shanghai, P.R. China
- School of Civil and Environmental Engineering, Nanyang Technological University, Singapore
- Institute of Eco-Chongming, Shanghai, P.R. China
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23
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Hagiwara S, Paoli GM, Price PS, Gwinn MR, Guiseppi-Elie A, Farrell PJ, Hubbell BJ, Krewski D, Thomas RS. A value of information framework for assessing the trade-offs associated with uncertainty, duration, and cost of chemical toxicity testing. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2023; 43:498-515. [PMID: 35460101 PMCID: PMC10515440 DOI: 10.1111/risa.13931] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
A number of investigators have explored the use of value of information (VOI) analysis to evaluate alternative information collection procedures in diverse decision-making contexts. This paper presents an analytic framework for determining the value of toxicity information used in risk-based decision making. The framework is specifically designed to explore the trade-offs between cost, timeliness, and uncertainty reduction associated with different toxicity-testing methodologies. The use of the proposed framework is demonstrated by two illustrative applications which, although based on simplified assumptions, show the insights that can be obtained through the use of VOI analysis. Specifically, these results suggest that timeliness of information collection has a significant impact on estimates of the VOI of chemical toxicity tests, even in the presence of smaller reductions in uncertainty. The framework introduces the concept of the expected value of delayed sample information, as an extension to the usual expected value of sample information, to accommodate the reductions in value resulting from delayed decision making. Our analysis also suggests that lower cost and higher throughput testing also may be beneficial in terms of public health benefits by increasing the number of substances that can be evaluated within a given budget. When the relative value is expressed in terms of return-on-investment per testing strategy, the differences can be substantial.
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Affiliation(s)
- Shintaro Hagiwara
- Risk Sciences International, Ottawa, Canada
- School of Mathematics and Statistics, Carleton University, Ottawa, Canada
| | | | - Paul S. Price
- Center for Compuational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Maureen R. Gwinn
- Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Annette Guiseppi-Elie
- Center for Compuational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Patrick J. Farrell
- School of Mathematics and Statistics, Carleton University, Ottawa, Canada
| | - Bryan J. Hubbell
- Air, Climate, and Energy Research Program, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Daniel Krewski
- Risk Sciences International, Ottawa, Canada
- McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Canada
| | - Russell S. Thomas
- Center for Compuational Toxicology and Exposure, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina, USA
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24
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Magurany KA, Chang X, Clewell R, Coecke S, Haugabrooks E, Marty S. A Pragmatic Framework for the Application of New Approach Methodologies in One Health Toxicological Risk Assessment. Toxicol Sci 2023; 192:kfad012. [PMID: 36782355 PMCID: PMC10109535 DOI: 10.1093/toxsci/kfad012] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2023] Open
Abstract
Globally, industries and regulatory authorities are faced with an urgent need to assess the potential adverse effects of chemicals more efficiently by embracing new approach methodologies (NAMs). NAMs include cell and tissue methods (in vitro), structure-based/toxicokinetic models (in silico), methods that assess toxicant interactions with biological macromolecules (in chemico), and alternative models. Increasing knowledge on chemical toxicokinetics (what the body does with chemicals) and toxicodynamics (what the chemicals do with the body) obtained from in silico and in vitro systems continues to provide opportunities for modernizing chemical risk assessments. However, directly leveraging in vitro and in silico data for derivation of human health-based reference values has not received regulatory acceptance due to uncertainties in extrapolating NAM results to human populations, including metabolism, complex biological pathways, multiple exposures, interindividual susceptibility and vulnerable populations. The objective of this article is to provide a standardized pragmatic framework that applies integrated approaches with a focus on quantitative in vitro to in vivo extrapolation (QIVIVE) to extrapolate in vitro cellular exposures to human equivalent doses from which human reference values can be derived. The proposed framework intends to systematically account for the complexities in extrapolation and data interpretation to support sound human health safety decisions in diverse industrial sectors (food systems, cosmetics, industrial chemicals, pharmaceuticals etc.). Case studies of chemical entities, using new and existing data, are presented to demonstrate the utility of the proposed framework while highlighting potential sources of human population bias and uncertainty, and the importance of Good Method and Reporting Practices.
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Affiliation(s)
| | | | - Rebecca Clewell
- 21st Century Tox Consulting, Chapel Hill, North Carolina 27517, USA
| | - Sandra Coecke
- European Commission Joint Research Centre, Ispra, Italy
| | - Esther Haugabrooks
- Coca-Cola Company (formerly Physicians Committee for Responsible Medicine), Atlanta, Georgia 30313, USA
| | - Sue Marty
- The Dow Chemical Company, Midland, Michigan 48667, USA
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25
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Brescia S, Alexander-White C, Li H, Cayley A. Risk assessment in the 21st century: where are we heading? Toxicol Res (Camb) 2023; 12:1-11. [PMID: 36866215 PMCID: PMC9972812 DOI: 10.1093/toxres/tfac087] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/19/2022] [Accepted: 12/22/2022] [Indexed: 01/12/2023] Open
Abstract
Reliance on animal tests for chemical safety assessment is increasingly being challenged, not only because of ethical reasons, but also because they procrastinate regulatory decisions and because of concerns over the transferability of results to humans. New approach methodologies (NAMs) need to be fit for purpose and new thinking is required to reconsider chemical legislation, validation of NAMs and opportunities to move away from animal tests. This article summarizes the presentations from a symposium at the 2022 Annual Congress of the British Toxicology Society on the topic of the future of chemical risk assessment in the 21st century. The symposium included three case-studies where NAMs have been used in safety assessments. The first case illustrated how read-across augmented with some in vitro tests could be used reliably to perform the risk assessment of analogues lacking data. The second case showed how specific bioactivity assays could identify an NAM point of departure (PoD) and how this could be translated through physiologically based kinetic modelling in an in vivo PoD for the risk assessment. The third case showed how adverse-outcome pathway (AOP) information, including molecular-initiating event and key events with their underlying data, established for certain chemicals could be used to produce an in silico model that is able to associate chemical features of an unstudied substance with specific AOPs or AOP networks. The manuscript presents the discussions that took place regarding the limitations and benefits of these new approaches, and what are the barriers and the opportunities for their increased use in regulatory decision making.
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Affiliation(s)
- Susy Brescia
- Health & Safety Executive, Chemicals Regulation Division, Redgrave Court, Merton Road, Bootle, Merseyside L20 7HS, UK
| | | | - Hequn Li
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ, UK
| | - Alex Cayley
- Lhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds LS11, 5PS, UK
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26
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Beal MA, Audebert M, Barton-Maclaren T, Battaion H, Bemis JC, Cao X, Chen C, Dertinger SD, Froetschl R, Guo X, Johnson G, Hendriks G, Khoury L, Long AS, Pfuhler S, Settivari RS, Wickramasuriya S, White P. Quantitative in vitro to in vivo extrapolation of genotoxicity data provides protective estimates of in vivo dose. ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 2023; 64:105-122. [PMID: 36495195 DOI: 10.1002/em.22521] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 11/29/2022] [Accepted: 11/30/2022] [Indexed: 06/17/2023]
Abstract
Genotoxicity assessment is a critical component in the development and evaluation of chemicals. Traditional genotoxicity assays (i.e., mutagenicity, clastogenicity, and aneugenicity) have been limited to dichotomous hazard classification, while other toxicity endpoints are assessed through quantitative determination of points-of-departures (PODs) for setting exposure limits. The more recent higher-throughput in vitro genotoxicity assays, many of which also provide mechanistic information, offer a powerful approach for determining defined PODs for potency ranking and risk assessment. In order to obtain relevant human dose context from the in vitro assays, in vitro to in vivo extrapolation (IVIVE) models are required to determine what dose would elicit a concentration in the body demonstrated to be genotoxic using in vitro assays. Previous work has demonstrated that application of IVIVE models to in vitro bioactivity data can provide PODs that are protective of human health, but there has been no evaluation of how these models perform with in vitro genotoxicity data. Thus, the Genetic Toxicology Technical Committee, under the Health and Environmental Sciences Institute, conducted a case study on 31 reference chemicals to evaluate the performance of IVIVE application to genotoxicity data. The results demonstrate that for most chemicals considered here (20/31), the PODs derived from in vitro data and IVIVE are health protective relative to in vivo PODs from animal studies. PODs were also protective by assay target: mutations (8/13 chemicals), micronuclei (9/12), and aneugenicity markers (4/4). It is envisioned that this novel testing strategy could enhance prioritization, rapid screening, and risk assessment of genotoxic chemicals.
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Affiliation(s)
- Marc A Beal
- Bureau of Chemical Safety, Health Products and Food Branch, Health Canada, Ottawa, Ontario, Canada
| | - Marc Audebert
- Toxalim UMR1331, Toulouse University, INRAE, Toulouse, France
| | - Tara Barton-Maclaren
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Hannah Battaion
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | | | - Xuefei Cao
- Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA
| | - Connie Chen
- Health and Environmental Sciences Institute, Washington, District of Columbia, USA
| | | | | | - Xiaoqing Guo
- Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas, USA
| | | | | | | | - Alexandra S Long
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Stefan Pfuhler
- Global Product Stewardship, Procter & Gamble, Cincinnati, Ohio, USA
| | - Raja S Settivari
- Mammalian Toxicology Center, Corteva Agriscience, Newark, Delaware, USA
| | - Shamika Wickramasuriya
- Existing Substances Risk Assessment Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Paul White
- Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
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27
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Boyce M, Favela KA, Bonzo JA, Chao A, Lizarraga LE, Moody LR, Owens EO, Patlewicz G, Shah I, Sobus JR, Thomas RS, Williams AJ, Yau A, Wambaugh JF. Identifying xenobiotic metabolites with in silico prediction tools and LCMS suspect screening analysis. FRONTIERS IN TOXICOLOGY 2023; 5:1051483. [PMID: 36742129 PMCID: PMC9889941 DOI: 10.3389/ftox.2023.1051483] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 01/03/2023] [Indexed: 01/19/2023] Open
Abstract
Understanding the metabolic fate of a xenobiotic substance can help inform its potential health risks and allow for the identification of signature metabolites associated with exposure. The need to characterize metabolites of poorly studied or novel substances has shifted exposure studies towards non-targeted analysis (NTA), which often aims to profile many compounds within a sample using high-resolution liquid-chromatography mass-spectrometry (LCMS). Here we evaluate the suitability of suspect screening analysis (SSA) liquid-chromatography mass-spectrometry to inform xenobiotic chemical metabolism. Given a lack of knowledge of true metabolites for most chemicals, predictive tools were used to generate potential metabolites as suspect screening lists to guide the identification of selected xenobiotic substances and their associated metabolites. Thirty-three substances were selected to represent a diverse array of pharmaceutical, agrochemical, and industrial chemicals from Environmental Protection Agency's ToxCast chemical library. The compounds were incubated in a metabolically-active in vitro assay using primary hepatocytes and the resulting supernatant and lysate fractions were analyzed with high-resolution LCMS. Metabolites were simulated for each compound structure using software and then combined to serve as the suspect screening list. The exact masses of the predicted metabolites were then used to select LCMS features for fragmentation via tandem mass spectrometry (MS/MS). Of the starting chemicals, 12 were measured in at least one sample in either positive or negative ion mode and a subset of these were used to develop the analysis workflow. We implemented a screening level workflow for background subtraction and the incorporation of time-varying kinetics into the identification of likely metabolites. We used haloperidol as a case study to perform an in-depth analysis, which resulted in identifying five known metabolites and five molecular features that represent potential novel metabolites, two of which were assigned discrete structures based on in silico predictions. This workflow was applied to five additional test chemicals, and 15 molecular features were selected as either reported metabolites, predicted metabolites, or potential metabolites without a structural assignment. This study demonstrates that in some-but not all-cases, suspect screening analysis methods provide a means to rapidly identify and characterize metabolites of xenobiotic chemicals.
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Affiliation(s)
- Matthew Boyce
- Center for Computational Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | | | - Jessica A. Bonzo
- Thermo Fisher Scientific, South San Francisco, CA, United States
| | - Alex Chao
- Center for Computational Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - Lucina E. Lizarraga
- Center for Public Health and Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Cincinnati, OH, United States
| | - Laura R. Moody
- Thermo Fisher Scientific, South San Francisco, CA, United States
| | - Elizabeth O. Owens
- Center for Public Health and Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Cincinnati, OH, United States
| | - Grace Patlewicz
- Center for Computational Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - Imran Shah
- Center for Computational Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - Jon R. Sobus
- Center for Computational Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - Russell S. Thomas
- Center for Computational Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - Antony J. Williams
- Center for Computational Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States
| | - Alice Yau
- Southwest Research Institute, San Antonio, TX, United States
| | - John F. Wambaugh
- Center for Computational Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, United States,*Correspondence: John F. Wambaugh,
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28
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Chiu WA, Lynch MT, Lay CR, Antezana A, Malek P, Sokolinski S, Rogers RD. Bayesian Estimation of Human Population Toxicokinetics of PFOA, PFOS, PFHxS, and PFNA from Studies of Contaminated Drinking Water. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:127001. [PMID: 36454223 PMCID: PMC9714558 DOI: 10.1289/ehp10103] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 08/03/2022] [Accepted: 10/27/2022] [Indexed: 05/20/2023]
Abstract
BACKGROUND Setting health-protective standards for poly- and perfluoroalkyl substances (PFAS) exposure requires estimates of their population toxicokinetics, but existing studies have reported widely varying PFAS half-lives (T½) and volumes of distribution (Vd). OBJECTIVES We combined data from multiple studies to develop harmonized estimates of T½ and Vd, along with their interindividual variability, for four PFAS commonly found in drinking water: perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), perfluorononanoic acid (PFNA), and perfluorohexane sulfonate (PFHxS). METHODS We identified published data on PFAS concentrations in human serum with corresponding drinking water measurements, separated into training and testing data sets. We fit training data sets to a one-compartment model incorporating interindividual variability, time-dependent drinking water concentrations, and background exposures. Use of a hierarchical Bayesian approach allowed us to incorporate informative priors at the population level, as well as at the study level. We compared posterior predictions to testing data sets to evaluate model performance. RESULTS Posterior median (95% CI) estimates of T½ (in years) for the population geometric mean were 3.14 (2.69, 3.73) for PFOA, 3.36 (2.52, 4.42) for PFOS, 2.35 (1.65, 3.16) for PFNA, and 8.30 (5.38, 13.5) for PFHxS, all of which were within the range of previously published values. The extensive individual-level data for PFOA allowed accurate estimation of population variability, with a population geometric standard deviation of 1.57 (95% CI: 1.42, 1.73); data from other PFAS were also consistent with this degree of population variability. Vd estimates ranged from 0.19 to 0.43L/kg across the four PFAS, which tended to be slightly higher than previously published estimates. DISCUSSION These results have direct application in both risk assessment (quantitative interspecies extrapolation and uncertainty factors for interindividual variability) and risk communication (interpretation of monitoring data). In addition, this study provides a rigorous methodology for further refinement with additional data, as well as application to other PFAS. https://doi.org/10.1289/EHP10103.
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Affiliation(s)
- Weihsueh A. Chiu
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas, USA
- Department of Veterinary Physiology and Pharmacology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA
| | | | | | | | | | | | - Rachel D. Rogers
- Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry, Atlanta, Georgia, USA
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Patlewicz G, Richard AM, Williams AJ, Judson RS, Thomas RS. Towards reproducible structure-based chemical categories for PFAS to inform and evaluate toxicity and toxicokinetic testing. COMPUTATIONAL TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2022; 24:10.1016/j.comtox.2022.100250. [PMID: 36969381 PMCID: PMC10031514 DOI: 10.1016/j.comtox.2022.100250] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Per- and Polyfluoroalkyl substances (PFAS) are a class of synthetic chemicals that are in widespread use and present concerns for persistence, bioaccumulation and toxicity. Whilst a handful of PFAS have been characterised for their hazard profiles, the vast majority of PFAS have not been studied. The US Environmental Protection Agency (EPA) undertook a research project to screen ~150 PFAS through an array of different in vitro high throughput toxicity and toxicokinetic tests in order to inform chemical category and read-across approaches. A previous publication described the rationale behind the selection of an initial set of 75 PFAS, whereas herein, we describe how various category approaches were applied and extended to inform the selection of a second set of 75 PFAS from our library of approximately 430 commercially procured PFAS. In particular, we focus on the challenges in grouping PFAS for prospective analysis and how we have sought to develop and apply objective structure-based categories to profile the testing library and other PFAS inventories. We additionally illustrate how these categories can be enriched with other information to facilitate read-across inferences once experimental data become available. The availability of flexible, objective, reproducible and chemically intuitive categories to explore PFAS constitutes an important step forward in prioritising PFAS for further testing and assessment.
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Affiliation(s)
- Grace Patlewicz
- Center for Computational Toxicology and Exposure (CCTE), Office of Research and Development, US Environmental Protection Agency, 109 TW Alexander Dr, Research Triangle Park, NC 27711, USA
| | - Ann M. Richard
- Center for Computational Toxicology and Exposure (CCTE), Office of Research and Development, US Environmental Protection Agency, 109 TW Alexander Dr, Research Triangle Park, NC 27711, USA
| | - Antony J. Williams
- Center for Computational Toxicology and Exposure (CCTE), Office of Research and Development, US Environmental Protection Agency, 109 TW Alexander Dr, Research Triangle Park, NC 27711, USA
| | - Richard S. Judson
- Center for Computational Toxicology and Exposure (CCTE), Office of Research and Development, US Environmental Protection Agency, 109 TW Alexander Dr, Research Triangle Park, NC 27711, USA
| | - Russell S. Thomas
- Center for Computational Toxicology and Exposure (CCTE), Office of Research and Development, US Environmental Protection Agency, 109 TW Alexander Dr, Research Triangle Park, NC 27711, USA
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Wlodkowic D, Jansen M. High-throughput screening paradigms in ecotoxicity testing: Emerging prospects and ongoing challenges. CHEMOSPHERE 2022; 307:135929. [PMID: 35944679 DOI: 10.1016/j.chemosphere.2022.135929] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 06/09/2022] [Accepted: 07/31/2022] [Indexed: 06/15/2023]
Abstract
The rapidly increasing number of new production chemicals coupled with stringent implementation of global chemical management programs necessities a paradigm shift towards boarder uses of low-cost and high-throughput ecotoxicity testing strategies as well as deeper understanding of cellular and sub-cellular mechanisms of ecotoxicity that can be used in effective risk assessment. The latter will require automated acquisition of biological data, new capabilities for big data analysis as well as computational simulations capable of translating new data into in vivo relevance. However, very few efforts have been so far devoted into the development of automated bioanalytical systems in ecotoxicology. This is in stark contrast to standardized and high-throughput chemical screening and prioritization routines found in modern drug discovery pipelines. As a result, the high-throughput and high-content data acquisition in ecotoxicology is still in its infancy with limited examples focused on cell-free and cell-based assays. In this work we outline recent developments and emerging prospects of high-throughput bioanalytical approaches in ecotoxicology that reach beyond in vitro biotests. We discuss future importance of automated quantitative data acquisition for cell-free, cell-based as well as developments in phytotoxicity and in vivo biotests utilizing small aquatic model organisms. We also discuss recent innovations such as organs-on-a-chip technologies and existing challenges for emerging high-throughput ecotoxicity testing strategies. Lastly, we provide seminal examples of the small number of successful high-throughput implementations that have been employed in prioritization of chemicals and accelerated environmental risk assessment.
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Affiliation(s)
- Donald Wlodkowic
- The Neurotox Lab, School of Science, RMIT University, Melbourne, VIC, 3083, Australia.
| | - Marcus Jansen
- LemnaTec GmbH, Nerscheider Weg 170, 52076, Aachen, Germany
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Stanfield Z, Setzer RW, Hull V, Sayre RR, Isaacs KK, Wambaugh JF. Bayesian inference of chemical exposures from NHANES urine biomonitoring data. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2022; 32:833-846. [PMID: 35978002 PMCID: PMC9979158 DOI: 10.1038/s41370-022-00459-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 07/05/2022] [Accepted: 07/12/2022] [Indexed: 05/25/2023]
Abstract
BACKGROUND Knowing which environmental chemicals contribute to metabolites observed in humans is necessary for meaningful estimates of exposure and risk from biomonitoring data. OBJECTIVE Employ a modeling approach that combines biomonitoring data with chemical metabolism information to produce chemical exposure intake rate estimates with well-quantified uncertainty. METHODS Bayesian methodology was used to infer ranges of exposure for parent chemicals of biomarkers measured in urine samples from the U.S population by the National Health and Nutrition Examination Survey (NHANES). Metabolites were probabilistically linked to parent chemicals using the NHANES reports and text mining of PubMed abstracts. RESULTS Chemical exposures were estimated for various population groups and translated to risk-based prioritization using toxicokinetic (TK) modeling and experimental data. Exposure estimates were investigated more closely for children aged 3 to 5 years, a population group that debuted with the 2015-2016 NHANES cohort. SIGNIFICANCE The methods described here have been compiled into an R package, bayesmarker, and made publicly available on GitHub. These inferred exposures, when coupled with predicted toxic doses via high throughput TK, can help aid in the identification of public health priority chemicals via risk-based bioactivity-to-exposure ratios.
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Affiliation(s)
- Zachary Stanfield
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - R Woodrow Setzer
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Victoria Hull
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
- Oak Ridge Associated Universities (ORAU), Oak Ridge, TN, 37830, USA
| | - Risa R Sayre
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Kristin K Isaacs
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - John F Wambaugh
- 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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Breen M, Wambaugh JF, Bernstein A, Sfeir M, Ring CL. Simulating toxicokinetic variability to identify susceptible and highly exposed populations. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2022; 32:855-863. [PMID: 36329211 PMCID: PMC9979157 DOI: 10.1038/s41370-022-00491-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 10/19/2022] [Accepted: 10/20/2022] [Indexed: 05/02/2023]
Abstract
BACKGROUND Toxicokinetic (TK) data needed for chemical risk assessment are not available for most chemicals. To support a greater number of chemicals, the U.S. Environmental Protection Agency (EPA) created the open-source R package "httk" (High Throughput ToxicoKinetics). The "httk" package provides functions and data tables for simulation and statistical analysis of chemical TK, including a population variability simulator that uses biometrics data from the National Health and Nutrition Examination Survey (NHANES). OBJECTIVE Here we modernize the "HTTK-Pop" population variability simulator based on the currently available data and literature. We provide explanations of the algorithms used by "httk" for variability simulation and uncertainty propagation. METHODS We updated and revised the population variability simulator in the "httk" package with the most recent NHANES biometrics (up to the 2017-18 NHANES cohort). Model equations describing glomerular filtration rate (GFR) were revised to more accurately represent physiology and population variability. The model output from the updated "httk" package was compared with the current version. RESULTS The revised population variability simulator in the "httk" package now provides refined, more relevant, and better justified estimations. SIGNIFICANCE Fulfilling the U.S. EPA's mission to provide open-source data and models for evaluations and applications by the broader scientific community, and continuously improving the accuracy of the "httk" package based on the currently available data and literature.
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Affiliation(s)
- Miyuki Breen
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - John F Wambaugh
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Amanda Bernstein
- Oak Ridge Institute for Science and Education (ORISE) fellow at the Center for Public Health and Environmental Assessment, Research Triangle Park, NC, USA
| | - Mark Sfeir
- Oak Ridge Institute for Science and Education (ORISE) fellow at the Center for Computational Toxicology and Exposure, Research Triangle Park, NC, USA
| | - Caroline L Ring
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC, USA.
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Arnot JA, Toose L, Armitage JM, Sangion A, Looky A, Brown TN, Li L, Becker RA. Developing an internal threshold of toxicological concern (iTTC). JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2022; 32:877-884. [PMID: 36347933 PMCID: PMC9731903 DOI: 10.1038/s41370-022-00494-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 10/25/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Threshold of Toxicological Concern (TTC) approaches are used for chemical safety assessment and risk-based priority setting for data poor chemicals. TTCs are derived from in vivo No Observed Effect Level (NOEL) datasets involving an external administered dose from a single exposure route, e.g., oral intake rate. Thus, a route-specific TTC can only be compared to a route-specific exposure estimate and such TTCs cannot be used for other exposure scenarios such as aggregate exposures. OBJECTIVE Develop and apply a method for deriving internal TTCs (iTTCs) that can be used in chemical assessments for multiple route-specific exposures (e.g., oral, inhalation or dermal) or aggregate exposures. METHODS Chemical-specific toxicokinetics (TK) data and models are applied to calculate internal concentrations (whole-body and blood) from the reported administered oral dose NOELs used to derive the Munro TTCs. The new iTTCs are calculated from the 5th percentile of cumulative distributions of internal NOELs and the commonly applied uncertainty factor of 100 to extrapolate animal testing data for applications in human health assessment. RESULTS The new iTTCs for whole-body and blood are 0.5 nmol/kg and 0.1 nmol/L, respectively. Because the iTTCs are expressed on a molar basis they are readily converted to chemical mass iTTCs using the molar mass of the chemical of interest. For example, the median molar mass in the dataset is 220 g/mol corresponding to an iTTC of 22 ng/L-blood (22 pg/mL-blood). The iTTCs are considered broadly applicable for many organic chemicals except those that are genotoxic or acetylcholinesterase inhibitors. The new iTTCs can be compared with measured or estimated whole-body or blood exposure concentrations for chemical safety screening and priority-setting. SIGNIFICANCE Existing Threshold of Toxicological Concern (TTC) approaches are limited in their applications for route-specific exposure scenarios only and are not suitable for chemical risk and safety assessments under conditions of aggregate exposure. New internal Threshold of Toxicological Concern (iTTC) values are developed to address data gaps in chemical safety estimation for multi-route and aggregate exposures.
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Affiliation(s)
- Jon A Arnot
- ARC Arnot Research and Consulting Inc., Toronto, ON, Canada.
- Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada.
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada.
| | - Liisa Toose
- ARC Arnot Research and Consulting Inc., Toronto, ON, Canada
| | | | - Alessandro Sangion
- ARC Arnot Research and Consulting Inc., Toronto, ON, Canada
- Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | | | - Trevor N Brown
- ARC Arnot Research and Consulting Inc., Toronto, ON, Canada
| | - Li Li
- School of Public Health, University of Nevada Reno, Reno, NV, USA
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Wambaugh JF, Rager JE. Exposure forecasting - ExpoCast - for data-poor chemicals in commerce and the environment. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2022; 32:783-793. [PMID: 36347934 PMCID: PMC9742338 DOI: 10.1038/s41370-022-00492-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 10/21/2022] [Accepted: 10/21/2022] [Indexed: 05/10/2023]
Abstract
Estimates of exposure are critical to prioritize and assess chemicals based on risk posed to public health and the environment. The U.S. Environmental Protection Agency (EPA) is responsible for regulating thousands of chemicals in commerce and the environment for which exposure data are limited. Since 2009 the EPA's ExpoCast ("Exposure Forecasting") project has sought to develop the data, tools, and evaluation approaches required to generate rapid and scientifically defensible exposure predictions for the full universe of existing and proposed commercial chemicals. This review article aims to summarize issues in exposure science that have been addressed through initiatives affiliated with ExpoCast. ExpoCast research has generally focused on chemical exposure as a statistical systems problem intended to inform thousands of chemicals. The project exists as a companion to EPA's ToxCast ("Toxicity Forecasting") project which has used in vitro high-throughput screening technologies to characterize potential hazard posed by thousands of chemicals for which there are limited toxicity data. Rapid prediction of chemical exposures and in vitro-in vivo extrapolation (IVIVE) of ToxCast data allow for prioritization based upon risk of adverse outcomes due to environmental chemical exposure. ExpoCast has developed (1) integrated modeling approaches to reliably predict exposure and IVIVE dose, (2) highly efficient screening tools for chemical prioritization, (3) efficient and affordable tools for generating new exposure and dose data, and (4) easily accessible exposure databases. The development of new exposure models and databases along with the application of technologies like non-targeted analysis and machine learning have transformed exposure science for data-poor chemicals. By developing high-throughput tools for chemical exposure analytics and translating those tools into public health decisions ExpoCast research has served as a crucible for identifying and addressing exposure science knowledge gaps.
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Affiliation(s)
- John F Wambaugh
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. EPA, Research Triangle Park, NC, USA.
- Department of Environmental Sciences & Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Julia E Rager
- Department of Environmental Sciences & Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Isaacs KK, Egeghy P, Dionisio KL, Phillips KA, Zidek A, Ring C, Sobus JR, Ulrich EM, Wetmore BA, Williams AJ, Wambaugh JF. The chemical landscape of high-throughput new approach methodologies for exposure. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2022; 32:820-832. [PMID: 36435938 PMCID: PMC9882966 DOI: 10.1038/s41370-022-00496-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 10/26/2022] [Accepted: 10/27/2022] [Indexed: 05/25/2023]
Abstract
The rapid characterization of risk to humans and ecosystems from exogenous chemicals requires information on both hazard and exposure. The U.S. Environmental Protection Agency's ToxCast program and the interagency Tox21 initiative have screened thousands of chemicals in various high-throughput (HT) assay systems for in vitro bioactivity. EPA's ExpoCast program is developing complementary HT methods for characterizing the human and ecological exposures necessary to interpret HT hazard data in a real-world risk context. These new approach methodologies (NAMs) for exposure include computational and analytical tools for characterizing multiple components of the complex pathways chemicals take from their source to human and ecological receptors. Here, we analyze the landscape of exposure NAMs developed in ExpoCast in the context of various chemical lists of scientific and regulatory interest, including the ToxCast and Tox21 libraries and the Toxic Substances Control Act (TSCA) inventory. We examine the landscape of traditional and exposure NAM data covering chemical use, emission, environmental fate, toxicokinetics, and ultimately external and internal exposure. We consider new chemical descriptors, machine learning models that draw inferences from existing data, high-throughput exposure models, statistical frameworks that integrate multiple model predictions, and non-targeted analytical screening methods that generate new HT monitoring information. We demonstrate that exposure NAMs drastically improve the coverage of the chemical landscape compared to traditional approaches and recommend a set of research activities to further expand the development of HT exposure data for application to risk characterization. Continuing to develop exposure NAMs to fill priority data gaps identified here will improve the availability and defensibility of risk-based metrics for use in chemical prioritization and screening. IMPACT: This analysis describes the current state of exposure assessment-based new approach methodologies across varied chemical landscapes and provides recommendations for filling key data gaps.
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Affiliation(s)
- Kristin K Isaacs
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA.
| | - Peter Egeghy
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Kathie L Dionisio
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Katherine A Phillips
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Angelika Zidek
- Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Caroline Ring
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Jon R Sobus
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Elin M Ulrich
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Barbara A Wetmore
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Antony J Williams
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - John F Wambaugh
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
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Kapraun DF, Sfeir M, Pearce RG, Davidson-Fritz SE, Lumen A, Dallmann A, Judson RS, Wambaugh JF. Evaluation of a rapid, generic human gestational dose model. Reprod Toxicol 2022; 113:172-188. [PMID: 36122840 PMCID: PMC9761697 DOI: 10.1016/j.reprotox.2022.09.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Revised: 08/30/2022] [Accepted: 09/14/2022] [Indexed: 10/14/2022]
Abstract
Chemical risk assessment considers potentially susceptible populations including pregnant women and developing fetuses. Humans encounter thousands of chemicals in their environments, few of which have been fully characterized. Toxicokinetic (TK) information is needed to relate chemical exposure to potentially bioactive tissue concentrations. Observational data describing human gestational exposures are unavailable for most chemicals, but physiologically based TK (PBTK) models estimate such exposures. Development of chemical-specific PBTK models requires considerable time and resources. As an alternative, generic PBTK approaches describe a standardized physiology and characterize chemicals with a set of standard physical and TK descriptors - primarily plasma protein binding and hepatic clearance. Here we report and evaluate a generic PBTK model of a human mother and developing fetus. We used a published set of formulas describing the major anatomical and physiological changes that occur during pregnancy to augment the High-Throughput Toxicokinetics (httk) software package. We simulated the ratio of concentrations in maternal and fetal plasma and compared to literature in vivo measurements. We evaluated the model with literature in vivo time-course measurements of maternal plasma concentrations in pregnant and non-pregnant women. Finally, we prioritized chemicals measured in maternal serum based on predicted fetal brain concentrations. This new model can be used for TK simulations of 859 chemicals with existing human-specific in vitro TK data as well as any new chemicals for which such data become available. This gestational model may allow for in vitro to in vivo extrapolation of point of departure doses relevant to reproductive and developmental toxicity.
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Affiliation(s)
- Dustin F Kapraun
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Mark Sfeir
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA; Oak Ridge Institute for Science and Education, Oak Ridge, TN 37831, USA
| | - Robert G Pearce
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA; Oak Ridge Institute for Science and Education, Oak Ridge, TN 37831, USA
| | - Sarah E Davidson-Fritz
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Annie Lumen
- National Center for Toxicological Research, US Food and Drug Administration, USA
| | - André Dallmann
- Pharmacometrics/Modeling and Simulation, Research and Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
| | - Richard S Judson
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - John F Wambaugh
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
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Najjar A, Punt A, Wambaugh J, Paini A, Ellison C, Fragki S, Bianchi E, Zhang F, Westerhout J, Mueller D, Li H, Shi Q, Gant TW, Botham P, Bars R, Piersma A, van Ravenzwaay B, Kramer NI. Towards best use and regulatory acceptance of generic physiologically based kinetic (PBK) models for in vitro-to-in vivo extrapolation (IVIVE) in chemical risk assessment. Arch Toxicol 2022; 96:3407-3419. [PMID: 36063173 PMCID: PMC9584981 DOI: 10.1007/s00204-022-03356-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 08/03/2022] [Indexed: 11/28/2022]
Abstract
With an increasing need to incorporate new approach methodologies (NAMs) in chemical risk assessment and the concomitant need to phase out animal testing, the interpretation of in vitro assay readouts for quantitative hazard characterisation becomes more important. Physiologically based kinetic (PBK) models, which simulate the fate of chemicals in tissues of the body, play an essential role in extrapolating in vitro effect concentrations to in vivo bioequivalent exposures. As PBK-based testing approaches evolve, it will become essential to standardise PBK modelling approaches towards a consensus approach that can be used in quantitative in vitro-to-in vivo extrapolation (QIVIVE) studies for regulatory chemical risk assessment based on in vitro assays. Based on results of an ECETOC expert workshop, steps are recommended that can improve regulatory adoption: (1) define context and implementation, taking into consideration model complexity for building fit-for-purpose PBK models, (2) harmonise physiological input parameters and their distribution and define criteria for quality chemical-specific parameters, especially in the absence of in vivo data, (3) apply Good Modelling Practices (GMP) to achieve transparency and design a stepwise approach for PBK model development for risk assessors, (4) evaluate model predictions using alternatives to in vivo PK data including read-across approaches, (5) use case studies to facilitate discussions between modellers and regulators of chemical risk assessment. Proof-of-concepts of generic PBK modelling approaches are published in the scientific literature at an increasing rate. Working on the previously proposed steps is, therefore, needed to gain confidence in PBK modelling approaches for regulatory use.
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Affiliation(s)
| | - Ans Punt
- Wageningen Food Safety Research, Wageningen, The Netherlands
| | - John Wambaugh
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC USA
| | | | | | - Styliani Fragki
- National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | | | | | - Joost Westerhout
- The Netherlands Organisation for Applied Scientific Research TNO, Utrecht, The Netherlands
| | - Dennis Mueller
- Research and Development, Crop Science, Bayer AG, Monheim, Germany
| | - Hequn Li
- Unilever Safety and Environmental Assurance Centre, Colworth Science Park, Sharnbrook, Bedfordshire UK
| | - Quan Shi
- Shell Global Solutions International B.V, The Hague, The Netherlands
| | - Timothy W. Gant
- School of Public Health, Faculty of Medicine, Imperial College London, London, UK
| | - Phil Botham
- Syngenta, Jealott’s Hill, Bracknell, Berkshire UK
| | - Rémi Bars
- Crop Science Division, Bayer S.A.S., Sophia Antipolis, France
| | - Aldert Piersma
- National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | | | - Nynke I. Kramer
- Toxicology Division, Wageningen University, PO Box 8000, 6700 EA Wageningen, The Netherlands
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Khalidi H, Onasanwo A, Islam B, Jo H, Fisher C, Aidley R, Gardner I, Bois FY. SimRFlow: An R-based workflow for automated high-throughput PBPK simulation with the Simcyp® simulator. Front Pharmacol 2022; 13:929200. [PMID: 36091744 PMCID: PMC9455594 DOI: 10.3389/fphar.2022.929200] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/01/2022] [Indexed: 11/24/2022] Open
Abstract
SimRFlow is a high-throughput physiologically based pharmacokinetic (PBPK) modelling tool which uses Certara’s Simcyp® simulator. The workflow is comprised of three main modules: 1) a Data Collection module for automated curation of physicochemical (from ChEMBL and the Norman Suspect List databases) and experimental data (i.e.: clearance, plasma-protein binding, and blood-to-plasma ratio, from httk-R package databases), 2) a Simulation module which activates the Simcyp® simulator and runs Monte Carlo simulations on virtual subjects using the curated data, and 3) a Data Visualisation module for understanding the simulated compound-specific profiles and predictions. SimRFlow has three administration routes (oral, intravenous, dermal) and allows users to change some simulation parameters including the number of subjects, simulation duration, and dosing. Users are only expected to provide a file of the compounds they wish to simulate, and in return the workflow provides summary statistics, concentration-time profiles of various tissue types, and a database file (containing in-depth results) for each simulated compound. This is presented within a guided and easy-to-use R Shiny interface which provides many plotting options for the visualisation of concentration-time profiles, parameter distributions, trends between the different parameters, as well as comparison of predicted parameters across all batch-simulated compounds. The in-built R functions can be assembled in user-customised scripts which allows for the modification of the workflow for different purposes. SimRFlow proves to be a time-efficient tool for simulating a large number of compounds without any manual curation of physicochemical or experimental data necessary to run Simcyp® simulations.
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Middleton AM, Reynolds J, Cable S, Baltazar MT, Li H, Bevan S, Carmichael PL, Dent MP, Hatherell S, Houghton J, Kukic P, Liddell M, Malcomber S, Nicol B, Park B, Patel H, Scott S, Sparham C, Walker P, White A. Are Non-animal Systemic Safety Assessments Protective? A Toolbox and Workflow. Toxicol Sci 2022; 189:124-147. [PMID: 35822611 PMCID: PMC9412174 DOI: 10.1093/toxsci/kfac068] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
An important question in toxicological risk assessment is whether non-animal new approach methodologies (NAMs) can be used to make safety decisions that are protective of human health, without being overly conservative. In this work, we propose a core NAM toolbox and workflow for conducting systemic safety assessments for adult consumers. We also present an approach for evaluating how protective and useful the toolbox and workflow are by benchmarking against historical safety decisions. The toolbox includes physiologically based kinetic (PBK) models to estimate systemic Cmax levels in humans, and 3 bioactivity platforms, comprising high-throughput transcriptomics, a cell stress panel, and in vitro pharmacological profiling, from which points of departure are estimated. A Bayesian model was developed to quantify the uncertainty in the Cmax estimates depending on how the PBK models were parameterized. The feasibility of the evaluation approach was tested using 24 exposure scenarios from 10 chemicals, some of which would be considered high risk from a consumer goods perspective (eg, drugs that are systemically bioactive) and some low risk (eg, existing food or cosmetic ingredients). Using novel protectiveness and utility metrics, it was shown that up to 69% (9/13) of the low risk scenarios could be identified as such using the toolbox, whilst being protective against all (5/5) the high-risk ones. The results demonstrated how robust safety decisions could be made without using animal data. This work will enable a full evaluation to assess how protective and useful the toolbox and workflow are across a broader range of chemical-exposure scenarios.
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Affiliation(s)
| | - Joe Reynolds
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
| | - Sophie Cable
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
| | | | - Hequn Li
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
| | | | - Paul L Carmichael
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
| | - Matthew Philip Dent
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
| | - Sarah Hatherell
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
| | - Jade Houghton
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
| | - Predrag Kukic
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
| | - Mark Liddell
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
| | - Sophie Malcomber
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
| | - Beate Nicol
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
| | | | - Hiral Patel
- Charles River Laboratories, Cambridgeshire, CB10 1XL, UK
| | - Sharon Scott
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
| | - Chris Sparham
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
| | - Paul Walker
- Cyprotex Discovery Ltd, Cheshire SK10 4TG, UK
| | - Andrew White
- Unilever Safety and Environmental Assurance Centre, Bedfordshire MK44 1LQ, UK
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40
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Algharably EA, Di Consiglio E, Testai E, Pistollato F, Mielke H, Gundert-Remy U. In Vitro- In Vivo Extrapolation by Physiologically Based Kinetic Modeling: Experience With Three Case Studies and Lessons Learned. FRONTIERS IN TOXICOLOGY 2022; 4:885843. [PMID: 35924078 PMCID: PMC9340473 DOI: 10.3389/ftox.2022.885843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 05/09/2022] [Indexed: 11/27/2022] Open
Abstract
Physiologically based kinetic (PBK) modeling has been increasingly used since the beginning of the 21st century to support dose selection to be used in preclinical and clinical safety studies in the pharmaceutical sector. For chemical safety assessment, the use of PBK has also found interest, however, to a smaller extent, although an internationally agreed document was published already in 2010 (IPCS/WHO), but at that time, PBK modeling was based mostly on in vivo data as the example in the IPCS/WHO document indicates. Recently, the OECD has published a guidance document which set standards on how to characterize, validate, and report PBK models for regulatory purposes. In the past few years, we gained experience on using in vitro data for performing quantitative in vitro–in vivo extrapolation (QIVIVE), in which biokinetic data play a crucial role to obtain a realistic estimation of human exposure. In addition, pharmaco-/toxicodynamic aspects have been introduced into the approach. Here, three examples with different drugs/chemicals are described, in which different approaches have been applied. The lessons we learned from the exercise are as follows: 1) in vitro conditions should be considered and compared to the in vivo situation, particularly for protein binding; 2) in vitro inhibition of metabolizing enzymes by the formed metabolites should be taken into consideration; and 3) it is important to extrapolate from the in vitro measured intracellular concentration and not from the nominal concentration to the tissue/organ concentration to come up with an appropriate QIVIVE for the relevant adverse effects.
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Affiliation(s)
- Engi Abdelhady Algharably
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Clinical Pharmacology and Toxicology, Berlin, Germany
| | - Emma Di Consiglio
- Mechanisms, Biomarkers and Models Unit, Environment and Health Department, Istituto Superiore di Sanità, Rome, Italy
| | - Emanuela Testai
- Mechanisms, Biomarkers and Models Unit, Environment and Health Department, Istituto Superiore di Sanità, Rome, Italy
| | | | - Hans Mielke
- Federal Institute for Risk Assessment, Berlin, Germany
| | - Ursula Gundert-Remy
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Clinical Pharmacology and Toxicology, Berlin, Germany.,Federal Institute for Risk Assessment, Berlin, Germany
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41
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Sweeney LM. Case study on the impact of the source of metabolism parameters in next generation physiologically based pharmacokinetic models: Implications for occupational exposures to trimethylbenzenes. Regul Toxicol Pharmacol 2022; 134:105238. [PMID: 35931234 DOI: 10.1016/j.yrtph.2022.105238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 07/14/2022] [Accepted: 07/19/2022] [Indexed: 10/16/2022]
Abstract
Physiologically based pharmacokinetic (PBPK) models are a means of making important linkages between exposure assessment and in vitro toxicity. A key constraint on rapid application of PBPK models in risk assessment is traditional reliance on substance-specific in vivo toxicokinetic data to evaluate model quality. Bounding conditions, in silico, in vitro, and chemical read-across approaches have been proposed as alternative sources for metabolic clearance estimates. A case study to test consistency of predictive ability across these approaches was conducted using trimethylbenzenes (TMB) as prototype chemicals. Substantial concordance was found among TMB isomers with respect to accuracy (or inaccuracy) of approaches to estimating metabolism; for example, the bounding conditions never reproduced the human in vivo toxicokinetic data within two-fold. Using only approaches that gave acceptable prediction of in vivo toxicokinetics for the source compound (1,2,4-TMB) substantially narrowed the range of plausible internal doses for a given external dose for occupational, emergency response, and environmental/community health risk assessment scenarios for TMB isomers. Thus, risk assessments developed using the target compound models with a constrained subset of metabolism estimates (determined for source chemical models) can be used with greater confidence that internal dosimetry will be estimated with accuracy sufficient for the purpose at hand.
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Affiliation(s)
- Lisa M Sweeney
- UES, Inc, 4401 Dayton Xenia Road, Dayton, OH, 45432, USA(contractor assigned to the U.S. Air Force Research Laboratory 711th Human Performance Wing, Wright Patterson AFB, OH USA).
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42
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Alvarez-Mora I, Mijangos L, Lopez-Herguedas N, Amigo JM, Eguiraun H, Salvoch M, Monperrus M, Etxebarria N. SETApp: A machine learning and image analysis based application to automate the sea urchin embryo test. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 241:113728. [PMID: 35689888 DOI: 10.1016/j.ecoenv.2022.113728] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 05/24/2022] [Accepted: 05/30/2022] [Indexed: 06/15/2023]
Abstract
Since countless xenobiotic compounds are being found in the environment, ecotoxicology faces an astounding challenge in identifying toxicants. The combination of high-throughput in vivo/in vitro bioassays with high-resolution chemical analysis is an effective way to elucidate the cause-effect relationship. However, these combined strategies imply an enormous workload that can hinder their implementation in routine analysis. The purpose of this study was to develop a new high throughput screening method that could be used as a predictive expert system that automatically quantifies the size increase and malformation of the larvae and, thus, eases the application of the sea urchin embryo test in complex toxicant identification pipelines such as effect-directed analysis. For this task, a training set of 242 images was used to calibrate the size-increase and malformation level of the larvae. Two classification models based on partial least squares discriminant analysis (PLS-DA) were built and compared. Moreover, Hierarchical PLS-DA shows a high proficiency in classifying the larvae, achieving a prediction accuracy of 84 % in validation. The scripts built along the work were compiled in a user-friendly standalone app (SETApp) freely accessible at https://github.com/UPV-EHU-IBeA/SETApp. The SETApp was tested in a real case scenario to fulfill the tedious requirements of a WWTP effect-directed analysis.
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Affiliation(s)
- Iker Alvarez-Mora
- Department of Analytical Chemistry, University of the Basque Country, Leioa, Biscay, Basque Country 48080, Spain; Plentzia Marine Station, University of the Basque Country, Plentzia, Biscay, Basque Country 48620, Spain.
| | - Leire Mijangos
- Department of Analytical Chemistry, University of the Basque Country, Leioa, Biscay, Basque Country 48080, Spain; Plentzia Marine Station, University of the Basque Country, Plentzia, Biscay, Basque Country 48620, Spain.
| | - Naroa Lopez-Herguedas
- Department of Analytical Chemistry, University of the Basque Country, Leioa, Biscay, Basque Country 48080, Spain; Plentzia Marine Station, University of the Basque Country, Plentzia, Biscay, Basque Country 48620, Spain.
| | - Jose M Amigo
- Department of Analytical Chemistry, University of the Basque Country, Leioa, Biscay, Basque Country 48080, Spain; Ikerbasque, Basque Foundation for Science, Bilbao, Biscay, Basque Country 48009, Spain.
| | - Harkaitz Eguiraun
- Plentzia Marine Station, University of the Basque Country, Plentzia, Biscay, Basque Country 48620, Spain; Department of Graphic Design and Engineering Projects, University of the Basque Country, Bilbao, Biscay, Basque Country 48013, Spain.
| | - Maddi Salvoch
- Department of Analytical Chemistry, University of the Basque Country, Leioa, Biscay, Basque Country 48080, Spain; Plentzia Marine Station, University of the Basque Country, Plentzia, Biscay, Basque Country 48620, Spain.
| | - Mathilde Monperrus
- Institut des Sciences Analytiques et de Physico-chimie pour l'Environnement et les matériaux, Université de Pau et des Pays de l'Adour, Angelu, Basque Country 64000, France.
| | - Nestor Etxebarria
- Department of Analytical Chemistry, University of the Basque Country, Leioa, Biscay, Basque Country 48080, Spain; Plentzia Marine Station, University of the Basque Country, Plentzia, Biscay, Basque Country 48620, Spain.
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Kuo B, Beal MA, Wills JW, White PA, Marchetti F, Nong A, Barton-Maclaren TS, Houck K, Yauk CL. Comprehensive interpretation of in vitro micronucleus test results for 292 chemicals: from hazard identification to risk assessment application. Arch Toxicol 2022; 96:2067-2085. [PMID: 35445829 PMCID: PMC9151546 DOI: 10.1007/s00204-022-03286-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 02/23/2022] [Indexed: 11/08/2022]
Abstract
Risk assessments are increasingly reliant on information from in vitro assays. The in vitro micronucleus test (MNvit) is a genotoxicity test that detects chromosomal abnormalities, including chromosome breakage (clastogenicity) and/or whole chromosome loss (aneugenicity). In this study, MNvit datasets for 292 chemicals, generated by the US EPA's ToxCast program, were evaluated using a decision tree-based pipeline for hazard identification. Chemicals were tested with 19 concentrations (n = 1) up to 200 µM, in the presence and absence of Aroclor 1254-induced rat liver S9. To identify clastogenic chemicals, %MN values at each concentration were compared to a distribution of batch-specific solvent controls; this was followed by cytotoxicity assessment and benchmark concentration (BMC) analyses. The approach classified 157 substances as positives, 25 as negatives, and 110 as inconclusive. Using the approach described in Bryce et al. (Environ Mol Mutagen 52:280-286, 2011), we identified 15 (5%) aneugens. IVIVE (in vitro to in vivo extrapolation) was employed to convert BMCs into administered equivalent doses (AEDs). Where possible, AEDs were compared to points of departure (PODs) for traditional genotoxicity endpoints; AEDs were generally lower than PODs based on in vivo endpoints. To facilitate interpretation of in vitro MN assay concentration-response data for risk assessment, exposure estimates were utilized to calculate bioactivity exposure ratio (BER) values. BERs for 50 clastogens and two aneugens had AEDs that approached exposure estimates (i.e., BER < 100); these chemicals might be considered priorities for additional testing. This work provides a framework for the use of high-throughput in vitro genotoxicity testing for priority setting and chemical risk assessment.
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Affiliation(s)
- Byron Kuo
- Environmental Health Science and Research Bureau, Environmental and Radiation Health Sciences Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Marc A Beal
- Bureau of Chemical Safety, Food Directorate, Health Products and Food Branch, Health Canada, Ottawa, ON, Canada
| | - John W Wills
- Environmental Health Science and Research Bureau, Environmental and Radiation Health Sciences Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
- Biominerals Research, Department of Veterinary Medicine, University of Cambridge, Cambridge, CB3 0ES, UK
| | - Paul A White
- Environmental Health Science and Research Bureau, Environmental and Radiation Health Sciences Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Francesco Marchetti
- Environmental Health Science and Research Bureau, Environmental and Radiation Health Sciences Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Andy Nong
- Environmental Health Science and Research Bureau, Environmental and Radiation Health Sciences Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Tara S Barton-Maclaren
- Existing Substances Risk Assessment Bureau, Safe Environments Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada
| | - Keith Houck
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, 27711, USA
| | - Carole L Yauk
- Environmental Health Science and Research Bureau, Environmental and Radiation Health Sciences Directorate, Healthy Environment and Consumer Safety Branch, Health Canada, Ottawa, ON, Canada.
- Department of Biology, University of Ottawa, 30 Marie Curie Private, Room 269, Ottawa, ON, K1N 6N5, Canada.
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44
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Elsaid HH, Badary OA, Shouman SA, Elmazar M, El-Khatib AS. Enhanced antitumor activity of combined methotrexate and histone deacetylase inhibitor valproic acid on mammary cancer in vitro and in vivo. Can J Physiol Pharmacol 2022; 100:915-925. [PMID: 35679619 DOI: 10.1139/cjpp-2021-0799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Histone deacetylase inhibitors (HDACIs) act as antiproliferative agents by promoting differentiation and inducing apoptosis. Valproic acid (VPA) is an HDACI that shows promising chemotherapeutic effect in several tumor cells. The present study aimed to investigate the inhibitory effect of VPA on the viability of mammary cancer cells and its enhancing effect with methotrexate (MTX) in vitro and in vivo. Treatment with VPA or MTX alone induced concentration-dependent cytotoxic effects in two breast cancer cell lines. VPA significantly increased the cytotoxicity of MTX 3 times against MCF7. VPA addition to MTX, however, did not produce any significant changes on MTX cytotoxicity against MDA-MB231. VPA (150 and 200 mg/kg) significantly inhibited the growth of IP and SC Ehrlich ascites carcinoma tumor mouse models and improved results were achieved for tumor inhibition when VPA was combined with MTX (1 and 2 mg/kg) in vivo. The antitumor activity was not associated with a significant increase in toxicity or mice mortality rate. All these findings suggest that the combination of MTX and VPA may have clinical and/or adjuvant therapeutic application in the treatment of mammary cancer.
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Affiliation(s)
- Hadia Hosny Elsaid
- The British University in Egypt, 120633, Department of Pharmacology and Biochemistry, El Shorouk, Cairo, Egypt;
| | - Osama A Badary
- The British University in Egypt, 120633, Department of Clinical Pharmacy Practice, El Shorouk, Cairo, Egypt;
| | - Samia A Shouman
- National Cancer Institute Cairo University, 68804, Cairo, Egypt;
| | - Mohey Elmazar
- The British University in Egypt, 120633, Department of Pharmacology and Biochemistry, Cairo,, Cairo, Egypt;
| | - Aiman S El-Khatib
- Cairo University Faculty of Pharmacy, 110154, Pharmacology and Toxicology, Cairo, Egypt;
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45
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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: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [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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46
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Moreau M, Mallick P, Smeltz M, Haider S, Nicolas CI, Pendse SN, Leonard JA, Linakis MW, McMullen PD, Clewell RA, Clewell HJ, Yoon M. Considerations for Improving Metabolism Predictions for In Vitro to In Vivo Extrapolation. FRONTIERS IN TOXICOLOGY 2022; 4:894569. [PMID: 35573278 PMCID: PMC9099212 DOI: 10.3389/ftox.2022.894569] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 04/13/2022] [Indexed: 12/14/2022] Open
Abstract
High-throughput (HT) in vitro to in vivo extrapolation (IVIVE) is an integral component in new approach method (NAM)-based risk assessment paradigms, for rapidly translating in vitro toxicity assay results into the context of in vivo exposure. When coupled with rapid exposure predictions, HT-IVIVE supports the use of HT in vitro assays for risk-based chemical prioritization. However, the reliability of prioritization based on HT bioactivity data and HT-IVIVE can be limited as the domain of applicability of current HT-IVIVE is generally restricted to intrinsic clearance measured primarily in pharmaceutical compounds. Further, current approaches only consider parent chemical toxicity. These limitations occur because current state-of-the-art HT prediction tools for clearance and metabolite kinetics do not provide reliable data to support HT-IVIVE. This paper discusses current challenges in implementation of IVIVE for prioritization and risk assessment and recommends a path forward for addressing the most pressing needs and expanding the utility of IVIVE.
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Affiliation(s)
- Marjory Moreau
- ScitoVation, LLC, Durham, NC, United States
- *Correspondence: Marjory Moreau,
| | | | | | | | | | | | - Jeremy A. Leonard
- Oak Ridge Institute for Science and Education, Oak Ridge, TN, United States
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47
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Dobreniecki S, Mendez E, Lowit A, Freudenrich TM, Wallace K, Carpenter A, Wetmore BA, Kreutz A, Korol-Bexell E, Friedman KP, Shafer TJ. Integration of toxicodynamic and toxicokinetic new approach methods into a weight-of-evidence analysis for pesticide developmental neurotoxicity assessment: A case-study with DL- and L-glufosinate. Regul Toxicol Pharmacol 2022; 131:105167. [PMID: 35413399 DOI: 10.1016/j.yrtph.2022.105167] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 02/14/2022] [Accepted: 04/06/2022] [Indexed: 01/13/2023]
Abstract
DL-glufosinate ammonium (DL-GLF) is a registered herbicide for which a guideline Developmental Neurotoxicity (DNT) study has been conducted. Offspring effects included altered brain morphometrics, decreased body weight, and increased motor activity. Guideline DNT studies are not available for its enriched isomers L-GLF acid and L-GLF ammonium; conducting one would be time consuming, resource-intensive, and possibly redundant given the existing DL-GLF DNT. To support deciding whether to request a guideline DNT study for the L-GLF isomers, DL-GLF and the L-GLF isomers were screened using in vitro assays for network formation and neurite outgrowth. DL-GLF and L-GLF isomers were without effects in both assays. DL-GLF and L-GLF (1-100 μM) isomers increased mean firing rate of mature networks to 120-140% of baseline. In vitro toxicokinetic assessments were used to derive administered equivalent doses (AEDs) for the in vitro testing concentrations. The AED for L-GLF was ∼3X higher than the NOAEL from the DL-GLF DNT indicating that the available guideline study would be protective of potential DNT due to L-GLF exposure. Based in part on the results of these in vitro studies, EPA is not requiring L-GLF isomer guideline DNT studies, thereby providing a case study for a useful application of DNT screening assays.
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Affiliation(s)
| | | | - Anna Lowit
- Office of Pesticide Programs USEPA, Washington, DC, USA
| | - Theresa M Freudenrich
- Center for Computational Toxicology and Exposure, Office of Research and Development. US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Kathleen Wallace
- Center for Computational Toxicology and Exposure, Office of Research and Development. US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Amy Carpenter
- Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN, USA
| | - Barbara A Wetmore
- Center for Computational Toxicology and Exposure, Office of Research and Development. US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Anna Kreutz
- Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN, USA
| | | | - Katie Paul Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development. US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Timothy J Shafer
- Center for Computational Toxicology and Exposure, Office of Research and Development. US Environmental Protection Agency, Research Triangle Park, NC, USA.
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48
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Rivera BN, Wilson LB, Kim DN, Pande P, Anderson KA, Tilton SC, Tanguay RL. A Comparative Multi-System Approach to Characterizing Bioactivity of Commonly Occurring Chemicals. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:3829. [PMID: 35409514 PMCID: PMC8998123 DOI: 10.3390/ijerph19073829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 03/15/2022] [Accepted: 03/19/2022] [Indexed: 12/10/2022]
Abstract
A 2019 retrospective study analyzed wristband personal samplers from fourteen different communities across three different continents for over 1530 organic chemicals. Investigators identified fourteen chemicals (G14) detected in over 50% of personal samplers. The G14 represent a group of chemicals that individuals are commonly exposed to, and are mainly associated with consumer products including plasticizers, fragrances, flame retardants, and pesticides. The high frequency of exposure to these chemicals raises questions of their potential adverse human health effects. Additionally, the possibility of exposure to mixtures of these chemicals is likely due to their co-occurrence; thus, the potential for mixtures to induce differential bioactivity warrants further investigation. This study describes a novel approach to broadly evaluate the hazards of personal chemical exposures by coupling data from personal sampling devices with high-throughput bioactivity screenings using in vitro and non-mammalian in vivo models. To account for species and sensitivity differences, screening was conducted using primary normal human bronchial epithelial (NHBE) cells and early life-stage zebrafish. Mixtures of the G14 and most potent G14 chemicals were created to assess potential mixture effects. Chemical bioactivity was dependent on the model system, with five and eleven chemicals deemed bioactive in NHBE and zebrafish, respectively, supporting the use of a multi-system approach for bioactivity testing and highlighting sensitivity differences between the models. In both NHBE and zebrafish, mixture effects were observed when screening mixtures of the most potent chemicals. Observations of BMC-based mixtures in NHBE (NHBE BMC Mix) and zebrafish (ZF BMC Mix) suggested antagonistic effects. In this study, consumer product-related chemicals were prioritized for bioactivity screening using personal exposure data. High-throughput high-content screening was utilized to assess the chemical bioactivity and mixture effects of the most potent chemicals.
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Affiliation(s)
- Brianna N. Rivera
- Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 97331, USA; (B.N.R.); (L.B.W.); (K.A.A.); (S.C.T.)
| | - Lindsay B. Wilson
- Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 97331, USA; (B.N.R.); (L.B.W.); (K.A.A.); (S.C.T.)
| | - Doo Nam Kim
- Pacific Northwest National Laboratory, Biological Sciences Division, Richland, WA 99354, USA; (D.N.K.); (P.P.)
| | - Paritosh Pande
- Pacific Northwest National Laboratory, Biological Sciences Division, Richland, WA 99354, USA; (D.N.K.); (P.P.)
| | - Kim A. Anderson
- Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 97331, USA; (B.N.R.); (L.B.W.); (K.A.A.); (S.C.T.)
| | - Susan C. Tilton
- Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 97331, USA; (B.N.R.); (L.B.W.); (K.A.A.); (S.C.T.)
| | - Robyn L. Tanguay
- Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 97331, USA; (B.N.R.); (L.B.W.); (K.A.A.); (S.C.T.)
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49
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Punt A, Louisse J, Pinckaers N, Fabian E, van Ravenzwaay B. Predictive Performance of Next Generation Physiologically Based Kinetic (PBK) Model Predictions in Rats Based on In Vitro and In Silico Input Data. Toxicol Sci 2022; 186:18-28. [PMID: 34927682 PMCID: PMC8883350 DOI: 10.1093/toxsci/kfab150] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
The goal of the present study was to assess the predictive performance of a minimal generic rat physiologically based kinetic (PBK) model based on in vitro and in silico input data to predict peak plasma concentrations (Cmax) upon single oral dosing. To this purpose, a dataset was generated of 3960 Cmax predictions for 44 compounds, applying different combinations of in vitro and in silico approaches for chemical parameterization, and comparison of the predictions to reported in vivo data. Best performance was obtained when (1) the hepatic clearance was parameterized based on in vitro measured intrinsic clearance values, (2) the method of Rodgers and Rowland for calculating partition coefficients, and (3) in silico calculated fraction unbound plasma and Papp values (the latter especially for very lipophilic compounds). Based on these input data, the median Cmax of 32 compounds could be predicted within 10-fold of the observed Cmax, with 22 out of these 32 compounds being predicted within 5-fold, and 8 compounds within 2-fold. Overestimations of more than 10-fold were observed for 12 compounds, whereas no underestimations of more than 10-fold occurred. Median Cmax predictions were frequently found to be within 10-fold of the observed Cmax when the scaled unbound hepatic intrinsic clearance (Clint,u) was either higher than 20 l/h or lower than 1 l/h. Similar findings were obtained with a test set of 5 in-house BASF compounds. Overall, this study provides relevant insights in the predictive performance of a minimal PBK model based on in vitro and in silico input data.
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Affiliation(s)
- Ans Punt
- Wageningen Food Safety Research, Wageningen University and Research, 6700 AE Wageningen, the Netherlands
| | - Jochem Louisse
- Wageningen Food Safety Research, Wageningen University and Research, 6700 AE Wageningen, the Netherlands
| | - Nicole Pinckaers
- Wageningen Food Safety Research, Wageningen University and Research, 6700 AE Wageningen, the Netherlands
| | - Eric Fabian
- Experimental Toxicology and Ecology, BASF SE, 67056 Ludwigshafen, Germany
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50
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Schmidt S. Filling in the Blanks: A New Tool to Predict Chemical Pathways from Production to Exposure. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:24002. [PMID: 35175097 PMCID: PMC8852263 DOI: 10.1289/ehp10756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 01/19/2022] [Indexed: 06/14/2023]
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