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Chen M, Du R, Zhang T, Li C, Bao W, Xin F, Hou S, Yang Q, Chen L, Wang Q, Zhu A. The Application of a Physiologically Based Toxicokinetic Model in Health Risk Assessment. TOXICS 2023; 11:874. [PMID: 37888724 PMCID: PMC10611306 DOI: 10.3390/toxics11100874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 10/17/2023] [Accepted: 10/19/2023] [Indexed: 10/28/2023]
Abstract
Toxicokinetics plays a crucial role in the health risk assessments of xenobiotics. Classical compartmental models are limited in their ability to determine chemical concentrations in specific organs or tissues, particularly target organs or tissues, and their limited interspecific and exposure route extrapolation hinders satisfactory health risk assessment. In contrast, physiologically based toxicokinetic (PBTK) models quantitatively describe the absorption, distribution, metabolism, and excretion of chemicals across various exposure routes and doses in organisms, establishing correlations with toxic effects. Consequently, PBTK models serve as potent tools for extrapolation and provide a theoretical foundation for health risk assessment and management. This review outlines the construction and application of PBTK models in health risk assessment while analyzing their limitations and future perspectives.
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Affiliation(s)
- Mengting Chen
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Ruihu Du
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, China
| | - Tao Zhang
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, China
| | - Chutao Li
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Wenqiang Bao
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Fan Xin
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
| | - Shaozhang Hou
- Department of Pathology, School of Basic Medical Sciences, Ningxia Medical University, Yinchuan 750004, China
| | - Qiaomei Yang
- Department of Gynecology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou 350001, China
| | - Li Chen
- Department of Gynecology, Fujian Maternity and Child Health Hospital (Fujian Obstetrics and Gynecology Hospital), Fuzhou 350001, China
| | - Qi Wang
- Department of Toxicology, School of Public Health, Peking University, Beijing 100191, China
- Key Laboratory of State Administration of Traditional Chinese Medicine for Compatibility Toxicology, Beijing 100191, China
- Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Beijing 100191, China
| | - An Zhu
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350108, China
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Mozaffari S, Bayatian M, Hsieh NH, Khadem M, Garmaroudi AA, Ashrafi K, Shahtaheri SJ. Reconstruction of exposure to methylene diphenyl-4,4'-diisocyanate (MDI) aerosol using computational fluid dynamics, physiologically based toxicokinetics and statistical modeling. Inhal Toxicol 2023; 35:285-299. [PMID: 38019695 DOI: 10.1080/08958378.2023.2285772] [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: 04/24/2023] [Accepted: 11/10/2023] [Indexed: 12/01/2023]
Abstract
OBJECTIVES This study employed computational fluid dynamics (CFD), physiologically based toxicokinetics (PBTK), and statistical modeling to reconstruct exposure to methylene diphenyl-4,4'-diisocyanate (MDI) aerosol. By utilizing a validated CFD model, human respiratory deposition of MDI aerosol in different workload conditions was investigated, while a PBTK model was calibrated using experimental rat data. Biomonitoring data and Markov Chain Monte Carlo (MCMC) simulation were utilized for exposure assessment. RESULTS Deposition fraction of MDI in the respiratory tract at the light, moderate, and heavy activity were 0.038, 0.079, and 0.153, respectively. Converged MCMC results as the posterior means and prior values were obtained for several PBTK model parameters. In our study, we calibrated a rat model to investigate the transport, absorption, and elimination of 4,4'-MDI via inhalation exposure. The calibration process successfully captured experimental data in the lungs, liver, blood, and kidneys, allowing for a reasonable representation of MDI distribution within the rat model. Our calibrated model also represents MDI dynamics in the bloodstream, facilitating the assessment of bioavailability. For human exposure, we validated the model for recent and long-term MDI exposure using data from relevant studies. CONCLUSION Our computational models provide reasonable insights into MDI exposure, contributing to informed risk assessment and the development of effective exposure reduction strategies.
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Affiliation(s)
- Sajjad Mozaffari
- Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Majid Bayatian
- Department of Occupational Health Engineering, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Nan-Hung Hsieh
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, TX A&M University, College Station, TX, USA
| | - Monireh Khadem
- Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Amir Abbasi Garmaroudi
- Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Khosro Ashrafi
- Department of Environmental Engineering, Faculty of Environment, University of Tehran, Tehran, Iran
| | - Seyed Jamaleddin Shahtaheri
- Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
- Center for Water Quality Research, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran
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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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Human Biomonitoring Data in Health Risk Assessments Published in Peer-Reviewed Journals between 2016 and 2021: Confronting Reality after a Preliminary Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19063362. [PMID: 35329058 PMCID: PMC8955248 DOI: 10.3390/ijerph19063362] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/09/2022] [Accepted: 03/11/2022] [Indexed: 02/01/2023]
Abstract
Human biomonitoring (HBM) is a rapidly developing field that is emphasized as an important approach for the assessment of health risks. However, its value for health risk assessment (HRA) remains to be clarified. We performed a review of publications concerned with applications of HBM in the assessment of health risks. The selection of publications for this review was limited by the search engines used (only PubMed and Scopus) and a timeframe of the last five years. The review focused on the clarity of 10 HRA elements, which influence the quality of HRA. We show that the usage of HBM data in HRA is limited and unclear. Primarily, the key HRA elements are not consistently applied or followed when using HBM in such assessments, and secondly, there are inconsistencies regarding the understanding of fundamental risk analysis principles and good practices in risk analysis. Our recommendations are as follows: (i) potential usage of HBM data in HRA should not be non-critically overestimated but rather limited and aligned to a specific value for exposure assessment or for the interpretation of health damage; (ii) improvements to HRA approaches, using HBM information or not, are needed and should strictly follow theoretical foundations of risk analysis.
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Kluxen FM, Felkers E, Baumann J, Morgan N, Wiemann C, Stauber F, Strupp C, Adham S, Kuster CJ. Compounded conservatism in European re-entry worker risk assessment of pesticides. Regul Toxicol Pharmacol 2021; 121:104864. [PMID: 33450327 DOI: 10.1016/j.yrtph.2021.104864] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 12/18/2020] [Accepted: 01/08/2021] [Indexed: 01/04/2023]
Abstract
We review the risk parameters and drivers in the current European Union (EU) worker risk assessment for pesticides, for example considering crop maintenance, crop inspection or harvesting activities, and show that the current approach is very conservative due to multiple worst-case default assumptions. As a case study, we compare generic exposure model estimates with measured worker re-entry exposure values which shows that external cumulative exposure is overpredicted by about 50-fold on average. For this exercise, data from 16 good laboratory practice (GLP)-compliant worker exposure studies in 6 crops were evaluated with a total number of 184 workers. As generic overprediction does not allow efficient risk management or realistic risk communication, we investigate how external exposure can be better predicted within the generic model, and outline options for possible improvements in the current methodology. We show that simply using averages achieves more meaningful exposure estimates, while still being conservative, with an average exposure overprediction of about 9-fold. Overall, EU risk assessment includes several numerically unaccounted "hidden safety factors", which means that workers are well protected; but simultaneously risk assessments are biased towards failing due to compounded conservatism. This should be considered for further global or regional guidance developments and performing more exposure-relevant risk assessment.
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Affiliation(s)
| | | | | | | | | | - Franz Stauber
- BASF SE, Agricultural Solutions, Ludwigshafen, Germany
| | | | - Sarah Adham
- Corteva Agriscience, Abingdon, United Kingdom
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