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Ali Daoud Y, Tebby C, Beaudouin R, Brochot C. Development of a physiologically based toxicokinetic model for lead in pregnant women: The role of bone tissue in the maternal and fetal internal exposure. Toxicol Appl Pharmacol 2023; 476:116651. [PMID: 37549741 DOI: 10.1016/j.taap.2023.116651] [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: 06/17/2023] [Revised: 08/01/2023] [Accepted: 08/04/2023] [Indexed: 08/09/2023]
Abstract
Epidemiological studies have shown associations between prenatal exposure to lead (Pb) and neurodevelopmental effects in young children. Prenatal exposure is generally characterized by measuring the concentration in the umbilical cord at delivery or in the maternal blood during pregnancy. To assess internal Pb exposure during prenatal life, we developed a pregnancy physiologically based pharmacokinetic (p-PBPK) model that to simulates Pb levels in blood and target tissues in the fetus, especially during critical periods for brain development. An existing Pb PBPK model was adapted to pregnant women and fetuses. Using data from literature, both the additional maternal bone remodeling, that causes Pb release into the blood, and the Pb placental transfers were estimated by Bayesian inference. Additional maternal bone remodeling was estimated to start at 21.6 weeks. Placental transfers were estimated between 4.6 and 283 L.day-1 at delivery with high interindividual variability. Once calibrated, the p-PBPK model was used to simulate fetal exposure to Pb. Internal fetal exposure greatly varies over the pregnancy with two peaks of Pb levels in blood and brain at the end of the 1st and 3rd trimesters. Sensitivity analysis shows that the fetal blood lead levels are affected by the maternal burden of bone Pb via maternal bone remodeling and by fetal bone formation at different pregnancy stages. Coupling the p-PBPK model with an effect model such as an adverse outcome pathway could help to predict the effects on children's neurodevelopment.
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Affiliation(s)
- Yourdasmine Ali Daoud
- Experimental toxicology and modeling unit (MIV/TEAM), Institut National de l'Environnement Industriel et des Risques, 60550 Verneuil-en-Halatte, France; Péritox, UMR-I 01, University of Picardie Jules Verne, 80025 Amiens, France
| | - Cleo Tebby
- Experimental toxicology and modeling unit (MIV/TEAM), Institut National de l'Environnement Industriel et des Risques, 60550 Verneuil-en-Halatte, France.
| | - Rémy Beaudouin
- Experimental toxicology and modeling unit (MIV/TEAM), Institut National de l'Environnement Industriel et des Risques, 60550 Verneuil-en-Halatte, France; Sebio, UMR-I 02, Institut National de l'Environnement Industriel et des Risques, 60550 Verneuil-en-Halatte, France
| | - Céline Brochot
- Experimental toxicology and modeling unit (MIV/TEAM), Institut National de l'Environnement Industriel et des Risques, 60550 Verneuil-en-Halatte, France; Certara UK Ltd, Simcyp Division, Sheffield, UK
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Rajput AJ, Aldibani HKA, Rostami-Hodjegan A. In-depth analysis of patterns in selection of different physiologically based pharmacokinetic modeling tools: PartI - Applications and rationale behind the use of open source-code software. Biopharm Drug Dispos 2023. [PMID: 37083200 DOI: 10.1002/bdd.2357] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 03/29/2023] [Accepted: 04/04/2023] [Indexed: 04/22/2023]
Abstract
PBPK applications published in the literature support a greater adoption of non-open source-code (NOSC) software as opposed to open source-code (OSC) alternatives. However, a significant number of PBPK modelers are still using OSC software, understanding the rationale for the use of this modality is important and may help those embarking on PBPK modeling. No previous analysis of PBPK modeling trends has included the rationale of the modeler. An in-depth analysis of PBPK applications of OSC software is warranted to determine the true impact of OSC software on the rise of PBPK. Publications focussing on PBPK modeling applications, which used OSC software, were identified by systematically searching the scientific literature for original articles. A total of 171 articles were extracted from the narrowed subset. The rise in the use of OSC software for PBPK applications was greater than the general discipline of pharmacokinetics (9 vs. 4), but less than the overall growth of the PBPK area (9 vs. 43). Our report demonstrates conclusively that the surge in PBPK usage is primarily attributable to the availability and implementations of NOSC software. Modelers preferred not to share the reasons for their selection of certain modeling software and no 'explicit' rationale was given to support the use of OSC analysed by this study. As the preference for NOSC versus OSC software tools in the PBPK area continues to be divided, initiatives to add the rationale in using one form over another to every future PBPK modeling report will be a welcomed and informative addition.
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Affiliation(s)
- Arham Jamaal Rajput
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
| | | | - Amin Rostami-Hodjegan
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK
- Certara UK Limited, Sheffield, UK
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Mitchell CA, Burden N, Bonnell M, Hecker M, Hutchinson TH, Jagla M, LaLone CA, Lagadic L, Lynn SG, Shore B, Song Y, Vliet SM, Wheeler JR, Embry MR. New Approach Methodologies for the Endocrine Activity Toolbox: Environmental Assessment for Fish and Amphibians. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2023; 42:757-777. [PMID: 36789969 PMCID: PMC10258674 DOI: 10.1002/etc.5584] [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: 10/07/2022] [Revised: 11/07/2022] [Accepted: 02/06/2023] [Indexed: 06/14/2023]
Abstract
Multiple in vivo test guidelines focusing on the estrogen, androgen, thyroid, and steroidogenesis pathways have been developed and validated for mammals, amphibians, or fish. However, these tests are resource-intensive and often use a large number of laboratory animals. Developing alternatives for in vivo tests is consistent with the replacement, reduction, and refinement principles for animal welfare considerations, which are supported by increasing mandates to move toward an "animal-free" testing paradigm worldwide. New approach methodologies (NAMs) hold great promise to identify molecular, cellular, and tissue changes that can be used to predict effects reliably and more efficiently at the individual level (and potentially on populations) while reducing the number of animals used in (eco)toxicological testing for endocrine disruption. In a collaborative effort, experts from government, academia, and industry met in 2020 to discuss the current challenges of testing for endocrine activity assessment for fish and amphibians. Continuing this cross-sector initiative, our review focuses on the current state of the science regarding the use of NAMs to identify chemical-induced endocrine effects. The present study highlights the challenges of using NAMs for safety assessment and what work is needed to reduce their uncertainties and increase their acceptance in regulatory processes. We have reviewed the current NAMs available for endocrine activity assessment including in silico, in vitro, and eleutheroembryo models. New approach methodologies can be integrated as part of a weight-of-evidence approach for hazard or risk assessment using the adverse outcome pathway framework. The development and utilization of NAMs not only allows for replacement, reduction, and refinement of animal testing but can also provide robust and fit-for-purpose methods to identify chemicals acting via endocrine mechanisms. Environ Toxicol Chem 2023;42:757-777. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
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Affiliation(s)
| | - Natalie Burden
- National Centre for the 3Rs (NC3Rs), London, United Kingdom
| | - Mark Bonnell
- Environment and Climate Change Canada, Ottawa, Canada
| | - Markus Hecker
- Toxicology Centre and School of the Environment & Sustainability, University of Saskatchewan, Saskatoon, Canada
| | | | | | - Carlie A. LaLone
- Office of Research and Development, Great Lakes Toxicology & Ecology Division, US Environmental Protection Agency, Duluth, Minnesota
| | - Laurent Lagadic
- Research and Development, Crop Science, Environmental Safety, Bayer, Monheim am Rhein, Germany
| | - Scott G. Lynn
- Office of Pesticide Programs, US Environmental Protection Agency, Washington, DC
| | - Bryon Shore
- Environment and Climate Change Canada, Ottawa, Canada
| | - You Song
- Norwegian Institute for Water Research, Oslo, Norway
| | - Sara M. Vliet
- Office of Research and Development, Scientific Computing and Data Curation Division, US Environmental Protection Agency, Duluth, Minnesota
| | | | - Michelle R. Embry
- The Health and Environmental Sciences Institute, Washington, DC, USA
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Deepika D, Kumar V. The Role of "Physiologically Based Pharmacokinetic Model (PBPK)" New Approach Methodology (NAM) in Pharmaceuticals and Environmental Chemical Risk Assessment. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3473. [PMID: 36834167 PMCID: PMC9966583 DOI: 10.3390/ijerph20043473] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/10/2023] [Accepted: 02/14/2023] [Indexed: 06/18/2023]
Abstract
Physiologically Based Pharmacokinetic (PBPK) models are mechanistic tools generally employed in the pharmaceutical industry and environmental health risk assessment. These models are recognized by regulatory authorities for predicting organ concentration-time profiles, pharmacokinetics and daily intake dose of xenobiotics. The extension of PBPK models to capture sensitive populations such as pediatric, geriatric, pregnant females, fetus, etc., and diseased populations such as those with renal impairment, liver cirrhosis, etc., is a must. However, the current modelling practices and existing models are not mature enough to confidently predict the risk in these populations. A multidisciplinary collaboration between clinicians, experimental and modeler scientist is vital to improve the physiology and calculation of biochemical parameters for integrating knowledge and refining existing PBPK models. Specific PBPK covering compartments such as cerebrospinal fluid and the hippocampus are required to gain mechanistic understanding about xenobiotic disposition in these sub-parts. The PBPK model assists in building quantitative adverse outcome pathways (qAOPs) for several endpoints such as developmental neurotoxicity (DNT), hepatotoxicity and cardiotoxicity. Machine learning algorithms can predict physicochemical parameters required to develop in silico models where experimental data are unavailable. Integrating machine learning with PBPK carries the potential to revolutionize the field of drug discovery and development and environmental risk. Overall, this review tried to summarize the recent developments in the in-silico models, building of qAOPs and use of machine learning for improving existing models, along with a regulatory perspective. This review can act as a guide for toxicologists who wish to build their careers in kinetic modeling.
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Affiliation(s)
- Deepika Deepika
- Environmental Engineering Laboratory, Departament d’Enginyeria Quimica, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Catalonia, Spain
- Pere Virgili Health Research Institute (IISPV), Hospital Universitari Sant Joan de Reus, Universitat Rovira i Virgili, 43204 Reus, Catalonia, Spain
| | - Vikas Kumar
- Environmental Engineering Laboratory, Departament d’Enginyeria Quimica, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Catalonia, Spain
- Pere Virgili Health Research Institute (IISPV), Hospital Universitari Sant Joan de Reus, Universitat Rovira i Virgili, 43204 Reus, Catalonia, Spain
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El-Masri H, Paul Friedman K, Isaacs K, Wetmore BA. Advances in computational methods along the exposure to toxicological response paradigm. Toxicol Appl Pharmacol 2022; 450:116141. [PMID: 35777528 PMCID: PMC9619339 DOI: 10.1016/j.taap.2022.116141] [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: 04/12/2022] [Revised: 05/27/2022] [Accepted: 06/23/2022] [Indexed: 10/17/2022]
Abstract
Human health risk assessment is a function of chemical toxicity, bioavailability to reach target biological tissues, and potential environmental exposure. These factors are complicated by many physiological, biochemical, physical and lifestyle factors. Furthermore, chemical health risk assessment is challenging in view of the large, and continually increasing, number of chemicals found in the environment. These challenges highlight the need to prioritize resources for the efficient and timely assessment of those environmental chemicals that pose greatest health risks. Computational methods, either predictive or investigative, are designed to assist in this prioritization in view of the lack of cost prohibitive in vivo experimental data. Computational methods provide specific and focused toxicity information using in vitro high throughput screening (HTS) assays. Information from the HTS assays can be converted to in vivo estimates of chemical levels in blood or target tissue, which in turn are converted to in vivo dose estimates that can be compared to exposure levels of the screened chemicals. This manuscript provides a review for the landscape of computational methods developed and used at the U.S. Environmental Protection Agency (EPA) highlighting their potentials and challenges.
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Affiliation(s)
- Hisham El-Masri
- Center for Computational Toxicology and Exposure, Office of Research and Development, U. S. Environmental Protection Agency, Research Triangle Park, NC, USA.
| | - Katie Paul Friedman
- Center for Computational Toxicology and Exposure, Office of Research and Development, U. S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Kristin Isaacs
- 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
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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: 35] [Impact Index Per Article: 17.5] [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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Tebby C, Gao W, Delp J, Carta G, van der Stel W, Leist M, Jennings P, van de Water B, Bois FY. A quantitative AOP of mitochondrial toxicity based on data from three cell lines. Toxicol In Vitro 2022; 81:105345. [PMID: 35278637 DOI: 10.1016/j.tiv.2022.105345] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 02/22/2022] [Accepted: 03/07/2022] [Indexed: 11/30/2022]
Abstract
Adverse Outcome Pathways (AOPs) are increasingly used to support the integration of in vitro data in hazard assessment for chemicals. Quantitative AOPs (qAOPs) use mathematical models to describe the relationship between key events (KEs). In this paper, data obtained in three cell lines, LHUMES, HepG2 and RPTEC/TERT1, using similar experimental protocols, was used to calibrate a qAOP of mitochondrial toxicity for two chemicals, rotenone and deguelin. The objectives were to determine whether the same qAOP could be used for the three cell types, and to test chemical-independence by cross-validation with a dataset obtained on eight other chemicals in LHUMES cells. Repeating the calibration approach for both chemicals in three cell lines highlighted various practical difficulties. Even when the same readouts of KEs are measured, the mathematical functions used to describe the key event relationships may not be the same. Cross-validation in LHUMES cells was attempted by estimating chemical-specific potency at the molecular initiating events and using the rest of the calibrated qAOP to predict downstream KEs: toxicity of azoxystrobin, carboxine, mepronil and thifluzamide was underestimated. Selection of most relevant readouts and accurate characterization of the molecular initiating event for cross-validation are critical when designing in vitro experiments targeted at calibrating qAOPs.
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Affiliation(s)
- Cleo Tebby
- Experimental Toxicology and Modeling (TEAM) Unit, Ineris, rue Jacques Taffanel, 60550 Verneuil-en-Halatte, France.
| | - Wang Gao
- Experimental Toxicology and Modeling (TEAM) Unit, Ineris, rue Jacques Taffanel, 60550 Verneuil-en-Halatte, France; Applied Mathematics Laboratory (LMAC EA 2222), Université Technologique de Compiègne (UTC), 57 avenue de Landshut, 60203 Compiègne Cedex, France
| | - Johannes Delp
- In Vitro Toxicology and Biomedicine, Department inaugurated by the Doerenkamp-Zbinden Foundation, University of Konstanz, Universitaetsstr. 10, 78464, Konstanz, Germany; Cooperative Doctorate College InViTe, University of Konstanz, Konstanz, Germany
| | - Giada Carta
- Division of Molecular and Computational Toxicology, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Wanda van der Stel
- Division of Drug Discovery and Safety, Leiden Academic Centre of Drug Research, Leiden University, Leiden, the Netherlands
| | - Marcel Leist
- In Vitro Toxicology and Biomedicine, Department inaugurated by the Doerenkamp-Zbinden Foundation, University of Konstanz, Universitaetsstr. 10, 78464, Konstanz, Germany
| | - Paul Jennings
- Division of Molecular and Computational Toxicology, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Bob van de Water
- Division of Drug Discovery and Safety, Leiden Academic Centre of Drug Research, Leiden University, Leiden, the Netherlands
| | - Frederic Y Bois
- Experimental Toxicology and Modeling (TEAM) Unit, Ineris, rue Jacques Taffanel, 60550 Verneuil-en-Halatte, France; Certara, Simcyp, Sheffield, United Kingdom
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Silva M, Kwok RKH. Use of Computational Toxicology Tools to Predict In Vivo Endpoints Associated with Mode of Action and the Endocannabinoid System: A Case Study with Chlorpyrifos, Chlorpyrifos-oxon and Δ9Tetrahydrocannabinol. Curr Res Toxicol 2022; 3:100064. [PMID: 35243363 PMCID: PMC8860916 DOI: 10.1016/j.crtox.2022.100064] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 01/16/2022] [Accepted: 02/03/2022] [Indexed: 01/04/2023] Open
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9
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Adverse Outcome Pathways in reproductive and developmental toxicology. REPRODUCTIVE AND DEVELOPMENTAL TOXICOLOGY 2022. [DOI: 10.1016/b978-0-323-89773-0.00004-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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10
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Angiogenesis in Wound Healing following Pharmacological and Toxicological Exposures. CURRENT PATHOBIOLOGY REPORTS 2020. [DOI: 10.1007/s40139-020-00212-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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11
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Matsuzaka Y, Uesawa Y. Prediction Model with High-Performance Constitutive Androstane Receptor (CAR) Using DeepSnap-Deep Learning Approach from the Tox21 10K Compound Library. Int J Mol Sci 2019; 20:ijms20194855. [PMID: 31574921 PMCID: PMC6801383 DOI: 10.3390/ijms20194855] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2019] [Revised: 09/23/2019] [Accepted: 09/27/2019] [Indexed: 12/30/2022] Open
Abstract
The constitutive androstane receptor (CAR) plays pivotal roles in drug-induced liver injury through the transcriptional regulation of drug-metabolizing enzymes and transporters. Thus, identifying regulatory factors for CAR activation is important for understanding its mechanisms. Numerous studies conducted previously on CAR activation and its toxicity focused on in vivo or in vitro analyses, which are expensive, time consuming, and require many animals. We developed a computational model that predicts agonists for the CAR using the Toxicology in the 21st Century 10k library. Additionally, we evaluate the prediction performance of novel deep learning (DL)-based quantitative structure-activity relationship analysis called the DeepSnap-DL approach, which is a procedure of generating an omnidirectional snapshot portraying three-dimensional (3D) structures of chemical compounds. The CAR prediction model, which applies a 3D structure generator tool, called CORINA-generated and -optimized chemical structures, in the DeepSnap-DL demonstrated better performance than the existing methods using molecular descriptors. These results indicate that high performance in the prediction model using the DeepSnap-DL approach may be important to prepare suitable 3D chemical structures as input data and to enable the identification of modulators of the CAR.
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Affiliation(s)
- Yasunari Matsuzaka
- Department of Medical Molecular Informatics, Meiji Pharmaceutical University, Tokyo 204-8588, Japan.
| | - Yoshihiro Uesawa
- Department of Medical Molecular Informatics, Meiji Pharmaceutical University, Tokyo 204-8588, Japan.
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12
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Dallmann A, Liu XI, Burckart GJ, van den Anker J. Drug Transporters Expressed in the Human Placenta and Models for Studying Maternal-Fetal Drug Transfer. J Clin Pharmacol 2019; 59 Suppl 1:S70-S81. [PMID: 31502693 PMCID: PMC7304533 DOI: 10.1002/jcph.1491] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 06/25/2019] [Indexed: 12/30/2022]
Abstract
Tremendous efforts have been directed to investigate the ontogeny of drug transporters in fetuses, neonates, infants, and children based on their importance for understanding drug pharmacokinetics. During development (ie, in the fetus and newborn infant), there is special interest in transporters expressed in the placenta that modulate placental drug transfer. Many of these transporters can decrease or increase drug concentrations in the fetus and at birth, stressing the relevance of elucidating expression in the placenta and potential gestational age-dependent changes therein. Hence, the main objective of this review was to summarize the current knowledge about expression and ontogeny of transporters in the human placenta in healthy pregnant women. In addition, various in vitro, ex vivo, and in silico models that can be used to investigate placental drug transfer, namely, placental cancer cell lines, ex vivo cotyledon perfusion experiments, and physiologically based pharmacokinetic (PBPK) models, are discussed together with their advantages and shortcomings. A particular focus was placed on PBPK models because these models can integrate different types of information, such as expression data, ontogeny information, and observations obtained from the ex vivo cotyledon perfusion experiment. Such a mechanistic modeling framework may leverage the available information and ultimately help to improve knowledge about the adequacy and safety of pharmacotherapy in pregnant women and their fetuses.
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Affiliation(s)
- André Dallmann
- Pediatric Pharmacology and Pharmacometrics Research Center, University Children’s Hospital Basel (UKBB), Switzerland
| | - Xiaomei I. Liu
- Division of Clinical Pharmacology, Children’s National Medical Center, Washington, DC, USA
| | - Gilbert J. Burckart
- US Food and Drug Administration, Office of Clinical Pharmacology, Silver Spring, MD, USA
| | - John van den Anker
- Pediatric Pharmacology and Pharmacometrics Research Center, University Children’s Hospital Basel (UKBB), Switzerland
- Division of Clinical Pharmacology, Children’s National Medical Center, Washington, DC, USA
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13
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Brochot C, Casas M, Manzano-Salgado C, Zeman FA, Schettgen T, Vrijheid M, Bois FY. Prediction of maternal and foetal exposures to perfluoroalkyl compounds in a Spanish birth cohort using toxicokinetic modelling. Toxicol Appl Pharmacol 2019; 379:114640. [PMID: 31251942 DOI: 10.1016/j.taap.2019.114640] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 06/14/2019] [Accepted: 06/24/2019] [Indexed: 10/26/2022]
Abstract
Prenatal exposures to perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) have been associated with child health outcomes, but many of these associations remain poorly characterized. The aim of this work was to provide new indicators of foetal exposure for the Spanish INMA birth cohort. First, a pregnancy and lactation physiologically based pharmacokinetic (PBPK) model was calibrated in a population framework to provide quantitative estimates for the PFOA and PFOS placental transfers in humans. The estimated distributions indicated that PFOA crosses the placental barrier at a rate three times higher than PFOS and shows a higher variability between mothers. The PBPK model was then used to back-calculate the time-varying daily intakes of the INMA mothers corrected for their individual history from a spot maternal concentration. We showed the importance of accounting for the mothers' history as different dietary intakes can result in similar measured concentrations at one time point. Finally, the foetal exposure was simulated in target organs over pregnancy using the PBPK model and the estimated maternal intakes. We showed that the pattern of PFOA and PFOS exposures varies greatly among the foetuses. About a third has levels of either one compound always higher than the levels of the other compound. The other two thirds showed different ranking of PFOA and PFOS in terms of concentrations in the target organs. Our simulated foetal exposures bring additional information to the measured maternal spot concentrations and can help to better characterize the prenatal exposure in target organs during windows of susceptibility.
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Affiliation(s)
- Céline Brochot
- Institut National de l'Environnement Industriel et des Risques (INERIS), Unité Modèles pour l'Ecotoxicologie et la Toxicologie (METO), Parc ALATA BP2, 60550 Verneuil en Halatte, France.
| | - Maribel Casas
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiologa y Salud Pública (CIBERESP), Madrid, Spain
| | - Cyntia Manzano-Salgado
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiologa y Salud Pública (CIBERESP), Madrid, Spain
| | - Florence A Zeman
- Institut National de l'Environnement Industriel et des Risques (INERIS), Unité Modèles pour l'Ecotoxicologie et la Toxicologie (METO), Parc ALATA BP2, 60550 Verneuil en Halatte, France
| | - Thomas Schettgen
- Institute for Occupational Medicine, RWTH Aachen University, Aachen, Germany
| | - Martine Vrijheid
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiologa y Salud Pública (CIBERESP), Madrid, Spain
| | - Frédéric Y Bois
- Institut National de l'Environnement Industriel et des Risques (INERIS), Unité Modèles pour l'Ecotoxicologie et la Toxicologie (METO), Parc ALATA BP2, 60550 Verneuil en Halatte, France
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14
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Nguyen EH, Dombroe MJ, Fisk DL, Daly WT, Sorenson CM, Murphy WL, Sheibani N. Neurovascular Organotypic Culture Models Using Induced Pluripotent Stem Cells to Assess Adverse Chemical Exposure Outcomes. ACTA ACUST UNITED AC 2019; 5:92-110. [PMID: 32292797 DOI: 10.1089/aivt.2018.0025] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Introduction: Human-induced pluripotent stem cells (iPSCs) represent a promising cell source for the construction of organotypic culture models for chemical toxicity screening and characterization. Materials and Methods: To characterize the effects of chemical exposure on the human neurovasculature, we constructed neurovascular unit (NVU) models consisting of endothelial cells (ECs) and astrocytes (ACs) derived from human-iPSCs, as well as human brain-derived pericytes (PCs). The cells were cocultured on synthetic poly(ethylene glycol) (PEG) hydrogels that guided the self-assembly of capillary-like vascular networks. High-content epifluorescence microscopy evaluated dose-dependent changes to multiple aspects of NVU morphology. Results: Cultured vascular networks underwent quantifiable morphological changes when incubated with vascular disrupting chemicals. The activity of predicted vascular disrupting chemicals from a panel of 38 compounds (U.S. Environmental Protection Agency) was ranked based on morphological features detected in the NVU model. In addition, unique morphological neurovascular disruption signatures were detected per chemical. A comparison of PEG-based NVU and Matrigel™-based NVU models found greater sensitivity and consistency in chemical detection by the PEG-based NVU models. Discussion: We suspect that specific morphological changes may be used for discerning adverse outcome pathways initiated by chemical exposure and rapid mechanistic characterization of chemical exposure to neurovascular function. Conclusion: The use of human stem cell-derived vascular tissue and PEG hydrogels in the construction of NVU models leads to rapid detection of adverse chemical effects on neurovascular stability. The use of multiple cell types in coculture elucidates potential mechanisms of action by chemicals applied to the model.
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Affiliation(s)
- Eric H Nguyen
- Human Models for Analysis of Pathways Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Micah J Dombroe
- School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin
| | - Debra L Fisk
- Human Models for Analysis of Pathways Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - William T Daly
- Human Models for Analysis of Pathways Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,Department of Biomedical Engineering, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,Department of Orthopedics and Rehabilitation, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Christine M Sorenson
- Department of Pediatrics, and University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - William L Murphy
- Human Models for Analysis of Pathways Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,Department of Biomedical Engineering, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,Department of Orthopedics and Rehabilitation, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Nader Sheibani
- Human Models for Analysis of Pathways Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,Department of Biomedical Engineering, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,Department of Cell and Regenerative Biology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
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15
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Kapraun DF, Wambaugh JF, Setzer RW, Judson RS. Empirical models for anatomical and physiological changes in a human mother and fetus during pregnancy and gestation. PLoS One 2019; 14:e0215906. [PMID: 31048866 PMCID: PMC6497258 DOI: 10.1371/journal.pone.0215906] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 04/10/2019] [Indexed: 12/28/2022] Open
Abstract
Many parameters treated as constants in traditional physiologically based pharmacokinetic models must be formulated as time-varying quantities when modeling pregnancy and gestation due to the dramatic physiological and anatomical changes that occur during this period. While several collections of empirical models for such parameters have been published, each has shortcomings. We sought to create a repository of empirical models for tissue volumes, blood flow rates, and other quantities that undergo substantial changes in a human mother and her fetus during the time between conception and birth, and to address deficiencies with similar, previously published repositories. We used maximum likelihood estimation to calibrate various models for the time-varying quantities of interest, and then used the Akaike information criterion to select an optimal model for each quantity. For quantities of interest for which time-course data were not available, we constructed composite models using percentages and/or models describing related quantities. In this way, we developed a comprehensive collection of formulae describing parameters essential for constructing a PBPK model of a human mother and her fetus throughout the approximately 40 weeks of pregnancy and gestation. We included models describing blood flow rates through various fetal blood routes that have no counterparts in adults. Our repository of mathematical models for anatomical and physiological quantities of interest provides a basis for PBPK models of human pregnancy and gestation, and as such, it can ultimately be used to support decision-making with respect to optimal pharmacological dosing and risk assessment for pregnant women and their developing fetuses. The views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.
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Affiliation(s)
- Dustin F. Kapraun
- National Center for Environmental Assessment, US Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America
- * E-mail:
| | - John F. Wambaugh
- National Center for Computational Toxicology, US Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America
| | - R. Woodrow Setzer
- National Center for Computational Toxicology, US Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America
| | - Richard S. Judson
- National Center for Computational Toxicology, US Environmental Protection Agency, Research Triangle Park, North Carolina, United States of America
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16
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Integration of Food Animal Residue Avoidance Databank (FARAD) empirical methods for drug withdrawal interval determination with a mechanistic population-based interactive physiologically based pharmacokinetic (iPBPK) modeling platform: example for flunixin meglumine administration. Arch Toxicol 2019; 93:1865-1880. [PMID: 31025081 DOI: 10.1007/s00204-019-02464-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Accepted: 04/18/2019] [Indexed: 12/31/2022]
Abstract
Violative chemical residues in animal-derived food products affect food safety globally and have impact on the trade of international agricultural products. The Food Animal Residue Avoidance Databank program has been developing scientific tools to provide appropriate withdrawal interval (WDI) estimations after extralabel drug use in food animals for the past three decades. One of the tools is physiologically based pharmacokinetic (PBPK) modeling, which is a mechanistic-based approach that can be used to predict tissue residues and WDIs. However, PBPK models are complicated and difficult to use by non-modelers. Therefore, a user-friendly PBPK modeling framework is needed to move this field forward. Flunixin was one of the top five violative drug residues identified in the United States from 2010 to 2016. The objective of this study was to establish a web-based user-friendly framework for the development of new PBPK models for drugs administered to food animals. Specifically, a new PBPK model for both cattle and swine after administration of flunixin meglumine was developed. Population analysis using Monte Carlo simulations was incorporated into the model to predict WDIs following extralabel administration of flunixin meglumine. The population PBPK model was converted to a web-based interactive PBPK (iPBPK) framework to facilitate its application. This iPBPK framework serves as a proof-of-concept for further improvements in the future and it can be applied to develop new models for other drugs in other food animal species, thereby facilitating the application of PBPK modeling in WDI estimation and food safety assessment.
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17
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Tan YM, Worley RR, Leonard JA, Fisher JW. Challenges Associated With Applying Physiologically Based Pharmacokinetic Modeling for Public Health Decision-Making. Toxicol Sci 2019; 162:341-348. [PMID: 29385573 DOI: 10.1093/toxsci/kfy010] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
The development and application of physiologically based pharmacokinetic (PBPK) models in chemical toxicology have grown steadily since their emergence in the 1980s. However, critical evaluation of PBPK models to support public health decision-making across federal agencies has thus far occurred for only a few environmental chemicals. In order to encourage decision-makers to embrace the critical role of PBPK modeling in risk assessment, several important challenges require immediate attention from the modeling community. The objective of this contemporary review is to highlight 3 of these challenges, including: (1) difficulties in recruiting peer reviewers with appropriate modeling expertise and experience; (2) lack of confidence in PBPK models for which no tissue/plasma concentration data exist for model evaluation; and (3) lack of transferability across modeling platforms. Several recommendations for addressing these 3 issues are provided to initiate dialog among members of the PBPK modeling community, as these issues must be overcome for the field of PBPK modeling to advance and for PBPK models to be more routinely applied in support of public health decision-making.
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Affiliation(s)
- Yu-Mei Tan
- National Exposure Research Laboratory, United States Environmental Protection Agency, Research Triangle Park, North Carolina 27709
| | - Rachel R Worley
- Agency for Toxic Substances and Disease Registry, Atlanta, Georgia 30341
| | - Jeremy A Leonard
- Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee 37830
| | - Jeffrey W Fisher
- National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, Arizona 72079
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18
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Cohen Hubal EA, Wetmore BA, Wambaugh JF, El-Masri H, Sobus JR, Bahadori T. Advancing internal exposure and physiologically-based toxicokinetic modeling for 21st-century risk assessments. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2019; 29:11-20. [PMID: 30116055 PMCID: PMC6760598 DOI: 10.1038/s41370-018-0046-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2017] [Revised: 03/15/2018] [Accepted: 03/19/2018] [Indexed: 05/22/2023]
Abstract
Scientifically sound, risk-informed evaluation of chemicals is essential to protecting public health. Systematically leveraging information from exposure, toxicology, and epidemiology studies can provide a holistic understanding of how real-world exposure to chemicals may impact the health of populations, including sensitive and vulnerable individuals and life-stages. Increasingly, public health policy makers are employing toxicokinetic (TK) modeling tools to integrate these data streams and predict potential human health impact. Development of a suite of tools for predicting internal exposure, including physiologically-based toxicokinetic (PBTK) models, is being driven by needs to address large numbers of data-poor chemicals efficiently, translate bioactivity, and mechanistic information from new in vitro test systems, and integrate multiple lines of evidence to enable scientifically sound, risk-informed decisions. New modeling approaches are being designed "fit for purpose" to inform specific decision contexts, with applications ranging from rapid screening of hundreds of chemicals, to improved prediction of risks during sensitive stages of development. New data are being generated experimentally and computationally to support these models. Progress to meet the demand for internal exposure and PBTK modeling tools will require transparent publication of models and data to build credibility in results, as well as opportunities to partner with decision makers to evaluate and build confidence in use of these for improved decisions that promote safe use of chemicals.
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Affiliation(s)
| | - Barbara A Wetmore
- National Exposure Research Laboratory (NERL), US EPA, Washington, USA
| | - John F Wambaugh
- National Center for Computational Toxicology (NCCT), US EPA, Washington, USA
| | - Hisham El-Masri
- National Health and Environmental Effects Laboratory (NHEERL), US EPA, Washington, USA
| | - Jon R Sobus
- National Exposure Research Laboratory (NERL), US EPA, Washington, USA
| | - Tina Bahadori
- National Center for Environmental Assessment (NCEA), US EPA, Washington, USA
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19
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Smits A, De Cock P, Vermeulen A, Allegaert K. Physiologically based pharmacokinetic (PBPK) modeling and simulation in neonatal drug development: how clinicians can contribute. Expert Opin Drug Metab Toxicol 2018; 15:25-34. [PMID: 30554542 DOI: 10.1080/17425255.2019.1558205] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Introduction: Legal initiatives to stimulate neonatal drug development should be accompanied by development of valid research tools. Physiologically based (PB)-pharmacokinetic (PK) modeling and simulation are established tools, accepted by regulatory authorities. Consequently, PBPK holds promise to be a strong research tool to support neonatal drug development. Area covered: The currently available PBPK models still have poor predictive performance in neonates. Using an illustrative approach on distinct PK processes of absorption, distribution, metabolism, excretion, and real-world data in neonates, we provide evidence on the need to further refine available PBPK system parameters through generation and integration of new knowledge. This necessitates cross talk between clinicians and modelers to integrate knowledge (PK datasets, system knowledge, maturational physiology) or test and refine PBPK models. Expert opinion: Besides refining these models for 'small molecules', PBPK model development should also be more widely applied for therapeutic proteins and to determine exposure through breastfeeding. Researchers should also be aware that PBPK modeling in combination with clinical observations can also be used to elucidate age-related changes that are almost impossible to study based on in vivo or in vitro data. This approach has been explored for hepatic biliary excretion, renal tubular activity, and central nervous system exposure.
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Affiliation(s)
- Anne Smits
- a Neonatal Intensive Care Unit , University Hospitals Leuven , Leuven , Belgium.,b Department of Development and Regeneration , KU Leuven , Leuven , Belgium
| | - Pieter De Cock
- c Department of Pharmacy , Ghent University Hospital , Ghent , Belgium.,d Heymans Institute of Pharmacology , Ghent University , Ghent , Belgium.,e Department of Pediatric Intensive Care , Ghent University , Ghent , Belgium
| | - An Vermeulen
- f Laboratory of Medical Biochemistry and Clinical Analysis, Faculty of Pharmaceutical Sciences , Ghent University , Ghent , Belgium
| | - Karel Allegaert
- b Department of Development and Regeneration , KU Leuven , Leuven , Belgium.,g Department of Pediatrics, Division of Neonatology , Erasmus MC Sophia Children's Hospital, University Medical Center Rotterdam , Rotterdam , The Netherlands
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20
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Dallmann A, Ince I, Solodenko J, Meyer M, Willmann S, Eissing T, Hempel G. Physiologically Based Pharmacokinetic Modeling of Renally Cleared Drugs in Pregnant Women. Clin Pharmacokinet 2018; 56:1525-1541. [PMID: 28391404 DOI: 10.1007/s40262-017-0538-0] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
BACKGROUND Since pregnant women are considerably underrepresented in clinical trials, information on optimal dosing in pregnancy is widely lacking. Physiologically based pharmacokinetic (PBPK) modeling may provide a method for predicting pharmacokinetic changes in pregnancy to guide subsequent in vivo pharmacokinetic trials in pregnant women, minimizing associated risks. OBJECTIVES The goal of this study was to build and verify a population PBPK model that predicts the maternal pharmacokinetics of three predominantly renally cleared drugs (namely cefazolin, cefuroxime, and cefradine) at different stages of pregnancy. It was further evaluated whether the fraction unbound (f u) could be estimated in pregnant women using a proposed scaling approach. METHODS Based on a recent literature review on anatomical and physiological changes during pregnancy, a pregnancy population PBPK model was built using the software PK-Sim®/MoBi®. This model comprised 27 compartments, including nine pregnancy-specific compartments. The PBPK model was verified by comparing the predicted maternal pharmacokinetics of cefazolin, cefuroxime, and cefradine with observed in vivo data taken from the literature. The proposed scaling approach for estimating the f u in pregnancy was evaluated by comparing the predicted f u with experimentally observed f u values of 32 drugs taken from the literature. RESULTS The pregnancy population PBPK model successfully predicted the pharmacokinetics of cefazolin, cefuroxime, and cefradine at all tested stages of pregnancy. All predicted plasma concentrations fell within a 2-fold error range and 85% of the predicted concentrations within a 1.25-fold error range. The f u in pregnancy could be adequately predicted using the proposed scaling approach, although a slight underestimation was evident in case of drugs bound to α1-acidic glycoprotein. CONCLUSION Pregnancy population PBPK models can provide a valuable tool to predict a priori the pharmacokinetics of predominantly renally cleared drugs in pregnant women. These models can ultimately support informed decision making regarding optimal dosing regimens in this vulnerable special population.
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Affiliation(s)
- André Dallmann
- Department of Pharmaceutical and Medical Chemistry-Clinical Pharmacy, Westfälische Wilhelm-University Münster, 48149, Münster, Germany
| | - Ibrahim Ince
- Bayer AG, Drug Discovery, Pharmaceuticals, Systems Pharmacology & Medicine I, Kaiser-Wilhelm-Allee, 51373, Leverkusen, Germany.
| | - Juri Solodenko
- Bayer AG, ET-TD-ET Systems Pharmacology ONC, 51368, Leverkusen, Germany
| | - Michaela Meyer
- Bayer AG, DD-CS Clinical Pharmacometrics, 42113, Wuppertal, Germany
| | - Stefan Willmann
- Bayer AG, DD-CS Clinical Pharmacometrics, 42113, Wuppertal, Germany
| | - Thomas Eissing
- Bayer AG, Drug Discovery, Pharmaceuticals, Systems Pharmacology & Medicine I, Kaiser-Wilhelm-Allee, 51373, Leverkusen, Germany
| | - Georg Hempel
- Department of Pharmaceutical and Medical Chemistry-Clinical Pharmacy, Westfälische Wilhelm-University Münster, 48149, Münster, Germany
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21
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Dallmann A, Pfister M, van den Anker J, Eissing T. Physiologically Based Pharmacokinetic Modeling in Pregnancy: A Systematic Review of Published Models. Clin Pharmacol Ther 2018; 104:1110-1124. [PMID: 29633257 DOI: 10.1002/cpt.1084] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2018] [Revised: 03/16/2018] [Accepted: 03/30/2018] [Indexed: 12/21/2022]
Abstract
During recent years there has been a surge in developing and applying physiologically based pharmacokinetic (PBPK) models in pregnant women to better understand and predict changes in drug pharmacokinetics throughout pregnancy. As a consequence, the number of publications focusing on pregnancy PBPK models has increased substantially. However, to date these models, especially across various platforms, have not been systematically evaluated. Hence, this review aims to assess published PBPK models in pregnancy used for therapeutic purposes.
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Affiliation(s)
- André Dallmann
- Pediatric Pharmacology and Pharmacometrics Research Center, University Children's Hospital Basel, Basel, Switzerland
| | - Marc Pfister
- Pediatric Pharmacology and Pharmacometrics Research Center, University Children's Hospital Basel, Basel, Switzerland.,Certara, Princeton, New Jersey, USA
| | - John van den Anker
- Pediatric Pharmacology and Pharmacometrics Research Center, University Children's Hospital Basel, Basel, Switzerland.,Division of Clinical Pharmacology, Children's National Health System, Washington, DC, USA.,Intensive Care and Department of Pediatric Surgery, Erasmus Medical Center-Sophia Children's Hospital, Rotterdam, the Netherlands
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22
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Bell SM, Chang X, Wambaugh JF, Allen DG, Bartels M, Brouwer KLR, Casey WM, Choksi N, Ferguson SS, Fraczkiewicz G, Jarabek AM, Ke A, Lumen A, Lynn SG, Paini A, Price PS, Ring C, Simon TW, Sipes NS, Sprankle CS, Strickland J, Troutman J, Wetmore BA, Kleinstreuer NC. In vitro to in vivo extrapolation for high throughput prioritization and decision making. Toxicol In Vitro 2017; 47:213-227. [PMID: 29203341 DOI: 10.1016/j.tiv.2017.11.016] [Citation(s) in RCA: 146] [Impact Index Per Article: 20.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2017] [Revised: 11/28/2017] [Accepted: 11/30/2017] [Indexed: 01/10/2023]
Abstract
In vitro chemical safety testing methods offer the potential for efficient and economical tools to provide relevant assessments of human health risk. To realize this potential, methods are needed to relate in vitro effects to in vivo responses, i.e., in vitro to in vivo extrapolation (IVIVE). Currently available IVIVE approaches need to be refined before they can be utilized for regulatory decision-making. To explore the capabilities and limitations of IVIVE within this context, the U.S. Environmental Protection Agency Office of Research and Development and the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods co-organized a workshop and webinar series. Here, we integrate content from the webinars and workshop to discuss activities and resources that would promote inclusion of IVIVE in regulatory decision-making. We discuss properties of models that successfully generate predictions of in vivo doses from effective in vitro concentration, including the experimental systems that provide input parameters for these models, areas of success, and areas for improvement to reduce model uncertainty. Finally, we provide case studies on the uses of IVIVE in safety assessments, which highlight the respective differences, information requirements, and outcomes across various approaches when applied for decision-making.
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Affiliation(s)
- Shannon M Bell
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA.
| | - Xiaoqing Chang
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA.
| | - John F Wambaugh
- U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Research Triangle Park, NC 27709, USA.
| | - David G Allen
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA.
| | | | - Kim L R Brouwer
- UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Campus Box 7569, Chapel Hill, NC 27599, USA.
| | - Warren M Casey
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, USA.
| | - Neepa Choksi
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA.
| | - Stephen S Ferguson
- National Toxicology Program, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, USA.
| | | | - Annie M Jarabek
- U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Research Triangle Park, NC 27709, USA.
| | - Alice Ke
- Simcyp Limited (a Certara company), John Street, Sheffield, S2 4SU, United Kingdom.
| | - Annie Lumen
- National Center for Toxicological Research, U.S. Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079, USA.
| | - Scott G Lynn
- U.S. Environmental Protection Agency, William Jefferson Clinton Building, 1200 Pennsylvania Ave. NW, Washington, DC 20460, USA.
| | - Alicia Paini
- European Commission, Joint Research Centre, Directorate Health, Consumers and Reference Materials, Chemical Safety and Alternative Methods Unit incorporating EURL ECVAM, Via E. Fermi 2749, Ispra, Varese 20127, Italy.
| | - Paul S Price
- U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Research Triangle Park, NC 27709, USA.
| | - Caroline Ring
- Oak Ridge Institute for Science and Education, P.O. Box 2008, Oak Ridge, TN 37831, USA.
| | - Ted W Simon
- Ted Simon LLC, 4184 Johnston Road, Winston, GA 30187, USA.
| | - Nisha S Sipes
- National Toxicology Program, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, USA.
| | - Catherine S Sprankle
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA.
| | - Judy Strickland
- Integrated Laboratory Systems, Inc., P.O. Box 13501, Research Triangle Park, NC 27709, USA.
| | - John Troutman
- Central Product Safety, The Procter & Gamble Company, Cincinnati, OH 45202, USA.
| | - Barbara A Wetmore
- ScitoVation LLC, 6 Davis Drive, Research Triangle Park, NC 27709, USA.
| | - Nicole C Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, USA.
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23
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Cronin MT, Richarz AN. Relationship Between Adverse Outcome Pathways and Chemistry-BasedIn SilicoModels to Predict Toxicity. ACTA ACUST UNITED AC 2017. [DOI: 10.1089/aivt.2017.0021] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
- Mark T.D. Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, England
| | - Andrea-Nicole Richarz
- European Commission, Joint Research Centre, Directorate for Health, Consumers and Reference Materials, Ispra, Italy
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Burgdorf T, Dunst S, Ertych N, Fetz V, Violet N, Vogl S, Schönfelder G, Schwarz F, Oelgeschläger M. The AOP Concept: How Novel Technologies Can Support Development of Adverse Outcome Pathways. ACTA ACUST UNITED AC 2017. [DOI: 10.1089/aivt.2017.0011] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- Tanja Burgdorf
- Department Experimental Toxicology and ZEBET, German Centre for The Protection of Laboratory Animals (Bf3R), German Federal Institute for Risk Assessment, Berlin, Germany
| | - Sebastian Dunst
- Department Experimental Toxicology and ZEBET, German Centre for The Protection of Laboratory Animals (Bf3R), German Federal Institute for Risk Assessment, Berlin, Germany
| | - Norman Ertych
- Department Experimental Toxicology and ZEBET, German Centre for The Protection of Laboratory Animals (Bf3R), German Federal Institute for Risk Assessment, Berlin, Germany
| | - Verena Fetz
- Department Experimental Toxicology and ZEBET, German Centre for The Protection of Laboratory Animals (Bf3R), German Federal Institute for Risk Assessment, Berlin, Germany
| | - Norman Violet
- Department Experimental Toxicology and ZEBET, German Centre for The Protection of Laboratory Animals (Bf3R), German Federal Institute for Risk Assessment, Berlin, Germany
| | - Silvia Vogl
- Department Experimental Toxicology and ZEBET, German Centre for The Protection of Laboratory Animals (Bf3R), German Federal Institute for Risk Assessment, Berlin, Germany
| | - Gilbert Schönfelder
- Department Experimental Toxicology and ZEBET, German Centre for The Protection of Laboratory Animals (Bf3R), German Federal Institute for Risk Assessment, Berlin, Germany
- Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Clinical Pharmacology and Toxicology, Berlin, Germany
| | - Franziska Schwarz
- Department Experimental Toxicology and ZEBET, German Centre for The Protection of Laboratory Animals (Bf3R), German Federal Institute for Risk Assessment, Berlin, Germany
| | - Michael Oelgeschläger
- Department Experimental Toxicology and ZEBET, German Centre for The Protection of Laboratory Animals (Bf3R), German Federal Institute for Risk Assessment, Berlin, Germany
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Bois FY, Golbamaki-Bakhtyari N, Kovarich S, Tebby C, Gabb HA, Lemazurier E. High-Throughput Analysis of Ovarian Cycle Disruption by Mixtures of Aromatase Inhibitors. ENVIRONMENTAL HEALTH PERSPECTIVES 2017; 125:077012. [PMID: 28886606 PMCID: PMC5744692 DOI: 10.1289/ehp742] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2016] [Revised: 12/07/2016] [Accepted: 02/24/2017] [Indexed: 05/25/2023]
Abstract
BACKGROUND Combining computational toxicology with ExpoCast exposure estimates and ToxCast™ assay data gives us access to predictions of human health risks stemming from exposures to chemical mixtures. OBJECTIVES We explored, through mathematical modeling and simulations, the size of potential effects of random mixtures of aromatase inhibitors on the dynamics of women's menstrual cycles. METHODS We simulated random exposures to millions of potential mixtures of 86 aromatase inhibitors. A pharmacokinetic model of intake and disposition of the chemicals predicted their internal concentration as a function of time (up to 2 y). A ToxCast™ aromatase assay provided concentration-inhibition relationships for each chemical. The resulting total aromatase inhibition was input to a mathematical model of the hormonal hypothalamus-pituitary-ovarian control of ovulation in women. RESULTS Above 10% inhibition of estradiol synthesis by aromatase inhibitors, noticeable (eventually reversible) effects on ovulation were predicted. Exposures to individual chemicals never led to such effects. In our best estimate, ∼10% of the combined exposures simulated had mild to catastrophic impacts on ovulation. A lower bound on that figure, obtained using an optimistic exposure scenario, was 0.3%. CONCLUSIONS These results demonstrate the possibility to predict large-scale mixture effects for endocrine disrupters with a predictive toxicology approach that is suitable for high-throughput ranking and risk assessment. The size of the effects predicted is consistent with an increased risk of infertility in women from everyday exposures to our chemical environment. https://doi.org/10.1289/EHP742.
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Affiliation(s)
- Frederic Y Bois
- Models for Ecotoxicology and Toxicology Unit (DRC/VIVA/METO), Institut National de l'Environnement Industriel et des Risques (INERIS) , Verneuil en Halatte, France
| | - Nazanin Golbamaki-Bakhtyari
- Models for Ecotoxicology and Toxicology Unit (DRC/VIVA/METO), Institut National de l'Environnement Industriel et des Risques (INERIS) , Verneuil en Halatte, France
| | | | - Cleo Tebby
- Models for Ecotoxicology and Toxicology Unit (DRC/VIVA/METO), Institut National de l'Environnement Industriel et des Risques (INERIS) , Verneuil en Halatte, France
| | - Henry A Gabb
- School of Information Sciences, University of Illinois at Urbana-Champaign , Champaign, Illinois, USA
| | - Emmanuel Lemazurier
- Models for Ecotoxicology and Toxicology Unit (DRC/VIVA/METO), Institut National de l'Environnement Industriel et des Risques (INERIS) , Verneuil en Halatte, France
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Abstract
The physiological relevance of Matrigel as a cell-culture substrate and in angiogenesis assays is often called into question. Here, we describe an array-based method for the identification of synthetic hydrogels that promote the formation of robust in vitro vascular networks for the detection of putative vascular disruptors, and that support human embryonic stem cell expansion and pluripotency. We identified hydrogel substrates that promoted endothelial-network formation by primary human umbilical vein endothelial cells and by endothelial cells derived from human induced pluripotent stem cells, and used the hydrogels with endothelial networks to identify angiogenesis inhibitors. The synthetic hydrogels show superior sensitivity and reproducibility over Matrigel when evaluating known inhibitors, as well as in a blinded screen of a subset of 38 chemicals, selected according to predicted vascular disruption potential, from the Toxicity ForeCaster library of the US Environmental Protection Agency. The identified synthetic hydrogels should be suitable alternatives to Matrigel for common cell-culture applications.
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Kleinstreuer NC, Ceger P, Watt ED, Martin M, Houck K, Browne P, Thomas RS, Casey WM, Dix DJ, Allen D, Sakamuru S, Xia M, Huang R, Judson R. Development and Validation of a Computational Model for Androgen Receptor Activity. Chem Res Toxicol 2016; 30:946-964. [PMID: 27933809 PMCID: PMC5396026 DOI: 10.1021/acs.chemrestox.6b00347] [Citation(s) in RCA: 144] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Testing thousands of chemicals to identify potential androgen receptor (AR) agonists or antagonists would cost millions of dollars and take decades to complete using current validated methods. High-throughput in vitro screening (HTS) and computational toxicology approaches can more rapidly and inexpensively identify potential androgen-active chemicals. We integrated 11 HTS ToxCast/Tox21 in vitro assays into a computational network model to distinguish true AR pathway activity from technology-specific assay interference. The in vitro HTS assays probed perturbations of the AR pathway at multiple points (receptor binding, coregulator recruitment, gene transcription, and protein production) and multiple cell types. Confirmatory in vitro antagonist assay data and cytotoxicity information were used as additional flags for potential nonspecific activity. Validating such alternative testing strategies requires high-quality reference data. We compiled 158 putative androgen-active and -inactive chemicals from a combination of international test method validation efforts and semiautomated systematic literature reviews. Detailed in vitro assay information and results were compiled into a single database using a standardized ontology. Reference chemical concentrations that activated or inhibited AR pathway activity were identified to establish a range of potencies with reproducible reference chemical results. Comparison with existing Tier 1 AR binding data from the U.S. EPA Endocrine Disruptor Screening Program revealed that the model identified binders at relevant test concentrations (<100 μM) and was more sensitive to antagonist activity. The AR pathway model based on the ToxCast/Tox21 assays had balanced accuracies of 95.2% for agonist (n = 29) and 97.5% for antagonist (n = 28) reference chemicals. Out of 1855 chemicals screened in the AR pathway model, 220 chemicals demonstrated AR agonist or antagonist activity and an additional 174 chemicals were predicted to have potential weak AR pathway activity.
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Affiliation(s)
- Nicole C Kleinstreuer
- NIH/NIEHS/DNTP/The NTP Interagency Center for the Evaluation of Alternative Toxicological Methods , Research Triangle Park, North Carolina 27713, United States
| | - Patricia Ceger
- Integrated Laboratory Systems, Inc. , Research Triangle Park, North Carolina 27560, United States
| | - Eric D Watt
- EPA/ORD/National Center for Computational Toxicology , Research Triangle Park, North Carolina 27711, United States
| | - Matthew Martin
- EPA/ORD/National Center for Computational Toxicology , Research Triangle Park, North Carolina 27711, United States
| | - Keith Houck
- EPA/ORD/National Center for Computational Toxicology , Research Triangle Park, North Carolina 27711, United States
| | - Patience Browne
- OECD Environment Directorate, Environment Health and Safety Division , Paris 75775, France
| | - Russell S Thomas
- EPA/ORD/National Center for Computational Toxicology , Research Triangle Park, North Carolina 27711, United States
| | - Warren M Casey
- NIH/NIEHS/DNTP/The NTP Interagency Center for the Evaluation of Alternative Toxicological Methods , Research Triangle Park, North Carolina 27713, United States
| | - David J Dix
- EPA/OCSPP/Office of Science Coordination and Policy , Washington, DC, 20460, United States
| | - David Allen
- Integrated Laboratory Systems, Inc. , Research Triangle Park, North Carolina 27560, United States
| | - Srilatha Sakamuru
- NIH/National Center for Advancing Translational Sciences , Bethesda, Maryland 20892, United States
| | - Menghang Xia
- NIH/National Center for Advancing Translational Sciences , Bethesda, Maryland 20892, United States
| | - Ruili Huang
- NIH/National Center for Advancing Translational Sciences , Bethesda, Maryland 20892, United States
| | - Richard Judson
- EPA/ORD/National Center for Computational Toxicology , Research Triangle Park, North Carolina 27711, United States
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