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1. Limitations of acetaminophen as a reference hepatotoxin for the evaluation of in vitro liver models.

Author

Livoti, Lucia A, Sison-Young, Rowena, Reddyhoff, Dennis, Fisher, Ciarán P, Gardner, Iain, Diaz-Nieto, Rafael, Goldring, Christopher E, and Copple, Ian M

Subjects
CYTOCHROME P-450, CELL death, DRUG side effects, LIVER cells, LIVER injuries, ACETAMINOPHEN
Abstract

Acetaminophen is commonly used as a reference hepatotoxin to demonstrate that in vitro human liver platforms can emulate features of clinical drug-induced liver injury. However, the induction of substantial cell death in these models typically requires acetaminophen concentrations (∼10 mM) far higher than blood concentrations of the drug associated with clinical hepatotoxicity (∼1 mM). Using the cytochrome P450 inhibitor 1-aminobenzotriazole, we show that acetaminophen toxicity in cultured human, mouse, and rat hepatocytes is not dependent on N-acetyl-p-benzoquinonimine formation, unlike the in vivo setting. This finding highlights the limitation of using acetaminophen as a reference hepatotoxin for the evaluation of in vitro liver models. Hence, we make recommendations on the selection of reference hepatotoxins for this purpose. [ABSTRACT FROM AUTHOR]

Published
2025
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3. Integrate mechanistic evidence from new approach methodologies (NAMs) into a read-across assessment to characterise trends in shared mode of action

Author

Escher, Sylvia E., Aguayo-Orozco, Alejandro, Benfenati, Emilio, Bitsch, Annette, Braunbeck, Thomas, Brotzmann, Katharina, Bois, Frederic, van der Burg, Bart, Castel, Jose, Exner, Thomas, Gadaleta, Domenico, Gardner, Iain, Goldmann, Daria, Hatley, Oliver, Golbamaki, Nazanin, Graepel, Rabea, Jennings, Paul, Limonciel, Alice, Long, Anthony, Maclennan, Richard, Mombelli, Enrico, Norinder, Ulf, Jain, Sankalp, Capinha, Liliana Santos, Taboureau, Olivier T., Tolosa, Laia, Vrijenhoek, Nanette G., van Vugt-Lussenburg, Barbara M.A., Walker, Paul, van de Water, Bob, Wehr, Matthias, White, Andrew, Zdrazil, Barbara, and Fisher, Ciarán

Published
2022
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6. The EU-ToxRisk method documentation, data processing and chemical testing pipeline for the regulatory use of new approach methods

Author

Krebs, Alice, van Vugt-Lussenburg, Barbara M. A., Waldmann, Tanja, Albrecht, Wiebke, Boei, Jan, ter Braak, Bas, Brajnik, Maja, Braunbeck, Thomas, Brecklinghaus, Tim, Busquet, Francois, Dinnyes, Andras, Dokler, Joh, Dolde, Xenia, Exner, Thomas E., Fisher, Ciarán, Fluri, David, Forsby, Anna, Hengstler, Jan G., Holzer, Anna-Katharina, Janstova, Zofia, Jennings, Paul, Kisitu, Jaffar, Kobolak, Julianna, Kumar, Manoj, Limonciel, Alice, Lundqvist, Jessica, Mihalik, Balázs, Moritz, Wolfgang, Pallocca, Giorgia, Ulloa, Andrea Paola Cediel, Pastor, Manuel, Rovida, Costanza, Sarkans, Ugis, Schimming, Johannes P., Schmidt, Bela Z., Stöber, Regina, Strassfeld, Tobias, van de Water, Bob, Wilmes, Anja, van der Burg, Bart, Verfaillie, Catherine M., von Hellfeld, Rebecca, Vrieling, Harry, Vrijenhoek, Nanette G., and Leist, Marcel

Published
2020
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8. Towards grouping concepts based on new approach methodologies in chemical hazard assessment: the read-across approach of the EU-ToxRisk project

Author

Escher, Sylvia E., Kamp, Hennicke, Bennekou, Susanne H., Bitsch, Annette, Fisher, Ciarán, Graepel, Rabea, Hengstler, Jan G., Herzler, Matthias, Knight, Derek, Leist, Marcel, Norinder, Ulf, Ouédraogo, Gladys, Pastor, Manuel, Stuard, Sharon, White, Andrew, Zdrazil, Barbara, van de Water, Bob, and Kroese, Dinant

Published
2019
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9. The integrated stress response‐related expression of CHOP due to mitochondrial toxicity is a warning sign for DILI liability.

Author

Vlasveld, Matthijs, Callegaro, Giulia, Fisher, Ciarán, Eakins, Julie, Walker, Paul, Lok, Samantha, van Oost, Siddh, de Jong, Brechtje, Pellegrino‐Coppola, Damiano, Burger, Gerhard, Wink, Steven, and van de Water, Bob

Subjects
DNA repair, MITOCHONDRIA, GENE regulatory networks, GENE ontology, DRUG development, CENTRAL nervous system
Abstract

Background and Aims: Drug‐induced liver injury (DILI) is one of the most frequent reasons for failure of drugs in clinical trials or market withdrawal. Early assessment of DILI risk remains a major challenge during drug development. Here, we present a mechanism‐based weight‐of‐evidence approach able to identify certain candidate compounds with DILI liabilities due to mitochondrial toxicity. Methods: A total of 1587 FDA‐approved drugs and 378 kinase inhibitors were screened for cellular stress response activation associated with DILI using an imaging‐based HepG2 BAC‐GFP reporter platform including the integrated stress response (CHOP), DNA damage response (P21) and oxidative stress response (SRXN1). Results: In total 389, 219 and 104 drugs were able to induce CHOP‐GFP, P21‐GFP and SRXN1‐GFP expression at 50 μM respectively. Concentration response analysis identified 154 FDA‐approved drugs as critical CHOP‐GFP inducers. Based on predicted and observed (pre‐)clinical DILI liabilities of these drugs, nine antimycotic drugs (e.g. butoconazole, miconazole, tioconazole) and 13 central nervous system (CNS) agents (e.g. duloxetine, fluoxetine) were selected for transcriptomic evaluation using whole‐genome RNA‐sequencing of primary human hepatocytes. Gene network analysis uncovered mitochondrial processes, NRF2 signalling and xenobiotic metabolism as most affected by the antimycotic drugs and CNS agents. Both the selected antimycotics and CNS agents caused impairment of mitochondrial oxygen consumption in both HepG2 and primary human hepatocytes. Conclusions: Together, the results suggest that early pre‐clinical screening for CHOP expression could indicate liability of mitochondrial toxicity in the context of DILI, and, therefore, could serve as an important warning signal to consider during decision‐making in drug development. [ABSTRACT FROM AUTHOR]

Published
2024
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10. A systems approach reveals species differences in hepatic stress response capacity

Author

Russomanno, Giusy, primary, Sison-Young, Rowena, additional, Livoti, Lucia A, additional, Coghlan, Hannah, additional, Jenkins, Rosalind E, additional, Kunnen, Steven J, additional, Fisher, Ciarán P, additional, Reddyhoff, Dennis, additional, Gardner, Iain, additional, Rehman, Adeeb H, additional, Fenwick, Stephen W, additional, Jones, Andrew R, additional, Vermeil De Conchard, Guy, additional, Simonin, Gilles, additional, Bertheux, Helene, additional, Weaver, Richard J, additional, Johnson, Robert L, additional, Liguori, Michael J, additional, Clausznitzer, Diana, additional, Stevens, James L, additional, Goldring, Christopher E, additional, and Copple, Ian M, additional

Published
2023
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11. Adverse outcome pathways: opportunities, limitations and open questions

Author

Leist, Marcel, Ghallab, Ahmed, Graepel, Rabea, Marchan, Rosemarie, Hassan, Reham, Bennekou, Susanne Hougaard, Limonciel, Alice, Vinken, Mathieu, Schildknecht, Stefan, Waldmann, Tanja, Danen, Erik, van Ravenzwaay, Ben, Kamp, Hennicke, Gardner, Iain, Godoy, Patricio, Bois, Frederic Y., Braeuning, Albert, Reif, Raymond, Oesch, Franz, Drasdo, Dirk, Höhme, Stefan, Schwarz, Michael, Hartung, Thomas, Braunbeck, Thomas, Beltman, Joost, Vrieling, Harry, Sanz, Ferran, Forsby, Anna, Gadaleta, Domenico, Fisher, Ciarán, Kelm, Jens, Fluri, David, Ecker, Gerhard, Zdrazil, Barbara, Terron, Andrea, Jennings, Paul, van der Burg, Bart, Dooley, Steven, Meijer, Annemarie H., Willighagen, Egon, Martens, Marvin, Evelo, Chris, Mombelli, Enrico, Taboureau, Olivier, Mantovani, Alberto, Hardy, Barry, Koch, Bjorn, Escher, Sylvia, van Thriel, Christoph, Cadenas, Cristina, Kroese, D., van de Water, Bob, and Hengstler, Jan G.

Published
2017
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14. Correction to: Proteomic identification and characterization of hepatic glyoxalase 1 dysregulation in non-alcoholic fatty liver disease

Author

Spanos, Christos, Maldonado, Elaina M., Fisher, Ciarán P., Leenutaphong, Petchpailin, Oviedo-Orta, Ernesto, Windridge, David, Salguero, Francisco J., Bermúdez-Fajardo, Alexandra, Weeks, Mark E., Evans, Caroline, Corfe, Bernard M., Rabbani, Naila, Thornalley, Paul J., Miller, Michael H., Wang, Huan, Dillon, John F., Quaglia, Alberto, Dhawan, Anil, Fitzpatrick, Emer, and Moore, J. Bernadette

Published
2018
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16. Proteomic identification and characterization of hepatic glyoxalase 1 dysregulation in non-alcoholic fatty liver disease

Author

Spanos, Christos, Maldonado, Elaina M., Fisher, Ciarán P., Leenutaphong, Petchpailin, Oviedo-Orta, Ernesto, Windridge, David, Salguero, Francisco J., Bermúdez-Fajardo, Alexandra, Weeks, Mark E., Evans, Caroline, Corfe, Bernard M., Rabbani, Naila, Thornalley, Paul J., Miller, Michael H., Wang, Huan, Dillon, John F., Quaglia, Alberto, Dhawan, Anil, Fitzpatrick, Emer, and Bernadette Moore, J.

Published
2018
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18. A systems approach reveals species differences in hepatic stress response capacity

Author

Russomanno, Giusy, primary, Sison-Young, Rowena, additional, Livoti, Lucia A., additional, Coghlan, Hannah, additional, Jenkins, Rosalind E., additional, Kunnen, Steven J., additional, Fisher, Ciarán P., additional, Reddyhoff, Dennis, additional, Gardner, Iain, additional, Rehman, Adeeb H., additional, Fenwick, Stephen W., additional, Jones, Andrew R., additional, De Conchard, Guy Vermeil, additional, Simonin, Gilles, additional, Bertheux, Helene, additional, Weaver, Richard J., additional, Liguori, Michael J., additional, Clausznitzer, Diana, additional, Stevens, James L., additional, Goldring, Christopher E., additional, and Copple, Ian M., additional

Published
2022
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22. Effective exposure of chemicals in in vitro cell systems: A review of chemical distribution models

Author

IRAS OH Toxicology, dIRAS RA-1, Proença, Susana, Escher, Beate I, Fischer, Fabian C, Fisher, Ciarán, Grégoire, Sébastien, Hewitt, Nicky J, Nicol, Beate, Paini, Alicia, Kramer, Nynke I, IRAS OH Toxicology, dIRAS RA-1, Proença, Susana, Escher, Beate I, Fischer, Fabian C, Fisher, Ciarán, Grégoire, Sébastien, Hewitt, Nicky J, Nicol, Beate, Paini, Alicia, and Kramer, Nynke I

Published
2021

24. Chemical concentrations in cell culture compartments (C5) – free concentrations

Author

Kisitu, Jaffar, Hollert, Henner, Fisher, Ciarán, Leist, Marcel, Kisitu, Jaffar, Hollert, Henner, Fisher, Ciarán, and Leist, Marcel

Abstract

In biological systems (cell culture media, cells, body fluids), drugs/toxicants are usually not freely dissolved but partially bound to biomolecules; only a fraction of the chemical is free/unbound (fu). To predict pharmacological effects and toxicity, it is important that the fu of the drug is known. As the differences between free and nominal concentrations are determined by test system parameters (e.g., the protein and lipid content, and the type of surface material), comparison of nominal concentrations between two different new approach methods (NAM) may lead to faulty conclusions. The same problem exists when in vitro concentrations are compared to those in human subjects. Therefore, the respective fu of a chemical in a test system needs to be determined for in vitro-to-in vivo extrapolations (IVIVE). Besides direct measurements, prediction models can help to obtain fu. Here we describe a simplified approach to approximate fu and provide background information on the underlying assumptions. Comparative predictions and measurements of fu of various drugs are shown to exemplify the approach. Basic input data, like protein and lipid concentrations, are also provided. Beyond such test systems data, the only required chemical-specific inputs are the lipophilicity of the candidate drug and its ionization state, as determined by the dissociation constants of its acidic or basic groups. This overview is intended to be used by any lab scientist without specific toxicokinetics training to obtain an estimate of fu in a given cell culture medium.

Published
2020

26. Understanding Interindividual Variability in the Drug Interaction of a Highly Extracted CYP1A2 Substrate Tizanidine: Application of a Permeability-Limited Multicompartment Liver Model in a Population Based Physiologically Based Pharmacokinetic Framework

Author

Zhang, Mian, Fisher, Ciarán, Gardner, Iain, Pan, Xian, Kilford, Peter, Bois, Frederic Y., and Jamei, Masoud

Abstract

Tizanidine, a centrally acting skeletal muscle relaxant, is predominantly metabolized by CYP1A2 and undergoes extensive hepatic first-pass metabolism after oral administration. As a highly extracted drug, the systemic exposure to tizanidine exhibits considerable interindividual variability and is altered substantially when coadministered with CYP1A2 inhibitors or inducers. The aim of the current study was to compare the performance of a permeability-limited multicompartment liver (PerMCL) model, which operates as an approximation of the dispersion model, and the well stirred model (WSM) for predicting tizanidine drug-drug interactions (DDIs). Physiologically based pharmacokinetic models were developed for tizanidine, incorporating the PerMCL model and the WSM, respectively, to simulate the interaction of tizanidine with a range of CYP1A2 inhibitors and inducers. Whereas the WSM showed a tendency to underpredict the fold change of tizanidine area under the plasma concentration-time curve (AUC ratio) in the presence of perpetrators, the use of PerMCL model increased precision (absolute average-fold error: 1.32–1.42 versus 1.58) and decreased bias (average-fold error: 0.97–1.25 versus 0.63) for the predictions of mean AUC ratios as compared with the WSM. The PerMCL model captured the observed range of individual AUC ratios of tizanidine as well as the correlation between individual AUC ratios and CYP1A2 activities without interactions, whereas the WSM was not able to capture these. The results demonstrate the advantage of using the PerMCL model over the WSM in predicting the magnitude and interindividual variability of DDIs for a highly extracted sensitive substrate tizanidine.SIGNIFICANCE STATEMENTThis study demonstrates the advantages of the PerMCL model, which operates as an approximation of the dispersion model, in mitigating the tendency of the WSM to underpredict the magnitude and variability of DDIs of a highly extracted CYP1A2 substrate tizanidine when it is administered with CYP1A2 inhibitors or inducers. The physiologically based pharmacokinetic modeling approach described herein is valuable to the understanding of drug interactions of highly extracted substrates and the source of its interindividual variability.

Published
2022
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30. Adverse outcome pathways:opportunities, limitations and open questions

Author

Leist, Marcel, Ghallab, Ahmed, Graepel, Rabea, Marchan, Rosemarie, Hassan, Reham, Bennekou, Susanne Hougaard, Limonciel, Alice, Vinken, Mathieu, Schildknecht, Stefan, Waldmann, Tanja, Danen, Erik, van Ravenzwaay, Ben, Kamp, Hennicke, Gardner, Iain, Godoy, Patricio, Bois, Frederic Y, Braeuning, Albert, Reif, Raymond, Oesch, Franz, Drasdo, Dirk, Höhme, Stefan, Schwarz, Michael, Hartung, Thomas, Braunbeck, Thomas, Beltman, Joost, Vrieling, Harry, Sanz, Ferran, Forsby, Anna, Gadaleta, Domenico, Fisher, Ciarán, Kelm, Jens, Fluri, David, Ecker, Gerhard, Zdrazil, Barbara, Terron, Andrea, Jennings, Paul, van der Burg, Bart, Dooley, Steven, Meijer, Annemarie H, Willighagen, Egon, Martens, Marvin, Evelo, Chris, Mombelli, Enrico, Taboureau, Olivier, Mantovani, Alberto, Hardy, Barry, Koch, Bjorn, Escher, Sylvia, van Thriel, Christoph, Cadenas, Cristina, Kroese, D, van de Water, Bob, Hengstler, Jan G, Leist, Marcel, Ghallab, Ahmed, Graepel, Rabea, Marchan, Rosemarie, Hassan, Reham, Bennekou, Susanne Hougaard, Limonciel, Alice, Vinken, Mathieu, Schildknecht, Stefan, Waldmann, Tanja, Danen, Erik, van Ravenzwaay, Ben, Kamp, Hennicke, Gardner, Iain, Godoy, Patricio, Bois, Frederic Y, Braeuning, Albert, Reif, Raymond, Oesch, Franz, Drasdo, Dirk, Höhme, Stefan, Schwarz, Michael, Hartung, Thomas, Braunbeck, Thomas, Beltman, Joost, Vrieling, Harry, Sanz, Ferran, Forsby, Anna, Gadaleta, Domenico, Fisher, Ciarán, Kelm, Jens, Fluri, David, Ecker, Gerhard, Zdrazil, Barbara, Terron, Andrea, Jennings, Paul, van der Burg, Bart, Dooley, Steven, Meijer, Annemarie H, Willighagen, Egon, Martens, Marvin, Evelo, Chris, Mombelli, Enrico, Taboureau, Olivier, Mantovani, Alberto, Hardy, Barry, Koch, Bjorn, Escher, Sylvia, van Thriel, Christoph, Cadenas, Cristina, Kroese, D, van de Water, Bob, and Hengstler, Jan G

Abstract

Adverse outcome pathways (AOPs) are a recent toxicological construct that connects, in a formalized, transparent and quality-controlled way, mechanistic information to apical endpoints for regulatory purposes. AOP links a molecular initiating event (MIE) to the adverse outcome (AO) via key events (KE), in a way specified by key event relationships (KER). Although this approach to formalize mechanistic toxicological information only started in 2010, over 200 AOPs have already been established. At this stage, new requirements arise, such as the need for harmonization and re-assessment, for continuous updating, as well as for alerting about pitfalls, misuses and limits of applicability. In this review, the history of the AOP concept and its most prominent strengths are discussed, including the advantages of a formalized approach, the systematic collection of weight of evidence, the linkage of mechanisms to apical end points, the examination of the plausibility of epidemiological data, the identification of critical knowledge gaps and the design of mechanistic test methods. To prepare the ground for a broadened and appropriate use of AOPs, some widespread misconceptions are explained. Moreover, potential weaknesses and shortcomings of the current AOP rule set are addressed (1) to facilitate the discussion on its further evolution and (2) to better define appropriate vs. less suitable application areas. Exemplary toxicological studies are presented to discuss the linearity assumptions of AOP, the management of event modifiers and compensatory mechanisms, and whether a separation of toxicodynamics from toxicokinetics including metabolism is possible in the framework of pathway plasticity. Suggestions on how to compromise between different needs of AOP stakeholders have been added. A clear definition of open questions and limitations is provided to encourage further progress in the field.

Published
2017

35. SimRFlow: An R-based workflow for automated high-throughput PBPK simulation with the Simcyp ® simulator.

Author

Khalidi H, Onasanwo A, Islam B, Jo H, Fisher C, Aidley R, Gardner I, and Bois FY

Abstract

SimRFlow is a high-throughput physiologically based pharmacokinetic (PBPK) modelling tool which uses Certara's Simcyp® simulator. The workflow is comprised of three main modules: 1) a Data Collection module for automated curation of physicochemical (from ChEMBL and the Norman Suspect List databases) and experimental data (i.e.: clearance, plasma-protein binding, and blood-to-plasma ratio, from httk -R package databases), 2) a Simulation module which activates the Simcyp® simulator and runs Monte Carlo simulations on virtual subjects using the curated data, and 3) a Data Visualisation module for understanding the simulated compound-specific profiles and predictions. SimRFlow has three administration routes (oral, intravenous, dermal) and allows users to change some simulation parameters including the number of subjects, simulation duration, and dosing. Users are only expected to provide a file of the compounds they wish to simulate, and in return the workflow provides summary statistics, concentration-time profiles of various tissue types, and a database file (containing in-depth results) for each simulated compound. This is presented within a guided and easy-to-use R Shiny interface which provides many plotting options for the visualisation of concentration-time profiles, parameter distributions, trends between the different parameters, as well as comparison of predicted parameters across all batch-simulated compounds. The in-built R functions can be assembled in user-customised scripts which allows for the modification of the workflow for different purposes. SimRFlow proves to be a time-efficient tool for simulating a large number of compounds without any manual curation of physicochemical or experimental data necessary to run Simcyp® simulations., Competing Interests: All authors were employees of Certara UK Limited and may own shares in the company., (Copyright © 2022 Khalidi, Onasanwo, Islam, Jo, Fisher, Aidley, Gardner and Bois.)

Published
2022
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36. Chemical concentrations in cell culture compartments (C5) - free concentrations.

Author

Kisitu J, Hollert H, Fisher C, and Leist M

Subjects
Animals, Cell Culture Techniques, Culture Media, Humans, Pharmacokinetics, Protein Binding, Models, Biological, Pharmaceutical Preparations chemistry, Pharmaceutical Preparations metabolism
Abstract

In biological systems (cell culture media, cells, body fluids), drugs/toxicants are usually not freely dissolved but partially bound to biomolecules; only a fraction of the chemical is free/unbound (fu). To predict pharmacological effects and toxicity, it is important that the fu of the drug is known. As the differences between free and nominal concentrations are determined by test system parameters (e.g., the protein and lipid content, and the type of surface material), comparison of nominal concentrations between two different new approach methods (NAM) may lead to faulty conclusions. The same problem exists when in vitro concentrations are compared to those in human subjects. Therefore, the respective fu of a chemical in a test system needs to be determined for in vitro-to-in vivo extrapolations (IVIVE). Besides direct measurements, prediction models can help to obtain fu. Here we describe a simplified approach to approximate fu and provide background information on the underlying assumptions. Comparative predictions and measurements of fu of various drugs are shown to exemplify the approach. Basic input data, like protein and lipid concentrations, are also provided. Beyond such test systems data, the only required chemical-specific inputs are the lipophilicity of the candidate drug and its ionization state, as determined by the dissociation constants of its acidic or basic groups. This overview is intended to be used by any lab scientist without specific toxicokinetics training to obtain an estimate of fu in a given cell culture medium.

Published
2020
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