Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations

Wiebke Albrecht; Franziska Kappenberg; Tim Brecklinghaus; Regina Stoeber; Rosemarie Marchan; Mian Zhang; Kristina Ebbert; Hendrik Kirschner; Marianna Grinberg; Marcel Leist; Wolfgang Moritz; Cristina Cadenas; Ahmed Ghallab; Jörg Reinders; Nachiket Vartak; Christoph van Thriel; Klaus Golka; Laia Tolosa; José V Castell; Georg Damm; Daniel Seehofer; Alfonso Lampen; Albert Braeuning; Thorsten Buhrke; Anne-Cathrin Behr; Axel Oberemm; Xiaolong Gu; Naim Kittana; Bob van de Water; Reinhard Kreiling; Susann Fayyaz; Leon van Aerts; Bård Smedsrød; Heidrun Ellinger-Ziegelbauer; Thomas Steger-Hartmann; Ursula Gundert-Remy; Anja Zeigerer; Anett Ullrich; Dieter Runge; Serene M L Lee; Tobias S Schiergens; Lars Kuepfer; Alejandro Aguayo-Orozco; Agapios Sachinidis; Karolina Edlund; Iain Gardner; Jörg Rahnenführer; Jan G Hengstler

doi:10.1007/s00204-019-02492-9

Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations

Wiebke Albrecht, Franziska Kappenberg, Tim Brecklinghaus, Regina Stoeber, Rosemarie Marchan, Mian Zhang, Kristina Ebbert, Hendrik Kirschner, Marianna Grinberg, Marcel Leist, Wolfgang Moritz, Cristina Cadenas, Ahmed Ghallab, Jörg Reinders, Nachiket Vartak, Christoph van Thriel, Klaus Golka, Laia Tolosa, José V Castell, Georg DammDaniel Seehofer, Alfonso Lampen, Albert Braeuning, Thorsten Buhrke, Anne-Cathrin Behr, Axel Oberemm, Xiaolong Gu, Naim Kittana, Bob van de Water, Reinhard Kreiling, Susann Fayyaz, Leon van Aerts, Bård Smedsrød, Heidrun Ellinger-Ziegelbauer, Thomas Steger-Hartmann, Ursula Gundert-Remy, Anja Zeigerer, Anett Ullrich, Dieter Runge, Serene M L Lee, Tobias S Schiergens, Lars Kuepfer, Alejandro Aguayo-Orozco, Agapios Sachinidis, Karolina Edlund, Iain Gardner, Jörg Rahnenführer, Jan G Hengstler

Disease Systems Biology Program

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Abstract

Drug-induced liver injury (DILI) cannot be accurately predicted by animal models. In addition, currently available in vitro methods do not allow for the estimation of hepatotoxic doses or the determination of an acceptable daily intake (ADI). To overcome this limitation, an in vitro/in silico method was established that predicts the risk of human DILI in relation to oral doses and blood concentrations. This method can be used to estimate DILI risk if the maximal blood concentration (Cmax) of the test compound is known. Moreover, an ADI can be estimated even for compounds without information on blood concentrations. To systematically optimize the in vitro system, two novel test performance metrics were introduced, the toxicity separation index (TSI) which quantifies how well a test differentiates between hepatotoxic and non-hepatotoxic compounds, and the toxicity estimation index (TEI) which measures how well hepatotoxic blood concentrations in vivo can be estimated. In vitro test performance was optimized for a training set of 28 compounds, based on TSI and TEI, demonstrating that (1) concentrations where cytotoxicity first becomes evident in vitro (EC10) yielded better metrics than higher toxicity thresholds (EC50); (2) compound incubation for 48 h was better than 24 h, with no further improvement of TSI after 7 days incubation; (3) metrics were moderately improved by adding gene expression to the test battery; (4) evaluation of pharmacokinetic parameters demonstrated that total blood compound concentrations and the 95%-population-based percentile of Cmax were best suited to estimate human toxicity. With a support vector machine-based classifier, using EC10 and Cmax as variables, the cross-validated sensitivity, specificity and accuracy for hepatotoxicity prediction were 100, 88 and 93%, respectively. Concentrations in the culture medium allowed extrapolation to blood concentrations in vivo that are associated with a specific probability of hepatotoxicity and the corresponding oral doses were obtained by reverse modeling. Application of this in vitro/in silico method to the rat hepatotoxicant pulegone resulted in an ADI that was similar to values previously established based on animal experiments. In conclusion, the proposed method links oral doses and blood concentrations of test compounds to the probability of hepatotoxicity.

Original language	English
Journal	Archives of Toxicology
Volume	93
Issue number	6
Pages (from-to)	1609-1637
Number of pages	29
ISSN	0340-5761
DOIs	https://doi.org/10.1007/s00204-019-02492-9
Publication status	Published - 1 Jun 2019

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Albrecht, W., Kappenberg, F., Brecklinghaus, T., Stoeber, R., Marchan, R., Zhang, M., Ebbert, K., Kirschner, H., Grinberg, M., Leist, M., Moritz, W., Cadenas, C., Ghallab, A., Reinders, J., Vartak, N., van Thriel, C., Golka, K., Tolosa, L., Castell, J. V., ... Hengstler, J. G. (2019). Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations. Archives of Toxicology, 93(6), 1609-1637. https://doi.org/10.1007/s00204-019-02492-9

Albrecht, W, Kappenberg, F, Brecklinghaus, T, Stoeber, R, Marchan, R, Zhang, M, Ebbert, K, Kirschner, H, Grinberg, M, Leist, M, Moritz, W, Cadenas, C, Ghallab, A, Reinders, J, Vartak, N, van Thriel, C, Golka, K, Tolosa, L, Castell, JV, Damm, G, Seehofer, D, Lampen, A, Braeuning, A, Buhrke, T, Behr, A-C, Oberemm, A, Gu, X, Kittana, N, van de Water, B, Kreiling, R, Fayyaz, S, van Aerts, L, Smedsrød, B, Ellinger-Ziegelbauer, H, Steger-Hartmann, T, Gundert-Remy, U, Zeigerer, A, Ullrich, A, Runge, D, Lee, SML, Schiergens, TS, Kuepfer, L, Aguayo-Orozco, A, Sachinidis, A, Edlund, K, Gardner, I, Rahnenführer, J & Hengstler, JG 2019, 'Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations', Archives of Toxicology, vol. 93, no. 6, pp. 1609-1637. https://doi.org/10.1007/s00204-019-02492-9

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abstract = "Drug-induced liver injury (DILI) cannot be accurately predicted by animal models. In addition, currently available in vitro methods do not allow for the estimation of hepatotoxic doses or the determination of an acceptable daily intake (ADI). To overcome this limitation, an in vitro/in silico method was established that predicts the risk of human DILI in relation to oral doses and blood concentrations. This method can be used to estimate DILI risk if the maximal blood concentration (Cmax) of the test compound is known. Moreover, an ADI can be estimated even for compounds without information on blood concentrations. To systematically optimize the in vitro system, two novel test performance metrics were introduced, the toxicity separation index (TSI) which quantifies how well a test differentiates between hepatotoxic and non-hepatotoxic compounds, and the toxicity estimation index (TEI) which measures how well hepatotoxic blood concentrations in vivo can be estimated. In vitro test performance was optimized for a training set of 28 compounds, based on TSI and TEI, demonstrating that (1) concentrations where cytotoxicity first becomes evident in vitro (EC10) yielded better metrics than higher toxicity thresholds (EC50); (2) compound incubation for 48 h was better than 24 h, with no further improvement of TSI after 7 days incubation; (3) metrics were moderately improved by adding gene expression to the test battery; (4) evaluation of pharmacokinetic parameters demonstrated that total blood compound concentrations and the 95%-population-based percentile of Cmax were best suited to estimate human toxicity. With a support vector machine-based classifier, using EC10 and Cmax as variables, the cross-validated sensitivity, specificity and accuracy for hepatotoxicity prediction were 100, 88 and 93%, respectively. Concentrations in the culture medium allowed extrapolation to blood concentrations in vivo that are associated with a specific probability of hepatotoxicity and the corresponding oral doses were obtained by reverse modeling. Application of this in vitro/in silico method to the rat hepatotoxicant pulegone resulted in an ADI that was similar to values previously established based on animal experiments. In conclusion, the proposed method links oral doses and blood concentrations of test compounds to the probability of hepatotoxicity.",

author = "Wiebke Albrecht and Franziska Kappenberg and Tim Brecklinghaus and Regina Stoeber and Rosemarie Marchan and Mian Zhang and Kristina Ebbert and Hendrik Kirschner and Marianna Grinberg and Marcel Leist and Wolfgang Moritz and Cristina Cadenas and Ahmed Ghallab and J{\"o}rg Reinders and Nachiket Vartak and {van Thriel}, Christoph and Klaus Golka and Laia Tolosa and Castell, {Jos{\'e} V} and Georg Damm and Daniel Seehofer and Alfonso Lampen and Albert Braeuning and Thorsten Buhrke and Anne-Cathrin Behr and Axel Oberemm and Xiaolong Gu and Naim Kittana and {van de Water}, Bob and Reinhard Kreiling and Susann Fayyaz and {van Aerts}, Leon and B{\aa}rd Smedsr{\o}d and Heidrun Ellinger-Ziegelbauer and Thomas Steger-Hartmann and Ursula Gundert-Remy and Anja Zeigerer and Anett Ullrich and Dieter Runge and Lee, {Serene M L} and Schiergens, {Tobias S} and Lars Kuepfer and Alejandro Aguayo-Orozco and Agapios Sachinidis and Karolina Edlund and Iain Gardner and J{\"o}rg Rahnenf{\"u}hrer and Hengstler, {Jan G}",

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doi = "10.1007/s00204-019-02492-9",

language = "English",

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T1 - Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations

AU - Albrecht, Wiebke

AU - Kappenberg, Franziska

AU - Brecklinghaus, Tim

AU - Stoeber, Regina

AU - Marchan, Rosemarie

AU - Zhang, Mian

AU - Ebbert, Kristina

AU - Kirschner, Hendrik

AU - Grinberg, Marianna

AU - Leist, Marcel

AU - Moritz, Wolfgang

AU - Cadenas, Cristina

AU - Ghallab, Ahmed

AU - Reinders, Jörg

AU - Vartak, Nachiket

AU - van Thriel, Christoph

AU - Golka, Klaus

AU - Tolosa, Laia

AU - Castell, José V

AU - Damm, Georg

AU - Seehofer, Daniel

AU - Lampen, Alfonso

AU - Braeuning, Albert

AU - Buhrke, Thorsten

AU - Behr, Anne-Cathrin

AU - Oberemm, Axel

AU - Gu, Xiaolong

AU - Kittana, Naim

AU - van de Water, Bob

AU - Kreiling, Reinhard

AU - Fayyaz, Susann

AU - van Aerts, Leon

AU - Smedsrød, Bård

AU - Ellinger-Ziegelbauer, Heidrun

AU - Steger-Hartmann, Thomas

AU - Gundert-Remy, Ursula

AU - Zeigerer, Anja

AU - Ullrich, Anett

AU - Runge, Dieter

AU - Lee, Serene M L

AU - Schiergens, Tobias S

AU - Kuepfer, Lars

AU - Aguayo-Orozco, Alejandro

AU - Sachinidis, Agapios

AU - Edlund, Karolina

AU - Gardner, Iain

AU - Rahnenführer, Jörg

AU - Hengstler, Jan G

PY - 2019/6/1

Y1 - 2019/6/1

N2 - Drug-induced liver injury (DILI) cannot be accurately predicted by animal models. In addition, currently available in vitro methods do not allow for the estimation of hepatotoxic doses or the determination of an acceptable daily intake (ADI). To overcome this limitation, an in vitro/in silico method was established that predicts the risk of human DILI in relation to oral doses and blood concentrations. This method can be used to estimate DILI risk if the maximal blood concentration (Cmax) of the test compound is known. Moreover, an ADI can be estimated even for compounds without information on blood concentrations. To systematically optimize the in vitro system, two novel test performance metrics were introduced, the toxicity separation index (TSI) which quantifies how well a test differentiates between hepatotoxic and non-hepatotoxic compounds, and the toxicity estimation index (TEI) which measures how well hepatotoxic blood concentrations in vivo can be estimated. In vitro test performance was optimized for a training set of 28 compounds, based on TSI and TEI, demonstrating that (1) concentrations where cytotoxicity first becomes evident in vitro (EC10) yielded better metrics than higher toxicity thresholds (EC50); (2) compound incubation for 48 h was better than 24 h, with no further improvement of TSI after 7 days incubation; (3) metrics were moderately improved by adding gene expression to the test battery; (4) evaluation of pharmacokinetic parameters demonstrated that total blood compound concentrations and the 95%-population-based percentile of Cmax were best suited to estimate human toxicity. With a support vector machine-based classifier, using EC10 and Cmax as variables, the cross-validated sensitivity, specificity and accuracy for hepatotoxicity prediction were 100, 88 and 93%, respectively. Concentrations in the culture medium allowed extrapolation to blood concentrations in vivo that are associated with a specific probability of hepatotoxicity and the corresponding oral doses were obtained by reverse modeling. Application of this in vitro/in silico method to the rat hepatotoxicant pulegone resulted in an ADI that was similar to values previously established based on animal experiments. In conclusion, the proposed method links oral doses and blood concentrations of test compounds to the probability of hepatotoxicity.

AB - Drug-induced liver injury (DILI) cannot be accurately predicted by animal models. In addition, currently available in vitro methods do not allow for the estimation of hepatotoxic doses or the determination of an acceptable daily intake (ADI). To overcome this limitation, an in vitro/in silico method was established that predicts the risk of human DILI in relation to oral doses and blood concentrations. This method can be used to estimate DILI risk if the maximal blood concentration (Cmax) of the test compound is known. Moreover, an ADI can be estimated even for compounds without information on blood concentrations. To systematically optimize the in vitro system, two novel test performance metrics were introduced, the toxicity separation index (TSI) which quantifies how well a test differentiates between hepatotoxic and non-hepatotoxic compounds, and the toxicity estimation index (TEI) which measures how well hepatotoxic blood concentrations in vivo can be estimated. In vitro test performance was optimized for a training set of 28 compounds, based on TSI and TEI, demonstrating that (1) concentrations where cytotoxicity first becomes evident in vitro (EC10) yielded better metrics than higher toxicity thresholds (EC50); (2) compound incubation for 48 h was better than 24 h, with no further improvement of TSI after 7 days incubation; (3) metrics were moderately improved by adding gene expression to the test battery; (4) evaluation of pharmacokinetic parameters demonstrated that total blood compound concentrations and the 95%-population-based percentile of Cmax were best suited to estimate human toxicity. With a support vector machine-based classifier, using EC10 and Cmax as variables, the cross-validated sensitivity, specificity and accuracy for hepatotoxicity prediction were 100, 88 and 93%, respectively. Concentrations in the culture medium allowed extrapolation to blood concentrations in vivo that are associated with a specific probability of hepatotoxicity and the corresponding oral doses were obtained by reverse modeling. Application of this in vitro/in silico method to the rat hepatotoxicant pulegone resulted in an ADI that was similar to values previously established based on animal experiments. In conclusion, the proposed method links oral doses and blood concentrations of test compounds to the probability of hepatotoxicity.

U2 - 10.1007/s00204-019-02492-9

DO - 10.1007/s00204-019-02492-9

M3 - Journal article

C2 - 31250071

SN - 0340-5761

VL - 93

SP - 1609

EP - 1637

JO - Archives of Toxicology

JF - Archives of Toxicology

IS - 6

ER -

Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations

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