Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations
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Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations. / Albrecht, Wiebke; Kappenberg, Franziska; Brecklinghaus, Tim; Stoeber, Regina; Marchan, Rosemarie; Zhang, Mian; Ebbert, Kristina; Kirschner, Hendrik; Grinberg, Marianna; Leist, Marcel; Moritz, Wolfgang; Cadenas, Cristina; Ghallab, Ahmed; Reinders, Jörg; Vartak, Nachiket; van Thriel, Christoph; Golka, Klaus; Tolosa, Laia; Castell, José V; Damm, Georg; Seehofer, Daniel; Lampen, Alfonso; Braeuning, Albert; Buhrke, Thorsten; Behr, Anne-Cathrin; Oberemm, Axel; Gu, Xiaolong; Kittana, Naim; van de Water, Bob; Kreiling, Reinhard; Fayyaz, Susann; van Aerts, Leon; Smedsrød, Bård; Ellinger-Ziegelbauer, Heidrun; Steger-Hartmann, Thomas; Gundert-Remy, Ursula; Zeigerer, Anja; Ullrich, Anett; Runge, Dieter; Lee, Serene M L; Schiergens, Tobias S; Kuepfer, Lars; Aguayo-Orozco, Alejandro; Sachinidis, Agapios; Edlund, Karolina; Gardner, Iain; Rahnenführer, Jörg; Hengstler, Jan G.
In: Archives of Toxicology, Vol. 93, No. 6, 2019, p. 1609-1637.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
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
Y1 - 2019
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
VL - 93
SP - 1609
EP - 1637
JO - Archives of Toxicology
JF - Archives of Toxicology
SN - 0340-5761
IS - 6
ER -
ID: 227135938