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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, Jose 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; Smedsrod, Bard; 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; Rahnenfuehrer, Jörg; Hengstler, Jan G. (2019): Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations. In: Archives of Toxicology, Vol. 93, No. 6: pp. 1609-1637
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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 (C-max) 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 48h was better than 24h, with no further improvement of TSI after 7days 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 C-max were best suited to estimate human toxicity. With a support vector machine-based classifier, using EC10 and C-max 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.

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