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

Research output: Contribution to journalJournal articleResearchpeer-review

  • 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
  • Agapios Sachinidis
  • Karolina Edlund
  • Iain Gardner
  • Jörg Rahnenführer
  • Jan G Hengstler

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 languageEnglish
JournalArchives of Toxicology
Issue number6
Pages (from-to)1609-1637
Number of pages29
Publication statusPublished - 2019

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