RDT, liver toxicity, NAM
Drug-induced liver injury (DILI) cannot be accurately predicted by animal models. Also, 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 concerning oral doses and blood concentrations.
Despite intensive research, it is currently not possible to reliably predict whether repeated exposure to a certain dose of a chemical leads to an increased risk of hepatotoxicity or can be considered harmless.
The main objectives of this case study are:
- To predict blood concentrations of chemicals that cause an increased risk of hepatotoxicity and to identify concentration ranges that can be considered harmless.
- To predict oral doses of chemicals that cause an increased risk of hepatotoxicity (reverse modelling).
The developed novel in vitro/in silico method can be used to estimate DILI risk if the maximal blood concentration 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 compounds, based on TSI and TEI, to identify the most performing concentrations and incubation time. Additionally, metrics were moderately improved by adding gene expression to the test battery and evaluation of pharmacokinetic parameters were evaluated. With a support vector machine-based classifier, the cross-validated sensitivity, specificity, and accuracy for hepatotoxicity prediction were highly relevant, respectively 100, 88, and 93%. Currently, the novel in vitro/in silico method is validated in a set of >200 test compounds. A constantly ongoing activity in this project is the identification of key events of DILI that can be tested in vitro in order to integrate them into our in vitro test battery.
Albrecht et al. 2019 [link]; Gu et al. 2018 [link]; Leist et al. 2017 [link]; Sachinidis et al. 2019 [link]; Ghallab et al. 2018 [link]; Jansen et al. 2016 [link]; Kappenberg et al. 2021 [link]; Gupta et al. 2020 [link]; Kappenberg et al. [link]; Krebs et al. 2020 [link]; Hengstler et al. 2020 [link]; Fasbender et al. 2020 [link]; Ruoß et al. 2020 [link]; Campos et al. 2020 [link]; Ghallab et al. 2019 [link]
IFADO, UL, UKN, UM, UNILEVER, RISE, KI, CE, TNO, ITEM, DC, SimCyp, EBI, UNIVIE, UCPH, TissUse, JHSPH, IS, L’Oreal.