A Comparative Analysis of Drug-Induced Hepatotoxicity in Clinically Relevant Situations
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Drug-induced toxicity is a significant problem in clinical care. A key problem here is a general understanding of the molecular mechanisms accompanying the transition from desired drug effects to adverse events following administration of either therapeutic or toxic doses, in particular within a patient context. Here, a comparative toxicity analysis was performed for fifteen hepatotoxic drugs by evaluating toxic changes reflecting the transition from therapeutic drug responses to toxic reactions at the cellular level. By use of physiologically-based pharmacokinetic modeling, in vitro toxicity data were first contextualized to quantitatively describe time-resolved drug responses within a patient context. Comparatively studying toxic changes across the considered hepatotoxicants allowed the identification of subsets of drugs sharing similar perturbations on key cellular processes, functional classes of genes, and individual genes. The identified subsets of drugs were next analyzed with regard to drug-related characteristics and their physicochemical properties. Toxic changes were finally evaluated to predict both molecular biomarkers and potential drug-drug interactions. The results may facilitate the early diagnosis of adverse drug events in clinical application.
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Karatza E, Sinha J, Maglalang P, Edginton A, Gonzalez D Clin Pharmacokinet. 2024; 63(10):1435-1448.
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Baier V, Cordes H, Thiel C, Castell J, Neumann U, Blank L Front Physiol. 2019; 10:1192.
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Kalra P, Brandl J, Gaub T, Niederalt C, Lippert J, Sahle S PLoS One. 2019; 14(2):e0209587.
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