Publication: Modeling drug-induced liver injury: current status and future prospects.
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Date
2022-09-16
Authors
Di Zeo-Sánchez, Daniel E
Segovia-Zafra, Antonio
Matilla-Cabello, Gonzalo
Pinazo-Bandera, José M
Andrade, Raúl J
Lucena, M Isabel
Villanueva-Paz, Marina
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Abstract
Idiosyncratic drug-induced liver injury (iDILI) is a challenging and unpredictable multifactorial condition. At present, validated preclinical models for the prediction of the hepatotoxic potential of a given drug are scarce. This review intends to sum up the current knowledge about in vitro (including hepatocyte 2D cultures, cocultures with non-parenchymal cells, 3D configurations and non-typical closer to reality in vitro models), in vivo (covering models for immunological and oxidative stress features, humanized mouse-based and non-rodent models) and in silico approaches for iDILI modeling, highlighting the recent advances in each topic. The future strategy for iDILI modeling should be patient-centered. Future animal and cell-based models, with more predictive value, will be easier to design by using a more translational approach based on mechanisms demonstrated in humans. Genetic and epigenetic information gathered from iDILI patients, together with data from in vitro and in vivo studies, could be used to develop sophisticated predictive in silico models to find compounds with iDILI potential. Collecting genetic, metabolic, and biomarker data from patient cohorts might be another option to create a 'fingerprint' characteristic of people at risk, allowing for the development of new, mechanistic strategies to enhance iDILI in vitro evaluation.
Description
MeSH Terms
Animals
Biomarkers
Chemical and Drug Induced Liver Injury
Drug-Related Side Effects and Adverse Reactions
Hepatocytes
Humans
Liver
Mice
Biomarkers
Chemical and Drug Induced Liver Injury
Drug-Related Side Effects and Adverse Reactions
Hepatocytes
Humans
Liver
Mice
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Keywords
DILI, Hepatotoxicity, iDILI, immune response, mechanisms, mitochondrial damage, oxidative stress, preclinical model, prediction