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In vitro models for non-alcoholic fatty liver disease: Emerging platforms and their applications.
Ramos, Maria Jimenez; Bandiera, Lucia; Menolascina, Filippo; Fallowfield, Jonathan Andrew.
Afiliação
  • Ramos MJ; Centre for Inflammation Research, The University of Edinburgh, The Queen's Medical Research Institute, Edinburgh EH16 4TJ, UK.
  • Bandiera L; Institute for Bioengineering, The University of Edinburgh, Edinburgh EH9 3BF, UK.
  • Menolascina F; Synthsys - Centre for Synthetic and Systems Biology, The University of Edinburgh, Edinburgh EH9 3BF, UK.
  • Fallowfield JA; Institute for Bioengineering, The University of Edinburgh, Edinburgh EH9 3BF, UK.
iScience ; 25(1): 103549, 2022 Jan 21.
Article em En | MEDLINE | ID: mdl-34977507
Non-alcoholic fatty liver disease (NAFLD) represents a global healthcare challenge, affecting 1 in 4 adults, and death rates are predicted to rise inexorably. The progressive form of NAFLD, non-alcoholic steatohepatitis (NASH), can lead to fibrosis, cirrhosis, and hepatocellular carcinoma. However, no medical treatments are licensed for NAFLD-NASH. Identifying efficacious therapies has been hindered by the complexity of disease pathogenesis, a paucity of predictive preclinical models and inadequate validation of pharmacological targets in humans. The development of clinically relevant in vitro models of the disease will pave the way to overcome these challenges. Currently, the combined application of emerging technologies (e.g., organ-on-a-chip/microphysiological systems) and control engineering approaches promises to unravel NAFLD biology and deliver tractable treatment candidates. In this review, we will describe advances in preclinical models for NAFLD-NASH, the recent introduction of novel technologies in this space, and their importance for drug discovery endeavors in the future.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: IScience Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: IScience Ano de publicação: 2022 Tipo de documento: Article