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Liver-on-chips for drug discovery and development.
Mehta, Viraj; Karnam, Guruswamy; Madgula, Vamsi.
Afiliação
  • Mehta V; Organoid Technology Lab, DMPK Department, Sai Life Sciences, Hyderabad, 500078, India.
  • Karnam G; Organoid Technology Lab, DMPK Department, Sai Life Sciences, Hyderabad, 500078, India.
  • Madgula V; Organoid Technology Lab, DMPK Department, Sai Life Sciences, Hyderabad, 500078, India.
Mater Today Bio ; 27: 101143, 2024 Aug.
Article em En | MEDLINE | ID: mdl-39070097
ABSTRACT
Recent FDA modernization act 2.0 has led to increasing industrial R&D investment in advanced in vitro 3D models such as organoids, spheroids, organ-on-chips, 3D bioprinting, and in silico approaches. Liver-related advanced in vitro models remain the prime area of interest, as liver plays a central role in drug clearance of compounds. Growing evidence indicates the importance of recapitulating the overall liver microenvironment to enhance hepatocyte maturity and culture longevity using liver-on-chips (LoC) in vitro. Hence, pharmaceutical industries have started exploring LoC assays in the two of the most challenging areas accurate in vitro-in vivo extrapolation (IVIVE) of hepatic drug clearance and drug-induced liver injury. We examine the joint efforts of commercial chip manufacturers and pharmaceutical companies to present an up-to-date overview of the adoption of LoC technology in the drug discovery. Further, several roadblocks are identified to the rapid adoption of LoC assays in the current drug development framework. Finally, we discuss some of the underexplored application areas of LoC models, where conventional 2D hepatic models are deemed unsuitable. These include clearance prediction of metabolically stable compounds, immune-mediated drug-induced liver injury (DILI) predictions, bioavailability prediction with gut-liver systems, hepatic clearance prediction of drugs given during pregnancy, and dose adjustment studies in disease conditions. We conclude the review by discussing the importance of PBPK modeling with LoC, digital twins, and AI/ML integration with LoC.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article