Back to Search Start Over

Studying metabolism with multi-organ chips: new tools for disease modelling, pharmacokinetics and pharmacodynamics

Authors :
Tanvi Shroff
Kehinde Aina
Christian Maass
Madalena Cipriano
Joeri Lambrecht
Frank Tacke
Alexander Mosig
Peter Loskill
Source :
Open Biology, Vol 12, Iss 3 (2022)
Publication Year :
2022
Publisher :
The Royal Society, 2022.

Abstract

Non-clinical models to study metabolism including animal models and cell assays are often limited in terms of species translatability and predictability of human biology. This field urgently requires a push towards more physiologically accurate recapitulations of drug interactions and disease progression in the body. Organ-on-chip systems, specifically multi-organ chips (MOCs), are an emerging technology that is well suited to providing a species-specific platform to study the various types of metabolism (glucose, lipid, protein and drug) by recreating organ-level function. This review provides a resource for scientists aiming to study human metabolism by providing an overview of MOCs recapitulating aspects of metabolism, by addressing the technical aspects of MOC development and by providing guidelines for correlation with in silico models. The current state and challenges are presented for two application areas: (i) disease modelling and (ii) pharmacokinetics/pharmacodynamics. Additionally, the guidelines to integrate the MOC data into in silico models could strengthen the predictive power of the technology. Finally, the translational aspects of metabolizing MOCs are addressed, including adoption for personalized medicine and prospects for the clinic. Predictive MOCs could enable a significantly reduced dependence on animal models and open doors towards economical non-clinical testing and understanding of disease mechanisms.

Details

Language :
English
ISSN :
20462441
Volume :
12
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Open Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.6021618bbcb940019884b6d998dd99de
Document Type :
article
Full Text :
https://doi.org/10.1098/rsob.210333