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Cited by 196

The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.

Microfluidic organoids-on-a-chip: The future of human models

Saorin, Gloria, Caligiuri, Isabella, Rizzolio, Flavio·2023·Seminars in Cell & Developmental Biology

Abstract

Microfluidics opened the possibility to model the physiological environment by controlling fluids flows, and therefore nutrients supply. It allows to integrate external stimuli such as electricals or mechanicals and in situ monitoring important parameters such as pH, oxygen and metabolite concentrations. Organoids are self-organized 3D organ-like clusters, which allow to closely model original organ functionalities. Applying microfluidics to organoids allows to generate powerful human models for studying organ development, diseases, and drug testing. In this review, after a brief introduction on microfluidics, organoids and organoids-on-a-chip are described by organs (brain, heart, gastrointestinal tract, liver, pancreas) highlighting the microfluidic approaches since this point of view was overlooked in previously published reviews. Indeed, the review aims to discuss from a different point of view, primary microfluidics, the available literature on organoids-on-a-chip, standing out from the published literature by focusing on each specific organ.

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Metadata

Authors
Saorin, G., Caligiuri, I., & Rizzolio, F.
Venue
Seminars in Cell & Developmental Biology
Publisher
Elsevier BV
Published
2023-07
Volume
144
Pages
41-54
ISSN
1084-9521 (ISSN-L)
OpenAlex
W4304190482
Cited by
196
References
19
FWCI
10.19
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Microfluidic organoids-on-a-chip: The future of human models. https://app.cochat.ai/papers/10.1016/j.semcdb.2022.10.001
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Saorin, G., Caligiuri, I., & Rizzolio, F. (2023). Microfluidic organoids-on-a-chip: The future of human models. Seminars in Cell & Developmental Biology. https://doi.org/10.1016/j.semcdb.2022.10.001

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.