<i>In vitro</i>
            and
            <i>in silico</i>
            approaches to engineering three-dimensional biological tissues and organoids

Byrne, Helen

doi:10.1098/rsfs.2022.0046

Cited by 1 publication

(1 citation statement)

References 14 publications

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“…The inherent properties of organoid models, such as recapitulating and maintaining biological features of their tissue of origin, accessibility and their comparably small size, make them an ideal tool to inform and/or validate computational simulations (Figure 2). Various approaches in 2D and 3D, such as agentbased models, vertex models, Potts models, and finite element models have been utilized to model cellular interactions and biomechanical properties in organoids (Montes-Olivas et al, 2019;Norfleet et al, 2020;Byrne, 2022). Furthermore, computational modeling has also been used to optimize culture conditions (Goto-Silva et al, 2019).…”

Section: Computational Modeling With Organoidsmentioning

confidence: 99%

Organoids in high-throughput and high-content screenings

2023

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Organoids are self-organized three-dimensional (3D) multicellular tissue cultures which derive from cancerous and healthy stem cells, sharing a highly similarity to the corresponding in vivo organs. Since their introduction in 2009, they have emerged as a valuable model for studying early embryogenesis, organ and tissue development, as well as tools in drug screening, disease modeling and personalized therapy. Organoids can now be established for various tissues, including brain, retina, thyroid, gastrointestinal, lung, liver, pancreas, and kidney. These micro-tissues resemble the native organ in terms of gene expression, protein expression, tissue architecture and cell-cell interactions. Despite the success of organoid-based research and the advances in patient-derived organoid culture, important challenges remain. In this review, we briefly showcase the evolution from the primary 3D systems to complex, multilayered 3D structures such as assembloids, gastruloids and ETiX embryoids. We discuss current developments in organoid research and highlight developments in organoid culturing systems and analysis tools which make organoids accessible for high-throughput and high-content screening. Finally, we summarize the potential of machine learning and computational modeling in conjunction with organoid systems.

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