| Title: | Integrating computational fluid dynamics into organ-on-chip systems: a glioblastoma-centred design and validation framework |
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| Authors: | ID Taleban, Hooman (Author)
ID Li, Xinzhong (Author)
ID Ali, Zulfiqur (Author)
ID Kalesh, Karunakaran (Author)
ID Prakash, Jai (Author)
ID Bagci-Onder, Tugba (Author)
ID Breznik, Barbara (Author) |
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| Files: |  URL - Source URL, visit https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2025.1716813/full
 DOCX - Presentation file, download (716,80 KB)
MD5: 48B7376B709BD734B059E339B1B60E2B
 PDF - Presentation file, download (3,79 MB)
MD5: CE33D2D6DC34B08C26ED264971A4768B
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| Language: | English |
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| Typology: | 1.02 - Review Article |
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| Organization: |  NIB - National Institute of Biology
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| Abstract: | Glioblastoma GBM: Glioblastoma multiforme (GBM) remains one of the most lethal and treatment-resistant brain cancers, driven in part by the complexity of its tumour microenvironment (TME). While organ-on-chip (OoC) platforms offer more physiologically relevant models than traditional 2D or static 3D systems, their design remains largely empirical, lacking predictive control over flow conditions, biochemical gradients, and mechanical cues. Computational Fluid Dynamics (CFD) has emerged as a powerful tool to enhance the design, precision, and biological fidelity of OoC platforms. This comprehensive review highlights current limitations in replicating GBM’s biological complexity and technical constraints in device fabrication and maintenance, mapping them to specific CFD strategies. It synthesises current strategies into a structured workflow for integrating CFD into the design, optimisation, and validation of microfluidic tumour models—bridging engineering precision with biological complexity. In addition, validation frameworks reported in the literature are highlighted and mapped onto GBM-on-chip applications have been recommended, drawing on widely recognised international standards for engineering validation and regulatory modelling practices. Finally, this review positions CFD as a core component of GBM-on-chip development and explores how its integration with AI-based optimisation can advance the creation of more predictive, scalable, and biologically relevant in vitro tumour models. |
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| Keywords: | AI, computational fluid dynamics, glioblastoma, In silicosimulation, in vitro modelling, microfluidic perfusion, organ-on-chip, tumour microenvironment |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Publication date: | 22.01.2026 |
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| Year of publishing: | 2026 |
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| Number of pages: | str. 1-22 |
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| Numbering: | Vol. 13, [article no.] 1716813 |
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| PID: | 20.500.12556/DiRROS-27571  |
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| UDC: | 577.2 |
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| ISSN on article: | 2296-4185 |
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| DOI: | 10.3389/fbioe.2025.1716813 |
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| COBISS.SI-ID: | 267196675 |
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| Note: | Nasl. z nasl. zaslona;
Opis vira z dne 3. 2. 2026;
Soavtorji: Xinzhong Li, Zulfiqur Ali, Karunakaran Kalesh, Jai Prakash, Tugba Bagci-Onder, Barbara Breznik;
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| Publication date in DiRROS: | 13.02.2026 |
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| Views: | 373 |
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| Downloads: | 142 |
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