Evidence map›Paper›PMID 39064385›Full record

ReviewMicromachines2024

Advances in Microfluidic Systems and Numerical Modeling in Biomedical Applications: A Review.

Mariana Ferreira, Violeta Carvalho, João Ribeiro, Rui A Lima, Senhorinha Teixeira, Diana Pinho

Abstract readReview
In one paragraph

Review in Micromachines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

  1. Review
  2. Computational approaches in bioprinting processes.Nature reviews bioengineering · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Review
  11. Review
  12. Review
  13. Article
  14. Article
  15. Review
  16. Review
  17. Review
  18. Review
  19. Review
  20. 3DFrontiers in pharmacology · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mariana FerreiraCenter for Microelectromechanical Systems (CMEMS-UMinho), University of Minho, Campus de Azurém, 4800-058 Guimaraes, Portugal.
Violeta CarvalhoCenter for Microelectromechanical Systems (CMEMS-UMinho), University of Minho, Campus de Azurém, 4800-058 Guimaraes, Portugal.ORCID 0000-0002-9447-4746
João RibeiroInstituto Politécnico de Bragança, 5300-052 Bragança, Portugal.ORCID 0000-0001-6300-148X
Rui A LimaMEtRICs, Mechanical Engineering Department, University of Minho, Campus de Azurém, 4800-058 Guimaraes, Portugal.ORCID 0000-0003-3428-637X
Senhorinha TeixeiraLABBELS-Associate Laboratory, 4800-058 Guimaraes, Portugal.ORCID 0000-0002-7464-3944
Diana PinhoCenter for Microelectromechanical Systems (CMEMS-UMinho), University of Minho, Campus de Azurém, 4800-058 Guimaraes, Portugal.ORCID 0000-0002-3884-6496

Funding

Foundation for Science and Technology 2021.00027.CEECIND/CP1664/CT0007Foundation for Science and Technology 2022.02085.PTDCFoundation for Science and Technology 2022.06207.PTDCFoundation for Science and Technology LA/P/0045/2020Foundation for Science and Technology PTDC/EEI-EEE/2846/2021Foundation for Science and Technology UI/BD/151028/2021Foundation for Science and Technology UIDB/00532/2020Foundation for Science and Technology UIDB/00690/2020Foundation for Science and Technology UIDB/04077/2020Foundation for Science and Technology UIDB/04436/2020Foundation for Science and Technology UIDB/04650/2020Foundation for Science and Technology UIDP/04077/2020Foundation for Science and Technology UIDP/04436/2020
6 · The paper itself

Abstract

The evolution in the biomedical engineering field boosts innovative technologies, with microfluidic systems standing out as transformative tools in disease diagnosis, treatment, and monitoring. Numerical simulation has emerged as a tool of increasing importance for better understanding and predicting fluid-flow behavior in microscale devices. This review explores fabrication techniques and common materials of microfluidic devices, focusing on soft lithography and additive manufacturing. Microfluidic systems applications, including nucleic acid amplification and protein synthesis, as well as point-of-care diagnostics, DNA analysis, cell cultures, and organ-on-a-chip models (e.g., lung-, brain-, liver-, and tumor-on-a-chip), are discussed. Recent studies have applied computational tools such as ANSYS Fluent 2024 software to numerically simulate the flow behavior. Outside of the study cases, this work reports fundamental aspects of microfluidic simulations, including fluid flow, mass transport, mixing, and diffusion, and highlights the emergent field of organ-on-a-chip simulations. Additionally, it takes into account the application of geometries to improve the mixing of samples, as well as surface wettability modification. In conclusion, the present review summarizes the most relevant contributions of microfluidic systems and their numerical modeling to biomedical engineering.

Indexed as

microfluidicsmicrofluidics systemsmixingnumerical simulationorgan-on-a-chip

Identifiers

PMID39064385
PMCPMC11279158

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.