Evidence map›Paper›PMID 40124012›Full record

ReviewACS omega2025

Revolutionizing Biomedical Research: Unveiling the Power of Microphysiological Systems with Advanced Assays, Integrated Sensor Technologies, and Real-Time Monitoring.

Anupama Samantasinghar, Naina Sunildutt, Faheem Ahmed, Fida Hussain Memon, Chulung Kang, Kyung Hyun Choi

Abstract readReview
In one paragraph

Review in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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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.

Anupama SamantasingharDepartment of Mechatronics Engineering, Jeju National University, Jeju 63243, Republic of Korea.
Naina SunilduttDepartment of Mechatronics Engineering, Jeju National University, Jeju 63243, Republic of Korea.
Faheem AhmedDepartment of Mechatronics Engineering, Jeju National University, Jeju 63243, Republic of Korea.ORCID https://orcid.org/0000-0001-8908-2599
Fida Hussain MemonDepartment of Mechatronics Engineering, Jeju National University, Jeju 63243, Republic of Korea.
Chulung KangDepartment of Mechatronics Engineering, Jeju National University, Jeju 63243, Republic of Korea.
Kyung Hyun ChoiDepartment of Mechatronics Engineering, Jeju National University, Jeju 63243, Republic of Korea.ORCID https://orcid.org/0000-0002-4503-2458

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The limitation of animal models to imitate a therapeutic response in humans is a key problem that challenges their use in fundamental research. Organ-on-a-chip (OOC) devices, also called microphysiological systems (MPS), are devices containing a lining of living cells grown under dynamic flow to recapitulate the important features of human physiology and pathophysiology with high precision. Recent advances in microfabrication and tissue engineering techniques have led to the wide adoption of OOC in next-generation experimental platforms. This review presents a comprehensive analysis of the OOC systems, categorizing them by flow types (single-pass and multipass), operational mechanisms (pumpless and pump-driven), and configurations (single-organ and multiorgan systems), along with their respective advantages and limitations. Furthermore, it explores the integration of qualitative and quantitative assay techniques, providing a comparative evaluation of systems with and without sensor integration. This review aims to fill essential knowledge gaps, driving the progress of the development of OOC systems and paving the way for breakthroughs in biomedical research, pharmaceutical innovation, and tissue engineering.

Identifiers

PMID40124012
PMCPMC11923667

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.