ArticleBiosensors2022
Academic User View: Organ-on-a-Chip Technology.
Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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.
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.
Who cites it
16 citing papers in PubMed.
- Biosensor applications in organ-on-a-chip platforms and disease modeling.Frontiers in bioengineering and biotechnology · 2026Review
- Potential of organ-on-a-chip in advancing synthetic extracellular matrix technology for bone tissue engineering in dentistry (Review).Biomedical reports · 2026Review
- Enterocyte Culture on a Hybrid Transwell-Inserted Gut-on-a-Chip for Liquid-Liquid and Air-Liquid Interface Conditions.ACS omega · 2025Article
- Microfluidic Systems to Mimic the Blood-Brain Barrier: from Market to Engineering Challenges and Perspectives.ACS biomaterials science & engineering · 2025Review
- Cancer-on-chip: a breakthrough organ-on-a-chip technology in cancer cell modeling.Medical & biological engineering & computing · 2025Review
- Modeling ALS with Patient-Derived iPSCs: Recent Advances and Future Potentials.Brain sciences · 2025Review
- Heart-on-a-chip: a revolutionary organ-on-chip platform for cardiovascular disease modeling.Journal of translational medicine · 2025Review
- Organoids: development and applications in disease models, drug discovery, precision medicine, and regenerative medicine.MedComm · 2024Review
- Revolutionizing Drug Discovery: The Impact of Distinct Designs and Biosensor Integration in Microfluidics-Based Organ-on-a-Chip Technology.Biosensors · 2024Review
- Pump-Less, Recirculating Organ-on-Chip (rOoC) Platform to Model the Metabolic Crosstalk between Islets and Liver.Advanced healthcare materials · 2024Article
- Contributions of diverse models of the female reproductive tract to the study of Chlamydia trachomatis-host interactions.Current opinion in microbiology · 2024Review
- Liquid plug propagation in computer-controlled microfluidic airway-on-a-chip with semi-circular microchannels.Lab on a chip · 2024Article
- Vascularization of kidney organoids: different strategies and perspectives.Frontiers in urology · 2024Review
- Review
- Boosting the Clinical Translation of Organ-on-a-Chip Technology.Bioengineering (Basel, Switzerland) · 2022Article
- Pressure-Driven Perfusion System to Control, Multiplex and Recirculate Cell Culture Medium for Organs-on-Chips.Micromachines · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Organ-on-a-Chip (OoC) systems bring together cell biology, engineering, and material science for creating systems that recapitulate the in vivo microenvironment of tissues and organs. The versatility of OoC systems enables in vitro models for studying physiological processes, drug development, and testing in both academia and industry. This paper evaluates current platforms from the academic end-user perspective, elaborating on usability, complexity, and robustness. We surveyed 187 peers in 35 countries and grouped the responses according to preliminary knowledge and the source of the OoC systems that are used. The survey clearly shows that current commercial OoC platforms provide a substantial level of robustness and usability-which is also indicated by an increasing adaptation of the pharmaceutical industry-but a lack of complexity can challenge their use as a predictive platform. Self-made systems, on the other hand, are less robust and standardized but provide the opportunity to develop customized and more complex models, which are often needed for human disease modeling. This perspective serves as a guide for researchers in the OoC field and encourages the development of next-generation OoCs.
Indexed as
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What OpenQuestion holds
Registered trials
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.