ReviewLab on a chip2019
Personalised organs-on-chips: functional testing for precision medicine.
Review in Lab on a chip, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 117 papers, 1 of them a synthesis that pooled 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.
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
117 citing papers in PubMed, 1 synthesis or guideline pooled it, 266 citations in OpenAlex.
- mHealth Apps Using Behavior Change Techniques to Self-report Data: Systematic Review.JMIR mHealth and uHealth · 2022Pooled it
- Article
- 3D-Bioprinted Multifunctional Nanocomposite Scaffolds for Alveolar Bone-Periodontal Ligament-Root Cementum Regeneration: A Narrative Review.Biomimetics (Basel, Switzerland) · 2026Review
- Polyendocrine metabolic ovarian syndrome (PMOS)/polycystic ovary syndrome (PCOS): current and future trends.The Journal of clinical investigation · 2026Review
- How new approach methods are reshaping virology research.Journal of virology · 2026Review
- Label-free assessment of a microfluidic vessel-on-chip model with visible-light optical tomography reveals structural changes in vascular networks.Lab on a chip · 2026Article
- New and Emerging Research Models for Sepsis.Cells · 2026Review
- Personalized Models of Biological Barriers and Their Diseases: Recent Progress with Organs-On-Chips.Advanced biology · 2026Review
- Bridging the Gap Between Static Histology and Dynamic Organ-on-a-Chip Models.Pathophysiology : the official journal of the International Society for Pathophysiology · 2026Review
- Biomimetic electrospun scaffolds for engineered heart tissue: from design parameters to drug testing platforms.Frontiers in bioengineering and biotechnology · 2026Review
- Advances and Applications of Organ-on-a-Chip and Tissue-on-a-Chip Technology.Bioengineering (Basel, Switzerland) · 2025Review
- Microphysiological systems as an emerging in vitro approach for the evaluation of drug absorption, distribution, metabolism, and excretion and toxicity.Drug metabolism and disposition: the biological fate of chemicals · 2025Review
- Vessel-on-a-Chip to Study Vascular Endothelial Inflammation.Current protocols · 2025Article
- Microelectrode arrays cultured with in vitro neural networks for motion control tasks: encoding and decoding progress and advances.Microsystems & nanoengineering · 2025Review
- The ethical aspects of human organ-on-chip models: A mapping review.Stem cell reports · 2025Review
- Multi modal optical coherence tomography flowmetry of organ on chip devices.Scientific reports · 2025Article
- Cancer-on-a-chip for precision cancer medicine.Lab on a chip · 2025Review
- Modeling cancer-microbiome interactions in vitro: A guide to co-culture platforms.International journal of cancer · 2025Review
- Engineering in vitro vascular microsystems.Microsystems & nanoengineering · 2025Review
- Organoid, organ-on-a-chip and traditional Chinese medicine.Chinese medicine · 2025Review
57 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Organs-on-chips are microfluidic systems with controlled, dynamic microenvironments in which cultured cells exhibit functions that emulate organ-level physiology. They can in principle be 'personalised' to reflect individual physiology, for example by including blood samples, primary human tissue, and cells derived from induced pluripotent stem cell-derived cells, as well as by tuning key physico-chemical parameters of the cell culture microenvironment based on personal health data. The personalised nature of such systems, combined with physiologically relevant read-outs, provides new opportunities for person-specific assessment of drug efficacy and safety, as well as personalised strategies for disease prevention and treatment; together, this is known as 'precision medicine'. There are multiple reports of how to personalise organs-on-chips, with examples including airway-on-a-chip systems containing primary patient alveolar epithelial cells, vessels-on-chips with shapes based on personal biomedical imaging data and lung-on-a-chip systems that can be exposed to various regimes of cigarette smoking. In addition, multi-organ chip systems even allow the systematic and dynamic integration of more complex combinations of personalised cell culture parameters. Current personalised organs-on-chips have not yet been used for precision medicine as such. The major challenges that affect the implementation of personalised organs-on-chips in precision medicine are related to obtaining access to personal samples and corresponding health data, as well as to obtaining data on patient outcomes that can confirm the predictive value of personalised organs-on-chips. We argue here that involving all biomedical stakeholders from clinicians and patients to pharmaceutical companies will be integral to transition personalised organs-on-chips to precision medicine.
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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.