The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Revisiting lab-on-a-chip technology for drug discovery
Open accessAbstract
The field of microfluidics or lab-on-a-chip technology aims to improve and extend the possibilities of bioassays, cell biology and biomedical research based on the idea of miniaturization. Microfluidic systems allow more accurate modelling of physiological situations for both fundamental research and drug development, and enable systematic high-volume testing for various aspects of drug discovery. Microfluidic systems are in development that not only model biological environments but also physically mimic biological tissues and organs; such 'organs on a chip' could have an important role in expediting early stages of drug discovery and help reduce reliance on animal testing. This Review highlights the latest lab-on-a-chip technologies for drug discovery and discusses the potential for future developments in this field.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Delivery of siRNA to the mouse brain by systemic injection of targeted exosomes
Alvarez-Erviti, L., Seow, Y., Yin, H., Betts, C., Lakhal, S., & Wood, M. J. A. (2011) · Nature Biotechnology · doi:10.1038/nbt.1807 · Cited by 4,930
Reconstituting organ-level lung functions on a chip
Huh, D., Matthews, B. D., Mammoto, A., Montoya-Zavala, M., Hsin, H. Y., & Ingber, D. E. (2010) · Science · doi:10.1126/science.1188302 · Cited by 4,250
How to improve R&D productivity: the pharmaceutical industry's grand challenge
Paul, S. M., Mytelka, D. S., Dunwiddie, C. T., Persinger, C. C., Munos, B. H., Lindborg, S. R., & Schacht, A. L. (2010) · Nature Reviews Drug Discovery · doi:10.1038/nrd3078 · Cited by 3,566
How many drug targets are there?
Overington, J. P., Al-Lazikani, B., & Hopkins, A. L. (2006) · Nature Reviews Drug Discovery · doi:10.1038/nrd2199 · Cited by 3,505
Programming cells by multiplex genome engineering and accelerated evolution
Wang, H. H., Isaacs, F. J., Carr, P. A., Sun, Z. Z., Xu, G., Forest, C. R., & Church, G. M. (2009) · Nature · doi:10.1038/nature08187 · Cited by 1,529
High-throughput 3D spheroid culture and drug testing using a 384 hanging drop array
Tung, Y.-C., Hsiao, A. Y., Allen, S. G., Torisawa, Y.-S., Ho, M., & Takayama, S. (2011) · The Analyst · doi:10.1039/c0an00609b · Cited by 969
The use of 3-d cultures for high-throughput screening: the multicellular spheroid model.
Kunz-Schughart, L. A., Freyer, J. P., Hofstaedter, F., & Ebner, R. (2004) · SLAS DISCOVERY · doi:10.1177/1087057104265040 · Cited by 797
A systems approach to measuring the binding energy landscapes of transcription factors.
Maerkl, S. J., & Quake, S. R. (2007) · Science · doi:10.1126/science.1131007 · Cited by 584
van Midwoud, P. M., Merema, M. T., Verpoorte, E., & Groothuis, G. M. M. (2010) · Lab on a Chip · doi:10.1039/c0lc00043d · Cited by 203
Baker, M. (2011) · Nature · doi:10.1038/471661a · Cited by 188
Cited by
25th Anniversary Article: Rational Design and Applications of Hydrogels in Regenerative Medicine
Annabi, N., Tamayol, A., Uquillas, J. A., Akbari, M., Bertassoni, L. E., Cha, C., Camci‐Unal, G., Dokmeci, M. R., Peppas, N. A., & Khademhosseini, A. (2014) · Advanced Materials · doi:10.1002/adma.201303233 · Cited by 1,409
Organs-on-chips at the frontiers of drug discovery
Esch, E. W., Bahinski, A., & Huh, D. (2015) · Nature Reviews Drug Discovery · doi:10.1038/nrd4539 · Cited by 1,185
Advances in Microfluidic Materials, Functions, Integration, and Applications
Nge, P. N., Rogers, C. I., & Woolley, A. T. (2013) · Chemical Reviews · doi:10.1021/cr300337x · Cited by 958
Surface acoustic wave microfluidics
Ding, X., Li, P., Lin, S.-C. S., Stratton, Z. S., Nama, N., Guo, F., Slotcavage, D., Mao, X., Shi, J., Costanzo, F., et al. (2013) · Lab on a Chip · doi:10.1039/c3lc50361e · Cited by 926
Self-citationLee, H., & Cho, D.-W. (2016) · Lab on a Chip · doi:10.1039/c6lc00450d · Cited by 363
Metadata
- Authors
- Neužil, P., Giselbrecht, S., Länge, K., Huang, T. J., & Manz, A.
- Venue
- Nature Reviews Drug Discovery
- Published
- 2012-08
- Volume
- 11
- Issue
- 8
- Pages
- 620-632
- ISSN
- 1474-1776 (ISSN-L)
- 1474-1784
- OpenAlex
- W2062409563
- Cited by
- 487
- References
- 11
- FWCI
- 4.18
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Revisiting lab-on-a-chip technology for drug discovery. https://app.cochat.ai/papers/10.1038/nrd3799
- The paper
- Neužil, P., Giselbrecht, S., Länge, K., Huang, T. J., & Manz, A. (2012). Revisiting lab-on-a-chip technology for drug discovery. Nature Reviews Drug Discovery. https://doi.org/10.1038/nrd3799
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
