ReviewSensors (Basel, Switzerland)2011
Commercialisation of CMOS integrated circuit technology in multi-electrode arrays for neuroscience and cell-based biosensors.
Review in Sensors (Basel, Switzerland), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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
11 citing papers in PubMed.
- Large-Scale Neural Recording Technologies for Investigating Circuit Dysfunction and Functional Biomarker Discovery in Animal Models of Alzheimer's Disease.International journal of molecular sciences · 2026Review
- Customizable Fabrication of 2D and Conformal Multielectrode Arrays for 3D Printed Organotypic Bioelectronic Interfaces.Advanced healthcare materials · 2026Article
- Recent Progress and Perspectives on Neural Chip Platforms Integrating PDMS-Based Microfluidic Devices and Microelectrode Arrays.Micromachines · 2023Review
- All-Optical Reconfigurable Electronic Memory in a Graphene/SrTiOACS omega · 2022Article
- Inorganic semiconductor biointerfaces.Nature reviews. Materials · 2018Article
- Increasing cell-device adherence using cultured insect cells for receptor-based biosensors.Royal Society open science · 2018Article
- A biopotential optrode array: operation principles and simulations.Scientific reports · 2018Article
- A low-noise, modular, and versatile analog front-end intended for processing in vitro neuronal signals detected by microelectrode arrays.Computational intelligence and neuroscience · 2015Article
- Microelectronics-based biosensors dedicated to the detection of neurotransmitters: a review.Sensors (Basel, Switzerland) · 2014Review
- CMOS cell sensors for point-of-care diagnostics.Sensors (Basel, Switzerland) · 2012Review
- From understanding cellular function to novel drug discovery: the role of planar patch-clamp array chip technology.Frontiers in pharmacology · 2011Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The adaptation of standard integrated circuit (IC) technology as a transducer in cell-based biosensors in drug discovery pharmacology, neural interface systems and electrophysiology requires electrodes that are electrochemically stable, biocompatible and affordable. Unfortunately, the ubiquitous Complementary Metal Oxide Semiconductor (CMOS) IC technology does not meet the first of these requirements. For devices intended only for research, modification of CMOS by post-processing using cleanroom facilities has been achieved. However, to enable adoption of CMOS as a basis for commercial biosensors, the economies of scale of CMOS fabrication must be maintained by using only low-cost post-processing techniques. This review highlights the methodologies employed in cell-based biosensor design where CMOS-based integrated circuits (ICs) form an integral part of the transducer system. Particular emphasis will be placed on the application of multi-electrode arrays for in vitro neuroscience applications. Identifying suitable IC packaging methods presents further significant challenges when considering specific applications. The various challenges and difficulties are reviewed and some potential solutions are presented.
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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.