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Microfluidics Integration into Low-Noise Multi-Electrode Arrays.

Mafalda Ribeiro1,2, Pamela Ali2, Benjamin Metcalfe2

  • 1Centre for Accountable, Responsible, and Transparent AI (ART-AI), Department of Computer Science, University of Bath, Bath BA2 7AY, UK.

Micromachines
|July 2, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a dynamic microfluidic multi-electrode array (MEA) for Organ-on-Chip systems. This advancement enables more accurate, long-term cell recordings by ensuring consistent solution transfer and minimizing background noise.

Keywords:
Brain-on-ChipMEAOrgan-on-Chipbrain cellselectrical recordingsmicrofluidics

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Area of Science:

  • Biomedical Engineering
  • Microfluidics
  • Electrophysiology

Background:

  • Organ-on-Chip (OOC) technology utilizes microchips with cultured cells/tissues to mimic organ functions for drug development.
  • Microfluidic integration enhances OOC systems by replicating in vivo microenvironments for improved predictive power.
  • Current static (no-flow) systems have limitations in replicating dynamic physiological conditions.

Purpose of the Study:

  • To transition from static to dynamic multi-electrode arrays (MEAs) in Organ-on-Chip systems.
  • To develop a microfluidic system ensuring continuous and homogeneous electrolyte transfer for improved cell culture conditions.
  • To characterize the electrical performance of the dynamic MEA under various flow conditions.

Main Methods:

  • Design, simulation, and fabrication of a microfluidic system integrated with a multi-electrode array.
  • Electrical characterization of the microfluidic MEA under static and continuous flow conditions.
  • Assessment of background noise levels at a flow rate of 80 µL/min.

Main Results:

  • Successful transition from static to dynamic microfluidic MEA.
  • Demonstrated continuous and homogeneous electrolyte solution transfer across the measurement chamber.
  • Achieved minimal background disturbance with noise below 30 µVpp across tested flow rates.

Conclusions:

  • The developed microfluidic MEA enhances Organ-on-Chip systems by enabling more accurate and long-term electrophysiological recordings.
  • This dynamic system overcomes limitations of static setups, offering a more physiologically relevant microenvironment.
  • The technology paves the way for improved drug development and disease modeling using OOC platforms.