Selecting Electrochemical Biosensors for Muscle-on-Chip Systems: From

Introduction

A research team developing a muscle-on-chip microphysiological system sought guidance on selecting electrochemical biosensors for glucose and lactate monitoring in static, open-well cell culture — with a future transition to perfusion systems.

Their enquiry reflects a common challenge in bioengineering and organ-on-chip development:

How do you select the right sensors, electronics, and workflow to reliably measure metabolites in physiologically relevant conditions?

This article distils a real-world exchange into practical guidance for engineers and scientists working at the intersection of cell biology, biosensing, and device integration.

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The Use Case: Monitoring Metabolites in Cell Culture

The application involves:

• Skeletal muscle cell culture
• Static open-well format (initial phase)
• Planned transition to perfusion systems
• Target analytes:
  • Glucose: ~2–15 mM (physiological range ~5.5 mM)
  • Lactate: 0–15 mM

Key Technical Requirements

• Detection of low nanoamp current signals
• Ability to measure multiple analytes
• Integration with custom data pipelines (e.g. Python, LabVIEW)
• Operation in serum-containing culture media

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Recommended Starting Strategy: Begin with Glucose

A key recommendation from the response was to start with glucose sensing before progressing to lactate.

Suggested Glucose Setup

• Sensor:
  Glucose Sensor – Generation 1

• Electronics (dedicated board):
  Biosensor Single Purpose Board (Glucose)

• Calibration solutions:
  Glucose Calibration Solution Kit

• Rinse solution:
  Biosensor Rinse Solution

Why Start with Glucose?

• Typically more:
  • Stable
  • Reproducible
  • Straightforward to calibrate
• Enables teams to:
  • Validate instrumentation
  • Build data acquisition pipelines
  • Understand baseline noise and signal drift

Starting with a simpler analyte reduces integration risk and accelerates early-stage validation.

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Expanding to Lactate Measurement

Once glucose measurement is reliable, the system can be extended to include lactate sensing.

Suggested Lactate Setup

• Sensor:
  Lactate Sensor – Generation 1

• Electronics:
  Biosensor Single Purpose Board (Lactate)

• Calibration solutions:
  Lactate Calibration Solution Kit

• Rinse solution (shared):
  Biosensor Rinse Solution

Practical Insight

Compared to glucose, lactate sensing may be:

• More sensitive to:
  • Oxygen availability
  • Enzyme degradation
  • Media composition

This makes prior system validation using glucose particularly valuable before introducing additional complexity.

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Architecture Choice: Dedicated Electronics vs General Potentiostats

The original enquiry explored the use of multi-channel potentiostats with software/API integration.

However, the recommended approach focuses on:

Dedicated Single-Purpose Electronics

Instead of general-purpose potentiostats, the system uses:

• Application-specific boards per analyte
• Designed for:
  • Fixed-potential operation
  • Stable and simplified current measurement
  • Rapid deployment

Trade-Off Comparison

Approach	Advantages	Limitations
General potentiostat	High flexibility, multi-technique support	Greater complexity, integration overhead
Dedicated biosensor board	Simpler setup, robust performance	Limited configurability

For embedded and translational systems, simplicity and reproducibility are often more valuable than flexibility.

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Calibration: A Critical Part of the Workflow

The inclusion of dedicated calibration kits highlights the importance of structured calibration workflows.

Recommended Calibration Approach

1. Use standard solutions to establish:
   • Current vs concentration curves
2. Perform:
   • Initial calibration
   • Regular recalibration to track drift

Considerations for Cell Culture

• Matrix effects from:
  • Serum proteins
  • Additives such as phenol red
• Differences between:
  • PBS-based calibration
  • Culture media calibration

Best practice is to calibrate in a matrix that closely matches the experimental environment.

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Practical Integration into the Lab

Suggested Workflow

1. Install glucose sensor and electronics
2. Run calibration using the standard kit
3. Validate:
   • Signal stability
   • Noise levels
   • Data acquisition pipeline
4. Test with real culture samples
5. Monitor:
   • Signal drift
   • Biofouling effects
6. Expand to lactate sensing once stable

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Preparing for Multi-Analyte and Perfusion Systems

Although initial setups rely on separate sensors, future scaling may involve:

• Parallel sensing configurations
• Integration into microfluidic perfusion systems
• Continuous monitoring architectures

Forward Planning Considerations

• Synchronisation of data across channels
• Sensor placement within flow paths
• Strategies for biofouling mitigation

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Key Takeaways

• Begin with glucose sensing to establish a stable baseline system
• Use dedicated electronics to simplify integration and improve robustness
• Prioritise calibration and validation workflows
• Anticipate matrix effects in real biological media
• Scale incrementally towards:
  • Multi-analyte measurement
  • Perfused system integration

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Conclusion

Selecting biosensors for organ-on-chip and advanced in vitro systems is not just about choosing a sensor — it requires building a reliable, calibrated, and well-understood measurement platform.

A stepwise approach, starting with simple and validated systems, enables teams to reduce risk, accelerate development, and build confidence before moving to more complex configurations.

For teams working at the intersection of biosensing and microphysiological systems, this structured strategy provides a practical path from initial evaluation to scalable deployment.