Review on electrochemical sensors for anticancer drug susceptibility testing

Paula C R Corsato1, Christian O Silva2, Iris R S Ribeiro3

  • 1Brazilian Nanotechnology National Laboratory, Brazilian Center for Research in Energy and Materials, Campinas, São Paulo, 13083-970, Brazil; Institute of Chemistry, University of Campinas, Campinas, São Paulo, 13083-970, Brazil.

Analytica Chimica Acta
|January 12, 2026
PubMed

Insights

Electrochemical sensors offer a faster, real-time alternative to traditional anticancer drug susceptibility tests. These advanced biosensors monitor cellular and extracellular markers in 2D and 3D models, improving drug development and precision oncology.

Area of Science:

  • Biomedical Engineering
  • Analytical Chemistry
  • Oncology

Background:

  • Traditional anticancer drug susceptibility testing relies on time-consuming, end-point cell viability assays.
  • Existing methods lack the throughput and real-time monitoring capabilities crucial for modern drug development and precision oncology.
  • Electrochemical sensors present a promising avenue for rapid, real-time assessment of drug effects.

Purpose of the Study:

  • To critically review the principles, advantages, and disadvantages of state-of-the-art electrochemical drug screening devices.
  • To discuss advances in electrochemical sensors for monitoring cellular and extracellular markers in 2D and 3D cell models.
  • To provide an outlook on overcoming current bottlenecks and establishing new sensing paradigms for anticancer drug susceptibility testing.

Main Methods:

  • Review of electrochemical sensor operating principles for drug susceptibility testing.
  • Analysis of devices monitoring cellular markers (proliferation, adhesion, gap junctions) and extracellular markers (O2, pH, metabolites).
  • Discussion of sensor advancements utilizing nanomaterials and machine learning for 2D and 3D cell models (spheroids, organ-on-a-chip).

Main Results:

  • Electrochemical sensors enable monitoring of diverse cellular and extracellular indicators of drug response.
  • Nanomaterials and machine learning enhance sensor performance for improved drug screening.
  • 3D cell models combined with electrochemical sensing offer high-throughput, real-time, and accurate drug effect predictions.

Conclusions:

  • Electrochemical sensors provide a significant advancement over traditional methods for anticancer drug susceptibility testing.
  • Multisensor, microfluidic, and machine learning-aided devices with 3D cell models are poised to accelerate drug development.
  • These platforms can bridge the gap between research and clinical application in daily anticancer drug susceptibility testing.

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