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Updated: Jun 26, 2026

Multiplex Cytokine Profiling of Stimulated Mouse Splenocytes Using a Cytometric Bead-based Immunoassay Platform
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Transforming cytokine diagnostics: AI, multiplexing, and point-of-care biosensing technologies.

Kutay Icoz1, Zehra Tas2, Fawaz Azizieh3

  • 1College of Engineering and Energy, Abdullah Al Salem University, Khaldiya, Kuwait. kutay.icoz@aasu.edu.kw.

Mikrochimica Acta
|November 1, 2025
PubMed
Summary

New biosensor technology combines artificial intelligence (AI) with multiplexed cytokine detection for rapid point-of-care (POC) diagnostics. These AI-enabled systems offer faster, more sensitive immune monitoring, improving clinical decisions and precision medicine.

Keywords:
Artificial intelligenceBiosensorsCytokinesMultiplexingPoint-of-care diagnostics

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Area of Science:

  • Biomedical Engineering
  • Immunology
  • Artificial Intelligence

Background:

  • Cytokines are crucial immune biomarkers for diseases like cancer and infections.
  • Traditional cytokine detection methods are slow and lack portability for clinical use.
  • Point-of-care (POC) biosensors offer rapid, decentralized cytokine detection.

Purpose of the Study:

  • To review the integration of multiplexed biosensing and AI for cytokine diagnostics.
  • To highlight advancements in POC platforms for cytokine detection.
  • To discuss the potential of AI in enhancing biosensor performance and clinical utility.

Main Methods:

  • Review of literature on traditional and advanced cytokine detection platforms.
  • Summary of emerging review articles on cytokine biosensing in various diseases.
  • Examination of experimental studies on POC-compatible multiplexed cytokine detection.
  • Focus on next-generation biosensors integrating machine learning (ML) algorithms.

Main Results:

  • AI-enabled multiplex POC platforms achieve high sensitivity (0.01-100 pg/mL) and rapid results (5-30 min).
  • These systems use small sample volumes (1-50 µL) and offer wider dynamic ranges.
  • AI enhances biosensor performance with predictive outputs, uncertainty estimates, and drift monitoring.
  • ML algorithms like CNNs and decision-tree models enable autonomous signal processing.

Conclusions:

  • The convergence of multiplexed biosensing and AI is transforming cytokine diagnostics.
  • POC biosensors with AI offer faster, more actionable immune monitoring.
  • These technologies hold significant potential for precision medicine and global health.
  • Challenges in validation and explainability require further research.