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Shear stress optimization and smart control strategies toward AI-integrated tissue culture systems

  • Seoul National University of Science and Technology (SNUST)

Research output: Contribution to journalReview articlepeer-review

Abstract

Shear stress serves as a key physical stimulus in three-dimensional (3D) cell culture systems, regulating critical physiological processes such as cell alignment, polarity maintenance, and functional maturation. This review systematically analyses 87 peer-reviewed studies published between 2021 and 2025, focusing on the effects of shear stress across various 3D tissue culture models, including the liver, kidney, intestine, brain, heart, and vasculature. Rather than dividing organoid and organ module studies, we take an integrated view of 3D cellular systems, quantitatively and qualitatively comparing the optimal shear stress ranges and biological responses required for different organs. Our analysis reveals that while organoid-based studies have actively investigated shear stress, organ module systems with their higher structural complexity require more precise and dynamic shear regulation yet lack sufficient quantitative approaches. Furthermore, organ-specific sensitivity to shear stress is rooted in anatomical and physiological differences, which must be accounted for in the design of advanced 3D culture platforms. This review consolidates key findings on structural design parameters, organ-specific shear thresholds, and engineering strategies, while also exploring the potential integration of automation and artificial intelligence-based control frameworks. Based on these insights, we propose future directions for constructing physiologically relevant and reproducible smart bioreactor systems for regenerative medicine and artificial organ applications.

Original languageEnglish
Article number012009
JournalBiomedical Materials (Bristol)
Volume21
Issue number1
DOIs
StatePublished - 1 Feb 2026

Keywords

  • 3D cell culture
  • automation
  • organoid
  • perfusion bioreactor
  • reinforcement learning
  • shear stress
  • smart control

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