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Abstract

Trends in Telemedicine & E-health

The Future of Organoids Engineering: Biomaterials, Mechanobiology, Personalized Therapeutics

  • Open or CloseZarif Bin Akhtar1* and Ahmed Tajbiul Rawol2

    1Department of Computing, Institute of Electrical and Electronics Engineers, USA

    2Department of Computer Science, American International University-Bangladesh, Bangladesh

    *Corresponding author:Zarif Bin Akhtar, Department of Computing, Institute of Electrical and Electronics Engineers, USA

Submission: December 11, 2025;Published: March 23, 2026

DOI: 10.31031/TTEH.2026.06.000642

ISSN: 2689-2707
Volume6 Issue 4

Abstract

Organoid engineering has emerged as a powerful platform for disease modeling, drug discovery and personalized medicine by enabling three-dimensional in-vitro systems that closely recapitulate human tissue architecture and function. This investigation critically examines recent advances in organoid bioengineering with a focused emphasis on biomaterials, mechanobiological regulation and micro engineered platforms that enhance organoid maturation, functionality and reproducibility. Particular attention is given to the role of mechanical cues, ultrasound-based stimulation and acoustofluidic technologies in directing cellular organization and mechan transduction within organoid systems. The integration of organoids with organ-on-a-chip technologies and embedded biosensors is discussed as a strategy for real-time functional monitoring and improved experimental control, addressing key limitations related to variability and scalability. Additionally, current challenges in large-scale organoid manufacturing and clinical translation are analyzed, alongside emerging solutions aimed at standardization and personalized therapeutic applications. By consolidating advances across biomaterials science, mechanobiology, and microfluidics, this review highlights how engineered organoid platforms are reshaping precision medicine and provides a structured perspective on future directions in organoidbased biomedical research..

Keywords:Artificial intelligence; Biomedical engineering; Deep learning; Machine learning; Mechanobiological engineering; Organoids engineering

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