Next-generation discovery: empowering organoid research with machine learning, artificial intelligence, and mathematical modeling
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Updated: Jun 28, 2026

Multiparametric Tumor Organoid Drug Screening Using Widefield Live-Cell Imaging for Bulk and Single-Organoid Analysis
Published on: December 23, 2022
Sneha Pushpa Ramesan1, Jasmitha Boovadira Poonacha1, Dilan Pathirana2
1Life and Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany; Transdisciplinary Research Area (TRA) Life and Health, University of Bonn, Bonn, Germany.
Abstract:
Organoids have rapidly matured into powerful model systems. The field is pushing organoids toward architectural sophistication and functional fidelity, with longitudinal experiments producing ever-larger and more complex datasets. As a result, computational methods have become indispensable for experimental design, data analysis, and predictive modeling, as well as for obtaining mechanistic insights. In this review, we survey recent progress at the interface of organoid research and computational approaches, discuss key challenges on both fronts, and outline future directions to maximize impact in biomedical research through convergent, synergistic efforts.
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