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Updated: May 11, 2026

Generation of High-Throughput Three-Dimensional Tumor Spheroids for Drug Screening
Published on: September 5, 2018
From Spheroids to Tumor-on-a-Chip for Cancer Modeling and Therapeutic Testing
Maria Veronica Lipreri1, Marilina Tamara Totaro2, Nicola Baldini1,2
1Biomedical Science, Technologies, and Nanobiotechnology Lab, IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, Italy.
Microfluidic spheroid models offer advanced 3D tumor microenvironment simulation for better anticancer drug screening. These systems improve preclinical testing accuracy, addressing the high failure rate of cancer drugs in clinical trials.
Area of Science:
- Oncology
- Biomedical Engineering
- Drug Discovery
Background:
- High failure rates of anticancer drugs in clinical trials necessitate improved preclinical models.
- Conventional 2D cultures and animal models lack the complexity to predict clinical outcomes.
- Three-dimensional (3D) systems are being developed to better emulate the human tumor microenvironment.
Purpose of the Study:
- To review recent advances in microfluidic spheroid models for cancer research.
- To highlight the potential of these models in improving preclinical drug testing.
- To discuss device design, biomaterial integration, and translational validation of these systems.
Main Methods:
- Integration of 3D spheroids with microfluidic technology.
- Precise control of microenvironmental factors (nutrients, oxygen, shear stress, pressure).
- Co-culture capabilities with stromal, immune, and endothelial cells.
Main Results:
- Microfluidic spheroid models enable investigation of drug response, angiogenesis, metastasis, and immune interactions.
- These platforms offer dynamic and physiologically relevant conditions for cancer research.
- Recent advances cover device design, biomaterials, and translational validation for carcinomas and sarcomas.
Conclusions:
- Microfluidic spheroid technology offers a promising pathway for predictive, ethical, and personalized preclinical cancer testing.
- These models bridge the gap between in vitro studies and clinical oncology.
- Challenges include technical complexity, scalability, and standardization, which require further attention.
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