Generation of 3D Tumor Spheroids for Drug Evaluation Studies
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Updated: Aug 7, 2025
Generation of 3D Tumor Spheroids for Drug Evaluation Studies
Published on: February 24, 2023
Wei Hou1, Zilin Zhang2, Jing Zhang2
1Department of Oncology, School of Medicine, Southeast University; State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University.
Abstract:
In recent decades, in addition to monolayer-cultured cells, three-dimensional tumor spheroids have been developed as a potentially powerful tool for the evaluation of anticancer drugs. However, the conventional culture methods lack the ability to manipulate the tumor spheroids in a homogeneous manner at the three-dimensional level. To address this limitation, in this paper, we present a convenient and effective method of constructing average-sized tumor spheroids. Additionally, we describe a method of image-based analysis using artificial intelligence-based analysis software that can scan the whole plate and obtain data on three-dimensional spheroids. Several parameters were studied. By using a standard method of tumor spheroid construction and a high-throughput imaging and analysis system, the effectiveness and accuracy of drug tests performed on three-dimensional spheroids can be dramatically increased.
Insights
This study introduces a novel method for creating uniform three-dimensional tumor spheroids and analyzing them with AI. This advancement enhances the accuracy and efficiency of anticancer drug testing.
Area of Science:
- Oncology
- Biotechnology
- Drug Discovery
Background:
- Three-dimensional tumor spheroids are valuable for anticancer drug evaluation.
- Conventional methods struggle with homogeneous manipulation of 3D tumor spheroids.
Purpose of the Study:
- To present a method for constructing average-sized tumor spheroids.
- To introduce an AI-based image analysis system for 3D spheroid data acquisition.
Main Methods:
- Development of a standardized tumor spheroid construction technique.
- Implementation of a high-throughput imaging and AI-based analysis system.
- Evaluation of spheroid parameters using the developed system.
Main Results:
- Successful construction of homogeneous, average-sized tumor spheroids.
- Efficient data acquisition from 3D spheroids across entire plates.
- Demonstrated increase in the effectiveness and accuracy of drug tests.
Conclusions:
- The developed method offers a convenient and effective approach to 3D tumor spheroid construction.
- AI-powered image analysis significantly improves high-throughput drug screening.
- This integrated system enhances the reliability of anticancer drug efficacy studies.
