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Updated: Jun 6, 2026

Multiparametric Tumor Organoid Drug Screening Using Widefield Live-Cell Imaging for Bulk and Single-Organoid Analysis
Published on: December 23, 2022
Label-free interferometry platform for drug response profiling of bioprinted tumor organoids at single-organoid
Bowen Wang1,2, Peyton J Tebon1,3, Thang L Nguyen1,2
1Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA.
Abstract:
Organoids have become mainstay tools for drug discovery and personalized medicine. High-throughput imaging readouts for drug screening of tumor organoids are of particular interest as organoid-level quantification of responses provides insights into heterogeneity, which is relevant for predicting therapeutic efficacy and anticipating emergence of resistance. However, screening extracellular matrix (ECM)-embedded organoids remains technically challenging. Standard methods with manual cell seeding in thick ECM constructs impede imaging efficiency, whereas bulk endpoint assays are easy to implement but fail to resolve single-organoid-level drug response data. Here we present a protocol to bioprint cells within a temperature-sensitive ECM in thin, flat, square-shaped patterns in 96-well plates to establish three-dimensional (3D) cultures for efficient, high-throughput, time-resolved quantitative phase imaging at single-organoid resolution. Quantitative phase imaging of 3D-bioprinted organoids using high-speed live cell interferometry coupled with machine learning analyses enables label-free quantification of biomass, growth kinetics and drug response profiles of thousands of individual organoids per experiment. We demonstrate that the protocol can be leveraged to automatically generate plates containing thousands of organoids for high-throughput imaging and drug screening experiments, quantify growth and drug response heterogeneity, resolve rare phenotypes and identify predictive features of drug response profiles for fundamental studies and therapeutic decision-making. This protocol can be completed in 2 weeks or less and can be adapted to organoids derived from a variety of cell sources and to alternative screening paradigms. The protocol requires familiarity with coding and experience with 3D cell culture, optical assembly and software installation.
Insights
This study introduces a novel bioprinting protocol for 3D organoid cultures, enabling high-throughput drug screening. This method efficiently quantifies individual organoid responses, improving drug discovery and personalized medicine.
Area of Science:
- Biotechnology
- Drug Discovery
- Personalized Medicine
Background:
- Organoids are crucial for drug discovery and personalized medicine.
- Screening extracellular matrix (ECM)-embedded organoids is challenging due to manual seeding and imaging inefficiencies.
- Existing methods often lack single-organoid resolution for drug response data.
Purpose of the Study:
- To present a protocol for bioprinting organoids in thin ECM patterns for high-throughput imaging.
- To enable efficient, time-resolved, quantitative phase imaging of 3D-bioprinted organoids.
- To facilitate label-free quantification of organoid growth and drug response at single-organoid resolution.
Main Methods:
- Bioprinting cells within a temperature-sensitive ECM in thin, flat patterns in 96-well plates.
- Utilizing high-speed live cell interferometry and machine learning for quantitative phase imaging.
- Automated generation of plates with thousands of organoids for screening.
Main Results:
- Enabled label-free quantification of biomass, growth kinetics, and drug response profiles for thousands of organoids.
- Demonstrated quantification of growth and drug response heterogeneity and resolution of rare phenotypes.
- Identified predictive features of drug response profiles for therapeutic decision-making.
Conclusions:
- The developed protocol facilitates high-throughput, time-resolved imaging and drug screening of 3D-bioprinted organoids.
- This approach enhances understanding of organoid heterogeneity and improves prediction of therapeutic efficacy.
- The protocol is adaptable, can be completed within two weeks, and requires expertise in 3D cell culture and coding.

