Researchers at the UCLA Health Jonsson Comprehensive Cancer Center have introduced a new platform that integrates 3D bioprinting, advanced imaging, and artificial intelligence to monitor cancer treatment responses. The technology enables the creation of lab-grown tumor replicas, or organoids, from patient cells, allowing scientists to test potential therapies in a highly personalized manner. By continuously tracking how these organoids react to various drugs, the system provides detailed data on tumor behavior that was previously difficult to capture at scale. The study, published in Nature Protocols on June 22 2026, was led by Dr. Michael Teitell and Alice Soragni, with postdoctoral fellow Bowen Wang as the first author.

The workflow utilizes extrusion bioprinting to embed tumor organoids in extracellular matrix constructs designed for multiwell formats. Unlike traditional laboratory methods that often rely on dyes or destructive assays—which can alter cell characteristics and restrict observation windows—this platform employs high-speed, label-free quantitative phase imaging. This method tracks biomass and growth dynamics over time without interference. The integrated system incorporates automated image reconstruction and deep learning-based segmentation to quantify drug responses at the resolution of individual organoids, capturing data across thousands of samples.

This analytical approach allows researchers to look beyond average drug responses to identify rare resistant tumor populations and observe unique response profiles. According to Dr. Michael Teitell, the platform provides a deeper understanding of tumor heterogeneity and can effectively track how specific tumor subsets react to various treatments. The research team included contributors from UCLA and Virginia Commonwealth University, with funding provided by the Air Force Office of Scientific Research, the Department of Defense, the National Science Foundation, and the National Institutes of Health. The platform aims to assist doctors in identifying effective therapies for patients, especially those facing rare or treatment-resistant cancers.

Researchers at the UCLA Health Jonsson Comprehensive Cancer Center have introduced a new platform that integrates 3D bioprinting, advanced imaging, and artificial intelligence to monitor cancer treatment responses. The technology enables the creation of lab-grown tumor replicas, or organoids, from patient cells, allowing scientists to test potential therapies in a highly personalized manner. By continuously tracking how these organoids react to various drugs, the system provides detailed data on tumor behavior that was previously difficult to capture at scale. The study, published in Nature Protocols on June 22 2026, was led by Dr. Michael Teitell and Alice Soragni, with postdoctoral fellow Bowen Wang as the first author.

The workflow utilizes extrusion bioprinting to embed tumor organoids in extracellular matrix constructs designed for multiwell formats. Unlike traditional laboratory methods that often rely on dyes or destructive assays—which can alter cell characteristics and restrict observation windows—this platform employs high-speed, label-free quantitative phase imaging. This method tracks biomass and growth dynamics over time without interference. The integrated system incorporates automated image reconstruction and deep learning-based segmentation to quantify drug responses at the resolution of individual organoids, capturing data across thousands of samples.

This analytical approach allows researchers to look beyond average drug responses to identify rare resistant tumor populations and observe unique response profiles. According to Dr. Michael Teitell, the platform provides a deeper understanding of tumor heterogeneity and can effectively track how specific tumor subsets react to various treatments. The research team included contributors from UCLA and Virginia Commonwealth University, with funding provided by the Air Force Office of Scientific Research, the Department of Defense, the National Science Foundation, and the National Institutes of Health. The platform aims to assist doctors in identifying effective therapies for patients, especially those facing rare or treatment-resistant cancers.