T&R Biofab, a regenerative medicine company, announced on March 31 that it had developed a patient-specific tumor organoid by combining 3D bioprinting and artificial intelligence (AI) technology through joint research with domestic researchers.
A joint research team consisting of UNIST (Ulsan National Institute of Science and Technology), Seoul Asan Medical Center, and T&R Biofab succeeded in overcoming the limitations of existing cancer models and establishing a system that can precisely predict cancer characteristics and treatment responsiveness of individual patients. The results of this study were published in the international academic journal Advanced Science (Impact Factor 15.1).
The company explained that this research is a result that proves that the fusion of 3D bioprinting and AI technology can bring about real innovation in the field of personalized cancer treatment. It also added that it expects this research to make a significant contribution to the development of precision medicine and next-generation cancer treatment technology.
Existing patient-derived organ-like culture methods have had difficulty accurately analyzing differences in tumor characteristics between patients because they do not sufficiently reflect the complexity of the tumor microenvironment. To solve this problem, the research team developed a model that can more accurately simulate the tumor characteristics of bladder cancer and colon cancer patients using 3D bioprinting technology.
This technology is designed to more accurately mimic the cancer characteristics of each patient by arranging tumor organoids of uniform size and shape using 3D bioprinting technology and reproducing the substrate stiffness (approximately 7.5 kPa) and hypoxic environment similar to actual cancer tissue. In addition, it can accurately identify differences in tumor characteristics between patients by reflecting the expression pattern of tumor-specific proteins (CEACAM5), and can also be used to predict responsiveness to the anticancer drug 5-fluorouracil (5-FU).
The research team further developed an AI-based system that automatically classifies the patient’s cancer characteristics by analyzing tumor organoid image data generated by 3D bioprinting with a machine learning algorithm. This enables fast and accurate cancer characteristic evaluation without separate fluorescent staining or genetic analysis. The research team plans to contribute to the development of patient-tailored treatment strategies by modeling the tumor microenvironment, including immune cells and blood vessel structures, more precisely in the future.
“This technology has great significance as a personalized medical model that can analyze the cancer characteristics of individual patients more precisely and suggest optimal treatment strategies,” said Professor Kang Hyun-wook of UNIST’s Department of Biomedical Engineering, who led the study. “It is expected to be applied to a wider range of tumor research and treatment development in the future.”
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