High-throughput production and AI-based screening of organoids for label-free drug development assay

Important results from the project

The project aimed to develop a high-throughput bioreactor for large-scale organoid production and a label-free imaging system for non-invasive drug screening. A large in-house imaging dataset for machine learning and AI-based classification is being prepared. These goals were successfully met, overcoming key limitations in organoid research. The project achieved TRL3, validating the technology’s feasibility, and established a pathway for personalized medicine applications using patient-derived organoids for drug testing in future.

Expected long term effects

The project successfully delivered a scalable high-throughput organoid production and developed a label-free imaging method for drug screening. These results address critical challenges in organoid research and drug development. The expected effects include faster, more cost-effective drug testing and personalized medicine applications using patient-derived organoids, paving the way for more tailored treatments in future healthcare.

Approach and implementation

The project addressed scalability and automation in organoid production by integrating a multi-well bioreactor with label-free microscopy. Implementation focused on high-throughput organoid production and non-invasive imaging. Anticipated challenges, such as tissue-specific organoid production and reproducibility, were mitigated through infrastructure planning and collaborations. This sets the foundation for creating a large organoid imaging dataset for machine learning and AI driven advance drug testing and personalized medicine.