Senior Director of Advanced Research Xellar Biosystems Boston, Massachusetts, United States
Abstract: The traditional drug development process, relying on two-dimensional (2D) screening and animal models before human trials, is time-consuming, costly, and often fails to predict clinical outcomes accurately. To bridge this translational gap, we have developed OC-Plex, a scalable Organ Chip (OC) platform optimized for automation and imaging-based assays. We demonstrate its applications in modeling cell-cell interaction and mechanobiology in the tumor microenvironment. We also described the establishment of a Liver Chip model for drug-induced liver injury, which achieved over 90% predictive accuracy in a validation study, surpassing the performances with 2D and animal models. Finally, we showed the feasibility of cancer precision medicine by combing a patient-derived Cancer Chip model with deep-learning imaging analysis. The integration of scalable OC technology with artificial intelligence represents a transformative approach to modernizing drug discovery, improving predictive validity, and accelerating clinical translation.
