AI-Driven Cyborg Tissue Platform for Functional Maturation of Human Stem Cell-Derived Organoids

The ability to control and monitor the functional specialization and maturation of human-induced pluripotent stem cell-derived tissues is critical for tissue engineering, regenerative medicine, pharmacology, and synthetic biology. This talk will introduce an AI-driven cyborg tissue platform that integrates tissue-like flexible electronic sensors and actuators with developing tissues to offer multimodal recording and control. First, I will discuss seamless implantation, integration, and distribution of stretchable mesh nanoelectronics with miniaturized multifunctional sensors and electrical stimulators across the entire 3D organoids through organogenesis for continuous, multiplexed sensing and actuation. Then, I will discuss the integration of single-cell spatial transcriptomics with bioelectronics as an in situ electro-sequencing platform, capable of combining spatially resolved single-cell gene expression with the functional readouts from the electronics for multimodal characterizations. Next, I will discuss the utilization of different machine learning algorithms to analyze, integrate, and interpret multimodal electrical activities, gene regulatory, and signaling networks to determine the functional maturation and specialization of the organoids. Finally, I will discuss the implementation of reinforcement learning algorithms for real-time feedback control, electrical stimulation optimization, and model refinement to improve the functional maturation of organoids. Collectively, the potential applications of this platform as a cyber-physical biological system for various human organoid systems in both in vitro and in vivo settings will be highlighted.