AI Strategies for Control and Monitoring in Bioprinting Processes: Accelerating the Path to Future Industrialization

Bioprinting has transformed biomedical engineering, making it possible the precise arrangement of living cells, biomaterials, and other components into complex 3D structures. This cutting-edge technology has great potential for regenerative medicine, drug testing, and tissue engineering. However, building fully functional, large-scale organs is still a significant hurdle. The success of the process depends on precise control over cell survival, material properties, and tissue organization during printing. This chapter studies how Artificial Intelligence (AI) can improve bioprinting processes. Using machine learning, computer vision, and real-time monitoring, AI improves accuracy and efficiency. For instance, Convolutional Neural Networks (CNNs) analyze images during printing to detect flaws, while adaptive algorithms adjust printing parameters to maintain structural integrity and cell health. These advancements position AI as a key driver in automating bioprinting, paving the way for its transition from experimental research to industrial-scale biomedical applications.