The combination of bioprinting and artificial intelligence (AI) is leading in a precise medicine, advancing in tissue engineering and personalized therapies. This paper provides a comprehensive overview of next-generation bioprinting technologies enhanced by AI-based techniques, with a particular emphasis on their collaborative potential to transform healthcare industry. This review consists of fundamental bioprinting methods such as inkjet, extrusion-based, laser-assisted, and stereolithography as well as the essential role of bioinks in addressing major difficulties and critical process parameters controlling the sector. Further, AI techniques were discussed considered as an essential tool to collect data, monitor cells in real time, forecast cellular behavior, and optimize printing conditions, resulting in smarter, more accurate bioprinting systems. Its use in bioprinting structures such as smart bioprinting, digital twins, and closed-loop control systems is considered in relation to a wide range of applications, including individualized tissue and organ creation, drug screening, disease modeling, and prostheses. This review also addresses ongoing hurdles such as computing constraints, biological difficulties, and scaling concerns along with the future directions involving integration of domain knowledge, pre-trained neural networks, generative algorithms and human-machines interaction in bioprinting. • Bridging gap between bioprinting and Artificial Intelligence in healthcare industry. • Fundamentals of bioprinting technologies, their process parameters and challenges. • Role of AI in bioprinting from data handling to real-time control and optimization. • Healthcare applications span tissue engineering, drug testing, organ fabrication. • Future trends include generative AI and human machine collaborative systems.
Dhiman et al. (Sat,) studied this question.