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Updated: Jan 12, 2026

Viability of Bioprinted Cellular Constructs Using a Three Dispenser Cartesian Printer
Published on: September 22, 2015
The Synergy of Artificial Intelligence and 3D Bioprinting: Unlocking New Frontiers in Precision and Tissue
Joao Vitor Silva Robazzi1,2,3,4, I Deniz Derman1,2,5, Deepak Gupta1,2
1Engineering Science and Mechanics Department, Penn State University, University Park, PA, 16802, USA.
Abstract:
This Review examines the transformative role of artificial intelligence (AI) in 3D bioprinting, focusing on how advanced AI technologies enhance its precision, functionality, and scalability. AI, through branches, such as machine learning (ML), computer vision (CV), robotics, natural language processing and expert systems, provides critical improvements in real-time process monitoring, error correction, and optimization of bioprinting parameters. The integration of AI enables automated quality control and predictive maintenance, improving bioprinting outcomes by increasing cell viability and structural fidelity, and reducing the amount of bioink wasted. Specifically, ML algorithms are employed to predict optimal bioprinting conditions and streamline the bioprinting workflow, while deep learning enhances the ability to process complex datasets for precision tissue biofabrication. Furthermore, AI-powered robotics and CV systems ensure accurate bioink placement and facilitate the construction of complex tissues. Despite the remarkable progress, challenges remain, particularly in the areas of process monitoring, quality control, and the scalability of bioprinting systems. This Review also aims to guide scientists, engineers, and healthcare providers in understanding the complexities and potential of AI-enhanced bioprinting, fostering a deeper appreciation of its role in the future of regenerative medicine and personalized healthcare.

