journal article·2026-01Open access

The Synergy of Artificial Intelligence and 3D Bioprinting: Unlocking New Frontiers in Precision and Tissue Fabrication

Joao Vitor Silva Robazzi, Irem Deniz Derman, Deepak Gupta, Logan Haugh, Yogendra Pratap Singh, Vaibhav Pal, Yasar Ozer Yilmaz, Suihong Liu, Andre Luis Dias, Rogerio Andrade Flauzino, Ibrahim Tarik Ozbolat

Advanced Functional Materials· Volume 36· Issue 1

Abstract

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 (NLP), and expert systems (ES), 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.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: 3D Printing in Biomedical Research · Pluripotent Stem Cells Research · Cell Image Analysis Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Engineering Science and Mechanics Department Penn State University University Park PA 16802 USA

The Huck Institutes of Life Sciences Penn State University University Park PA 16802 USA

Department of Electrical and Computer Engineering Federal Institute of Sao Paulo Sertaozinho 14169 Brazil

Department of Electrical and Computer Engineering University of Sao Paulo Sao Carlos 13566 Brazil

Department of Polymer Science and Technology Istanbul Technical University Istanbul 34469 Turkey

Biomedical Engineering Department Penn State University University Park PA 16802 USA

Department of Chemistry Penn State University University Park PA 16802 USA

Department of Nanoscience and Nanoengineering Istanbul Technical University Istanbul 34469 Turkey

Materials Research Institute Penn State University University Park PA 16802 USA

Cancer Institute Penn State University University Park PA 16802 USA

Funding

National Institute of Allergy and Infectious Diseases · National Institute of Biomedical Imaging and Bioengineering · National Institute of Dental and Craniofacial Research

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