The Synergy of Artificial Intelligence and 3D Bioprinting: Unlocking New Frontiers in Precision and Tissue Fabrication
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.
Authors
- Suihong Liu (ORCID: https://orcid.org/0000-0001-5503-2980)
- İrem Deniz Derman (ORCID: https://orcid.org/0000-0001-9824-9071)
- André Luís Dias (ORCID: https://orcid.org/0000-0001-7910-562X)
- Rogério Andrade Flauzino (ORCID: https://orcid.org/0000-0003-3020-7582)
- João Vítor Silva Robazzi
- Yogendra Pratap Singh (ORCID: https://orcid.org/0000-0003-0959-0564)
- Vaibhav Pal (ORCID: https://orcid.org/0000-0001-9897-066X)
- Ibrahim Tarik Ozbolat (ORCID: https://orcid.org/0000-0001-8328-4528)
- Deepak Gupta (ORCID: https://orcid.org/0000-0003-0069-7488)
- Yasar Ozer Yilmaz (ORCID: https://orcid.org/0000-0001-8827-3860)
- Logan Haugh
Institutions
- Federal Institute of São Paulo (BR)
- Pennsylvania State University (US)
- Universidade Federal de São Carlos (BR)
- Institute of Physics (PL)
- Institute of Mathematics and Computer Science (MD)
- Istanbul Technical University (TR)
- Cukurova University (TR)
Publication Details
- Journal
- Advanced Functional Materials
- Published
- 2025-10-28
- DOI
- https://doi.org/10.1002/adfm.202509530
- Citations
- 3
- Primary Topic
- 3D Printing in Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 2.02
Funders
- National Institute of Allergy and Infectious Diseases