Back

3D Hybrid Bioprinting for Complex Multi-Tissue Engineering

Alizadeh, H. V.; Flores Perez, A. S.; Uno, T.; Muniz, R. S.; Kwon, S. H.; Balachandar, A.; Riley, N.; Le, C. A.; Li, J.; Zhao, P.; Lui, E.; Kim, C.; Moeinzadeh, S.; Pan, C.-C.; Bhutani, N.; Chu, C.; Kim, S.; Yang, Y. P.

2025-11-07 bioengineering
10.1101/2025.11.06.682452 bioRxiv
Show abstract

3D bioprinting has revolutionized tissue engineering, enabling intricate, physiologically relevant constructs unattainable with conventional techniques, yet it remains limited in integrating soft and rigid multifunctional components for complex multi-tissue applications. In this study, we introduce a 3D hybrid bioprinting approach implementing the Hybprinter platform, which integrates multiple 3D printing modules under optimized conditions for a continuous bioprinting process with multiple soft and hard biomaterials. This approach demonstrates robust biocompatibility and broad tissue engineering potential for modeling and therapeutic applications. The capacity to fabricate multi-hydrogel hybrid constructs is illustrated by representative examples highlighting vascularization, multifunctionality, mechanical robustness, and implant suturability. Notably, compared with commonly fabricated hydrogel-only constructs, the resulting hybrid constructs achieve over a 1000-fold increase in mechanical strength, and demonstrated enhanced osteogenic differentiation, underscoring their suitability for load-bearing musculoskeletal and orthopedic tissue engineering. Additionally, cell-laden hydrogel constructs demonstrated robust chondrogenic differentiation, highlighting the capacity for lineage-specific tissue development in vitro. Beyond these outcomes, the presented hybrid bioprinting approach integrates essential tissue engineering attributes that unites mechanical robustness and suturable capacity with multi-material integration, gradient property design, incorporation of bioactive agents, and support for multi-cell loading. This versatile platform advances complex tissue engineering and holds promise for patient specific, organ-on-demand applications.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Biofabrication
36 papers in training set
Top 0.1%
21.6%
2
Advanced Healthcare Materials
85 papers in training set
Top 0.1%
12.5%
3
Advanced Materials Technologies
29 papers in training set
Top 0.1%
5.4%
4
Advanced Functional Materials
46 papers in training set
Top 0.3%
4.4%
5
Biomaterials Science
24 papers in training set
Top 0.1%
4.3%
6
Bioactive Materials
20 papers in training set
Top 0.1%
4.0%
50% of probability mass above
7
Acta Biomaterialia
92 papers in training set
Top 0.4%
4.0%
8
Journal of Biomedical Materials Research Part A
20 papers in training set
Top 0.1%
3.2%
9
Advanced Science
286 papers in training set
Top 2%
3.2%
10
Materials Today Bio
20 papers in training set
Top 0.2%
3.2%
11
Biomaterials Advances
22 papers in training set
Top 0.2%
2.4%
12
ACS Applied Materials & Interfaces
39 papers in training set
Top 0.4%
2.1%
13
Nature Communications
5641 papers in training set
Top 42%
2.1%
14
Advanced Materials
56 papers in training set
Top 0.5%
1.9%
15
ACS Biomaterials Science & Engineering
37 papers in training set
Top 0.4%
1.9%
16
Lab on a Chip
96 papers in training set
Top 0.6%
1.7%
17
Small
78 papers in training set
Top 1%
1.5%
18
Frontiers in Bioengineering and Biotechnology
98 papers in training set
Top 1%
1.4%
19
Biomaterials
84 papers in training set
Top 1%
1.4%
20
Scientific Reports
3612 papers in training set
Top 66%
1.1%
21
Bioengineering & Translational Medicine
21 papers in training set
Top 0.4%
1.0%
22
PLOS ONE
5266 papers in training set
Top 58%
1.0%
23
Science Advances
1243 papers in training set
Top 28%
1.0%
24
ACS Applied Bio Materials
24 papers in training set
Top 0.7%
1.0%
25
Annals of Biomedical Engineering
37 papers in training set
Top 1.0%
0.9%
26
Advanced Materials Interfaces
10 papers in training set
Top 0.2%
0.8%
27
Biomacromolecules
29 papers in training set
Top 0.5%
0.8%
28
Tissue Engineering Part A
15 papers in training set
Top 0.3%
0.6%
29
Cellular and Molecular Bioengineering
22 papers in training set
Top 0.6%
0.6%