Biocompatible hydrogels with model-informed prediction on tunable mechanics for UV-free in-situ 3D printing
• Enzymatically crosslinked composite hydrogels provide tunable mechanical properties and tissue adhesivity for UV-free in-situ 3D printing. • An integrated method with model-informed prediction and rheological analysis was established to predict mechanical properties and 3D printability of hydrogels. • Biocompatible hydrogels of gelatin and hyaluronic acid with transglutaminase showed desirable cytocompatibility with stem cells. This article reports a composite hydrogel system composed of biocompatible gelatin (Gel) and hyaluronic acid (HyA) for UV-free in-situ 3D printing using an enzyme, transglutaminase (TG), for crosslinking. We tailored the composition of Gel and TG in the Gel-HyA-TG hydrogels to achieve tunable mechanical properties for extrusion-based 3D printing without the need for UV-crosslinking. We identified the printability window for the Gel-HyA-TG system at physiological temperature (37 °C), which aligns with the time window when its elastic modulus G′(t) falls between 70 and 258 Pa. Moreover, we developed a mathematical model that combines enzyme kinetics and macromolecular crowding effects, to inform rapid selection of Gel-HyA-TG composition with desired rheological/mechanical properties. We can predict mechanical properties and 3D printability for a given xGel-yHyA-zTG composition (x = 4–20 w/v %, y = 1 w/v%; z = 5–50 U/g), using an integrated method that combines the model-informed prediction, rheological testing, and the experimentally established printability window. This method enabled rapid tuning of the Gel-HyA-TG hydrogel composition toward desired properties for 3D printing. The in situ 3D printability of the Gel-HyA-TG hydrogel ink with intrinsic tissue-adhesivity was confirmed using a porcine brain defect ex-vivo . In vitro cell studies confirmed the cytocompatibility of Gel-HyA-TG hydrogels.
Authors
- Ruoyu Sheng
- Huinan Liu (ORCID: https://orcid.org/0000-0001-9366-6204)
- Nadia Carlesso (ORCID: https://orcid.org/0000-0002-5131-9885)
- Margarita Gutova (ORCID: https://orcid.org/0000-0002-7094-626X)
- Beomhyeok Lee
- Jinrui Tan (ORCID: https://orcid.org/0009-0001-4484-0744)
- Ryan Johnson
- Ime Stevenson
- Changlu Xu
- Yiqing Chen
- Natalia Garcia
- Esmeralda Ruiz-Garcia
Institutions
- University of California, Riverside (US)
- City Of Hope National Medical Center (US)
Publication Details
- Journal
- Materials & Design
- Published
- 2026-03-08
- DOI
- https://doi.org/10.1016/j.matdes.2026.115806
- Primary Topic
- 3D Printing in Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00