Biomimetic Scaffold Design for Stem Cell–Mediated Musculoskeletal and Craniofacial Regeneration

Orthopedic and craniofacial reconstruction procedures, such as anterior cruciate ligament (ACL) repair and mandibular bone reconstruction, continue to face high failure rates due to implant-related complications, including stress shielding, bioinert behavior, poor biological integration, and limited regenerative capacity. Conventional metallic and polymer-based implants often fail to actively interact with the biological environment, leading to delayed healing and revision surgeries. To address these limitations, this work presents a unified regenerative implant platform that integrates high-resolution digital light processing (DLP) 3D printing, biomimetic structural design, bioactive ceramic materials, surface modification, and stem cell–based strategies.

Patient-specific mandibular scaffolds and zirconia-based ACL interference screws were designed using biomimetic gradient and porous architectures to better replicate native bone structure and mechanical behavior. Yttria-stabilized zirconia (YSZ) and bioactive glass were incorporated into photocurable resin systems and fabricated using a high-resolution DLP printer, enabling precise control over geometry, surface features, and internal architecture. Post-fabrication surface treatments, including plasma etching and sandblasting, were employed to enhance surface chemistry and roughness. To promote biological functionality, decellularized bone marrow–derived extracellular matrix (ECM) hydrogels were prepared and used as carriers for mesenchymal stem cells (MSCs), enabling uniform cell infiltration and retention within the printed scaffolds.

Biological performance was evaluated through MSC seeding efficiency, proliferation, osteogenic marker expression (RUNX2, ALP, OCN), and mineralization. Preliminary results demonstrate the feasibility of combining ceramic-based DLP-printed implants with ECM-based, stem cell–laden hydrogels to enhance implant–tissue interaction. Overall, this work establishes a scalable and adaptable platform for stem cell–mediated musculoskeletal and craniofacial regeneration, with future efforts focused on integrating experimental outcomes with machine-learning–based analysis to develop predictive design rules for next-generation regenerative implants.