AI‐Driven Predictive Design and Functionalization of Three Dimensional‐Printed PEEK Implants with Tryptophan‐Enriched Alginate Hydrogel for Enhanced Biomimetic Surface Performance
Polyetheretherketone (PEEK) offers mechanical properties suitable for orthopedic and dental implants but experiences surface modification challenges, limited bioactivity, and suboptimal integration with host tissue. In this study, an AI‐guided design strategy is presented to predict an optimal surface functionalization recipe for 3D‐printed PEEK, enabling tailored material performance. The resulting assembly, termed TRYALPEEK, integrates sequential fused deposition modeling, coating with a sodium alginate hydrogel, and incorporation of L‐tryptophan as a model bioactive drug. The biomimetic hydrogel architecture is inspired by the structural organization of periodontal ligament fibers. Comprehensive characterization reveals that hydrogel modification significantly increases surface hydrophilicity, lowers surface roughness and friction coefficient, and enhances cytocompatibility and antibacterial performance against E. coli ‐green fluorescent protein, while supporting sustained tryptophan release. Finite element analysis further demonstrates favorable stress distribution patterns, suggesting reduced risk of localized stress concentration. Cooperatively, these findings establish TRYALPEEK as a multifunctional implant with improved surface properties and cytocompatibility. While these attributes may contribute to enhanced osseointegration and infection management consistent with prior literature, such biological effects remain to be validated through dedicated in vivo studies.
Authors
- Denisse A. Gutiérrez (ORCID: https://orcid.org/0000-0001-5421-2242)
- Wafa Benaatou (ORCID: https://orcid.org/0000-0002-8660-1557)
- Mahesh Narayan (ORCID: https://orcid.org/0000-0002-2194-5228)
- Armando Varela‐Ramírez (ORCID: https://orcid.org/0000-0002-2071-4874)
- Renato J. Aguilera (ORCID: https://orcid.org/0000-0003-3765-2793)
- Emir Esim (ORCID: https://orcid.org/0000-0003-0801-9155)
- Mohamed Noufal (ORCID: https://orcid.org/0009-0008-0123-4454)
- Filiz Yağcı (ORCID: https://orcid.org/0000-0002-1917-0822)
- Desirae M Nance
Institutions
- Hampton University (US)
- The University of Texas at El Paso (US)
- Erciyes University (TR)
Publication Details
- Journal
- Advanced Intelligent Systems
- Published
- 2025-09-23
- DOI
- https://doi.org/10.1002/aisy.202500548
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- University of Texas at El Paso
- National Institute on Minority Health and Health Disparities