Functional personalization in digital manufacturing: a translational framework for patient-specific implants, arthroscopic locators, and therapeutic constructs.

Authors

Qun Li, Yi-Han Yang, Jin-Wei Chu, Xu-Yang Wang, Song-Ying Du, Hong-Gang Zhu, Huai-Yu Yang

Published in

Frontiers in bioengineering and biotechnology. Volume 14. Pages 1903071. Epub Sep 28, 2026.

Abstract

Three-dimensional printing and digital manufacturing are increasingly used to produce patient-specific implants, surgical guides, arthroscopic locators, and therapeutic constructs. Yet the field is often described through a device-centered lens, emphasizing anatomical customization, printing accuracy, and material feasibility. This framing is becoming insufficient. Patient-specific manufacturing should not be understood merely as the fabrication of individualized objects, but as a clinically executable workflow that translates imaging data into surgical action, regenerative therapy, and outcome-informed iteration. This Perspective proposes that the next stage of 3D printing in medicine depends on three conceptual shifts: from anatomical matching to functional and procedural optimization; from passive printed products to interfaces that carry digital planning into the operating room; and from isolated fabrication success to clinically validated, regulation-aware, and feedback-driven manufacturing systems. Orthopedic applications are used as a representative context, with particular attention to 3D-printed arthroscopic locators for knee arthroscopic anterior cruciate ligament reconstruction. This example illustrates how patient-specific design can move beyond open reconstruction into minimally invasive procedures, where accurate localization, reproducibility, and workflow compatibility are central. We further discuss therapeutic constructs, artificial intelligence, digital twins, point-of-care manufacturing, and translational barriers. Rather than offering another broad review of 3D printing applications, this Perspective proposes a framework for defining success in patient-specific digital manufacturing as the reliable conversion of patient data into safe, reproducible, and clinically meaningful intervention.

PMID:
42865543
Bibliographic data and abstract were imported from PubMed on 13 Oct 2026.

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