Artificial intelligence in biomaterials for oral oncology.

Journal: Biomaterials
Published Date:

Abstract

Oral cancer and oral potentially malignant disorders (OPMDs) remain a significant challenge in diagnosis and therapy, primarily due to inherent limitations in early detection, targeted treatment, and postoperative rehabilitation. Conventional diagnostic and therapeutic modalities often lack sufficient sensitivity, specificity, and effectiveness in restoring oral function. Biomaterials including nanoparticles, hydrogels, and scaffolds, offer versatile solutions by virtue of their tuneable properties, biocompatibility, and versatility in drug delivery and tissue engineering. However, their clinical translation is limited by the need for personalisation and lingering efficacy concerns. Artificial intelligence (AI) has emerged as a transformative approach to advance the design, optimisation, and application of biomaterials in oral oncology. By integrating machine learning (ML) and data-driven modelling, AI enhances diagnostic accuracy through biosensing and radiomic analysis, guides the rational design of drug carriers and dosing regimens, and facilitates computer-aided scaffold fabrication for maxillofacial reconstruction. This review summarises recent advances at the intersection of AI and biomaterials in the context of oral cancer and OPMDs, highlighting innovations in early detection, targeted therapy, and postoperative repair. It also discusses current barriers, including data quality, model generalizability, and regulatory oversight, and outlines future directions for interdisciplinary research. When properly integrated, AI-enabled biomaterials hold considerable potential to deliver more precise, efficient, and patient-tailored solutions for oral cancer management.

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