Personalized Orthodontic Force Prediction Using Inflammatory Cytokine Profiling.

Abstract

Personalized orthodontic force prediction using inflammatory cytokine profiling represents an emerging precision-based approach for optimizing orthodontic tooth movement according to individual biological responses. Conventional orthodontic force selection largely relies on standardized clinical principles and anatomical characteristics, despite substantial interindividual variation in tissue remodeling and inflammatory activity. Cytokines and related molecular mediators within gingival crevicular fluid and saliva provide minimally invasive indicators of periodontal ligament inflammation, osteoclastogenesis, and alveolar bone remodeling. Profiling biomarkers such as interleukin-1β, interleukin-6, tumor necrosis factor-α, interleukin-8, receptor activator of nuclear factor kappa-B ligand, and osteoprotegerin may therefore facilitate prediction of a patient's biological responsiveness to orthodontic forces. Integrating longitudinal cytokine measurements with clinical parameters, imaging findings, digital treatment records, and tooth movement rates could enable predictive models that estimate optimal force magnitude and activation intervals. Artificial intelligence and machine-learning techniques may further improve individualized prediction by identifying complex relationships among molecular, biological, and mechanical variables. Such an approach could potentially enhance treatment efficiency, minimize excessive inflammatory responses, reduce adverse periodontal effects, and support adaptive treatment planning. Future validation through standardized longitudinal studies is essential before cytokine-guided force optimization can become a routine component of precision orthodontic practice.