Personalized Periodontal Treatment Protocols based on Oral Microbiome AI Analysis

Abstract

Periodontal disease is a multifactorial inflammatory condition influenced by complex interactions between the oral microbiome, host immune responses, environmental factors, and individual genetic susceptibility. Conventional periodontal treatment protocols often rely on standardized clinical assessments, which may not adequately address patient-specific microbial variations and differences in therapeutic response. Recent advances in artificial intelligence (AI) and microbiome sequencing technologies have enabled the development of personalized periodontal treatment strategies based on comprehensive microbial profiling. AI-driven analytical models can identify disease-associated microbial patterns, predict disease progression, estimate treatment outcomes, and support individualized clinical decision-making by integrating microbiological, clinical, and patient-related data. These personalized protocols facilitate targeted antimicrobial therapy, optimized non-surgical and surgical interventions, risk-based maintenance schedules, and continuous monitoring through digital health technologies and biomarker assessment. The integration of AI with oral microbiome analysis also enhances diagnostic precision, supports early detection of periodontal dysbiosis, and promotes preventive care through evidence-based recommendations. Despite challenges related to data standardization, algorithm validation, ethical considerations, and clinical implementation, this emerging approach represents a significant advancement toward precision periodontics. Personalized periodontal treatment protocols based on AI-assisted oral microbiome analysis have the potential to improve therapeutic effectiveness, minimize unnecessary interventions, and achieve more predictable long-term periodontal health outcomes while supporting patient-centered dental care.