Background: Current periodontal treatment strategies are primarily informed by population-level data, emphasizing average patient outcomes. Adjunctive antibiotic use-typically amoxicillin combined with metronidazole-is guided by clinical markers of disease severity and progression risk. However, such broad-spectrum regimens may disrupt the oral and gut microbiota, contributing to antimicrobial resistance.

Aim: This chapter evaluates the rationale for empirical versus individualized use of antimicrobial agents in periodontal therapy.

Materials and methods: A critical review of existing literature was conducted to assess the clinical efficacy and risks of empirical protocols and to explore the potential of personalized antimicrobial strategies.

Results: Evidence from clinical trials does not consistently support superior outcomes with microbiologically or biologically guided antimicrobial therapy. The cost-effectiveness and patient benefit of such testing remain unclear. Nonetheless, variability in pathogenic profiles, microbiome dynamics, individual host responses, and pharmacological factors supports a move toward personalized therapeutic approaches. Advances in personalized medicine-utilizing genetic testing, biomarkers, and machine learning-enable integration of genomic, proteomic, and metabolomic data to inform targeted interventions, potentially improving efficacy and minimizing adverse effects.

Clinical relevance: The future of periodontal therapy is likely to integrate population-based evidence with individualized treatment planning. This hybrid model aims to enhance clinical outcomes by combining broad evidence-based guidelines with patient-specific data, reflecting a shift toward precision medicine in clinical practice.