Optimization of Infectious Disease Treatment via Clinical Practice-Based Personalized Therapy and Big Data Analysis

Area of Science:

• Pharmacology and Public Health
• Infectious Disease Management
• Health Services Research

Background:

• Individualized pharmacotherapy requires considering patient-specific factors like hepatic dysfunction and CYP3A5 genotype for optimal drug exposure and infection risk.
• Patient-level optimization is insufficient for evaluating appropriate antimicrobial therapy across healthcare systems.
• Antimicrobial surveillance systems are crucial for quantifying use and establishing a foundation for stewardship.

Purpose of the Study:

• To link individualized pharmacotherapy with population-level evaluation for infectious disease treatment optimization.
• To explore how bedside clinical questions can inform surveillance infrastructure and big data analysis.
• To discuss the role of clinical pharmacists in bridging patient care with health policies and antimicrobial resistance strategies.

Main Methods:

• Review of research findings on optimizing infectious disease treatment.
• Discussion of therapeutic drug monitoring, pharmacogenomics, and pathophysiology-based dose optimization.
• Analysis of nationwide surveillance studies, healthcare databases, and big data analytics.

Main Results:

• Nationwide surveillance in Japan quantifies antimicrobial consumption and resistance patterns.
• Large healthcare databases enable evaluation of prescribing behavior, guideline adherence, and policy impacts.
• Antimicrobial stewardship can be assessed at both institutional and national levels.

Conclusions:

• Integrating patient-level data with population-level surveillance is essential for effective antimicrobial stewardship.
• Big data analysis and surveillance infrastructure can extend bedside clinical questions to inform health policies.
• Clinical pharmacists play a key role in advancing antimicrobial stewardship through evidence generation and policy contribution.