Optimizing Antimicrobial Therapy by Integrating Multi-Omics With Pharmacokinetic/Pharmacodynamic Models and Precision...

Area of Science:

• Pharmacology and Microbiology
• Infectious Diseases
• Mathematical Modeling in Medicine

Background:

• The rise of multi-drug resistant (MDR) pathogens necessitates optimized antibiotic strategies.
• Antibiotic therapy success is complex, influenced by patient, drug, and pathogen factors.
• Individual patient variability in drug response requires tailored dosing approaches.

Purpose of the Study:

• To review strategies for optimizing antimicrobial therapy in the face of antimicrobial resistance.
• To highlight the role of mathematical modeling in precision antimicrobial chemotherapy.
• To discuss the importance of personalized dosing for antibiotics, especially those with a narrow therapeutic index.

Main Methods:

• Review of mathematical modeling approaches: mechanism-based PK/PD, systems-based models, quantitative systems pharmacology (QSP), and population PK models.
• Discussion of model-informed precision dosing (MIPD) applications.
• Analysis of factors influencing antibiotic treatment success and failure.

Main Results:

• Quantitative systems pharmacology (QSP) shows potential for precision antimicrobial chemotherapy.
• Population PK models are utilized in model-informed precision dosing (MIPD).
• Tailored dosing is crucial to avoid therapeutic failure and toxicity, particularly for antibiotics with a narrow therapeutic index.

Conclusions:

• Optimizing antibiotic therapy through precision dosing is essential for managing infectious diseases caused by MDR pathogens.
• Mathematical modeling provides powerful tools for developing personalized antimicrobial treatment regimens.
• Personalized therapy, guided by modeling, can improve patient outcomes and mitigate risks associated with antibiotic use.