Design principles of collateral sensitivity-based dosing strategies.

Area of Science:

• Microbiology
• Mathematical Biology
• Pharmacology

Background:

• Antimicrobial resistance (AMR) is a growing global health threat.
• Collateral sensitivity (CS) offers a potential strategy to combat AMR by linking resistance to one drug with sensitivity to another.
• Designing effective CS-based treatment schedules remains a challenge.

Purpose of the Study:

• To investigate the impact of different treatment designs on bacterial population dynamics and resistance evolution using mathematical modeling.
• To identify key principles for designing effective CS-based antibiotic therapies.

Main Methods:

• Mathematical modeling was employed to simulate bacterial population dynamics under various treatment scenarios.
• The study analyzed the influence of pathogen- and drug-specific characteristics on resistance evolution.
• Different treatment schedules, including simultaneous and cycling therapies, were evaluated.

Main Results:

• Simultaneous and one-day cycling treatments effectively suppressed resistance when collateral sensitivity was present.
• The order of drug administration in cycling therapies critically influenced treatment efficacy.
• Reciprocal collateral sensitivity is not essential for suppressing resistance, expanding treatment possibilities.

Conclusions:

• CS-based antibiotic strategies show promise in limiting antimicrobial resistance.
• Optimizing drug administration order is crucial for effective CS cycling therapies.
• The findings provide essential guidance for developing novel treatment schedules to combat AMR.