Building Optimal Three-Drug Combination Chemotherapy Regimens

Area of Science:

• Microbiology
• Pharmacology
• Mathematical Modeling

Background:

• Multidrug therapy is crucial for treating infections, particularly tuberculosis (Mycobacterium tuberculosis).
• Previous research established a mathematical method for identifying synergistic 2-drug regimens.
• An optimal method for selecting 3-drug therapies was needed.

Purpose of the Study:

• To develop and validate a mathematical approach for identifying optimal 3-drug regimens against Mycobacterium tuberculosis.
• To evaluate the efficacy of a specific 3-drug combination: pretomanid, moxifloxacin, and bedaquiline (plus its M2 metabolite).

Main Methods:

• A full factorial study design was employed using Mycobacterium tuberculosis H37Rv.
• A mathematical model was fitted to data on total bacterial burden and less-susceptible bacterial populations.
• Monte Carlo simulations were used to evaluate the 3-drug regimen, with statistical analysis including bootstrapping and confidence intervals.

Main Results:

• The combination of pretomanid and moxifloxacin showed significant bacterial kill and suppressed resistance.
• Total bacterial burden was eradicated within 3 weeks in most evaluated combinations.
• Adding bedaquiline/M2 metabolite shortened eradication time by 1 week and demonstrated near synergistic interaction.
• No resistance amplification was observed with any combination regimen.

Conclusions:

• A model-based system approach effectively evaluates 3-agent combinations for tuberculosis treatment.
• The combination of pretomanid, moxifloxacin, and bedaquiline shows promise for rapid Mycobacterium tuberculosis eradication.
• This approach can accelerate the identification of effective multidrug therapies for clinical trials.