ABSTRACT
A major challenge for tuberculosis (TB) drug development is to prioritize promising combination regimens from a large and growing number of possibilities. This includes demonstrating individual drug contributions to the activity of higher-order combinations. A BALB/c mouse TB infection model was used to evaluate the contributions of each drug and pairwise combination in the clinically relevant Nix-TB regimen [bedaquiline-pretomanid-linezolid (BPaL)] during the first 3 weeks of treatment at human equivalent doses. The rRNA synthesis (RS) ratio, an exploratory pharmacodynamic (PD) marker of ongoing Mycobacterium tuberculosis rRNA synthesis, together with solid culture CFU counts and liquid culture time to positivity (TTP) were used as PD markers of treatment response in lung tissue; and their time-course profiles were mathematically modeled using rate equations with pharmacologically interpretable parameters. Antimicrobial interactions were quantified using Bliss independence and Isserlis formulas. Subadditive (or antagonistic) and additive effects on bacillary load, assessed by CFU and TTP, were found for bedaquiline-pretomanid and linezolid-containing pairs, respectively. In contrast, subadditive and additive effects on rRNA synthesis were found for pretomanid-linezolid and bedaquiline-containing pairs, respectively. Additionally, accurate predictions of the response to BPaL for all three PD markers were made using only the single-drug and pairwise effects together with an assumption of negligible three-way drug interactions. The results represent an experimental and PD modeling approach aimed at reducing combinatorial complexity and improving the cost-effectiveness of in vivo systems for preclinical TB regimen development.
Subject(s)
Antitubercular Agents , Diarylquinolines , Disease Models, Animal , Linezolid , Mice, Inbred BALB C , Mycobacterium tuberculosis , Animals , Antitubercular Agents/pharmacology , Antitubercular Agents/pharmacokinetics , Antitubercular Agents/therapeutic use , Linezolid/pharmacology , Linezolid/pharmacokinetics , Diarylquinolines/pharmacology , Diarylquinolines/pharmacokinetics , Mice , Mycobacterium tuberculosis/drug effects , Female , Nitroimidazoles/pharmacology , Nitroimidazoles/pharmacokinetics , Nitroimidazoles/therapeutic use , Drug Therapy, Combination , Lung/microbiology , Lung/drug effects , Tuberculosis/drug therapy , Tuberculosis/microbiology , Microbial Sensitivity Tests , Tuberculosis, Pulmonary/drug therapy , Tuberculosis, Pulmonary/microbiologyABSTRACT
A major challenge for tuberculosis (TB) drug development is to prioritize promising combination regimens from a large and growing number of possibilities. This includes demonstrating individual drug contributions to the activity of higher-order combinations. A BALB/c mouse TB infection model was used to evaluate the contributions of each drug and pairwise combination in the clinically relevant Nix-TB regimen (bedaquiline-pretomanid-linezolid [BPaL]) during the first three weeks of treatment at human equivalent doses. RS ratio, an exploratory pharmacodynamic (PD) marker of ongoing Mycobacterium tuberculosis rRNA synthesis, to-gether with solid culture CFU and liquid culture time to positivity (TTP) were used as PD markers of treatment response in lung tissue; and their time course profiles were mathematically modeled using rate equations with pharmacologically interpretable parameters. Antimicrobial interactions were quantified using Bliss independence and Isserlis formulas. Subadditive (or antagonistic) and additive effects on bacillary load, assessed by CFU and TTP, were found for bedaquiline-pretomanid and linezolid-containing pairs, respectively. In contrast, subadditive and additive effects on rRNA synthesis were found for pretomanid-linezolid and bedaquiline-containing pairs, respectively. Additionally, accurate predictions of the response to BPaL for all three PD markers were made using only the single-drug and pairwise effects together with an assumption of negligible three-way drug interactions. The results represent an experimental and PD modeling approach aimed at reducing combinatorial complexity and improving the cost-effectiveness of in vivo systems for preclinical TB regimen development.
