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Updated: Jun 30, 2025
A High-throughput Compatible Assay to Evaluate Drug Efficacy against Macrophage Passaged Mycobacterium tuberculosis
Published on: March 24, 2017
Use of multiple pharmacodynamic measures to deconstruct the Nix-TB regimen in a short-course murine model of
M A Lyons1, A Obregon-Henao1, M E Ramey1
1Department of Microbiology, Immunology and Pathology, Mycobacteria Research Laboratories, Colorado State University, Fort Collins, Colorado, USA.
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.
Insights
This study evaluated drug contributions in tuberculosis (TB) treatment combinations using a mouse model and pharmacodynamic markers. Mathematical modeling accurately predicted regimen response from individual drug effects, simplifying TB drug development.
Area of Science:
- Pharmacology
- Microbiology
- Mathematical Modeling
Background:
- Drug development for tuberculosis (TB) requires efficient prioritization of combination regimens.
- Understanding individual drug contributions within complex regimens is crucial for optimizing efficacy.
- The Nix-TB regimen (bedaquiline-pretomanid-linezolid, BPaL) is a clinically relevant combination for TB treatment.
Purpose of the Study:
- To evaluate the contribution of each drug and pairwise combination within the BPaL regimen in a mouse TB model.
- To utilize pharmacodynamic (PD) markers, including rRNA synthesis ratio, CFU counts, and time to positivity (TTP), to assess treatment response.
- To develop and validate a mathematical modeling approach for predicting combination regimen activity based on single-drug and pairwise effects.
Main Methods:
- Utilized a BALB/c mouse TB infection model to test drug combinations at human equivalent doses.
- Employed rRNA synthesis (RS) ratio, solid culture CFU, and liquid culture TTP as PD markers of treatment response in lung tissue.
- Applied mathematical modeling with rate equations and quantified antimicrobial interactions using Bliss independence and Isserlis formulas.
Main Results:
- Assessed bedaquiline-pretomanid and linezolid-containing pairs showing subadditive/antagonistic and additive effects on bacillary load (CFU, TTP), respectively.
- Observed subadditive and additive effects on rRNA synthesis for pretomanid-linezolid and bedaquiline-containing pairs, respectively.
- Accurately predicted the overall BPaL regimen response for all PD markers using only single-drug and pairwise interaction data, assuming negligible three-way interactions.
Conclusions:
- Demonstrated that mathematical modeling of PD markers can predict the efficacy of complex TB drug combinations.
- Showcased a cost-effective experimental and modeling approach to reduce combinatorial complexity in preclinical TB drug development.
- Validated the utility of the rRNA synthesis ratio as an exploratory PD marker for evaluating TB drug activity in vivo.
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