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Updated: Jul 10, 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
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 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.
Insights
This study evaluated drug combinations for tuberculosis treatment. Mathematical modeling predicted the effectiveness of the bedaquiline-pretomanid-linezolid regimen, aiding future drug development.
Area of Science:
- Pharmacology
- Microbiology
- Mathematical Modeling
Background:
- Tuberculosis (TB) drug development faces challenges in prioritizing effective combination regimens.
- Understanding individual drug contributions within complex regimens is crucial for preclinical evaluation.
Conclusions:
- The study demonstrates a predictive framework for TB drug combinations using PD markers and mathematical modeling.
- This approach can streamline preclinical TB regimen development by reducing the need for extensive experimental testing of all combinations.
- The findings support a more cost-effective and efficient strategy for identifying promising TB drug regimens.
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