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Updated: Apr 5, 2026

Quadruple-Checkerboard: A Modification of the Three-Dimensional Checkerboard for Studying Drug Combinations
Published on: July 24, 2021
Quantifying the impact of drug combination regimens on TB treatment efficacy and multidrug resistance probability
1Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan 10617, Republic of China.
Objectives:
TB patients' non-adherence to the multidrug treatment regimen is thought to be the main cause of the emergence of drug resistance. The purpose of this study was to quantify the impacts of two-drug combination regimens and non-adherence to these regimens on treatment efficacy and drug resistance probability.
Methods:
A drug treatment modelling strategy was developed by incorporating a pharmacokinetic/pharmacodynamic model into a bacterial population dynamic model to explore the dynamics of TB bacilli and evolution of resistance during multidrug combination therapy, with an emphasis on non-adherence. A Hill-equation-based pharmacodynamic model was used to assess the bactericidal efficacy of single drugs and to estimate drug interactions.
Results:
Non-adherence to the treatment regimen increased treatment duration by nearly 1.6- and 3.4-fold relative to compliance with treatment. Symptom-based intermittent treatment, a form of non-adherence, might lead to treatment failure and accelerated growth and evolution of resistant mutants, resulting in a dramatically higher probability of 4.17 × 10(-3) (95% CI 2.10 × 10(-4)-1.28 × 10(-2)) for the emergence of MDR TB. Overall, determination of the optimal treatment regimen depended on the different types of medication adherence.
Conclusions:
Our model not only predicts evolutionary dynamics, but also quantifies treatment efficacy. More broadly, our model provides a quantitative framework for improving treatment protocols and establishing an emergence threshold of resistance that can be used to prevent drug resistance.
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