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Updated: Mar 23, 2026
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An Automated Culture System for Use in Preclinical Testing of Host-Directed Therapies for Tuberculosis
Published on: August 16, 2021
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Output-driven feedback system control platform optimizes combinatorial therapy of tuberculosis using a macrophage
Aleidy Silva1, Bai-Yu Lee2, Daniel L Clemens2
1Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, CA 90095;
Summary
This study utilized feedback system control (FSC) to discover new tuberculosis (TB) drug combinations. Optimized regimens containing clofazimine showed superior efficacy, outperforming current TB treatments.
Area of Science:
- Microbiology
- Pharmacology
- Drug Discovery
Background:
- Tuberculosis (TB) is a significant global health issue requiring novel treatments to shorten therapy duration, reduce patient burden, and overcome drug resistance.
- Optimizing TB drug regimens is complex due to the vast number of potential drug-dose combinations.
- Current treatment strategies face challenges in effectively combating drug-resistant strains of Mycobacterium tuberculosis (Mtb).
Purpose of the Study:
- To identify improved drug-dose combinations for TB treatment using an innovative optimization platform.
- To explore novel therapeutic strategies for both drug-susceptible and drug-resistant TB.
- To demonstrate the utility of feedback system control (FSC) methodology in accelerating drug discovery for infectious diseases.
Main Methods:
- Employed a fluorescence-based human macrophage cell culture model infected with green fluorescent protein (GFP)-expressing Mycobacterium tuberculosis (Mtb).
- Utilized feedback system control (FSC) methodology for iterative optimization of drug-dose combinations.
- Validated identified combinations through an independent intramacrophage Mtb killing assay.
Main Results:
- Identified highly effective three- and four-drug TB treatment combinations after minimal screening and iterations.
- Optimized regimens demonstrated superior efficacy compared to the current standard TB drug regimen in vitro.
- Top-performing combinations consistently included clofazimine and excluded first-line drugs like isoniazid and rifampin.
Conclusions:
- The feedback system control (FSC) platform effectively identifies potent, previously unrecognized drug-dose combinations for TB treatment.
- Novel optimized regimens, notably excluding isoniazid and rifampin, show promise for treating multidrug- and extensively drug-resistant TB.
- This approach offers a powerful strategy for rapidly advancing TB drug discovery and development.
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