Beyond the Pair: A Hypothesis on Multi-Antibiotic Synergy for Optimized Bacterial Infection Control
DOI:
https://doi.org/10.33687/ricosbiol.04.04.116Keywords:
Multi-antibiotic therapy, antimicrobial resistance (AMR), synergistic combinations, polypharmacology, dose reduction, side effect mitigation, bacterial infection, combination therapy, mode of actionAbstract
The escalating crisis of antimicrobial resistance (AMR) poses an existential threat to modern medicine, necessitating innovative strategies beyond conventional single and dual-antibiotic therapies. This review article hypothesizes that employing more than two antibiotics concurrently may offer a superior paradigm for treating bacterial infections. We propose that a multi-antibiotic cocktail, featuring agents with distinct and overlapping modes of action (MoA), can simultaneously target multiple critical bacterial pathways (e.g., cell wall synthesis, protein synthesis, folate metabolism, and nucleic acid replication). This polypharmacological approach is theorized to achieve potent synergistic effects, enabling a significant reduction in the effective dose of each individual antibiotic. Consequently, lower doses could diminish dose-dependent toxicity, reduce selective pressure for resistance mutations, and potentially lower overall treatment costs by shortening therapy duration and preventing treatment failures from resistant strains. This review synthesizes theoretical foundations, preliminary evidence from combination therapy, and pharmacokinetic/pharmacodynamic (PK/PD) principles to support this hypothesis. We critically analyze potential risks, including antagonism and toxicity, and propose a roadmap for future research using in vitro synergy models and in vivovalidation. We conclude that while challenging, the strategic use of multi-antibiotic (≥3 agents) regimens warrants rigorous investigation as a promising weapon against the rising tide of AMR.
Downloads
References
Borisy, A. A., Elliott, P. J., Hurst, N. W., Lee, M. S., Lehar, J., Price, E. R., Serbedzija, G., Zimmermann, G. R., Foley, M. A., Stockwell, B. R., & Keith, C. T. (2003). Systematic discovery of multicomponent therapeutics. Proceedings of the National Academy of Sciences, 100(13), 7977–7982. https://doi.org/10.1073/pnas.1337088100
Chou, T. C. (2006). Theoretical basis, experimental design, and computerized simulation of synergism and antagonism in drug combination studies. Pharmacological Reviews, 58(3), 621–681. https://doi.org/10.1124/pr.58.3.10
Csermely, P., Ágoston, V., & Pongor, S. (2005). The efficiency of multi-target drugs: The network approach might help drug design. Trends in Pharmacological Sciences, 26(4), 178–182. https://doi.org/10.1016/j.tips.2005.02.007
Doern, C. D. (2014). When does 2 plus 2 equal 5? A review of antimicrobial synergy testing. Journal of Clinical Microbiology, 52(12), 4124–4128. https://doi.org/10.1128/JCM.01121-14
Drusano, G. L. (2004). Antimicrobial pharmacodynamics: Critical interactions of ‘bug and drug’. Nature Reviews Microbiology, 2(4), 289–300. https://doi.org/10.1038/nrmicro862
Fischbach, M. A. (2011). Combination therapies for combating antimicrobial resistance. Current Opinion in Microbiology, 14(5), 519–523. https://doi.org/10.1016/j.mib.2011.08.003
Odds, F. C. (2003). Synergy, antagonism, and what the chequerboard puts between them. Journal of Antimicrobial Chemotherapy, 52(1), 1. https://doi.org/10.1093/jac/dkg301
Torella, J. P., Chait, R., & Kishony, R. (2010). Optimal drug synergy in antimicrobial treatments. PLoS Computational Biology, 6(6), e1000796. https://doi.org/10.1371/journal.pcbi.1000796
Tricoli, M., Nobile, C., & De Carvalho, C. C. C. R. (2017). Biofilm formation by Pseudomonas aeruginosa and its clinical implications. Future Microbiology, 12(15), 1381–1394. https://doi.org/10.2217/fmb-2017-0123
World Health Organization. (2017). Global priority list of antibiotic-resistant bacteria to guide research, discovery, and development of new antibiotics. WHO Press.
World Health Organization. (2019). WHO consolidated guidelines on drug-resistant tuberculosis treatment. WHO Press.
Yeh, P. J., Hegreness, M. J., Aiden, A. P., & Kishony, R. (2009). Drug interactions and the evolution of antibiotic resistance. Nature Reviews Microbiology, 7(6), 460–466. https://doi.org/10.1038/nrmicro2133
Zhao, X., & Drlica, K. (2001). Restricting the selection of antibiotic-resistant mutants: A general strategy derived from fluoroquinolone studies. Clinical Infectious Diseases, 33(Supplement 3), S147–S156. https://doi.org/10.1086/321841
Published
Data Availability Statement
The data supporting the conclusions of this review are derived from previously published studies, which are cited throughout the manuscript. Any aggregated datasets used for comparative analysis, if applicable, are available from the corresponding author upon reasonable request.
Issue
Section
Categories
License
Copyright (c) 2026 Abouelhag H. A.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/ by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http:// creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
