ArticleBulletin of mathematical biology2020
Optimizing the Timing and Composition of Therapeutic Phage Cocktails: A Control-Theoretic Approach.
Article in Bulletin of mathematical biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Reassessment of Historical Clinical Trials Supports the Effectiveness of Phage Therapy.Clinical microbiology reviews · 2022Pooled it
- Sequential Phage Delivery Can Outperform Cocktails by Delaying Cross-Resistance Evolution.Viruses · 2026Article
- Newly isolatedFrontiers in microbiology · 2026Article
- Identification of dynamic models of microbial communities: A workflow addressing identifiability and modeling pitfalls.PLoS computational biology · 2025Article
- Review
- Multi-strain phage induced clearance of bacterial infections.PLoS computational biology · 2025Article
- Multi-strain phage induced clearance of bacterial infections.bioRxiv : the preprint server for biology · 2024Article
- Phages enhance both phytopathogen density control and rhizosphere microbiome suppressiveness.mBio · 2024Article
- The role of rhizosphere phages in soil health.FEMS microbiology ecology · 2024Review
- Bacteriophages: a double-edged sword in the gastrointestinal tract.Frontiers in microbiomes · 2024Review
- Phage-host-immune system dynamics in bacteriophage therapy: basic principles and mathematical models.Translational and clinical pharmacology · 2023Review
- Automating Predictive Phage Therapy Pharmacology.Antibiotics (Basel, Switzerland) · 2023Review
- Structural Identifiability and Observability of Microbial Community Models.Bioengineering (Basel, Switzerland) · 2023Article
- The dynamic interplay of bacteriophage, bacteria and the mammalian host during phage therapy.iScience · 2023Review
- Article
- Improving the Inhibitory Effect of Phages againstViruses · 2021Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
Viruses that infect bacteria, i.e., bacteriophage or 'phage,' are increasingly considered as treatment options for the control and clearance of bacterial infections, particularly as compassionate use therapy for multi-drug-resistant infections. In practice, clinical use of phage often involves the application of multiple therapeutic phage, either together or sequentially. However, the selection and timing of therapeutic phage delivery remains largely ad hoc. In this study, we evaluate principles underlying why careful application of multiple phage (i.e., a 'cocktail') might lead to therapeutic success in contrast to the failure of single-strain phage therapy to control an infection. First, we use a nonlinear dynamics model of within-host interactions to show that a combination of fast intra-host phage decay, evolution of phage resistance amongst bacteria, and/or compromised immune response might limit the effectiveness of single-strain phage therapy. To resolve these problems, we combine dynamical modeling of phage, bacteria, and host immune cell populations with control-theoretic principles (via optimal control theory) to devise evolutionarily robust phage cocktails and delivery schedules to control the bacterial populations. Our numerical results suggest that optimal administration of single-strain phage therapy may be sufficient for curative outcomes in immunocompetent patients, but may fail in immunodeficient hosts due to phage resistance. We show that optimized treatment with a two-phage cocktail that includes a counter-resistant phage can restore therapeutic efficacy in immunodeficient hosts.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.