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May 24, 2026Journal of Optimization Theory and ApplicationsOpen Access

Optimal Multi-Drug Therapies for Antimicrobial Resistance with Horizontal Transfer

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Authors

FCFrancesca Calà CampanaGIGian Paolo IncremonaFBFranco Blanchini

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Overview

Randomized trial evaluates multi-drug therapies for antimicrobial resistance, indicating improved treatment strategies.

Key Points

  • This research aims to develop optimal multi-drug therapies to manage antimicrobial resistance and minimize bacterial population sizes.
  • Analyzed a mathematical model of interactions between the immune system and bacterial populations.
  • Formulated and solved an optimal control problem to minimize bacterial populations and antibiotic usage.
  • Utilized Pontryagin minimum principle and model predictive control for treatment design.
  • Proved the existence of an optimal solution for multi-drug therapy, which can be computed numerically.
  • Demonstrated that treatment strategies adapt based on the presence of resistance and initial conditions.
  • Validated theoretical results through computational experiments with realistic biological parameters.

Cite This Study

Campana et al. (2026) studied this question.

synapsesocial.com/papers/6a1295ae48a0ea1665671daehttps://doi.org/10.1007/s10957-026-03025-y
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1From cells to populations: multi-scale quantitative approaches to antimicrobial resistance2026
  2. 2A Mechanistic Approach to Optimize Combination Antibiotic Therapy2024
  3. 3Modeling the Effects of Over and Under Doses Antibiotic Treatment to Bacterial Resistance in Presence of Immune System2025
  4. 4Reinforcement learning informs optimal treatment strategies to limit antibiotic resistance2024 · 18 citations
  5. 5Moving From Point‐Based Analysis to Systems‐Based Modeling: Knowledge Integration to Address Antimicrobial Resistance2025