Input-output approaches for personalized drug dosing of antibiotics

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Abstract

The aim of this chapter is to report analytical and individual-based methods for antibiotic dose selection that are based on tools from system and control theory. A brief system analysis of standard population pharmacokinetic models proves that such models are nonnegative and stable. Then, an input-output analysis leads to an open-loop control law which yields a dosing for the average patient, based on the equilibrium trajectory of the system. This approach is then incorporated into a “worst-case” analysis based on the monotony of the state trajectories with respect to the clearance (model parameter). Finally, a heuristic method of an estimated state feedback is presented. These methods were successively illustrated by numerical simulations on a model describing the pharmacokinetics of meropenem, an intravenous antibiotic for treatment of severe sepsis.

Original languageEnglish
Title of host publicationFeedback Control for Personalized Medicine
PublisherElsevier
Pages41-65
Number of pages25
ISBN (Electronic)9780323901710
ISBN (Print)9780323906654
DOIs
Publication statusPublished - 1 Jan 2022

Keywords

  • asymptotic analysis
  • drug dosing
  • monotone systems
  • pharmacokinetic systems
  • state estimation
  • state feedback
  • variability
  • worst-case design

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