Input-output approaches for personalized drug dosing of antibiotics

Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter


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
Number of pages25
ISBN (Electronic)9780323901710
ISBN (Print)9780323906654
Publication statusPublished - 1 Jan 2022


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


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