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 language | English |
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Title of host publication | Feedback Control for Personalized Medicine |
Publisher | Elsevier |
Pages | 41-65 |
Number of pages | 25 |
ISBN (Electronic) | 9780323901710 |
ISBN (Print) | 9780323906654 |
DOIs | |
Publication status | Published - 1 Jan 2022 |
Keywords
- asymptotic analysis
- drug dosing
- monotone systems
- pharmacokinetic systems
- state estimation
- state feedback
- variability
- worst-case design