A Branch and Bound method for the exact parameter identification of the PK/PD model for anesthetic drugs

We address the problem of parameter identification for the standard pharmacokinetic/pharmacodynamic (PK/PD) model for anesthetic drugs. Our main contribution is the development of a global optimization method that guarantees finding the parameters that minimize the one-step ahead prediction error. T...

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Bibliographic Details
Published in:arXiv.org 2024-03
Main Authors: Giulia Di Credico, Consolini, Luca, Laurini, Mattia, Locatelli, Marco, Milanesi, Marco, Schiavo, Michele, Visioli, Antonio
Format: Article
Language:English
Subjects:
Algorithms
Branch and bound methods
Convexity
Drugs
Global optimization
Mathematical models
Parameter identification
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Summary:We address the problem of parameter identification for the standard pharmacokinetic/pharmacodynamic (PK/PD) model for anesthetic drugs. Our main contribution is the development of a global optimization method that guarantees finding the parameters that minimize the one-step ahead prediction error. The method is based on a branch-and-bound algorithm, that can be applied to solve a more general class of nonlinear regression problems. We present some simulation results, based on a dataset of twelve patients. In these simulations, we are always able to identify the exact parameters, despite the non-convexity of the overall identification problem.
ISSN:2331-8422