A Branch and Bound method for the exact parameter identification of the PK/PD model for anesthetic drugs
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866910882348400640 |
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| author | Di Credico, Giulia Consolini, Luca Laurini, Mattia Locatelli, Marco Milanesi, Marco Schiavo, Michele Visioli, Antonio |
| author_facet | Di Credico, Giulia Consolini, Luca Laurini, Mattia Locatelli, Marco Milanesi, Marco Schiavo, Michele Visioli, Antonio |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_16742 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Branch and Bound method for the exact parameter identification of the PK/PD model for anesthetic drugs Di Credico, Giulia Consolini, Luca Laurini, Mattia Locatelli, Marco Milanesi, Marco Schiavo, Michele Visioli, Antonio Systems and Control 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. |
| title | A Branch and Bound method for the exact parameter identification of the PK/PD model for anesthetic drugs |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2403.16742 |