A Branch and Bound method for the exact parameter identification of the PK/PD model for anesthetic drugs
<|reference_start|>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. 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.<|reference_end|>
@article{di credico2024a,
    title={A Branch and Bound method for the exact parameter identification of the
  PK/PD model for anesthetic drugs},
    author={Giulia Di Credico, Luca Consolini, Mattia Laurini, Marco Locatelli,
  Marco Milanesi, Michele Schiavo, Antonio Visioli},
    journal={arXiv preprint arXiv:2403.16742},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.16742},
    primaryClass={eess.SY cs.SY}
}