@article{Abbiati2015a,
title = {A PSE approach to patient-individualized physiologically-based pharmacokinetic modeling},
author = { Roberto Andrea Abbiati and Gaetano Lamberti and Anna Angela Barba and Mario Grassi and Davide Manca},
url = {http://www.sciencedirect.com/science/article/pii/B9780444635785500104},
doi = {10.1016/B978-0-444-63578-5.50010-4},
issn = {15707946},
year = {2015},
date = {2015-01-01},
journal = {12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering},
volume = {37},
pages = {77--84},
publisher = {Elsevier},
series = {Computer Aided Chemical Engineering},
abstract = {Pharmacokinetic modeling allows predicting the drug concentration reached in the blood as a consequence of a specific administration. When such models are based on mammalian anatomy and physiology it is possible to theoretically evaluate the drug concentration in every organ and tissue of the body. This is the case of the so-called physiologically based pharmacokinetic (PBPK) models. This paper proposes and validates a procedure to deploy PBPK models based on a simplified, although highly consistent with human anatomy and physiology, approach. The article aims at reducing the pharmacokinetic variations among subjects due to inter-individual variability, by applying a strategy to individualize some model parameters. The simulation results are validated respect to experimental data on remifentanil.},
keywords = {Complexity reduction, In silico, Lumping, Personalization, Pharmacokinetics, Physiologically-Based modeling, Remifentanil},
pubstate = {published},
tppubtype = {article}
}