Literature DB >> 28939143

A physiologically-based model to predict individual pharmacokinetics and pharmacodynamics of remifentanil.

Sara Cascone1, Gaetano Lamberti2, Ornella Piazza3, Roberto Andrea Abbiati4, Davide Manca4.   

Abstract

Remifentanil based anesthesia is nowadays spread worldwide. This drug is characterized by a rapid onset of the analgesic effects, but also by a rapid onset of the side effects. For this reason, the knowledge of the remifentanil concentration in the human body is a key topic in anesthesiology. The aims of this work are to propose and validate a physiologically based pharmacokinetic model capable to predict both the pharmacokinetics and pharmacodynamics of remifentanil, and to take into account the inter-individual differences among the patients (such as height and body mass). The blood concentration of remifentanil has been successfully simulated and compared with experimental literature data. The pharmacodynamics, in terms of effect of remifentanil on minute ventilation and electroencephalogram, has been implemented in this model. Moreover, the remifentanil concentration in various organs and tissues is predicted, which is a significant improvement with respect to the traditional compartmental models. The availability of the model makes possible the prediction of the effects of remifentanil administration, also accounting for individual parameters.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  In silico models; PBPK models; Pharmacodynamics; Pharmacokinetics; Remifentanil

Mesh:

Substances:

Year:  2017        PMID: 28939143     DOI: 10.1016/j.ejps.2017.09.028

Source DB:  PubMed          Journal:  Eur J Pharm Sci        ISSN: 0928-0987            Impact factor:   4.384


  2 in total

1.  Computational framework for predictive PBPK-PD-Tox simulations of opioids and antidotes.

Authors:  Carrie German; Minu Pilvankar; Andrzej Przekwas
Journal:  J Pharmacokinet Pharmacodyn       Date:  2019-08-08       Impact factor: 2.745

2.  Experiments and modeling of controlled release behavior of commercial and model polymer-drug formulations using dialysis membrane method.

Authors:  Alok Ranjan; Prateek K Jha
Journal:  Drug Deliv Transl Res       Date:  2020-04       Impact factor: 4.617

  2 in total

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