Format

Send to

Choose Destination
See comment in PubMed Commons below
Int J Clin Pharmacol Ther. 2012 Sep;50(9):665-77. doi: 10.5414/CP201737.

Population pharmacokinetic meta-analysis of intranasal fentanyl spray as a means to enrich pharmacokinetic information for patients with cancer breakthrough pain.

Author information

1
Nycomed: a Takeda Company, Konstanz, Germany. nele.kaessner@takeda.com

Abstract

BACKGROUND:

The development of intranasal fentanyl (INFS) aimed for a rapid treatment of breakthrough pain (BTP) in cancer patients. The pharmacokinetics (PK) of INFS was well characterized in healthy subjects, while PK investigations in cancer patients are limited.

OBJECTIVES:

The objective was to develop a population PK model for fentanyl in volunteers and patients following INFS administration, to evaluate the influence of potential covariates and to simulate the exposure of fentanyl after repeated dosing in cancer patients.

METHODS:

PK data from ten clinical trials were used for model development. The final model was validated with nonparametric bootstrap and visual predictive check. In addition, the secondary PK parameters (AUC0-tlast, Cmax, tmax) of a separate validation data set of INFS were predicted and compared to noncompartmental analysis results. Afterwards, repeated dose PK profiles in cancer patients were simulated.

RESULTS:

Plasma profiles after INFS administration were best described by a three-compartment model. Significant covariate relationships were identified for naltrexone and oxymetazoline co-treatment. Influences of body weight, BMI, sex and cancer patient as subject type were considered not to be clinically relevant. PK parameters for subpopulations of cancer patients were derived. Steady state simulations revealed that an extension from the current SmPC scenario to 6 pain episodes per day would yield similar Cmax values.

CONCLUSIONS:

A robust population PK model for INFS was developed. The model enhances the understanding of fentanyl PK after INFS dosing in cancer patients with BTP, a population for whom real-life data would be very hard to obtain.

PMID:
22784611
DOI:
10.5414/CP201737
[Indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Dustri-Verlag Dr. Karl Feistle GmbH & Co. KG
    Loading ...
    Support Center