An evaluation of an optimal sampling strategy for meropenem in febrile neutropenics
(2005) In Journal of Clinical Pharmacology 45(7). p.832-835- Abstract
- Optimal sampling design with nonparametric population modeling offers the opportunity to determine pharma-cokinetic parameters for patients in whom blood sampling is restricted. This approach was compared to a standard individualized modeling method for meropenem pharmacokinetics in febrile neutropenic patients. The population modeling program, nonparametric approach of expectation maximization (NPEM), with a full data set was compared to a sparse data set selected by D-optimal sampling design. The authors demonstrated that the D-optimal sampling strategy, when applied to this clinical population, provided good pharmacokinetic parameter estimates along with their variability. Four individualized and optimally selected sampling time points... (More)
- Optimal sampling design with nonparametric population modeling offers the opportunity to determine pharma-cokinetic parameters for patients in whom blood sampling is restricted. This approach was compared to a standard individualized modeling method for meropenem pharmacokinetics in febrile neutropenic patients. The population modeling program, nonparametric approach of expectation maximization (NPEM), with a full data set was compared to a sparse data set selected by D-optimal sampling design. The authors demonstrated that the D-optimal sampling strategy, when applied to this clinical population, provided good pharmacokinetic parameter estimates along with their variability. Four individualized and optimally selected sampling time points provided the same parameter estimates as more intensive sampling regimens using traditional and population modeling techniques. The different modeling methods were considerably consistent, except for the estimation of CLd with sparse sampling. The findings suggest that D-optimal sparse sampling is a reasonable approach to population pharmacokinetic/pharmacodynamic studies during drug development when limited sampling is necessary. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/235669
- author
- Ariano, R E ; Zelenitsky, S A ; Nyhlén, Anna LU and Sitar, D S
- organization
- publishing date
- 2005
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- pharmacokinetics, D-optimal sampling, meropenem, febrile neutropenia
- in
- Journal of Clinical Pharmacology
- volume
- 45
- issue
- 7
- pages
- 832 - 835
- publisher
- SAGE Publications
- external identifiers
-
- pmid:15951473
- wos:000230088800010
- scopus:21044450208
- pmid:15951473
- ISSN
- 0091-2700
- DOI
- 10.1177/0091270005277937
- language
- English
- LU publication?
- yes
- additional info
- The information about affiliations in this record was updated in December 2015. The record was previously connected to the following departments: Division of Infection Medicine (SUS) (013008000)
- id
- c7b128b6-8063-4bbd-a884-52e4cc0de11a (old id 235669)
- date added to LUP
- 2016-04-01 16:14:15
- date last changed
- 2022-04-22 20:36:28
@article{c7b128b6-8063-4bbd-a884-52e4cc0de11a,
abstract = {{Optimal sampling design with nonparametric population modeling offers the opportunity to determine pharma-cokinetic parameters for patients in whom blood sampling is restricted. This approach was compared to a standard individualized modeling method for meropenem pharmacokinetics in febrile neutropenic patients. The population modeling program, nonparametric approach of expectation maximization (NPEM), with a full data set was compared to a sparse data set selected by D-optimal sampling design. The authors demonstrated that the D-optimal sampling strategy, when applied to this clinical population, provided good pharmacokinetic parameter estimates along with their variability. Four individualized and optimally selected sampling time points provided the same parameter estimates as more intensive sampling regimens using traditional and population modeling techniques. The different modeling methods were considerably consistent, except for the estimation of CLd with sparse sampling. The findings suggest that D-optimal sparse sampling is a reasonable approach to population pharmacokinetic/pharmacodynamic studies during drug development when limited sampling is necessary.}},
author = {{Ariano, R E and Zelenitsky, S A and Nyhlén, Anna and Sitar, D S}},
issn = {{0091-2700}},
keywords = {{pharmacokinetics; D-optimal sampling; meropenem; febrile neutropenia}},
language = {{eng}},
number = {{7}},
pages = {{832--835}},
publisher = {{SAGE Publications}},
series = {{Journal of Clinical Pharmacology}},
title = {{An evaluation of an optimal sampling strategy for meropenem in febrile neutropenics}},
url = {{http://dx.doi.org/10.1177/0091270005277937}},
doi = {{10.1177/0091270005277937}},
volume = {{45}},
year = {{2005}},
}