Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Estelle Chasseloup"'
Autor:
Kinjal Sanghavi, Jakob Ribbing, James A. Rogers, Mariam A. Ahmed, Mats O. Karlsson, Nick Holford, Estelle Chasseloup, Malidi Ahamadi, Kenneth G. Kowalski, Susan Cole, Essam Kerwash, Janet R. Wade, Chao Liu, Yaning Wang, Mirjam N. Trame, Hao Zhu, Justin J. Wilkins, for the ISoP Standards & Best Practices Committee
Publikováno v:
CPT: Pharmacometrics & Systems Pharmacology, Vol 13, Iss 5, Pp 710-728 (2024)
Abstract Modeling the relationships between covariates and pharmacometric model parameters is a central feature of pharmacometric analyses. The information obtained from covariate modeling may be used for dose selection, dose individualization, or th
Externí odkaz:
https://doaj.org/article/480b15b1cc5a4b0f8e7434ed8c4d630f
Autor:
Estelle Chasseloup, Mats O. Karlsson
Publikováno v:
Pharmaceutics, Vol 15, Iss 2, p 460 (2023)
Analyses of longitudinal data with non-linear mixed-effects models (NLMEM) are typically associated with high power, but sometimes at the cost of inflated type I error. Approaches to overcome this problem were published recently, such as model-averag
Externí odkaz:
https://doaj.org/article/401da06695ce4fe29d0b7dcf5a35ac26
Publikováno v:
Journal of Pharmacokinetics and Pharmacodynamics
The inclusion of covariates in population models during drug development is a key step to understanding drug variability and support dosage regimen proposal, but high correlation among covariates often complicates the identification of the true covar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ef0f0ea9ce3bceccfd8803caddbe4bd
http://europepmc.org/articles/PMC7520415
http://europepmc.org/articles/PMC7520415
Publikováno v:
Journal of Pharmacokinetics and Pharmacodynamics
The assumption of interindividual variability being unimodally distributed in nonlinear mixed effects models does not hold when the population under study displays multimodal parameter distributions. Mixture models allow the identification of paramet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24bac1e8e81535ce8affe9224a853d37
http://europepmc.org/articles/PMC6560505
http://europepmc.org/articles/PMC6560505
Publikováno v:
The AAPS Journal
Longitudinal pharmacometric models offer many advantages in the analysis of clinical trial data, but potentially inflated type I error and biased drug effect estimates, as a consequence of model misspecifications and multiple testing, are main drawba
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e2bbf5dacfab09ea3b6d824972e16c2
http://europepmc.org/articles/PMC8093168
http://europepmc.org/articles/PMC8093168
Autor:
Romain Guilhaumou, Amélie Marsot, Olivier Blin, Fabrice Michel, Olivier Paut, Estelle Chasseloup
Publikováno v:
Fundamental & Clinical Pharmacology
Fundamental & Clinical Pharmacology, Wiley, 2017, 31 (5), pp.558-566. ⟨10.1111/fcp.12291⟩
Fundamental & Clinical Pharmacology, Wiley, 2017, 31 (5), pp.558-566. ⟨10.1111/fcp.12291⟩
An external evaluation of phenobarbital population pharmacokinetic model described by Marsot et al. was performed in pediatric intensive care unit. Model evaluation is an important issue for dose adjustment. This external evaluation should allow conf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::acdcde26052c21b1ca3cc55690555023
https://doi.org/10.1111/fcp.12291
https://doi.org/10.1111/fcp.12291