A Signal Processing Approach to Pharmacokinetic Data Analysis.
bootstrap
linear systems
pharmacokinetics
signal processing
Journal
Pharmaceutical research
ISSN: 1573-904X
Titre abrégé: Pharm Res
Pays: United States
ID NLM: 8406521
Informations de publication
Date de publication:
Apr 2021
Apr 2021
Historique:
received:
25
07
2020
accepted:
04
11
2020
pubmed:
23
3
2021
medline:
9
11
2021
entrez:
22
3
2021
Statut:
ppublish
Résumé
The connection between pharmacokinetic models and system theory has been established for a long time. In this approach, the drug concentration is seen as the output of a system whose input is the drug administered at different times. In this article we further explore this connection. We show that system theory can be used to easily accommodate any therapeutic regime, no matter its complexity, allowing the identification of the pharmacokinetic parameters by means of a non-linear regression analysis. We illustrate how to exploit the properties of linear systems to identify non-linearities in the pharmacokinetic data. We also explore the use of bootstrapping as a way to compare populations of pharmacokinetic parameters and how to handle the common situation of using multiple hypothesis tests as a way to distinguish two different populations. Finally, we demonstrate how the bootstrap values can be used to estimate the distribution of derived parameters, as can be the allometric scale factors.
Identifiants
pubmed: 33751326
doi: 10.1007/s11095-021-03000-4
pii: 10.1007/s11095-021-03000-4
doi:
Substances chimiques
Benzamides
0
Propanolamines
0
iosmin
QPG0485VLS
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
625-635Références
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