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A theoretical framework for estimation of AUCs in complete and incomplete sampling designs.

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A theoretical framework for estimation of AUCs in complete and incomplete sampling designs. / Jaki, Thomas; Wolfsegger, Martin J.

In: Statistics in Biopharmaceutical Research, Vol. 1, No. 2, 05.2009, p. 176-184.

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Jaki, T & Wolfsegger, MJ 2009, 'A theoretical framework for estimation of AUCs in complete and incomplete sampling designs.', Statistics in Biopharmaceutical Research, vol. 1, no. 2, pp. 176-184. https://doi.org/10.1198/sbr.2009.0025

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Jaki, Thomas ; Wolfsegger, Martin J. / A theoretical framework for estimation of AUCs in complete and incomplete sampling designs. In: Statistics in Biopharmaceutical Research. 2009 ; Vol. 1, No. 2. pp. 176-184.

Bibtex

@article{a7c104d0e243463ea2a4b4e07bcfde3f,
title = "A theoretical framework for estimation of AUCs in complete and incomplete sampling designs.",
abstract = "Nonclinical in vivo animal studies have to be completed before starting clinical studies of the pharmacokinetic behavior of a drug in humans. The drug exposure in animal studies is often measured by the area under the concentration versus time curve (AUC). The classic complete data design, where each animal is sampled for analysis once per time point, is usually only applicable for large animals. In the case of rats and mice, where blood sampling is restricted, the batch design or the serial sampling design needs to be considered. In batch designs samples are taken more than once from each animal, but not at all time points. In serial sampling designs only one sample is taken from each animal. In this paper we present an estimator for the AUC from 0 to the last time point that is applicable to all three designs. The variance and asymptotic distribution of the estimator are derived and confidence intervals based upon the asymptotic results are discussed and evaluated in a simulation study. Further, we define an estimator for linear combinations of AUCs and investigate its asymptotic properties mathematically as well as in simulation.",
author = "Thomas Jaki and Wolfsegger, {Martin J.}",
year = "2009",
month = may,
doi = "10.1198/sbr.2009.0025",
language = "English",
volume = "1",
pages = "176--184",
journal = "Statistics in Biopharmaceutical Research",
issn = "1946-6315",
publisher = "Taylor and Francis Ltd.",
number = "2",

}

RIS

TY - JOUR

T1 - A theoretical framework for estimation of AUCs in complete and incomplete sampling designs.

AU - Jaki, Thomas

AU - Wolfsegger, Martin J.

PY - 2009/5

Y1 - 2009/5

N2 - Nonclinical in vivo animal studies have to be completed before starting clinical studies of the pharmacokinetic behavior of a drug in humans. The drug exposure in animal studies is often measured by the area under the concentration versus time curve (AUC). The classic complete data design, where each animal is sampled for analysis once per time point, is usually only applicable for large animals. In the case of rats and mice, where blood sampling is restricted, the batch design or the serial sampling design needs to be considered. In batch designs samples are taken more than once from each animal, but not at all time points. In serial sampling designs only one sample is taken from each animal. In this paper we present an estimator for the AUC from 0 to the last time point that is applicable to all three designs. The variance and asymptotic distribution of the estimator are derived and confidence intervals based upon the asymptotic results are discussed and evaluated in a simulation study. Further, we define an estimator for linear combinations of AUCs and investigate its asymptotic properties mathematically as well as in simulation.

AB - Nonclinical in vivo animal studies have to be completed before starting clinical studies of the pharmacokinetic behavior of a drug in humans. The drug exposure in animal studies is often measured by the area under the concentration versus time curve (AUC). The classic complete data design, where each animal is sampled for analysis once per time point, is usually only applicable for large animals. In the case of rats and mice, where blood sampling is restricted, the batch design or the serial sampling design needs to be considered. In batch designs samples are taken more than once from each animal, but not at all time points. In serial sampling designs only one sample is taken from each animal. In this paper we present an estimator for the AUC from 0 to the last time point that is applicable to all three designs. The variance and asymptotic distribution of the estimator are derived and confidence intervals based upon the asymptotic results are discussed and evaluated in a simulation study. Further, we define an estimator for linear combinations of AUCs and investigate its asymptotic properties mathematically as well as in simulation.

U2 - 10.1198/sbr.2009.0025

DO - 10.1198/sbr.2009.0025

M3 - Journal article

VL - 1

SP - 176

EP - 184

JO - Statistics in Biopharmaceutical Research

JF - Statistics in Biopharmaceutical Research

SN - 1946-6315

IS - 2

ER -