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Establishing bioequivalence in complete and incomplete data designs using AUCs.

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Establishing bioequivalence in complete and incomplete data designs using AUCs. / Jaki, Thomas; Wolfsegger, Martin J.; Lawo, John-Philip.

In: Journal of Biopharmaceutical Statistics, Vol. 20, No. 4, 07.2010, p. 803-820.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Jaki, T, Wolfsegger, MJ & Lawo, J-P 2010, 'Establishing bioequivalence in complete and incomplete data designs using AUCs.', Journal of Biopharmaceutical Statistics, vol. 20, no. 4, pp. 803-820. https://doi.org/10.1080/10543401003618835

APA

Jaki, T., Wolfsegger, M. J., & Lawo, J-P. (2010). Establishing bioequivalence in complete and incomplete data designs using AUCs. Journal of Biopharmaceutical Statistics, 20(4), 803-820. https://doi.org/10.1080/10543401003618835

Vancouver

Jaki T, Wolfsegger MJ, Lawo J-P. Establishing bioequivalence in complete and incomplete data designs using AUCs. Journal of Biopharmaceutical Statistics. 2010 Jul;20(4):803-820. https://doi.org/10.1080/10543401003618835

Author

Jaki, Thomas ; Wolfsegger, Martin J. ; Lawo, John-Philip. / Establishing bioequivalence in complete and incomplete data designs using AUCs. In: Journal of Biopharmaceutical Statistics. 2010 ; Vol. 20, No. 4. pp. 803-820.

Bibtex

@article{eea5c6921bb941b997e76af37407b940,
title = "Establishing bioequivalence in complete and incomplete data designs using AUCs.",
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 classical complete data design where each animal is sampled for analysis at every time point is applicable for large animals only. In the case of small animals, where blood sampling is restricted, the batch design or the serial sampling design need 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 article we derive the asymptotic distribution for the ratio of two AUCs and construct different confidence intervals, which are frequently used to assess bioequivalence. The performance of these intervals is then evaluated between the different designs in a simulation study. Additionally, the sample sizes required for the different designs are compared.",
keywords = "AUC, Batch design, Bioequivalence, Complete data design, Serial sampling design, Sparse sampling",
author = "Thomas Jaki and Wolfsegger, {Martin J.} and John-Philip Lawo",
note = "The final, definitive version of this article has been published in the Journal, Journal of Biopharmaceutical Statistics, 20 (4), 2010, {\textcopyright} Informa Plc",
year = "2010",
month = jul,
doi = "10.1080/10543401003618835",
language = "English",
volume = "20",
pages = "803--820",
journal = "Journal of Biopharmaceutical Statistics",
issn = "1054-3406",
publisher = "Taylor and Francis Ltd.",
number = "4",

}

RIS

TY - JOUR

T1 - Establishing bioequivalence in complete and incomplete data designs using AUCs.

AU - Jaki, Thomas

AU - Wolfsegger, Martin J.

AU - Lawo, John-Philip

N1 - The final, definitive version of this article has been published in the Journal, Journal of Biopharmaceutical Statistics, 20 (4), 2010, © Informa Plc

PY - 2010/7

Y1 - 2010/7

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 classical complete data design where each animal is sampled for analysis at every time point is applicable for large animals only. In the case of small animals, where blood sampling is restricted, the batch design or the serial sampling design need 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 article we derive the asymptotic distribution for the ratio of two AUCs and construct different confidence intervals, which are frequently used to assess bioequivalence. The performance of these intervals is then evaluated between the different designs in a simulation study. Additionally, the sample sizes required for the different designs are compared.

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 classical complete data design where each animal is sampled for analysis at every time point is applicable for large animals only. In the case of small animals, where blood sampling is restricted, the batch design or the serial sampling design need 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 article we derive the asymptotic distribution for the ratio of two AUCs and construct different confidence intervals, which are frequently used to assess bioequivalence. The performance of these intervals is then evaluated between the different designs in a simulation study. Additionally, the sample sizes required for the different designs are compared.

KW - AUC

KW - Batch design

KW - Bioequivalence

KW - Complete data design

KW - Serial sampling design

KW - Sparse sampling

U2 - 10.1080/10543401003618835

DO - 10.1080/10543401003618835

M3 - Journal article

VL - 20

SP - 803

EP - 820

JO - Journal of Biopharmaceutical Statistics

JF - Journal of Biopharmaceutical Statistics

SN - 1054-3406

IS - 4

ER -