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Optimal Designs for Non-Compartmental Analysis of Pharmacokinetic Studies

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Optimal Designs for Non-Compartmental Analysis of Pharmacokinetic Studies. / Barnett, Helen Yvette; Geys, Helena; Jacobs, Tom; Jaki, Thomas Friedrich.

In: Statistics in Biopharmaceutical Research, Vol. 10, No. 4, 2018, p. 255-263.

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Barnett, HY, Geys, H, Jacobs, T & Jaki, TF 2018, 'Optimal Designs for Non-Compartmental Analysis of Pharmacokinetic Studies', Statistics in Biopharmaceutical Research, vol. 10, no. 4, pp. 255-263. https://doi.org/10.1080/19466315.2018.1458647

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Barnett, Helen Yvette ; Geys, Helena ; Jacobs, Tom ; Jaki, Thomas Friedrich. / Optimal Designs for Non-Compartmental Analysis of Pharmacokinetic Studies. In: Statistics in Biopharmaceutical Research. 2018 ; Vol. 10, No. 4. pp. 255-263.

Bibtex

@article{046ee3c51ba0425992c6bb8efffd9cee,
title = "Optimal Designs for Non-Compartmental Analysis of Pharmacokinetic Studies",
abstract = "In traditional toxicology trials, pharmacokinetics (PK) is investigated in the satellite group of animals, and the pharmacodynamics (PD) is investigated in the study group of animals. The new blood sampling method of microsampling opens up the opportunity to investigate both PK and PD in the same animals. To avoid excessive burden on the animals from the required blood sampling, sparse sampling schemes are typically utilized. Motivated by this application, this paper introduces a procedure to choose an optimal sparse sampling scheme and sampling time points using non-compartmental methods but which can be applied to further settings beyond this. We discuss how robust designs can be obtained and we apply and evaluate the approach to a range of scenarios to give an example of how it may be implemented. The results are compared to optimal designs for model based PK.",
keywords = "Microsampling, Minimax, Sparse Sampling, Optimal Designs, Pharmacokinetic (PK) Sampling, Non-compartmental Analysis",
author = "Barnett, {Helen Yvette} and Helena Geys and Tom Jacobs and Jaki, {Thomas Friedrich}",
year = "2018",
doi = "10.1080/19466315.2018.1458647",
language = "English",
volume = "10",
pages = "255--263",
journal = "Statistics in Biopharmaceutical Research",
issn = "1946-6315",
publisher = "Taylor and Francis Ltd.",
number = "4",

}

RIS

TY - JOUR

T1 - Optimal Designs for Non-Compartmental Analysis of Pharmacokinetic Studies

AU - Barnett, Helen Yvette

AU - Geys, Helena

AU - Jacobs, Tom

AU - Jaki, Thomas Friedrich

PY - 2018

Y1 - 2018

N2 - In traditional toxicology trials, pharmacokinetics (PK) is investigated in the satellite group of animals, and the pharmacodynamics (PD) is investigated in the study group of animals. The new blood sampling method of microsampling opens up the opportunity to investigate both PK and PD in the same animals. To avoid excessive burden on the animals from the required blood sampling, sparse sampling schemes are typically utilized. Motivated by this application, this paper introduces a procedure to choose an optimal sparse sampling scheme and sampling time points using non-compartmental methods but which can be applied to further settings beyond this. We discuss how robust designs can be obtained and we apply and evaluate the approach to a range of scenarios to give an example of how it may be implemented. The results are compared to optimal designs for model based PK.

AB - In traditional toxicology trials, pharmacokinetics (PK) is investigated in the satellite group of animals, and the pharmacodynamics (PD) is investigated in the study group of animals. The new blood sampling method of microsampling opens up the opportunity to investigate both PK and PD in the same animals. To avoid excessive burden on the animals from the required blood sampling, sparse sampling schemes are typically utilized. Motivated by this application, this paper introduces a procedure to choose an optimal sparse sampling scheme and sampling time points using non-compartmental methods but which can be applied to further settings beyond this. We discuss how robust designs can be obtained and we apply and evaluate the approach to a range of scenarios to give an example of how it may be implemented. The results are compared to optimal designs for model based PK.

KW - Microsampling

KW - Minimax

KW - Sparse Sampling

KW - Optimal Designs

KW - Pharmacokinetic (PK) Sampling

KW - Non-compartmental Analysis

U2 - 10.1080/19466315.2018.1458647

DO - 10.1080/19466315.2018.1458647

M3 - Journal article

VL - 10

SP - 255

EP - 263

JO - Statistics in Biopharmaceutical Research

JF - Statistics in Biopharmaceutical Research

SN - 1946-6315

IS - 4

ER -