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Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data
Sample sizes for single-period clinical trials, including pharmacokinetic studies, are statistically determined by within-subject variability (WSV). However, it is difficult to determine WSV without replicate-designed clinical trial data, and statisticians typically estimate optimal sample sizes usi...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7913178/ https://www.ncbi.nlm.nih.gov/pubmed/33546114 http://dx.doi.org/10.3390/ph14020114 |
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author | Kang, Won-ho Lee, Jae-yeon Chae, Jung-woo Lee, Kyeong-Ryoon Baek, In-hwan Kim, Min-Soo Back, Hyun-moon Jung, Sangkeun Shaffer, Craig Savic, Rada Yun, Hwi-yeol |
author_facet | Kang, Won-ho Lee, Jae-yeon Chae, Jung-woo Lee, Kyeong-Ryoon Baek, In-hwan Kim, Min-Soo Back, Hyun-moon Jung, Sangkeun Shaffer, Craig Savic, Rada Yun, Hwi-yeol |
author_sort | Kang, Won-ho |
collection | PubMed |
description | Sample sizes for single-period clinical trials, including pharmacokinetic studies, are statistically determined by within-subject variability (WSV). However, it is difficult to determine WSV without replicate-designed clinical trial data, and statisticians typically estimate optimal sample sizes using total variability, not WSV. We have developed an efficient population-based method to predict WSV accurately with single-period clinical trial data and demonstrate method performance with eperisone. We simulated 1000 virtual pharmacokinetic clinical trial datasets based on single-period and dense sampling studies, with various study sizes and levels of WSV and interindividual variabilities (IIVs). The estimated residual variability (RV) resulting from population pharmacokinetic methods were compared with WSV values. In addition, 3 × 3 bioequivalence results of eperisone were used to evaluate method performance with a real clinical dataset. With WSV of 40% or less, regardless of IIV magnitude, RV was well approximated by WSV for sample sizes greater than 18 subjects. RV was underestimated at WSV of 50% or greater, even with datasets having low IIV and numerous subjects. Using the eperisone dataset, RV was 44% to 48%, close to the true value of 50%. In conclusion, the estimated RV accurately predicted WSV in single-period studies, validating this method for sample size estimation in clinical trials. |
format | Online Article Text |
id | pubmed-7913178 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79131782021-02-28 Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data Kang, Won-ho Lee, Jae-yeon Chae, Jung-woo Lee, Kyeong-Ryoon Baek, In-hwan Kim, Min-Soo Back, Hyun-moon Jung, Sangkeun Shaffer, Craig Savic, Rada Yun, Hwi-yeol Pharmaceuticals (Basel) Article Sample sizes for single-period clinical trials, including pharmacokinetic studies, are statistically determined by within-subject variability (WSV). However, it is difficult to determine WSV without replicate-designed clinical trial data, and statisticians typically estimate optimal sample sizes using total variability, not WSV. We have developed an efficient population-based method to predict WSV accurately with single-period clinical trial data and demonstrate method performance with eperisone. We simulated 1000 virtual pharmacokinetic clinical trial datasets based on single-period and dense sampling studies, with various study sizes and levels of WSV and interindividual variabilities (IIVs). The estimated residual variability (RV) resulting from population pharmacokinetic methods were compared with WSV values. In addition, 3 × 3 bioequivalence results of eperisone were used to evaluate method performance with a real clinical dataset. With WSV of 40% or less, regardless of IIV magnitude, RV was well approximated by WSV for sample sizes greater than 18 subjects. RV was underestimated at WSV of 50% or greater, even with datasets having low IIV and numerous subjects. Using the eperisone dataset, RV was 44% to 48%, close to the true value of 50%. In conclusion, the estimated RV accurately predicted WSV in single-period studies, validating this method for sample size estimation in clinical trials. MDPI 2021-02-03 /pmc/articles/PMC7913178/ /pubmed/33546114 http://dx.doi.org/10.3390/ph14020114 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kang, Won-ho Lee, Jae-yeon Chae, Jung-woo Lee, Kyeong-Ryoon Baek, In-hwan Kim, Min-Soo Back, Hyun-moon Jung, Sangkeun Shaffer, Craig Savic, Rada Yun, Hwi-yeol Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data |
title | Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data |
title_full | Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data |
title_fullStr | Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data |
title_full_unstemmed | Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data |
title_short | Population Pharmacokinetic Method to Predict Within-Subject Variability Using Single-Period Clinical Data |
title_sort | population pharmacokinetic method to predict within-subject variability using single-period clinical data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7913178/ https://www.ncbi.nlm.nih.gov/pubmed/33546114 http://dx.doi.org/10.3390/ph14020114 |
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