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Robust and Efficient Assessment of Potency (REAP) as a quantitative tool for dose-response curve estimation

The median-effect equation has been widely used to describe the dose-response relationship and identify compounds that activate or inhibit specific disease targets in contemporary drug discovery. However, the experimental data often contain extreme responses, which may significantly impair the estim...

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Autores principales: Zhou, Shouhao, Liu, Xinyi, Fang, Xinying, Chinchilli, Vernon M, Wang, Michael, Wang, Hong-Gang, Dokholyan, Nikolay V, Shen, Chan, Lee, J Jack
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9348845/
https://www.ncbi.nlm.nih.gov/pubmed/35921131
http://dx.doi.org/10.7554/eLife.78634
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author Zhou, Shouhao
Liu, Xinyi
Fang, Xinying
Chinchilli, Vernon M
Wang, Michael
Wang, Hong-Gang
Dokholyan, Nikolay V
Shen, Chan
Lee, J Jack
author_facet Zhou, Shouhao
Liu, Xinyi
Fang, Xinying
Chinchilli, Vernon M
Wang, Michael
Wang, Hong-Gang
Dokholyan, Nikolay V
Shen, Chan
Lee, J Jack
author_sort Zhou, Shouhao
collection PubMed
description The median-effect equation has been widely used to describe the dose-response relationship and identify compounds that activate or inhibit specific disease targets in contemporary drug discovery. However, the experimental data often contain extreme responses, which may significantly impair the estimation accuracy and impede valid quantitative assessment in the standard estimation procedure. To improve the quantitative estimation of the dose-response relationship, we introduce a novel approach based on robust beta regression. Substantive simulation studies under various scenarios demonstrate solid evidence that the proposed approach consistently provides robust estimation for the median-effect equation, particularly when there are extreme outcome observations. Moreover, simulation studies illustrate that the proposed approach also provides a narrower confidence interval, suggesting a higher power in statistical testing. Finally, to efficiently and conveniently perform common lab data analyses, we develop a freely accessible web-based analytic tool to facilitate the quantitative implementation of the proposed approach for the scientific community.
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spelling pubmed-93488452022-08-04 Robust and Efficient Assessment of Potency (REAP) as a quantitative tool for dose-response curve estimation Zhou, Shouhao Liu, Xinyi Fang, Xinying Chinchilli, Vernon M Wang, Michael Wang, Hong-Gang Dokholyan, Nikolay V Shen, Chan Lee, J Jack eLife Cancer Biology The median-effect equation has been widely used to describe the dose-response relationship and identify compounds that activate or inhibit specific disease targets in contemporary drug discovery. However, the experimental data often contain extreme responses, which may significantly impair the estimation accuracy and impede valid quantitative assessment in the standard estimation procedure. To improve the quantitative estimation of the dose-response relationship, we introduce a novel approach based on robust beta regression. Substantive simulation studies under various scenarios demonstrate solid evidence that the proposed approach consistently provides robust estimation for the median-effect equation, particularly when there are extreme outcome observations. Moreover, simulation studies illustrate that the proposed approach also provides a narrower confidence interval, suggesting a higher power in statistical testing. Finally, to efficiently and conveniently perform common lab data analyses, we develop a freely accessible web-based analytic tool to facilitate the quantitative implementation of the proposed approach for the scientific community. eLife Sciences Publications, Ltd 2022-08-03 /pmc/articles/PMC9348845/ /pubmed/35921131 http://dx.doi.org/10.7554/eLife.78634 Text en © 2022, Zhou, Liu, Fang et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Cancer Biology
Zhou, Shouhao
Liu, Xinyi
Fang, Xinying
Chinchilli, Vernon M
Wang, Michael
Wang, Hong-Gang
Dokholyan, Nikolay V
Shen, Chan
Lee, J Jack
Robust and Efficient Assessment of Potency (REAP) as a quantitative tool for dose-response curve estimation
title Robust and Efficient Assessment of Potency (REAP) as a quantitative tool for dose-response curve estimation
title_full Robust and Efficient Assessment of Potency (REAP) as a quantitative tool for dose-response curve estimation
title_fullStr Robust and Efficient Assessment of Potency (REAP) as a quantitative tool for dose-response curve estimation
title_full_unstemmed Robust and Efficient Assessment of Potency (REAP) as a quantitative tool for dose-response curve estimation
title_short Robust and Efficient Assessment of Potency (REAP) as a quantitative tool for dose-response curve estimation
title_sort robust and efficient assessment of potency (reap) as a quantitative tool for dose-response curve estimation
topic Cancer Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9348845/
https://www.ncbi.nlm.nih.gov/pubmed/35921131
http://dx.doi.org/10.7554/eLife.78634
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