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REAP-2: An interactive quantitative tool for robust and efficient dose-response curve estimation

REAP-2 is an interactive dose-response curve estimation tool for Robust and Efficient Assessment of drug Potency. It provides user-friendly dose-response curve estimation for in vitro studies and conducts statistical testing for model comparisons with a redesigned user interface. We also make a majo...

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Detalles Bibliográficos
Autores principales: Fang, Xinying, Liu, Xinyi, Chinchilli, Vernon M., Wang, Michael, Wang, Hong-Gang, Dokholyan, Nikolay V., Shen, Chan, Lee, J. Jack, Zhou, Shouhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10643933/
https://www.ncbi.nlm.nih.gov/pubmed/38028338
http://dx.doi.org/10.1017/cts.2023.642
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author Fang, Xinying
Liu, Xinyi
Chinchilli, Vernon M.
Wang, Michael
Wang, Hong-Gang
Dokholyan, Nikolay V.
Shen, Chan
Lee, J. Jack
Zhou, Shouhao
author_facet Fang, Xinying
Liu, Xinyi
Chinchilli, Vernon M.
Wang, Michael
Wang, Hong-Gang
Dokholyan, Nikolay V.
Shen, Chan
Lee, J. Jack
Zhou, Shouhao
author_sort Fang, Xinying
collection PubMed
description REAP-2 is an interactive dose-response curve estimation tool for Robust and Efficient Assessment of drug Potency. It provides user-friendly dose-response curve estimation for in vitro studies and conducts statistical testing for model comparisons with a redesigned user interface. We also make a major update of the underlying estimation method with penalized beta regression, which demonstrates great reliability and accuracy in dose estimation and uncertainty quantification. In this note, we describe the method and implementation of REAP-2 with a highlight on potency estimation and drug comparison.
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spelling pubmed-106439332023-10-13 REAP-2: An interactive quantitative tool for robust and efficient dose-response curve estimation Fang, Xinying Liu, Xinyi Chinchilli, Vernon M. Wang, Michael Wang, Hong-Gang Dokholyan, Nikolay V. Shen, Chan Lee, J. Jack Zhou, Shouhao J Clin Transl Sci Brief Report REAP-2 is an interactive dose-response curve estimation tool for Robust and Efficient Assessment of drug Potency. It provides user-friendly dose-response curve estimation for in vitro studies and conducts statistical testing for model comparisons with a redesigned user interface. We also make a major update of the underlying estimation method with penalized beta regression, which demonstrates great reliability and accuracy in dose estimation and uncertainty quantification. In this note, we describe the method and implementation of REAP-2 with a highlight on potency estimation and drug comparison. Cambridge University Press 2023-10-13 /pmc/articles/PMC10643933/ /pubmed/38028338 http://dx.doi.org/10.1017/cts.2023.642 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
spellingShingle Brief Report
Fang, Xinying
Liu, Xinyi
Chinchilli, Vernon M.
Wang, Michael
Wang, Hong-Gang
Dokholyan, Nikolay V.
Shen, Chan
Lee, J. Jack
Zhou, Shouhao
REAP-2: An interactive quantitative tool for robust and efficient dose-response curve estimation
title REAP-2: An interactive quantitative tool for robust and efficient dose-response curve estimation
title_full REAP-2: An interactive quantitative tool for robust and efficient dose-response curve estimation
title_fullStr REAP-2: An interactive quantitative tool for robust and efficient dose-response curve estimation
title_full_unstemmed REAP-2: An interactive quantitative tool for robust and efficient dose-response curve estimation
title_short REAP-2: An interactive quantitative tool for robust and efficient dose-response curve estimation
title_sort reap-2: an interactive quantitative tool for robust and efficient dose-response curve estimation
topic Brief Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10643933/
https://www.ncbi.nlm.nih.gov/pubmed/38028338
http://dx.doi.org/10.1017/cts.2023.642
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