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General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy

This white paper presents principles for validating proarrhythmia risk prediction models for regulatory use as discussed at the In Silico Breakout Session of a Cardiac Safety Research Consortium/Health and Environmental Sciences Institute/US Food and Drug Administration–sponsored Think Tank Meeting...

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Autores principales: Li, Zhihua, Mirams, Gary R., Yoshinaga, Takashi, Ridder, Bradley J., Han, Xiaomei, Chen, Janell E., Stockbridge, Norman L., Wisialowski, Todd A., Damiano, Bruce, Severi, Stefano, Morissette, Pierre, Kowey, Peter R., Holbrook, Mark, Smith, Godfrey, Rasmusson, Randall L., Liu, Michael, Song, Zhen, Qu, Zhilin, Leishman, Derek J., Steidl‐Nichols, Jill, Rodriguez, Blanca, Bueno‐Orovio, Alfonso, Zhou, Xin, Passini, Elisa, Edwards, Andrew G., Morotti, Stefano, Ni, Haibo, Grandi, Eleonora, Clancy, Colleen E., Vandenberg, Jamie, Hill, Adam, Nakamura, Mikiko, Singer, Thomas, Polonchuk, Liudmila, Greiter‐Wilke, Andrea, Wang, Ken, Nave, Stephane, Fullerton, Aaron, Sobie, Eric A., Paci, Michelangelo, Musuamba Tshinanu, Flora, Strauss, David G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6977398/
https://www.ncbi.nlm.nih.gov/pubmed/31709525
http://dx.doi.org/10.1002/cpt.1647
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author Li, Zhihua
Mirams, Gary R.
Yoshinaga, Takashi
Ridder, Bradley J.
Han, Xiaomei
Chen, Janell E.
Stockbridge, Norman L.
Wisialowski, Todd A.
Damiano, Bruce
Severi, Stefano
Morissette, Pierre
Kowey, Peter R.
Holbrook, Mark
Smith, Godfrey
Rasmusson, Randall L.
Liu, Michael
Song, Zhen
Qu, Zhilin
Leishman, Derek J.
Steidl‐Nichols, Jill
Rodriguez, Blanca
Bueno‐Orovio, Alfonso
Zhou, Xin
Passini, Elisa
Edwards, Andrew G.
Morotti, Stefano
Ni, Haibo
Grandi, Eleonora
Clancy, Colleen E.
Vandenberg, Jamie
Hill, Adam
Nakamura, Mikiko
Singer, Thomas
Polonchuk, Liudmila
Greiter‐Wilke, Andrea
Wang, Ken
Nave, Stephane
Fullerton, Aaron
Sobie, Eric A.
Paci, Michelangelo
Musuamba Tshinanu, Flora
Strauss, David G.
author_facet Li, Zhihua
Mirams, Gary R.
Yoshinaga, Takashi
Ridder, Bradley J.
Han, Xiaomei
Chen, Janell E.
Stockbridge, Norman L.
Wisialowski, Todd A.
Damiano, Bruce
Severi, Stefano
Morissette, Pierre
Kowey, Peter R.
Holbrook, Mark
Smith, Godfrey
Rasmusson, Randall L.
Liu, Michael
Song, Zhen
Qu, Zhilin
Leishman, Derek J.
Steidl‐Nichols, Jill
Rodriguez, Blanca
Bueno‐Orovio, Alfonso
Zhou, Xin
Passini, Elisa
Edwards, Andrew G.
Morotti, Stefano
Ni, Haibo
Grandi, Eleonora
Clancy, Colleen E.
Vandenberg, Jamie
Hill, Adam
Nakamura, Mikiko
Singer, Thomas
Polonchuk, Liudmila
Greiter‐Wilke, Andrea
Wang, Ken
Nave, Stephane
Fullerton, Aaron
Sobie, Eric A.
Paci, Michelangelo
Musuamba Tshinanu, Flora
Strauss, David G.
author_sort Li, Zhihua
collection PubMed
description This white paper presents principles for validating proarrhythmia risk prediction models for regulatory use as discussed at the In Silico Breakout Session of a Cardiac Safety Research Consortium/Health and Environmental Sciences Institute/US Food and Drug Administration–sponsored Think Tank Meeting on May 22, 2018. The meeting was convened to evaluate the progress in the development of a new cardiac safety paradigm, the Comprehensive in Vitro Proarrhythmia Assay (CiPA). The opinions regarding these principles reflect the collective views of those who participated in the discussion of this topic both at and after the breakout session. Although primarily discussed in the context of in silico models, these principles describe the interface between experimental input and model‐based interpretation and are intended to be general enough to be applied to other types of nonclinical models for proarrhythmia assessment. This document was developed with the intention of providing a foundation for more consistency and harmonization in developing and validating different models for proarrhythmia risk prediction using the example of the CiPA paradigm.
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spelling pubmed-69773982020-01-28 General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy Li, Zhihua Mirams, Gary R. Yoshinaga, Takashi Ridder, Bradley J. Han, Xiaomei Chen, Janell E. Stockbridge, Norman L. Wisialowski, Todd A. Damiano, Bruce Severi, Stefano Morissette, Pierre Kowey, Peter R. Holbrook, Mark Smith, Godfrey Rasmusson, Randall L. Liu, Michael Song, Zhen Qu, Zhilin Leishman, Derek J. Steidl‐Nichols, Jill Rodriguez, Blanca Bueno‐Orovio, Alfonso Zhou, Xin Passini, Elisa Edwards, Andrew G. Morotti, Stefano Ni, Haibo Grandi, Eleonora Clancy, Colleen E. Vandenberg, Jamie Hill, Adam Nakamura, Mikiko Singer, Thomas Polonchuk, Liudmila Greiter‐Wilke, Andrea Wang, Ken Nave, Stephane Fullerton, Aaron Sobie, Eric A. Paci, Michelangelo Musuamba Tshinanu, Flora Strauss, David G. Clin Pharmacol Ther White Paper This white paper presents principles for validating proarrhythmia risk prediction models for regulatory use as discussed at the In Silico Breakout Session of a Cardiac Safety Research Consortium/Health and Environmental Sciences Institute/US Food and Drug Administration–sponsored Think Tank Meeting on May 22, 2018. The meeting was convened to evaluate the progress in the development of a new cardiac safety paradigm, the Comprehensive in Vitro Proarrhythmia Assay (CiPA). The opinions regarding these principles reflect the collective views of those who participated in the discussion of this topic both at and after the breakout session. Although primarily discussed in the context of in silico models, these principles describe the interface between experimental input and model‐based interpretation and are intended to be general enough to be applied to other types of nonclinical models for proarrhythmia assessment. This document was developed with the intention of providing a foundation for more consistency and harmonization in developing and validating different models for proarrhythmia risk prediction using the example of the CiPA paradigm. John Wiley and Sons Inc. 2019-11-10 2020-01 /pmc/articles/PMC6977398/ /pubmed/31709525 http://dx.doi.org/10.1002/cpt.1647 Text en © 2019 The Authors Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle White Paper
Li, Zhihua
Mirams, Gary R.
Yoshinaga, Takashi
Ridder, Bradley J.
Han, Xiaomei
Chen, Janell E.
Stockbridge, Norman L.
Wisialowski, Todd A.
Damiano, Bruce
Severi, Stefano
Morissette, Pierre
Kowey, Peter R.
Holbrook, Mark
Smith, Godfrey
Rasmusson, Randall L.
Liu, Michael
Song, Zhen
Qu, Zhilin
Leishman, Derek J.
Steidl‐Nichols, Jill
Rodriguez, Blanca
Bueno‐Orovio, Alfonso
Zhou, Xin
Passini, Elisa
Edwards, Andrew G.
Morotti, Stefano
Ni, Haibo
Grandi, Eleonora
Clancy, Colleen E.
Vandenberg, Jamie
Hill, Adam
Nakamura, Mikiko
Singer, Thomas
Polonchuk, Liudmila
Greiter‐Wilke, Andrea
Wang, Ken
Nave, Stephane
Fullerton, Aaron
Sobie, Eric A.
Paci, Michelangelo
Musuamba Tshinanu, Flora
Strauss, David G.
General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy
title General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy
title_full General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy
title_fullStr General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy
title_full_unstemmed General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy
title_short General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy
title_sort general principles for the validation of proarrhythmia risk prediction models: an extension of the cipa in silico strategy
topic White Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6977398/
https://www.ncbi.nlm.nih.gov/pubmed/31709525
http://dx.doi.org/10.1002/cpt.1647
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