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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;
- Tshinanu, Flora Musuamba;
- Strauss, David G
- et al.
Published Web Location
https://doi.org/10.1002/cpt.1647Abstract
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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