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Clin Pharmacol Ther. 2020 Jan;107(1):102-111. doi: 10.1002/cpt.1647. Epub 2019 Nov 10.

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

Author information

1
Division of Applied Regulatory Science, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
2
Centre for Mathematical Medicine & Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, UK.
3
Global Cardiovascular Assessment, Eisai Co., Ltd., Tokyo, Japan.
4
Division of Biometrics VI, Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
5
Division of Cardiovascular and Renal Products, Office of Drug Evaluation I, Office of New Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
6
Global Safety Pharmacology, Pfizer, Inc., Groton, Connecticut, USA.
7
Global Safety Pharmacology/Nonclinical Safety, Janssen Research & Development, Raritan, New Jersey, USA.
8
Department of Electrical, Electronic, and Information Engineering, University of Bologna, Cesena, Italy.
9
Department of Safety Assessment and Laboratory Animal Resources, Merck & Co., Kenilworth, New Jersey, USA.
10
Main Line Health and Sidney Kimmel Medical College, Philadelphia, Pennsylvania, USA.
11
Certara, Ltd., Sheffield, UK.
12
Clyde Biosciences Ltd, Glasgow, UK.
13
Institute of Cardiovascular and Medical Sciences, Glasgow University, Glasgow, UK.
14
Department of Physiology and Biophysics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, New York, USA.
15
Division of Cardiology, Department of Medicine, University of California, Los Angeles, Los Angeles, California, USA.
16
Department of Toxicology and Pathology, Eli Lilly and Company, Indianapolis, Indiana, USA.
17
Covance Inc., Madison, Wisconsin, USA.
18
Department of Computer Science, University of Oxford, Oxford, UK.
19
Department of Pharmacology, University of California Davis, Davis, California, USA.
20
Victor Chang Cardiac Research Institute, Darlinghurst, New South Wales, Australia.
21
St Vincent's Clinical School, UNSW Sydney, Darlinghurst, New South Wales, Australia.
22
Clinical Pharmacology Department, Chugai Pharmaceutical Co., Ltd., Tokyo, Japan.
23
Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
24
Roche Product Development, Safety Science/Licensing & Early Development, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
25
Department of Safety Assessment, Genentech, Inc., South San Francisco, California, USA.
26
Icahn School of Medicine at Mount Sinai, New York, New York, USA.
27
BioMediTech, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
28
Federal Agency for Medicines and Health Products, Brussels, Belgium.
29
European Medicines Agency, Amsterdam, The Netherlands.

Abstract

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.

PMID:
31709525
DOI:
10.1002/cpt.1647

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