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Considering Population Variability of Electrophysiological Models Improves the In Silico Assessment of Drug-Induced Torsadogenic Risk

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Considering Population Variability of Electrophysiological Models Improves the In Silico Assessment of Drug-Induced Torsadogenic Risk

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Llopis Lorente, J.; Trénor Gomis, BA.; Saiz Rodríguez, FJ. (2022). Considering Population Variability of Electrophysiological Models Improves the In Silico Assessment of Drug-Induced Torsadogenic Risk. http://hdl.handle.net/10251/182593

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Title: Considering Population Variability of Electrophysiological Models Improves the In Silico Assessment of Drug-Induced Torsadogenic Risk
Author: Llopis Lorente, Jordi Trénor Gomis, Beatriz Ana Saiz Rodríguez, Francisco Javier
UPV Unit: Universitat Politècnica de València. Centro de Investigación e Innovación en Bioingeniería - Centre de Recerca i Innovació en Bioenginyeria
Issued date:
Abstract:
This repository contains the parameter sets of the population of TorORd models and the the population of ORdmD models, the ORdmD CellML file and MALTAB code used in Llopis-Lorente, J., Trenor, B., Saiz, J. (2022). Considering ...[+]
Subjects: In-silico study , Torsade de Pointes , Proarrhythmic risk , Cardiac safety , Population of models
Copyrigths: Reconocimiento - No comercial (by-nc)
Project ID:
info:eu-repo/grantAgreement/EC/H2020/101016496/EU/Simulation of Cardiac Devices & Drugs for in-silico Testing and Certification/
info:eu-repo/grantAgreement/GVA//PROMETEO%2F2020%2F043//MODELOS IN-SILICO MULTI-FISICOS Y MULTI-ESCALA DEL CORAZON PARA EL DESARROLLO DE NUEVOS METODOS DE PREVENCION, DIAGNOSTICO Y TRATAMIENTO EN MEDICINA PERSONALIZADA (HEART IN-SILICO MODELS)/
info:eu-repo/grantAgreement/MCIU//FPU18%2F01659/
Type: Software

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