Uncertainty assessment of proarrhythmia predictions derived from multi-level in silico models.

"all utilised data tables as well as the source code of the python scripts models and methods described here are freely accessible at github ( https://github com/phi-grib/cardiotox_uncertainty ) and usable under gnu gpl v3 open source license.; data availability data are provided in the github: https://github com/phi-grib/cardiotox_uncertainty declarations conflict of interest the authors declare no conflict of interest. xlsx" at https://riunet upv es/handle/10251/182593 . table 1"

"all utilised data tables as well as the source code of the python scripts models and methods described here are freely accessible at github ( https://github com/phi-grib/cardiotox_uncertainty ) and usable under gnu gpl v3 open source license.; data availability data are provided in the github: https://github com/phi-grib/cardiotox_uncertainty declarations conflict of interest the authors declare no conflict of interest."

"Declarations Conflict of interestThe authors declare no conflict of interest. Ethical standardsThe manuscript does not contain clinical studies nor patient data. Conflict of interest The authors declare no conflict of interest."

"Funding Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. The authors received funding from the eTRANSAFE project, Innovative Medicines Initiative 2 Joint Undertaking under Grant Agreement No. 777365, supported from European Union’s Horizon 2020 and the EFPIA. Authors declare that this work reflects only the author’s view, and that IMI-JU is not responsible for any use that may be made of the information it contains. Also, this project received funding from the European Union’s Horizon 2020 Research and Innovation programme under Grant Agreement No. 964537 (RISK-HUNT3R), which is part of the ASPIS cluster. We also received funding from the SimCardioTest supported by European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 101016496. J.L.L. is being funded by the Ministerio de Ciencia, Innovacion y Universidades for the “Formacion de Profesorado Universitario” (Grant Reference: FPU18/01659). The work was also partially support by the Dirección General de Política Científica de la Generalitat Valenciana (PROMETEO/2020/043)."