This README.txt file was generated on <2023-02-13> by Jordi Llopis-Lorente ------------------- GENERAL INFORMATION ------------------- Title of Dataset: Datasets associated to the paper "Uncertainty assessment of proarrhythmia predictions derived from multi-level in silico models" Author Information Principal Investigator: Karolina Kopanska; Research Programme on Biomedical Informatics (GRIB), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Hospital del Mar Medical Research Institute; Barcelona, Spain; karolinaweronika.kopanska@upf.edu; 0000-0001-6440-1776 Principal Investigator: Pablo Rodríguez-Belenguer; Research Programme on Biomedical Informatics (GRIB), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Hospital del Mar Medical Research Institute; Barcelona, Spain; Department of Pharmacy and Pharmaceutical Technology and Parasitology, Universitat de València; Valencia, Spain; pablo.rodriguezb@upf.edu; 0000-0001-5270-7452 Associate or Co-investigator: Jordi Llopis-Lorente; Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València; Valencia, Spain; jorllolo@etsii.upv.es; 0000-0002-3958-8062 Associate or Co-investigator: Beatriz Trénor; Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València; Valencia, Spain; btrenor@eln.upv.es; 0000-0001-9166-6112 Associate or Co-investigator: Javier Saiz; Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València; Valencia, Spain; jsaiz@ci2b.upv.es; 0000-0002-9850-0825 Associate or Co-investigator: Manuel Pastor; Research Programme on Biomedical Informatics (GRIB), Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Hospital del Mar Medical Research Institute; Barcelona, Spain; manuel.pastor@upf.edu; 0000-0001-8850-1341 Date of data collection: 2022-02-17 Geographic location of data collection: Valencia, Spain (39°28'11" N - 0°22'38" O) Information about funding sources or sponsorship that supported the collection of the data: European Union's Horizon 2020, Innovation Medicines Initiative 2 Joint Undertaking, eTRANSAFE project, grant agreement No 777365 European Union's Horizon 2020, Research and Innovation Programme, SimCardioTest project, grant agreement No 101016496 Ministerio de Ciencia, Innovación y Universidades, Formación de Profesorado Universitario, grant reference: FPU18/01659 Dirección General de Política Científica de la Generalitat Valenciana, PROMETEO, 2020/043 General description: These datasets were generated to train ("PopulationDrugsTrainingKrNaLCaL.xlsx") and test ("PopulationDrugsTestKrCaLNaL.xlsx") the uncertainty assessment models developed in the paper "Uncertainty assessment of proarrhythmia predictions derived from multi-level in silico models" by Kopanska, Rodríguez-Belenguer, et al. Keywords: cardiotoxicity, Torsade de Pointe, in silico, computational modelling, uncertainty assessment -------------------------- SHARING/ACCESS INFORMATION -------------------------- Open Access to data: Open Licenses/restrictions placed on the data, or limitations of reuse: CC BY-NC 3.0 Citation for and links to publications that cite or use the data: Kopanska, K, et al. (2023). Uncertainty assessment of proarrhythmia predictions derived from multi-level in silico models. IEEE Journal of Biomedical and Health Informatics -------------------- DATA & FILE OVERVIEW -------------------- File list: "PopulationDrugsTrainingKrNaLCaL.xlsx": It contains the predicted APD90 values of the population of models for a set of 125 input value combinations, also referred to as virtual drugs. "PopulationDrugsTestKrCaLNaL.xlsx": It contains the predicted APD90 values of the population of models for the 12 CiPA training drugs. Type of version of the dataset: final version Total size: 2.193 KB -------------------------- METHODOLOGICAL INFORMATION -------------------------- Description of methods used for collection/generation of data: In silico action potential (AP) modelling of the healthy human endocardial cardiomyocyte and APD90 measurements was done using the widely known model published by O’Hara and colleagues29, modified as described by Llopis-Lorente et al. (2020). We considered drug effects on APD90 as a function of the three selected currents IKr, ICaL, INaL, which are considered particularly relevant for drug-induced occurrence of ventricular arrhythmias and are usually included in the pre-clinical ion channel screening panel at pharmaceutical companies. Methods for processing the data: After running the simulations with the modified version of the O'Hara model, action potential duration at 90% repolarization (APD90) was determined. Software- or Instrument-specific information needed to interpret the data, including software and hardware version numbers: Excel -------------------------- DATA-SPECIFIC INFORMATION -------------------------- "PopulationDrugsTrainingKrNaLCaL.xlsx" Number of variables: 2 Number of cases/rows: 125 Variable list, defining any abbreviations, units of measure, codes or symbols used: "ADP90": action potential duration at 90% repolarization, measured in ms "EADs": it is a flag indicating whether an Early AfterDepolarization (EAD) appeared during the simulation (1) or not (0) "PopulationDrugsTestKrNaLCaL.xlsx" Number of variables: 2 Number of cases/rows: 13 Variable list, defining any abbreviations, units of measure, codes or symbols used: "ADP90": action potential duration at 90% repolarization, measured in ms "EADs": it is a flag indicating whether an Early AfterDepolarization (EAD) appeared during the simulation (1) or not (0)