Published July 27, 2020 | Version v2
Dataset Open

Drug-Induced TdP Risk Assessment

Description

A manually collected dataset that investigates the proarrhythmic risk of 109 drugs using parameters obtained from biophysical models. The dataset provides 4 torsade de pointes (TdP) risk categories.  For all 109 drugs, IC50 values and Hill coefficients (h) for INa, INaL, IKr, Ito, ICaL, IK1, and IKs and human effective free therapeutic plasma concentration (EFTPC) were obtained (Llopis-Lorente et al., 2020).

 

Task: The dataset can be used to study causal discovery methods aiming to infer ion channels selection for the drug-induced TdP risk.

 

Summary: 

  • Size of dataset: 109 x 16
  • Task: Causal Discovery Problem
  • Data Type: Mixed Data
  • Dataset Scope: Standalone Dataset
  • Ground Truth: Unknown Graph
  • Temporal Structure: Static Data
  • License: CC BY-NC 4.0 (see https://pubs.acs.org/page/policy/authorchoice_termsofuse.html)
  • Missing Values: Existing Missing Values

 

Missingness Statement: A dash in the dataset means that no value was found publicly available, thus it was considered that the drug effect on that current was negligible (Llopis-Lorente et al., 2020).

 

Features:

  • Class: Torsadogenic risk characterization.  Class 1 (known risk of TdP), class 2 (possible risk of TdP), class 3 (conditional risk of TdP), and class 4 (drugs with a lack of evidence of TdP).
  • EFTPC: Effective free therapeutic plasma concentration. EFTPC is the minimum concentration of the unbound form of a drug in plasma required to produce the intended therapeutic effect in the body.
  • IC50[...]: Value that represents the minimal concentration of a drug that is required for 50% inhibition in vitrovalues (given in nm). Drugs are in the set {Kr, INa,INaL, ICaL, IKs, IK1, Ito}.
  • h[...]: Hill coefficients of the currents. Drugs are in the set {Kr, INa,INaL, ICaL, IKs, IK1, Ito}.

 

Files: 

  • med_file.csv: dataset

Files

med_file.csv

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Additional details

Related works

References
Journal article: 10.1021/acs.jcim.0c00201 (DOI)
Conference proceeding: 10.22489/cinc.2023.009 (DOI)

References

  • Llopis-Lorente, Jordi and Gomis-Tena, Julio and Cano, Jordi and Romero, Lucía and Saiz, Javier and Trenor, Beatriz. InSilico Classifiers for the Assessment of Drug Proarrhythmicity. Journal of Chemical Information and Modeling, 2020, 60(10), 5172--5187, https://doi.org/10.1021/acs.jcim.0c00201
  • Al-Ali,Safaa and Llopis-Lorente, Jordi and Mora, Maria Teresa and Sermesant, Maxime and Trénor, Beatriz and Balelli, Irene. A causal discovery approach for streamline ion channels selection to improve drug-induced TdP risk assessment. 2023.hal-04105144, https://doi.org/10.22489/cinc.2023.009