PRODUCT
An innovative screening tool that predicts a compound’s proarrhythmic risk using electrophysiology and machine learning
Clinically Validated
Validated on a set of 109 known drug compounds, 51 of which torsadogenic
Display and Export
Compounds lists can be uploaded and results can be downloaded in JSON or CSV format
Easy to Use
Well-designed wizard that guides through the setup of computation step by step
QT/TdP Risk Screen is based on electrophysiology simulations that estimate a compound effect on the action potential of isolated endocardial cells (o’Hara et al. 2011). After computing novel torsadogenic indices, a machine learning algorithm classifies the drug at the concentration of interest as safe or unsafe in line with the CredibleMeds classification criteria.
This tool is easy to use since it only requires the compound’s in vitro IC50 values towards the IKs, IKr, ICaL and INaL ion channels and the compound’s concentration values for which the assessment of the proarrhythmic potential risk is needed.
The predictive performance of QT/TdP Risk Screen was evaluated by means of classifying the proarrhythmic risk of 109 known drug compounds, 51 of which torsadogenic (Llopis et al. 2020).
QT/TdP Risk Screen is the result of a collaboration among Universitat Politècnica de València (UPV, Valencia), Fundació Institut Hospital del Mar D’Investigacions Mèdiques (FIMIM, Barcelona), and InSilicoTrials Technologies
Jordi Llopis, Julio Gomis-Tena, Jordi Cano, Lucia Romero, Javier Saiz, and Beatriz Trenor
Journal of Chemical Information and Modeling 2020 https://doi.org/10.1021/acs.jcim.0c00201
Lucia Romero, Jordi Cano, Julio Gomis-Tena, Beatriz Trenor, Ferran Sanz, Manuel Pastor, and Javier Saiz
Journal of Chemical Information and Modeling 58 (4), 867-878, 2018
Thomas O’Hara, Lászlo ́Virág, Andraás Varró, and Yoram Rudy
PLoS Computational Biology 7(5): e1002061, 2011