A Conceptual Translational Bench-to-Bedside Cardiac Safety Framework for Predicting Drug-Induced QT Interval Prolongation from Molecular Structure to Clinical Data
10 affiliations
- 1InSilicoTrials Technologies B.V., 1017 BR Amsterdam, The Netherlands
- 2InSilicoTrials Technologies S.p.A., 34123 Trieste, Italy
- 3Dipartimento di Farmacia—Scienze del Farmaco, Università degli Studi di Bari “Aldo Moro”, 70125 Bari, Italy
- 4Dipartimento di Chimica, Università degli Studi di Bari “Aldo Moro”, 70125 Bari, Italy
- 5Centro de Investigación e Innovación en Bioingeniería (Ci2B), Universitat Politècnica de València, 46022 Valencia, Spain
- 6Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, FI-33720 Tampere, Finland
- 7Department of Electrical, Electronic and Information Engineering, University of Bologna, 47522 Cesena, Italy
- 8Prosilico AB, SE-141 45 Huddinge, Sweden
- 9Department of Molecular & Integrative Physiology, University of Michigan, Ann Arbor, MI 48109, USA
- 10The Jackson Laboratory, Bar Harbor, ME 04609, USA
Abstract
QT interval prolongation is associated with an increased risk of torsades de pointes (TdP), a potentially life-threatening ventricular arrhythmia, making assessment of cardiac repolarization a critical component of drug development. This work demonstrates how integrated in silico methodologies can be used to predict and quantitatively characterize QT liability across the drug discovery and development continuum. A proof-of concept translational workflow combining molecular structure analysis, in vitro pharmacology, animal data, and clinical exposure-response modeling was evaluated using the retrospective case examples verapamil and dofetilide. Molecular structure- and pharmacology-based assessments predicted hERG channel interaction and potential QT risk for both compounds. While initial in silico analyses suggested a high QT liability for verapamil and dofetilide, mechanistic electrophysiological modeling differentiated their effects. For verapamil, concurrent calcium channel inhibition offset hERG-mediated effects, resulting in predicted reductions in action potential duration and no clinically relevant QT prolongation. In contrast, dofetilide produced concentration-dependent increases in action potential duration, consistent with its known proarrhythmic potential. Translation of nonclinical findings to humans accurately predicted the absence of clinically meaningful QT effects for verapamil and identified QT prolongation exceeding the regulatory 10 ms threshold for dofetilide at therapeutic concentrations. Drug exposure and pharmacokinetic properties could be anticipated based solely on molecular structure. This conceptual workflow demonstrates how integrated quantitative in silico approaches can support earlier identification, characterization, and communication of QT risk, enabling informed decision-making and improved development efficiency from bench to bedside.
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BibTeX
@article{sips2026conceptual,
title = {{A Conceptual Translational Bench-to-Bedside Cardiac Safety Framework for Predicting Drug-Induced QT Interval Prolongation from Molecular Structure to Clinical Data}},
author = {Fianne Sips and Marc-Antonio Bisotti and Mario Torchia and Vincenzo Carbone and Nicola Gambacorta and Valentina Belgiovine and Fulvio Ciriaco and Orazio Nicolotti and Beatriz Trenor and Javier Saiz and Jari Hyttinen and Stefano Severi and Urban Fagerholm and Brian E. Carlson and Candice N. Baker and J Matthew Mahoney and Daniel Röshammar},
journal = {International Journal of Molecular Sciences},
year = {2026},
month = oct,
doi = {10.3390/ijms27209312},
url = {https://www.mdpi.com/1422-0067/27/20/9312},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - A Conceptual Translational Bench-to-Bedside Cardiac Safety Framework for Predicting Drug-Induced QT Interval Prolongation from Molecular Structure to Clinical Data
AU - Fianne Sips
AU - Marc-Antonio Bisotti
AU - Mario Torchia
AU - Vincenzo Carbone
AU - Nicola Gambacorta
AU - Valentina Belgiovine
AU - Fulvio Ciriaco
AU - Orazio Nicolotti
AU - Beatriz Trenor
AU - Javier Saiz
AU - Jari Hyttinen
AU - Stefano Severi
AU - Urban Fagerholm
AU - Brian E. Carlson
AU - Candice N. Baker
AU - J Matthew Mahoney
AU - Daniel Röshammar
PY - 2026
DA - 2026/10/20
JO - International Journal of Molecular Sciences
DO - 10.3390/ijms27209312
UR - https://www.mdpi.com/1422-0067/27/20/9312
AB - QT interval prolongation is associated with an increased risk of torsades de pointes (TdP), a potentially life-threatening ventricular arrhythmia, making assessment of cardiac repolarization a critical component of drug development. This work demonstrates how integrated in silico methodologies can be used to predict and quantitatively characterize QT liability across the drug discovery and development continuum. A proof-of concept translational workflow combining molecular structure analysis, in vitro pharmacology, animal data, and clinical exposure-response modeling was evaluated using the retrospective case examples verapamil and dofetilide. Molecular structure- and pharmacology-based assessments predicted hERG channel interaction and potential QT risk for both compounds. While initial in silico analyses suggested a high QT liability for verapamil and dofetilide, mechanistic electrophysiological modeling differentiated their effects. For verapamil, concurrent calcium channel inhibition offset hERG-mediated effects, resulting in predicted reductions in action potential duration and no clinically relevant QT prolongation. In contrast, dofetilide produced concentration-dependent increases in action potential duration, consistent with its known proarrhythmic potential. Translation of nonclinical findings to humans accurately predicted the absence of clinically meaningful QT effects for verapamil and identified QT prolongation exceeding the regulatory 10 ms threshold for dofetilide at therapeutic concentrations. Drug exposure and pharmacokinetic properties could be anticipated based solely on molecular structure. This conceptual workflow demonstrates how integrated quantitative in silico approaches can support earlier identification, characterization, and communication of QT risk, enabling informed decision-making and improved development efficiency from bench to bedside.
SN - 1422-0067
ER -