A Conceptual Translational Bench-to-Bedside Cardiac Safety Framework for Predicting Drug-Induced QT Interval Prolongation from Molecular Structure to Clinical Data
Authors:
- Fianne SipsFianne Sips
- Marc-Antonio BisottiMarc-Antonio Bisotti
- Mario TorchiaMario Torchia
- Vincenzo CarboneVincenzo Carbone
- Nicola GambacortaNicola Gambacorta
- Valentina BelgiovineValentina Belgiovine
- Fulvio CiriacoFulvio Ciriaco
- Orazio NicolottiOrazio Nicolotti
- Beatriz TrenorBeatriz Trenor
- Javier SaizJavier Saiz
- Jari HyttinenJari Hyttinen
- Stefano SeveriStefano Severi
Open Access
- 20 October 2026
- journal article
- research article
- Published by MDPI AG in International Journal of Molecular Sciences
- Vol. 27 (20) , 9312
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.Keywords
Funding Information
- Advanced Research Projects Agency for Health (1AY2AX000124)
This publication has 44 references indexed in Scilit:
- Target‐Engagement Prediction From Molecular Structure, In Vitro and Animal Data: A Tutorial for Early Assessment of Clinical Drug Exposure and Therapeutic/Adverse Potential Using the ANDROMEDA and PLATO Software on the InSilicoTrials PlatformCPT: Pharmacometrics & Systems Pharmacology, 2026
- The Hidden Cost of QTc Assessment: A Quantitative Weight of Evidence Framework to Eliminate Structural False Positives and Restore the Lost Opportunity Cost of Abandoned MedicinesClinical Pharmacology & Therapeutics, 2026
- Model informed assessment of QT prolongation during drug development: a five-year retrospective analysis of EMA scientific advicesJournal of Pharmacokinetics and Pharmacodynamics, 2026
- Practical guide to concentration-QTc modeling: a hands-on tutorialJournal of Pharmacokinetics and Pharmacodynamics, 2025
- FDA's insights: implementing new strategies for evaluating drug-induced QTc prolongationJournal of Pharmacokinetics and Pharmacodynamics, 2025
- Combining pharmacokinetic and electrophysiological models for early prediction of drug-induced arrhythmogenicityComputer Methods and Programs in Biomedicine, 2023
- DICTrank: The largest reference list of 1318 human drugs ranked by risk of drug-induced cardiotoxicity using FDA labelingDrug Discovery Today, 2023
- Human ether-à-go-go-related potassium channel: exploring SAR to improve drug designDrug Discovery Today, 2020
- General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico StrategyClinical Pharmacology & Therapeutics, 2019
- Scientific white paper on concentration-QTc modelingJournal of Pharmacokinetics and Pharmacodynamics, 2017