HPC Framework for Performing in Silico Trials Using a 3D Virtual Human Cardiac Population as Means to Assess

Jazmin Aguado-Sierra1,2, Renee Brigham3, Apollo K Baron4

  • 1Barcelona Supercomputing Center, Barcelona, Spain. jazmin.aguado@bsc.es.

Insights

A new computational framework enables in-silico clinical trials for cardiac drug safety. This virtual heart model accurately predicts pro-arrhythmic risk, reducing animal testing and accelerating drug development.

Area of Science:

  • Computational biology
  • Cardiovascular research
  • Pharmacology

Background:

  • Traditional drug cardiotoxicity testing relies on animal models and lengthy clinical trials.
  • Assessing pro-arrhythmic risk, particularly with drug combinations, remains a challenge.
  • Existing in-silico methods often lack detailed anatomical and physiological representation.

Purpose of the Study:

  • To develop and validate a high-performance computational framework for in-silico clinical trials.
  • To assess the pro-arrhythmic risk of hydroxychloroquine and azithromycin, alone and in combination.
  • To investigate drug-induced QT-prolongation and arrhythmia mechanisms in a virtual human heart model.

Main Methods:

  • Utilized 3D biventricular human heart models with phenotypic and sex-specific variations.
  • Performed electrophysiology simulations to analyze pseudo-ECGs, calcium dynamics, and activation patterns.
  • Validated in-silico findings with in-vitro experiments on reanimated swine hearts using Visible Heart® methodology.

Main Results:

  • The in-silico trials accurately predicted pro-arrhythmic risk (21.8% vs. 21% clinical risk).
  • Identified transmural heterogeneity in action potential prolongation as a key mechanism for drug-induced arrhythmias.
  • Demonstrated that common phenotype variants lead to distinct drug-induced arrhythmogenic outcomes.

Conclusions:

  • The computational framework provides a rapid and reliable method for in-silico drug cardiotoxicity trials.
  • This approach effectively reproduces complex cardiac electrophysiology in diverse virtual populations.
  • The study highlights the potential to reduce animal use and accelerate clinical trial timelines for drug safety assessment.

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