Virtual Assay

Virtual Assay performs in silico drug trials on populations of computational human cardiac electrophysiology models to predict drug-induced pro-arrhythmic cardiotoxicity.

Key Features:

• Mechanistic cardiac electrophysiology simulations: Implements biophysically detailed simulations of cardiac ion-channel dynamics.
• Virtual population generation: Constructs heterogeneous virtual populations reflecting inter-individual variability arising from sex, age, disease state, genetic background, and physiological conditions.
• High-throughput simulation pipelines: Evaluates drug effects across thousands of parameterized cardiac cell and tissue models.
• ADME and electrophysiological response modeling: Captures absorption, distribution, metabolism, and mechanistic electrophysiological responses to compounds.
• Rare-event detection: Identifies rare but clinically significant pro-arrhythmic liabilities that may be missed by homogeneous animal models.
• Translational integration: Bridges ion-channel screening assays and comprehensive cardiac safety evaluation to support translational risk assessment.

Scientific Applications:

• Early cardiac safety screening: Predicts drug-induced pro-arrhythmic cardiotoxicity during early stages of drug development.
• Population variability analysis: Enables scalable exploration of electrophysiological responses across sex, age, disease state, and genetic backgrounds.
• Regulatory and translational risk assessment: Supports regulatory adoption of in silico methodologies for translational assessment of cardiac risk.
• Reduction of animal reliance and attrition: Informs safety evaluation to reduce reliance on animal studies and lower attrition in drug development.
• Identification of clinically significant liabilities: Detects mechanistic adverse cardiac outcomes and rare pro-arrhythmic effects across virtual populations.

Methodology:

Performs biophysically detailed simulations of cardiac ion-channel dynamics on heterogeneous virtual populations, running high-throughput simulations across thousands of parameterized cardiac cell and tissue models that capture absorption, distribution, metabolism, and mechanistic electrophysiological responses.