Key result
An optimized in silico cardiac cell model using the qNet metric correctly classified 12 training drugs into their clinical Torsade-de-Pointes risk categories with zero training error at clinical concentrations.
Population
In silico cardiac cell model (IKr-dynamic ORd model) based on published human cardiomyocyte experimental data
Design
Preclinical
Authors
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Supports refinement of CiPA in silico models for TdP risk assessment; leaves open clinical translation and regulatory adoption.
An optimized in silico cardiac cell model improves the prediction and classification of drug-induced Torsade-de-Pointes risk, supporting the CiPA paradigm for regulatory assessment.
Dutta et al. (2017) studied Drug-induced Torsade-de-Pointes (TdP) (n=12). Optimized IKr-dynamic ORd model and qNet metric vs. Original ORd model and standard metrics was evaluated on Classification training error for TdP risk categories. An optimized in silico cardiac cell model using the qNet metric correctly classified 12 training drugs into their clinical Torsade-de-Pointes risk categories with zero training error at clinical concentrations.
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