ArticleScientific reports2023
In silico assessment on TdP risks of drug combinations under CiPA paradigm.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Improving In Silico Cardiac Safety Prediction by Consensus Averaging of Transmural Ventricular Cell Models.Annals of biomedical engineering · 2026Article
- A Narrative Review of Artificial Intelligence for Drug Repurposing: Lessons From COVID-19 and Oncology (2020-2025).CPT: pharmacometrics & systems pharmacology · 2026Review
- Toward Standardized Methodologies for Drug-Induced Proarrhythmia Classification: An In Silico Proof of Concept.Computational and structural biotechnology journal · 2026Article
- Validation of new AI-based classification method for in silico cardiac safety assessment of drugs following the CiPA framework.Archives of toxicology · 2025Article
- Cardiotoxicity evaluation of two-drug fixed-dose combination therapy under CiPA: a computational study.Translational and clinical pharmacology · 2024Article
- Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation.Physiological reviews · 2024Review
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Authors and funding
6 authors.
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Abstract
Researchers have recently proposed the Comprehensive In-vitro Proarrhythmia Assay (CiPA) to analyze medicines' TdP risks. Using the TdP metric known as qNet, numerous single-drug effects have been studied to classify the medications as low, intermediate, and high-risk. Furthermore, multiple medication therapies are recognized as a potential method for curing patients, mainly when limited drugs are available. This work expands the TdP risk assessment of drugs by introducing a CiPA-based in silico analysis of the TdP risk of combined drugs. The cardiac cell model was simulated using the population of models approach incorporating drug-drug interactions (DDIs) models on several ion channels for various drug pairs. Action potential duration (APD90), qNet, and calcium duration (CaD90) were computed and analyzed as biomarker features. The drug combination maps were also used to illustrate combined medicines' TdP risk. We found that the combined drugs alter cell responses in terms of biomarkers such as APD90, qNet, and CaD90 in a highly nonlinear manner. The results also revealed that combinations of high-risk with low-risk and intermediate-risk with low-risk drugs could result in compounds with varying TdP risks depending on the drug concentrations.
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