Key result
Integrated hiPSC-CM and pharmacokinetic model successfully predicts in vivo cardiotoxicity for 21 TKIs.
Why the study?
Tyrosine kinase inhibitor-induced cardiotoxicity can cause left ventricular dysfunction and heart failure leading to treatment discontinuation, creating an urgent need for more precise risk assessment methods.
A novel quantitative systems pharmacology model using hiPSC-CMs successfully identified key in vitro parameters to predict clinical TKI-induced cardiotoxicity and LVEF decline.
Answers are grounded in this paper and cite their sources.
Hypothesis-generating for TKI cardiotoxicity screening; leaves open clinical translation pending human validation.
Objectives: There is growing concern over tyrosine kinase inhibitor (TKI)-induced cardiotoxicity, particularly regarding left ventricular dysfunction and heart failure in clinical treatment. These adverse effects often lead to treatment discontinuation, severely impacting patient outcomes. Therefore, there is an urgent need for more precise risk assessment methods. This study aimed to assess the cardiotoxicity of TKIs, refine in vitro to in vivo extrapolation (IVIVE) methodologies to improve predictive accuracy, and identify critical in vitro parameters for assessment. Methods: By leveraging high-throughput cardiotoxicity screening with human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), a mechanism-based toxicodynamic (TD) model for TKIs was constructed. A QSP-PK-TD model was developed by integrating pharmacokinetic (PK) and quantitative systems pharmacology (QSP) models. This model incorporates critical drug exposure factors, such as plasma protein binding, tissue–plasma partitioning, and drug distribution heterogeneity to enhance extrapolation accuracy. Results: The QSP-PK-TD model validated the reliability of IVIVE and identified the area under the curve of drug effects on mitochondrial membrane potential (AEMMP) and cardiomyocyte contractility (AEAAC) as key in vitro parameters for assessing TKI-induced cardiotoxicity. Incorporating critical drug exposure factors obviously improved qualitative and quantitative extrapolation accuracy. Conclusions: This study established a framework for predicting in vivo cardiotoxicity from in vitro parameters, enabling efficient translation of preclinical data into clinical risk assessment. These findings provide valuable insights for drug development and regulatory decision-making, offering a powerful tool for evaluating TKI-induced cardiotoxicity.
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Wan et al. (2025) studied Tyrosine kinase inhibitor (TKI)-induced cardiotoxicity. Tyrosine Kinase Inhibitors was evaluated on In vivo cardiotoxicity prediction (LVEF decline risk). A QSP-PK-TD model integrating hiPSC-CM screening and pharmacokinetic factors successfully predicted in vivo cardiotoxicity for 21 tyrosine kinase inhibitors from in vitro parameters.
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