Bridging the Gap Between hiPSC-CMs Cardiotoxicity Assessment and Clinical LVEF Decline Risk: A Case Study of 21
Zhijie Wan1, Chenyu Wang2, Shizheng Luo2
1State Key Laboratory of Natural Medicine, Jiangsu Province Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing 210009, China.
Abstract:
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.
Insights
This study developed a predictive model to assess tyrosine kinase inhibitor (TKI) cardiotoxicity, improving risk assessment for heart failure and enhancing drug development safety.
Area of Science:
- Cardiovascular Toxicology
- Pharmacology
- Computational Biology
Background:
- Tyrosine kinase inhibitors (TKIs) can cause cardiotoxicity, leading to heart failure and treatment cessation.
- Current risk assessment methods for TKI cardiotoxicity require improvement for better patient outcomes.
Purpose of the Study:
- To assess TKI-induced cardiotoxicity using advanced modeling.
- To refine in vitro to in vivo extrapolation (IVIVE) for enhanced predictive accuracy.
- To identify key in vitro parameters for TKI cardiotoxicity assessment.
Main Methods:
- Utilized high-throughput screening with human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs).
- Developed a quantitative systems pharmacology-pharmacokinetic-toxicodynamic (QSP-PK-TD) model.
- Integrated drug exposure factors like protein binding and tissue distribution.
Main Results:
- The QSP-PK-TD model confirmed IVIVE reliability for TKI cardiotoxicity.
- Identified area under the curve of drug effects on mitochondrial membrane potential (AEMMP) and cardiomyocyte contractility (AEAAC) as critical parameters.
- Incorporating drug exposure factors significantly improved extrapolation accuracy.
Conclusions:
- Established a framework for predicting in vivo cardiotoxicity from in vitro data.
- Facilitates translation of preclinical findings to clinical risk assessment for TKIs.
- Provides a valuable tool for drug development and regulatory evaluation of TKI cardiotoxicity.
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