Sang Lan, Zhou Zhengying, Luo Shizheng, Zhang Yicui, Qian Hongjie, Zhou Ying, He Hua, Hao Kun
State Key Laboratory of Natural Medicines, Jiangsu Province Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, 210009, China.
Center of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, Nanjing, 210009, China.
Pharm Res. 2024 Feb;41(2):247-262. doi: 10.1007/s11095-023-03644-4. Epub 2023 Dec 26.
Antineoplastic agent-induced systolic dysfunction is a major reason for interruption of anticancer treatment. Although targeted anticancer agents infrequently cause systolic dysfunction, their combinations with chemotherapies remarkably increase the incidence. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) provide a potent in vitro model to assess cardiovascular safety. However, quantitatively predicting the reduction of ejection fraction based on hiPSC-CMs is challenging due to the absence of the body's regulatory response to cardiomyocyte injury.
Here, we developed and validated an in vitro-in vivo translational platform to assess the reduction of ejection fraction induced by antineoplastic drugs based on hiPSC-CMs. The translational platform integrates drug exposure, drug-cardiomyocyte interaction, and systemic response. The drug-cardiomyocyte interaction was implemented as a mechanism-based toxicodynamic (TD) model, which was then integrated into a quantitative system pharmacology-physiological-based pharmacokinetics (QSP-PBPK) model to form a complete translational platform. The platform was validated by comparing the model-predicted and clinically observed incidence of doxorubicin and trastuzumab-induced systolic dysfunction.
A total of 33,418 virtual patients were incorporated to receive doxorubicin and trastuzumab alone or in combination. For doxorubicin, the QSP-PBPK-TD model successfully captured the overall trend of systolic dysfunction incidences against the cumulative doses. For trastuzumab, the predicted incidence interval was 0.31-2.7% for single-agent treatment and 0.15-10% for trastuzumab-doxorubicin sequential treatment, covering the observations in clinical reports (0.50-1.0% and 1.5-8.3%, respectively).
In conclusion, the in vitro-in vivo translational platform is capable of predicting systolic dysfunction incidence almost merely depend on hiPSC-CMs, which could facilitate optimizing the treatment protocol of antineoplastic agents.
抗肿瘤药物引起的收缩功能障碍是中断抗癌治疗的主要原因。尽管靶向抗癌药物很少引起收缩功能障碍，但它们与化疗联合使用会显著增加其发生率。人诱导多能干细胞衍生的心肌细胞（hiPSC-CMs）提供了一个强大的体外模型来评估心血管安全性。然而，由于缺乏机体对心肌细胞损伤的调节反应，基于hiPSC-CMs定量预测射血分数的降低具有挑战性。
在此，我们开发并验证了一个体外-体内转化平台，以基于hiPSC-CMs评估抗肿瘤药物引起的射血分数降低。该转化平台整合了药物暴露、药物-心肌细胞相互作用和全身反应。药物-心肌细胞相互作用被实现为一个基于机制的毒代动力学（TD）模型，然后将其整合到一个定量系统药理学-基于生理的药代动力学（QSP-PBPK）模型中，形成一个完整的转化平台。通过比较模型预测的和临床观察到的多柔比星和曲妥珠单抗引起的收缩功能障碍发生率，对该平台进行了验证。
总共纳入了33418名虚拟患者，单独或联合接受多柔比星和曲妥珠单抗治疗。对于多柔比星，QSP-PBPK-TD模型成功捕捉到了收缩功能障碍发生率相对于累积剂量的总体趋势。对于曲妥珠单抗，单药治疗的预测发生率区间为0.31%-2.7%，曲妥珠单抗-多柔比星序贯治疗的预测发生率区间为0.15%-10%涵盖了临床报告中的观察结果（分别为0.50%-1.0%和1.5%-8.3%）。
总之，体外-体内转化平台几乎仅依靠hiPSC-CMs就能预测收缩功能障碍的发生率，这有助于优化抗肿瘤药物的治疗方案。
