School of Engineering, University of Warwick, Coventry, UK.
MSD, London, UK.
Clin Transl Sci. 2024 Mar;17(3):e13714. doi: 10.1111/cts.13714.
Tyrosine kinase inhibitors (TKIs) are routinely prescribed for the treatment of non-small cell lung cancer (NSCLC). As with all medications, patients can experience adverse events due to TKIs. Unfortunately, the relationship between many TKIs and the occurrence of certain adverse events remains unclear. There are limited in vivo studies which focus on TKIs and their effects on different regulation pathways. Many in vitro studies, however, that investigate the effects of TKIs observe additional changes, such as changes in gene activations or protein expressions. These studies could potentially help to gain greater understanding of the mechanisms for TKI induced adverse events. However, in order to utilize these pathways in a pharmacokinetic/pharmacodynamic (PK/PD) framework, an in vitro PK/PD model needs to be developed, in order to characterize the effects of TKIs in NSCLC cell lines. Through the use of ordinary differential equations, cell viability data and nonlinear mixed effects modeling, an in vitro TKI PK/PD model was developed with estimated PK and PD parameter values for the TKIs alectinib, crizotinib, erlotinib, and gefitinib. The relative standard errors for the population parameters are all less than 25%. The inclusion of random effects enabled the model to predict individual parameter values which provided a closer fit to the observed response. It is hoped that this model can be extended to include in vitro data of certain pathways that may potentially be linked with adverse events and provide a better understanding of TKI-induced adverse events.
酪氨酸激酶抑制剂 (TKI) 通常被开处方用于治疗非小细胞肺癌 (NSCLC)。与所有药物一样,患者可能会因 TKI 而出现不良反应。不幸的是,许多 TKI 与某些不良反应的发生之间的关系仍不清楚。很少有研究专注于 TKI 及其对不同调节途径的影响。然而,许多研究 TKI 对不同调节途径影响的体外研究观察到其他变化,例如基因激活或蛋白质表达的变化。这些研究可能有助于更好地了解 TKI 诱导不良反应的机制。然而,为了在药代动力学/药效学 (PK/PD) 框架中利用这些途径,需要开发体外 PK/PD 模型,以描述 TKI 在 NSCLC 细胞系中的作用。通过使用常微分方程、细胞活力数据和非线性混合效应建模,开发了一种体外 TKI PK/PD 模型,用于估计 TKI 艾乐替尼、克唑替尼、厄洛替尼和吉非替尼的 PK 和 PD 参数值。群体参数的相对标准误差均小于 25%。随机效应的纳入使模型能够预测个体参数值,从而更接近观察到的反应。希望该模型能够扩展到包括可能与不良反应相关的某些途径的体外数据,从而更好地了解 TKI 诱导的不良反应。