Du Shengnan, Hu Zheyi, Shen Jun, Hamuro Lora, Lam Justine, Lu Ming, Zhu Li, Roy Amit, Kondic Anna
Bristol-Myers Squibb, Princeton, New Jersey, USA.
Former Employee of BMS, Currently Employed at AbbVie Inc., North Chicago, Illinois, USA.
CPT Pharmacometrics Syst Pharmacol. 2025 Jul;14(7):1179-1190. doi: 10.1002/psp4.70036. Epub 2025 May 1.
Repotrectinib is approved in the US for treating ROS1-positive non-small cell lung cancer (NSCLC) and solid tumors harboring an NTRK gene fusion. A Population Pharmacokinetic (PopPK) model for repotrectinib was developed using data from 620 adults (118 healthy volunteers and 502 patients) across seven studies and 24 pediatric patients from one study. The PopPK model, a two-compartment model with first-order absorption and an absorption lag time, incorporating a time-varying clearance due to drug-induced autoinduction, adequately described all PK data. Clearance was modeled as a time- and concentration-dependent (Ctrough) autoinduction process, accounting for increased clearance over time. While empirical in nature, this Ctrough-driven autoinduction model effectively described the changes in clearance and avoided the abrupt concentration changes that can occur with discrete dose-driven autoinduction models. Additionally, this approach avoided time-consuming differential equation computations for the semi-mechanistic enzyme turnover autoinduction models. The model estimated that the maximum drug-induced clearance (CLMAX) was 4.9 times the baseline clearance. Body weight (BW) effects on clearance and volume of distribution were estimated as allometric scaling exponents of 0.477 and 0.962, respectively. Age was found to affect CLMAX, with younger patients generally exhibiting higher CLMAX values. Simulations suggested that a flat dosing regimen (e.g., 160 mg QD for 14 days followed by 160 mg BID) provides comparable drug exposures in both adult and adolescent patients. The PopPK model supported the health authority approval of the dosing regimen for repotrectinib in both adult and adolescent patients with NTRK gene fusion-positive solid tumors.
瑞波替尼在美国被批准用于治疗ROS1阳性非小细胞肺癌(NSCLC)以及携带NTRK基因融合的实体瘤。利用来自七项研究的620名成年人(118名健康志愿者和502名患者)的数据以及一项研究中的24名儿科患者的数据,建立了瑞波替尼的群体药代动力学(PopPK)模型。该PopPK模型是一个具有一级吸收和吸收滞后时间的二室模型,纳入了因药物诱导自身诱导而随时间变化的清除率,能够充分描述所有药代动力学数据。清除率被建模为一个时间和浓度依赖性(谷浓度)的自身诱导过程,解释了清除率随时间的增加。虽然本质上是经验性的,但这个由谷浓度驱动的自身诱导模型有效地描述了清除率的变化,避免了离散剂量驱动的自身诱导模型可能出现的浓度突然变化。此外,这种方法避免了半机制酶周转自身诱导模型耗时的微分方程计算。该模型估计,最大药物诱导清除率(CLMAX)是基线清除率的4.9倍。体重(BW)对清除率和分布容积的影响估计分别为异速生长指数0.477和0.962。发现年龄会影响CLMAX,年轻患者通常表现出更高的CLMAX值。模拟表明,固定剂量方案(例如,第14天每天一次160毫克,之后每天两次160毫克)在成年和青少年患者中提供了相当的药物暴露量。PopPK模型支持了监管机构对瑞波替尼在NTRK基因融合阳性实体瘤成年和青少年患者中给药方案的批准。