Population Pharmacokinetics of Tarlatamab, a Half-Life Extended DLL3-Directed Bispecific T-Cell Engager in Patients with Previously Treated Small Cell Lung Cancer.

IF 4.6 2区 医学 Q1 PHARMACOLOGY & PHARMACY
Clinical Pharmacokinetics Pub Date : 2025-05-01 Epub Date: 2025-04-22 DOI:10.1007/s40262-025-01499-z
Stephanie Kong, Mukul Minocha, Po-Wei Chen, Pablo Martinez, Erik S Anderson, Amanda Parkes, Brett E Houk, Chih-Wei Lin
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引用次数: 0

Abstract

Background and objective: Tarlatamab is a first in class, half-life extended delta-like ligand 3 (DLL3) directed bispecific T-cell engager (BiTE®) immunotherapy that has shown durable efficacy in patients with previously treated small cell lung cancer (SCLC). The purpose of this analysis was to develop a population pharmacokinetic (PK) model for tarlatamab.

Methods: This analysis includes data from 420 patients with previously treated small cell lung cancer (8509 samples) pooled across the Phase 1 DeLLphi-300 study (dose range 0.003-100 mg every 2 weeks and 200 mg every 3 weeks) and Phase 2 DeLLphi-301 study (10 mg and 100 mg every 2 weeks). The data were analyzed using a nonlinear-mixed effects modeling approach implemented in NONMEM (v7.5) software and validated using standard statistical approaches. The effects of intrinsic and extrinsic factors on PK parameters and exposures of tarlatamab were evaluated, and the impact of identified covariates were further assessed using simulations.

Results: Tarlatamab serum concentration data were best described by a two-compartment model with linear elimination. Tarlatamab clearance (CL) and central volume of distribution (VC) were 0.649 L/day and 3.44 L, respectively, for a typical 73-kg individual. The model-estimated median terminal phase elimination half-life was 11.2 days. Tarlatamab pharmacokinetics were not impacted by age, sex, ethnicity, estimates of renal and hepatic function, prior lines of therapy, or baseline disease status. The presence of antidrug antibody (ADA) at any time during the study and bodyweight were found to be statistically significant covariates on CL, and Asian race and bodyweight were found to be statistically significant covariates on VC; however, they did not lead to a clinically meaningful impact on exposures.

Conclusions: The pharmacokinetics of tarlatamab was well-described by a two-compartment model with linear elimination. No clinically significant differences were observed on the basis of age, sex, bodyweight, race, ethnicity, estimates of renal and hepatic function, prior lines of therapy, baseline disease status, or emergence of ADA. These results support that no dose adjustment is required on the basis of any of the evaluated covariates.

Tarlatamab是一种半衰期延长的dll3定向双特异性t细胞参与剂,在先前治疗过的小细胞肺癌患者中的群体药代动力学
背景和目的:Tarlatamab是一类首个半衰期延长的delta-样配体3 (DLL3)定向双特异性t细胞接触器(BiTE®)免疫疗法,在先前治疗过的小细胞肺癌(SCLC)患者中显示出持久的疗效。本分析的目的是建立tarlatamab的群体药代动力学(PK)模型。方法:本分析包括420例先前治疗过的小细胞肺癌患者(8509个样本)的数据,这些数据来自一期delphi -300研究(剂量范围为0.003- 100mg / 2周和200mg / 3周)和二期delphi -301研究(10mg和100mg / 2周)。使用NONMEM (v7.5)软件实现的非线性混合效应建模方法对数据进行分析,并使用标准统计方法进行验证。评估了内在和外在因素对药代动力学参数和tarlatamab暴露的影响,并通过模拟进一步评估了鉴定出的协变量的影响。结果:塔拉他抗血清浓度数据最好用线性消除的双室模型来描述。典型73-kg个体的塔拉他单抗清除率(CL)和中心分布容积(VC)分别为0.649 L/天和3.44 L。模型估计的中位末期消除半衰期为11.2天。塔拉他单抗的药代动力学不受年龄、性别、种族、肾功能和肝功能估计、既往治疗线或基线疾病状态的影响。抗药抗体(ADA)在研究中的任何时间的存在和体重被发现是有统计学意义的协变量CL,亚洲种族和体重被发现是有统计学意义的协变量VC;然而,它们并没有对暴露产生有临床意义的影响。结论:塔拉他单抗的药代动力学可以用线性消除的双室模型描述。在年龄、性别、体重、种族、肾功能和肝功能评估、既往治疗、基线疾病状态或ADA出现的基础上,没有观察到临床显著差异。这些结果支持在评估的协变量的基础上不需要调整剂量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.80
自引率
4.40%
发文量
86
审稿时长
6-12 weeks
期刊介绍: Clinical Pharmacokinetics promotes the continuing development of clinical pharmacokinetics and pharmacodynamics for the improvement of drug therapy, and for furthering postgraduate education in clinical pharmacology and therapeutics. Pharmacokinetics, the study of drug disposition in the body, is an integral part of drug development and rational use. Knowledge and application of pharmacokinetic principles leads to accelerated drug development, cost effective drug use and a reduced frequency of adverse effects and drug interactions.
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