the healthcare business of Merck KGaA, Darmstadt, Germany.
Merck Institute of Pharmacometrics, Lausanne, Switzerland, an affiliate of Merck KGaA, Darmstadt, Germany.
Clin Cancer Res. 2022 Apr 1;28(7):1363-1371. doi: 10.1158/1078-0432.CCR-21-2662.
Empirical time-varying clearance models have been reported for several immune checkpoint inhibitors, including avelumab (anti-programmed death ligand 1). To investigate the exposure-response relationship for avelumab, we explored semimechanistic pharmacokinetic (PK)-tumor growth dynamics (TGD) models.
Plasma PK data were pooled from three phase I and II trials (JAVELIN Merkel 200, JAVELIN Solid Tumor, and JAVELIN Solid Tumor JPN); tumor size (TS) data were collected from patients with metastatic Merkel cell carcinoma (mMCC) enrolled in JAVELIN Merkel 200. A PK model was developed first, followed by TGD modeling to investigate interactions between avelumab exposure and TGD. A PK-TGD feedback loop was evaluated with simultaneous fitting of the PK and TGD models.
In total, 1,835 PK observations and 338 TS observations were collected from 147 patients. In the final PK-TGD model, which included the bidirectional relationship between PK and TGD, avelumab PK was described by a two-compartment model with a positive association between clearance and longitudinal TS, with no additional empirical time-varying clearance identified. TGD was described by first-order tumor growth/shrinkage rates, with the tumor shrinkage rate decreasing exponentially over time; the exponential time-decay constant decreased with increasing drug concentration, representing the treatment effect through tumor shrinkage inhibition.
We developed a TGD model that mechanistically captures the prevention of loss of antitumor immunity (i.e., T-cell suppression in the tumor microenvironment) by avelumab, and a bidirectional interaction between PK and TGD in patients with mMCC treated with avelumab, thus mechanistically describing previously reported time variance of avelumab elimination.
已有报道称,包括avelumab(抗程序性死亡配体 1)在内的几种免疫检查点抑制剂存在经验性时变清除率模型。为了研究avelumab 的暴露-反应关系,我们探索了半机械论药代动力学(PK)-肿瘤生长动力学(TGD)模型。
来自三项 I 期和 II 期试验(JAVELIN Merkel 200、JAVELIN 实体瘤和 JAVELIN 实体瘤 JPN)的血浆 PK 数据进行了汇总;转移性 Merkel 细胞癌(mMCC)患者的肿瘤大小(TS)数据来自 JAVELIN Merkel 200 试验。首先开发 PK 模型,然后进行 TGD 建模以研究 avelumab 暴露与 TGD 之间的相互作用。通过同时拟合 PK 和 TGD 模型评估 PK-TGD 反馈回路。
共从 147 例患者中收集了 1835 个 PK 观察值和 338 个 TS 观察值。在包含 PK 和 TGD 之间双向关系的最终 PK-TGD 模型中,avelumab PK 由两室模型描述,清除率与纵向 TS 呈正相关,未发现其他经验性时变清除率。TGD 由一阶肿瘤生长/收缩率描述,随着时间的推移,肿瘤收缩率呈指数衰减;药物浓度增加时,指数时间衰减常数减小,代表通过抑制肿瘤收缩来发挥治疗作用。
我们开发了一种 TGD 模型,该模型从机制上捕获了 avelumab 对肿瘤微环境中抗肿瘤免疫丧失的预防作用(即 T 细胞抑制),以及接受 avelumab 治疗的 mMCC 患者中 PK 和 TGD 之间的双向相互作用,从而从机制上描述了先前报道的 avelumab 消除的时变。