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抗癌药物联合治疗的剂量优化:通过临床暴露-毒性/临床前暴露-疗效建模最大化治疗指数。

Dose Optimization for Anticancer Drug Combinations: Maximizing Therapeutic Index via Clinical Exposure-Toxicity/Preclinical Exposure-Efficacy Modeling.

机构信息

Quantitative Clinical Pharmacology, Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited, Cambridge, Massachusetts.

DMPK Modeling & Simulation, Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited, Cambridge, Massachusetts.

出版信息

Clin Cancer Res. 2019 Nov 15;25(22):6633-6643. doi: 10.1158/1078-0432.CCR-18-3882. Epub 2019 Jul 18.

Abstract

PURPOSE

Recommended phase II dose (RP2D) determination for combination therapy regimens is a constrained optimization problem of maximizing antitumor activity within the constraint of clinical tolerability to provide a wide therapeutic index. A methodology for addressing this problem was developed and tested using clinical and preclinical data from combinations of the investigational drugs TAK-117, a PI3Kα inhibitor, and TAK-228, a TORC1/2 dual inhibitor.

EXPERIMENTAL DESIGN

Utilizing free fraction-corrected average concentrations, [Formula: see text] and [Formula: see text], which are the primary pharmacokinetic predictors of single-agent preclinical antitumor activity, a preclinical exposure-efficacy surface was characterized, allowing for nonlinear interactions between growth rate inhibition of the agents on a MDA-MB-361 cell line xenograft model. Logistic regression was used to generate an exposure-effect surface for [Formula: see text] and [Formula: see text] versus clinical toxicity outcomes [experiencing a dose-limiting toxicity (DLT)] in single-agent and combination dose-escalation studies. A maximum tolerated exposure curve was defined at which DLT probability was 25%; predicted antitumor activity along this curve was used to determine optimal RP2D.

RESULTS

The toxicity constraint curve determined from early clinical data predicted that any clinically tolerable combination was unlikely to result in greater antitumor activity than either single-agent TAK-117 or TAK-228 administered at their respective MTDs. Similar results were obtained with 10 other cell lines, with one agent or the other predicted to outperform the combination.

CONCLUSIONS

This methodology represents a general, principled way of evaluating and selecting optimal RP2D combinations in oncology. The methodology will be retested upon availability of clinical data from TAK-117/TAK-228 combination phase II studies..

摘要

目的

联合治疗方案的推荐 II 期剂量(RP2D)确定是一个在临床可耐受范围内最大化抗肿瘤活性的约束优化问题,以提供广泛的治疗指数。本文开发并测试了一种解决该问题的方法,该方法利用了 TAK-117(一种 PI3Kα 抑制剂)和 TAK-228(一种 TORC1/2 双重抑制剂)联合用药的临床前和临床数据。

实验设计

利用游离分数校正后的平均浓度 [Formula: see text] 和 [Formula: see text],这是单药抗肿瘤活性的主要药代动力学预测指标,对药物的临床前暴露-疗效表面进行了特征描述,允许在 MDA-MB-361 细胞系异种移植模型中 agents 的生长抑制率之间存在非线性相互作用。利用逻辑回归生成了 [Formula: see text] 和 [Formula: see text] 与单药和联合剂量递增研究中临床毒性结局(发生剂量限制毒性(DLT))的暴露-效应曲面。在 DLT 概率为 25%的情况下定义了最大耐受暴露曲线;沿着该曲线预测的抗肿瘤活性用于确定最佳 RP2D。

结果

从早期临床数据中确定的毒性约束曲线表明,任何临床可耐受的组合都不太可能比单独使用各自 MTD 的 TAK-117 或 TAK-228 产生更大的抗肿瘤活性。用其他 10 种细胞系得到了类似的结果,其中一种药物或另一种药物的预测效果优于联合用药。

结论

该方法代表了一种在肿瘤学中评估和选择最佳 RP2D 组合的通用、有原则的方法。一旦有 TAK-117/TAK-228 联合 II 期研究的临床数据,该方法将进行重新测试。

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