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抗体药物偶联物在肿瘤内空间分布的机制建模:肿瘤学中给药策略的见解。

Mechanistic Modeling of Intra-Tumor Spatial Distribution of Antibody-Drug Conjugates: Insights into Dosing Strategies in Oncology.

机构信息

Clinical Pharmacology and Pharmacometrics, AbbVie Inc., North Chicago, Illinois, USA.

出版信息

Clin Transl Sci. 2021 Jan;14(1):395-404. doi: 10.1111/cts.12892. Epub 2020 Oct 19.

DOI:10.1111/cts.12892
PMID:33073529
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7877868/
Abstract

Antibody drug conjugates (ADCs) provide targeted delivery of cytotoxic agents directly inside tumor cells. However, many ADCs targeting solid tumors have exhibited limited clinical efficacy, in part, due to insufficient penetration within tumors. To better understand the relationship between ADC tumor penetration and efficacy, previously applied Krogh cylinder models that explore tumor growth dynamics following ADC administration in preclinical species were expanded to a clinical framework by integrating clinical pharmacokinetics, tumor penetration, and tumor growth inhibition. The objective of this framework is to link ADC tumor penetration and distribution to clinical efficacy. The model was validated by comparing virtual patient population simulations to observed overall response rates from trastuzumab-DM1 treated patients with metastatic breast cancer. To capture clinical outcomes, we expanded upon previous Krogh cylinder models to include the additional mechanism of heterogeneous tumor growth inhibition spatially across the tumor. This expansion mechanistically captures clinical response rates by describing heterogeneous ADC binding and tumor cell killing; high binding and tumor cell death close to capillaries vs. low binding, and high tumor cell proliferation far from capillaries. Sensitivity analyses suggest that clinical efficacy could be optimized through dose fractionation, and that clinical efficacy is primarily dependent on the ADC-target affinity, payload potency, and tumor growth rate. This work offers a mechanistic basis to predict and optimize ADC clinical efficacy for solid tumors, allowing dosing strategy optimization to improve patient outcomes.

摘要

抗体药物偶联物(ADCs)可将细胞毒性药物靶向递送至肿瘤细胞内。然而,许多针对实体瘤的 ADC 表现出有限的临床疗效,部分原因是在肿瘤内的穿透性不足。为了更好地理解 ADC 肿瘤穿透性与疗效之间的关系,先前应用于临床前物种的探索 ADC 给药后肿瘤生长动力学的 Krogh 圆柱模型通过整合临床药代动力学、肿瘤穿透性和肿瘤生长抑制作用扩展到临床框架中。该框架的目的是将 ADC 肿瘤穿透性和分布与临床疗效联系起来。该模型通过将虚拟患者群体模拟与曲妥珠单抗-DM1 治疗转移性乳腺癌患者的总缓解率进行比较来验证。为了捕获临床结果,我们在之前的 Krogh 圆柱模型基础上进行了扩展,包括在肿瘤内空间上具有异质性肿瘤生长抑制的额外机制。通过描述 ADC 结合和肿瘤细胞杀伤的异质性,该扩展在机制上捕捉了临床缓解率;靠近毛细血管的高结合和高肿瘤细胞杀伤与远离毛细血管的低结合和高肿瘤细胞增殖。敏感性分析表明,通过剂量分割可以优化临床疗效,并且临床疗效主要取决于 ADC 靶向亲和力、有效载荷效力和肿瘤生长速度。这项工作为预测和优化实体瘤 ADC 的临床疗效提供了一个机制基础,允许优化给药策略以改善患者结局。

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