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抗体药物偶联物疗效从小鼠实验性肿瘤到临床的转化:一种 PK/PD 方法。

On translation of antibody drug conjugates efficacy from mouse experimental tumors to the clinic: a PK/PD approach.

机构信息

Department of Pharmacokinetics Dynamics and Metabolism, Translational Research Group, Pfizer Global Research and Development, Groton, CT, 06340, USA,

出版信息

J Pharmacokinet Pharmacodyn. 2013 Oct;40(5):557-71. doi: 10.1007/s10928-013-9329-x. Epub 2013 Aug 10.

Abstract

Objectives of the present investigation were: (1) to compare three literature reported tumor growth inhibition (TGI) pharmacodynamic (PD) models and propose an optimal new model that best describes the xenograft TGI data for antibody drug conjugates (ADC), (2) to translate efficacy of the ADC Trastuzumab-emtansine (T-DM1) from mice to patients using the optimized PD model, and (3) to apply the translational strategy to predict clinically efficacious concentrations of a novel in-house anti-5T4 ADC, A1mcMMAF. First, the performance of all four of the PD models (i.e. 3 literature reported + 1 proposed) was evaluated using TGI data of T-DM1 obtained from four different xenografts. Based on the estimates of the pharmacodynamic/pharmacokinetic (PK/PD) modeling, a secondary parameter representing the efficacy index of the drug was calculated, which is termed as the tumor static concentration (TSC). TSC values derived from all four of the models were compared with each other, and with literature reported values, to assess the performance of these models. Subsequently, using the optimized PK/PD model, PD parameters obtained from different cell lines, human PK, and the proposed translational strategy, clinically efficacious doses of T-DM1 were projected. The accuracy of projected efficacious dose range for T-DM1 was verified by comparison with the clinical doses. Aforementioned strategy was then applied to A1mcMMAF for projecting its efficacious concentrations in clinic. TSC values for A1mcMMAF, obtained by fitting TGI data from 4 different xenografts with the proposed PK/PD model, were estimated to range from 0.6 to 11.5 μg mL⁻¹. Accordingly, the clinically efficacious doses for A1mcMMAF were projected retrospectively. All in all, the improved PD model and proposed translational strategy presented here suggest that appropriate correction for the clinical exposure and employing the TSC criterion can help translate mouse TGI data to predict first in human doses of ADCs.

摘要

本研究的目的是

(1)比较三种文献报道的肿瘤生长抑制(TGI)药效学(PD)模型,并提出一种最佳的新模型,以最佳描述抗体药物偶联物(ADC)的异种移植 TGI 数据;(2)利用优化的 PD 模型将 ADC 曲妥珠单抗-美坦新(T-DM1)在小鼠中的疗效转化为患者;(3)应用该转化策略预测新型内源性抗 5T4 ADC(A1mcMMAF)的临床有效浓度。首先,使用来自四种不同异种移植的 T-DM1 的 TGI 数据评估所有四种 PD 模型(即 3 种文献报道的+1 种提出的)的性能。基于药代动力学/药效学(PK/PD)建模的估计,计算了一个代表药物疗效指数的二次参数,称为肿瘤静态浓度(TSC)。比较了来自所有四个模型的 TSC 值彼此之间,并与文献报道的值进行了比较,以评估这些模型的性能。随后,使用优化的 PK/PD 模型,根据不同细胞系、人体 PK 和提出的转化策略获得的 PD 参数,预测 T-DM1 的临床有效剂量。通过比较与临床剂量,验证了预测的 T-DM1 有效剂量范围的准确性。然后,将上述策略应用于 A1mcMMAF,以预测其在临床上的有效浓度。通过将 4 种不同异种移植的 TGI 数据与提出的 PK/PD 模型拟合,估算 A1mcMMAF 的 TSC 值范围为 0.6 至 11.5μg/mL。因此,回顾性预测了 A1mcMMAF 的临床有效剂量。总之,这里提出的改进的 PD 模型和提出的转化策略表明,适当校正临床暴露并采用 TSC 标准有助于将小鼠 TGI 数据转化为预测 ADC 的首次人体剂量。

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