Division of Pharmacy and Optometry, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester, United Kingdom (D.H., H.M., L.A., K.O.); DMPK (S.G., J.Y.) and Biosciences (P.F., A.S.), Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, United Kingdom; and DMPK, Research and Early Development, Neuroscience R&D, AstraZeneca, Cambridge, United Kingdom (M.D.).
Division of Pharmacy and Optometry, Faculty of Biology, Medicine, and Health, University of Manchester, Manchester, United Kingdom (D.H., H.M., L.A., K.O.); DMPK (S.G., J.Y.) and Biosciences (P.F., A.S.), Research and Early Development, Oncology R&D, AstraZeneca, Cambridge, United Kingdom; and DMPK, Research and Early Development, Neuroscience R&D, AstraZeneca, Cambridge, United Kingdom (M.D.)
J Pharmacol Exp Ther. 2023 Oct;387(1):44-54. doi: 10.1124/jpet.122.001572. Epub 2023 Jun 22.
Clinical trials assessing the impact of radiotherapy (RT) in combination with DNA damage response pathway inhibitors (DDRis) and/or immune checkpoint blockade are currently ongoing. However, current methods for optimizing dosage and schedule are limited. A mathematical model was developed to capture the impacts of RT in combination with DDRi and/or anti-PD-L1 [immune checkpoint inhibitor (ICI)] on tumor immune interactions in the MC38 syngeneic tumor model. The model was fitted to datasets that assessed the impact of RT in combination with the DNA protein kinase inhibitor (DNAPKi) AZD7648. The model was further fitted to datasets from studies that were used to assess both RT/ICI combinations as well as RT/ICI combinations followed by concurrent administration of the poly ADP ribose polymerase inhibitor (PARPi) olaparib. Nonlinear mixed-effects modeling was performed followed by internal validation with visual predictive checks (VPC). Simulations of alternative dosage regimens and scheduling were performed to identify optimal candidate dosage regimens of RT/DNAPKi and RT/PARPi/ICI. Model fits and VPCs confirmed a successful internal validation for both datasets and demonstrated very small differences in the median, lower, and upper percentile values of tumor diameters between RT/ICI and RT/PARPi/ICI, which indicated that the triple combination of RT/PARPi/ICI at the given dosage and schedule does not provide additional benefit compared with ICI in combination with RT. Simulation of alternative dosage regimens indicated that lowering the dosage of ICI to between 2 and 4 mg/kg could induce similar benefits to the full dosage regimen, which could be of translational benefit. SIGNIFICANCE STATEMENT: This work provides a mixed-effects model framework to quantify the effects of combination radiotherapy/DNA damage response pathway inhibitors/immune checkpoint inhibitors in preclinical tumor models and identify optimal dosage regimens, which could be of translational benefit.
评估放疗（RT）联合 DNA 损伤反应通路抑制剂（DDRis）和/或免疫检查点抑制剂（ICI）对肿瘤免疫相互作用影响的临床试验正在进行中。然而，目前优化剂量和方案的方法有限。本研究建立了一个数学模型，以捕捉 RT 联合 DDRi 和/或抗 PD-L1（免疫检查点抑制剂（ICI））对 MC38 同源肿瘤模型中肿瘤免疫相互作用的影响。该模型适用于评估 RT 联合 DNA 蛋白激酶抑制剂（DNAPKi）AZD7648 影响的数据集。该模型进一步适用于评估 RT/ICI 组合以及 RT/ICI 组合后同时给予多聚 ADP 核糖聚合酶抑制剂（PARPi）奥拉帕利的研究数据集。进行非线性混合效应模型拟合，然后进行内部验证，采用可视化预测检查（VPC）。进行替代剂量方案和方案安排的模拟，以确定 RT/DNAPKi 和 RT/PARPi/ICI 的最佳候选剂量方案。模型拟合和 VPC 证实了两个数据集的内部验证均取得成功，并表明 RT/ICI 和 RT/PARPi/ICI 之间肿瘤直径中位数、下限和上限百分位数值非常小，这表明在给定剂量和方案下，RT/PARPi/ICI 的三联组合与 RT 联合 ICI 相比没有提供额外的益处。替代剂量方案的模拟表明，将 ICI 的剂量降低到 2 至 4 mg/kg 之间可能会产生与全剂量方案相似的获益，这可能具有转化意义。
本研究提供了一个混合效应模型框架，用于量化联合放疗/DNA 损伤反应通路抑制剂/免疫检查点抑制剂在临床前肿瘤模型中的作用，并确定最佳剂量方案，这可能具有转化意义。
