在过去的十年里，免疫检查点抑制剂仍然是晚期非小细胞肺癌（NSCLC）的标准治疗方法。在未经选择的患者中，抗 PD-(L)1 单一疗法的总体缓解率约为 20%。在这项分析中，我们为之前校准的定量系统药理学模型 (QSP) 开发了药代动力学和药效学模块，以模拟巨噬细胞靶向疗法与 PD-L1 抑制相结合在晚期 NSCLC 中的有效性。通过进行计算机模拟临床试验，该模型证实抗 CD47 治疗并不是对 PD-(L)1 阻断耐药的晚期 NSCLC 的二线和后期治疗的最佳选择。此外，该模型预测，与抗 PD-(L)1 疗法联合使用时，抑制巨噬细胞募集（例如使用 CCR2 抑制剂）可能会改善肿瘤体积的缩小，特别是对于可能对抗 PD-（ L)1 单一疗法和肿瘤相关巨噬细胞水平高的疗法。在这里，我们展示了 QSP 平台在根据临床前或早期临床试验数据预测涉及免疫检查点抑制剂的新型药物组合的有效性方面的应用。© 2024 作者。 《临床和转化科学》由 Wiley periodicals LLC 代表美国临床药理学和治疗学会出版。

Immune checkpoint inhibitors remained the standard-of-care treatment for advanced non-small cell lung cancer (NSCLC) for the past decade. In unselected patients, anti-PD-(L)1 monotherapy achieved an overall response rate of about 20%. In this analysis, we developed a pharmacokinetic and pharmacodynamic module for our previously calibrated quantitative systems pharmacology model (QSP) to simulate the effectiveness of macrophage-targeted therapies in combination with PD-L1 inhibition in advanced NSCLC. By conducting in silico clinical trials, the model confirmed that anti-CD47 treatment is not an optimal option of second- and later-line treatment for advanced NSCLC resistant to PD-(L)1 blockade. Furthermore, the model predicted that inhibition of macrophage recruitment, such as using CCR2 inhibitors, can potentially improve tumor size reduction when combined with anti-PD-(L)1 therapy, especially in patients who are likely to respond to anti-PD-(L)1 monotherapy and those with a high level of tumor-associated macrophages. Here, we demonstrate the application of the QSP platform on predicting the effectiveness of novel drug combinations involving immune checkpoint inhibitors based on preclinical or early-stage clinical trial data.© 2024 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.