Quantitative systems pharmacology modeling of macrophage‐targeted therapy combined with PD‐L1 inhibition in advanced NSCLC

Abstract

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.