Quantitative systems pharmacology model predictions for efficacy of atezolizumab and nab-paclitaxel in triple-negative breast cancer.

摘要: Background Immune checkpoint blockade therapy has clearly shown clinical activity in patients with triple-negative breast cancer, but less than half of the benefit from treatments. While a number ongoing trials are investigating different combinations inhibitors and chemotherapeutic agents, predictive biomarkers that identify most likely to remains one major challenges. Here we present modular quantitative systems pharmacology (QSP) platform for immuno-oncology incorporates detailed mechanisms immune–cancer cell interactions make efficacy predictions treatments using atezolizumab nab-paclitaxel. Methods A QSP model was developed based on published data cancer. With model, generated virtual patient cohort conduct silico retrospective analyses pivotal IMpassion130 trial led accelerated approval nab-paclitaxel programmed death-ligand 1 (PD-L1) positive Available were used calibration validation. Results calibrated placebo comparator arm trial, made identified potential experimental proposed model. The consistent clinically reported endpoints correlated immune biomarkers. We further performed series compare doses schedules two drugs simulated therapeutic optimization. Conclusions This study provides platform, which can be generate cohorts trials. Our findings demonstrate its making immunotherapies chemotherapies, identifying biomarkers, guiding future designs.