Patient-Specific Determinants of Response to BCMA- and GPRC5D-Targeted CAR T-Cell Therapy in Multiple Myeloma: A QSP Analysis of Clinical Trial and Real-World Data

Nearly all patients with relapsed/refractory multiple myeloma (RRMM) eventually relapse after CAR T-cell therapy. The authors built a mechanistic quantitative systems pharmacology (QSP) model of myeloma growth and CAR T-cell therapy, using clinically measurable biomarkers (M protein and serum-free light chain) to predict response and relapse. The model reproduced published pharmacokinetic and biomarker data from anti-BCMA (ide-cel, cilta-cel) and anti-GPRC5D (MCARH109) therapies, and was validated against real-world data from 29 RRMM patients treated with commercial anti-BCMA CAR T. Virtual-trial simulations identified tumor-intrinsic factors (disease burden, low antigen expression) and CAR T-intrinsic factors (low killing rate) as drivers of worse outcomes, and predicted that a lower baseline percentage of normal plasma cells is associated with better overall response. For combination strategies, sequential dosing beginning with anti-GPRC5D followed by anti-BCMA CAR T was predicted to give the most durable response. The model offers a framework for investigating relapse mechanisms, multi-antigen targeting, and clinical trial/dosing optimization. Built in Certara’s QSP Designer software.