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Issue 349: This artwork illustrates the interplay between antibody diversity and therapeutic response in oncology. The central bell-shaped curve represents variability in antibody affinities or concentrations across a patient population, highlighting differences in target engagement and immune activity. Surrounding antibodies and tumor cells depict the dynamic balance between immune synapse formation and tumor growth. Quantitative systems pharmacology (QSP) models capture this heterogeneity to predict treatment outcomes. This visualization accompanies our recent study in Nature Computational Science, where we integrate mechanistic modeling and data-driven approaches to optimize bispecific antibody (BsAb) therapy for multiple myeloma. Key findings include identifying exposure-response relationships, optimizing dosing strategies, and supporting biomarker-driven patient stratification. This work exemplifies how mechanistic models can justify BsAb dose and regimen within the framework of model-informed drug development.