Translating B-Cell and Plasma-Cell Targeting from Oncology to Autoimmunity: Modalities, Quantitative Bridging, and a Development Roadmap.

B cells drive B-cell malignancies and diverse autoimmune diseases through autoantibody production, antigen presentation, and cytokine dysregulation, and persistence of pathogenic B-cell or plasma-cell compartments. Across autoimmune diseases, the dominant pathogenic compartment varies, ranging from precursor-dependent states to tissue-compartment inflammation and long-lived plasma cell-weighted autoantibody production. This review synthesizes the biological rationale for B-cell-axis targeting across oncology and autoimmunity and proposes a pathobiological framework spanning precursor-dependent, compartment-dominant, and long-lived plasma cell-weighted archetypes. We outline the mechanisms, lineage coverage, depletion depth, durability, and tolerability of CD20-, CD19-, CD38-, and BCMA-directed antibodies, bispecific T-cell engagers, and chimeric antigen receptor (CAR) T cells, and map these modalities onto biologically defined autoimmune archetypes. We also compare dosing paradigms, pharmacokinetics/pharmacodynamics (PK/PD), exposure-response relationships, and safety trade-offs between oncology-style induction and chronic maintenance in autoimmunity, emphasizing biomarker-guided retreatment, infection-risk mitigation, and regimen adaptation for non-malignant disease. Clinically, therapies developed for lymphoma and myeloma have transformed B-cell cancer care and are now being repurposed for rheumatoid arthritis, multiple sclerosis, neuromyelitis optica spectrum disorder, IgG4-related disease, myasthenia gravis, systemic lupus erythematosus, and related disorders. We summarize pivotal translational inflection points, from rituximab extension beyond lymphoma to approvals of ocrelizumab, ofatumumab, ublituximab, and inebilizumab in neuroimmunology. We further review plasma cell-directed and T-cell-engaging strategies for deep immune resets in refractory disease, while clarifying implications for trial design, long-term safety, and implementation. Finally, we introduce a model-informed roadmap integrating population PK/PD, exposure-response, and quantitative systems pharmacology to optimize indication selection, patient enrichment, and dose/regimen design-supporting confident extrapolation rather than empiricism.