Review demonstrates the potential of quantitative systems pharmacology models for anti-CD19 CAR T-cell therapy in autoimmune diseases, highlighting pathways to optimize dosing and personalized care.
Anti-CD19 CAR T-cell therapy has produced major advances in treating hematologic malignancies. Recently, researchers have explored its use in autoimmune diseases. However, the complex pathogenesis and high heterogeneity of these disorders create substantial uncertainty about treatment efficacy and safety in clinical settings. Quantitative systems pharmacology (QSP) models integrate multiple pathophysiological mechanisms and map real patients onto virtual “digital twins” to simulate the in vivo behavior of a given CAR T-cell dose after infusion and to predict benefits and risks. Such models can also inform optimization of infusion dosing, advancing personalized therapy. This review summarizes current applications of anti-CD19 CAR T cells in autoimmune diseases and surveys the state of quantitative mathematical modeling in the field. Building on existing models, we propose an idealized QSP framework intended to guide the development of more refined, actionable models.
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Sun et al. (2026) studied this question.
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