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Understanding Variability in CAR-T Cell Therapy Kinetics

Axicabtagene ciloleucel (axi-cel), a CAR-T cell therapy for relapsed and refractory non-Hodgkin’s lymphoma (NHL), demonstrates substantial inter-individual variability in cellular kinetics. This variability complicates predicting therapeutic outcomes and managing associated toxicities, such as cytokine release syndrome (CRS) and neurological events (NEs). Identifying factors that influence CAR-T kinetics is critical for optimizing treatment and improving patient care.

Study Highlights:

  1. Kinetic Modeling:
    • A piecewise model described axi-cel kinetics, featuring a rapid expansion phase followed by a triexponential decline, including long-term persistence.
    • Over 400 patients from three clinical trials (ZUMA-1, ZUMA-5, ZUMA-7) were analyzed, with 2050 transgene observations contributing to the model.
  2. Covariate Analysis:
    • Despite assessing a broad range of covariates—including patient characteristics, product attributes, disease type, and tumor burden—none substantially influenced axi-cel exposure metrics like peak concentration or long-term persistence.
    • In vitro doubling time during manufacturing and total T-cell dose infused affected the growth phase duration but did not predict exposure variability.
    • Higher peak concentrations were linked to reactive use of tocilizumab or corticosteroids for managing toxicities.
  3. Clinical Implications:
    • Current covariates fail to fully explain the observed variability in axi-cel kinetics, highlighting the need for further research.
    • Future studies should explore additional biological or mechanistic factors to better understand CAR-T dynamics and establish dose–exposure relationships.

Conclusion:

This study sheds light on the challenges of modeling CAR-T kinetics and underscores the importance of continued investigation to refine therapeutic strategies for axi-cel and other CAR-T cell therapies.

Author(s): Magali Chartier, Simone Filosto, Thomas Peyret, Manoj Chiney, Francesca Milletti, Justin Budka, Andre Ndi, Jinghui Dong, Saran Vardhanabhuti, Daqin Mao, Stephen Duffull, Michael Dodds, Rhine Shen

Year:

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