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Model-informed drug development is increasingly used to support chimeric antigen receptor (CAR)-T-cell therapy programs. However, most population pharmacokinetic (PK) CAR-T-cell models available in literature are variations of an empirical piecewise-linear model, which accurately describes the observed data but lacks a mechanistic foundation. This limits its use for simulations of scenarios beyond the observed data. This work presents a mechanism-based population PK framework that aims to bridge existing empirical and mechanistic CAR-T-cell modeling approaches. The model was developed using a clinical database of 473 patients with various relapsed or refractory lymphomas (large B cell, follicular, marginal zone, or mantle cell) receiving axicabtagene ciloleucel or brexucabtagene autoleucel. The framework incorporates two CAR-T-cell compartments alongside a latent kinetic-pharmacodynamic tumor compartment, utilizing a continuous, mechanistically-driven approach to characterize the observed PK profiles. A covariate search identified five significant covariates impacting PK (P < 0.001). Among these, only product type/mantle cell lymphoma (MCL) disease type was deemed to have clinically relevant effects on exposure. Despite its mechanistic basis, the model remains parsimonious, requiring only seven structural parameters, and no additional data beyond post-infusion CAR-T-cell peripheral blood concentrations and covariate information routinely collected in clinical trials. With its mechanistic foundation but parsimonious structure, this model balances data-driven practicality with the integration of underlying biological processes. Its ability to identify relevant covariates could make it a valuable tool in supporting drug development decisions.
Laughlin et al. (Tue,) studied this question.