Speaker
Description
Blinatumomab is a bi-specific T-cell engager that links CD3+ T-cells to CD19+ B-cells, leading to T-cell-mediated B-cell lysis. While it has improved outcomes in relapsed/refractory B-cell precursor ALL (r/r B-ALL), treatment response remains highly variable and the underlying immunological mechanisms are not fully understood.
T-cell exhaustion and impaired immune fitness may contribute to treatment resistance. CD226 (DNAM-1) is a co-stimulatory receptor possibly implicated in anti-tumor immunity and its downregulation may reflect early transitions toward dysfunctional states.
We developed a mechanistic ordinary differential equation (ODE) model distinguishing CD226+ and CD226- T-cell subpopulations during blinatumomab treatment. We incorporate differences in baseline immune fitness between medium- and high-risk pediatric r/r B-ALL patients, reflecting differences in prior chemotherapy exposure. By integrating longitudinal patient cell-count data with Bayesian inference, we characterize patient-specific tumor-immune dynamics under treatment. We further assess parameter identifiability and sensitivity, and evaluate the clinical relevance of inferred immune fitness dynamics. Overall, our modeling, in close collaboration with clinical colleagues, establishes a productive cycle that integrates mathematical modeling and novel data collection strategies at clinically relevant time points to improve bi-specific T-cell engager therapy for pediatric B-ALL.
