Presentation: 'Bloody' good modeling in cell therapies for pediatric cancer

Cellular therapies such as hematopoietic cell transplantation (HCT) and CAR T-cell therapy involve highly complex clinical procedures, with numerous interacting parameters that make it challenging to compare studies or identify actionable parameters for improving outcomes. Moreover, in pediatric patients, the clinical value of biological predictors to guide immunotherapy outcomes remains limited.

Our research focuses on identifying and validating biological predictors that reliably predict outcomes across diverse pediatric HCT regimens. These predictors allow for the early evaluation of how changes in conditioning protocols or immunosuppressive strategies influence clinical success. This resulted in adaptation in clinical protocols and can be applied using model-based dosing or require therapeutic drug monitoring. We have extended this approach to CAR T-cell therapy, applying insights from HCT to better calibrate conditioning and optimize the efficacy–toxicity balance in CAR T-cell recipients.

To truly advance the field, I argue for greater adoption of standardized immune profiling and harmonized modeling approaches in multicenter trials. Leveraging these tools will enable more precise, data-driven optimization of cell therapies in pediatric oncology — promoting a shift from empirical adjustment to predictive, personalized strategies.