Sergio Márquez Díaz has presented his Master’s Final Project, titled “Prediction of relapse in Acute Lymphoblastic Leukemia: Discrete Stochastic Model versus Continuous Approaches.”

The work addresses relapse in pediatric acute lymphoblastic leukemia, a key clinical challenge that still affects ~15% of patients despite high overall survival rates.

Sergio developed a two-part modeling framework:

1. Continuous models (ODE-based) describing lymphoid cell dynamics and response to standard chemotherapy and CAR-T treatment.

2. A discrete stochastic model capable of naturally reproducing remission and relapse events by allowing leukemic cell extinction and regrowth.

The approach incorporates cellular heterogeneity to represent sensitive and resistant subclones, offering a mechanistic explanation for relapse and enabling probabilistic relapse prediction.

This work contributes to the Leukodomics Project and advances the development of future virtual patient twins for pediatric ALL.

Congratulations to Sergio for this excellent contribution!