Today, Álvaro Martínez-Rubio has presented his PhD thesis entitled "Data analysis and mathematical modelling to improve outcomes in pediatric hematooncology". 

Hematological malignancies are the most frequent cancers in patients between 0 and 19 years, with Acute Lymphoblastic Leukemia and Non-Hodgkin Lymphoma being the most common diagnoses. Chemotherapy schemes initiated in the 1960s have been progressively refined to reach an overall survival nearing 90%, but relapse still constitutes an important cause of disease-related death for this age group. New approaches are needed to identify this portion of patients and to optimize the new therapies that are being developed for tackling relapse.

In this thesis mathematical tools have been used to address these issues. First, to refine risk assessment by means of machine learning techniques based on fow cytometry data at diagnosis from a large database of pediatric patients. This diagnostic technique holds abundant single-cell information which is not currently employed in risk stratification. Second, to simulate CAR T-cell therapy by means of mathematical models. This therapy has become the most promising alternative for relapse patients but there are still a number of unknowns that preclude its optimal application.

With respect to diagnosis, the candidate has shown that different characterizations of flow cytometry data are required to uncover its potential prognostic value, pending the availability of high-dimensional omics data at diagnosis and more comprehensive panels of surface proteins. With respect to treatment, he demonstrated that mathematical models adequately describe the dynamics of CAR T-cell therapy and illustrated the crucial role of individual patient data for evaluating hypotheses, testing alternative protocols and identifying biomarkers of response.

Co-supervised by María Rosa (MOLAB-UCA) and Víctor M. Pérez-García (MOLAB-UCLM) this work has been sponsored by Asociación Pablo Ugarte (https://www.asociacionpablougarte.es/), who have supported Álvaro's PhD contract.