Early identification of relapse and treatment optimization in acute lymphoblastic leukaemias through mathematical modelling and discriminant analysis.

Acute lymphoblastic leukaemias is the most frequent type of pediatric cancer. About 30% of patients relapse after first-line chemotherapies and require other types of treatment. This project intends to identify precisely, using mathematical techniques, which patients cannot be cured using standard chemotherapies and help in designing optimal therapeutical strategies for them.

Why Mathematics?

Mathematics provides a solid foundation for the development of quantitative biomarkers and to contruct optimal treatment strategies on its basis. This project includes elements of different subfields of mathematics including: mathematical modelling, ordinary differential equations, topology and statistics.

The Team

The research team includes María Rosa Durán (MOLAB-UCA, PI), Cristina Blázquez (Jerez Hospital), F. J. Rodríguez (Jerez Hospital), Lourdes Hermosín (Jerez Hospital), Manuel Ramírez Orellana (Niño Jesús Children’s Hospital, Madrid), José C. Camacho (UCA, Spain), Víctor M. Pérez García (MOLAB-UCLM), Salvador Chulián (MOLAB-UCA) and Álvaro Martínez Rubio (MOLAB-UCA).

Beyond this project

The methodologies to be developed in this project can be extended to other haematologic malignancies such as adult leukaemias or lymphomas, where flow-cytometry techniques are also used for the diagnosis and follow-up of the disease.