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.
Funding entity
Junta de Andalucía (2020-2023)
Universidad de Cádiz
Principal investigator
3 years