The fight against cancer is no longer carried out only in laboratories and hospitals: it is also taking place among data, algorithms, and mathematical equations. The “Recaída 0” (Relapse 0, in english) project was created with an ambitious goal: to improve the early detection of relapse risk in leukemia patients through the use of mathematical tools, data analysis, and artificial intelligence. This multidisciplinary approach combines biology, computer science, and mathematical modeling to better understand the behavior of tumor cells and move toward more personalized and effective treatments.
The research focuses mainly on Lymphoblastic Leukemia, the type of cancer most frequently diagnosed in children. Although treatments have improved significantly in recent years, one of the major challenges remains identifying which patients are more likely to experience a relapse. Detecting this risk as early as possible would allow treatments to be better adapted and medical follow-up to be improved.
To achieve this, the project works with data obtained through flow cytometry, a technique capable of analyzing thousands of individual cells and providing highly detailed information about their behavior. Thanks to these data, an extensive database has been created, making it possible to better study the differences between patients and advance new methods of diagnosis and monitoring.
One of the project’s main achievements has been the development of algorithms capable of automatically recognizing different types of cells and detecting relevant patterns that may go unnoticed by the human eye. These tools not only speed up the work of specialists, but can also increase the accuracy of analyses and support more personalized clinical decisions.
In addition, the project uses mathematical models to simulate how tumor cells evolve within the bone marrow and how they respond to treatments during the early stages of the disease. These simulations help researchers better understand the interaction between healthy and cancerous cells and allow them to explore different scenarios in the progression of leukemia.
Projects such as “Recaída 0” are important because they help transform the vast amount of information generated by medical studies into useful tools for improving patient care. Through the combination of artificial intelligence, data analysis, and mathematics, it is possible to move toward more precise treatments tailored to each individual patient.
At a time when cancer continues to be one of the greatest challenges in medicine, research like this demonstrates the value of bringing together different scientific disciplines. Collaboration among specialists in biology, medicine, computer science, and mathematics can lead to real advances that improve both diagnosis and patients’ quality of life.
PhD in Mathematics with highest honors (cum laude) from the University of Cádiz, where she also completed her Bachelor’s degree in Mathematics as well as Master’s degrees in Mathematics and Education. Her research began and continues within the “Relapse 0: Mathematics Against Childhood Leukemia” project, focusing her work on the application of mathematical models to biomedical problems. She combines research and teaching with an intense cultural activity and active participation in science outreach initiatives and scientific events. She firmly believes in the power of mathematics as a tool to understand and improve people’s lives.