In search of digital twins for success in the treatment of children with leukemia

Leukemia is a disease that originates in the bone marrow and changes the characteristics of white blood cells in patients. This is the type of cancer that affects children and adolescents the most: about 300 cases are recorded in Spain every year. But at the same time, childhood leukemia is a mirror in which other diseases in the field of oncology want to see themselves. The survival rate has increased dramatically and more than 80% of children survive the trance. Now a multidisciplinary team led by the Nino Jesus University Children’s Hospital in Madrid wants to save the two out of ten pediatric patients who cannot.

Project key, named Leukodomica And presented this Thursday, it’s creating virtual twins of each patient that can simulate treatments and predict which will work best for each child or adolescent. “We want this to be a new tool to help pediatric oncologists interact with patients so they can simulate on a computer or in an app situations that happen every day when making decisions.” If there are alternatives, the doctor has to choose and would be very interested in experimenting with the child… but that’s not how it’s done. If the child had a twin on the computer, we would gain a lot,” explains Manuel Ramirez Orellana, coordinator of the initiative, head of the oncology department and director of advanced therapy at the state hospital.

This virtual avatar will be generated in a tool that combines “all the information that exists around children and adolescents with leukemia, not just about their disease: what we know about their cell biology, their genetic information, and aspects of It is related to features that have been little discussed before, both genetic and biophysical,” the expert notes.

“In certain cases, despite a successful treatment, usually chemotherapy, after a few years there can be a relapse with complications of the type of metastatic infiltration, in many cases fatal”, explains the professor and director of the Complutense University of Madrid. October 12 i+12 Research Institute Translational Biophysics, Francisco Monroy. The goal of the project is to create models that allow these years to be skipped and quickly and automatically identify the characteristics that make these cells prone to relapse, in order to decide the best approach to the disease.

In labs like Monroe’s, they can already identify these traits — comparable to eye color, hair, or cell height — by looking at them under a microscope. They will do this with the information of about a hundred patients who have passed through the hospital. His malignant cells and the microscope will be transferred to the computer.

This digital twin, which will tell the doctor the probability of treatment success in the case of a flesh-and-blood twin, will store all clinical, biological, genetic, biochemical information and the physical substrate of the abnormal cells. “Not only do we have to use techniques, we tend to develop new ones that allow us to take the data sources that Professor Monroy’s group provides us and do the translation,” explains the principal investigator of the Computational Biophysics Group (BioCompLad) in Pozuelo. De Alarcon, Diego Heraez. His team will be responsible for the development of this technology, which will allow the integration of a large number of biophysical parameters. “Each patient has such complexity that it is necessary to collect and interpret that complexity,” he explains.

“Understanding even the smallest detail of cells”

“It is necessary to understand even the smallest details of these cells,” says Carlos Toroja, the National Cardiovascular Research Center (CNIC) researcher responsible for the sequencing. The scientific and technological advances of the last decades made it possible to move from the analysis of a group of cells to the individual analysis of thousands of them. “When a patient responds to therapy, there’s always a small group in which they do very well … and another in which they don’t.” The purpose of including genetic information is to understand what happens when everything is not as it should be”, – develops the expert.

In order to integrate all these biophysical and genomic data into one platform, complex mathematical formulations will be required. At the Mathematical Oncology Laboratory (Molab) in Ciudad Real, they are experts in developing models to describe tumor progression in different types of malignant processes. One of its senior researchers and head of the University of Castilla-La Mancha, Gabriel Fernández Calvo, explains that the models developed in the project Leukodomica They should “equal to a volume of data that would be staggering, with feature maps of hundreds, even thousands, of cells.” “Through this map, we are trying to offer predictive tools that will allow us to determine the risks of how these patients will respond to first lines of treatment, whether they will really benefit or are better off choosing second lines,” says Fernández Calvo.

A little more than a decade ago, it was almost a utopia that mathematical experts could provide doctors with predictive tools. “This has changed dramatically in recent years, and it’s because of the value of data. If one thing becomes clear, it is that to describe reality and achieve the development of these powerful prediction tools, a large amount of information and powerful algorithms are needed,” notes the Molabi researcher.

In any case, the researchers don’t suggest that it’s the app that makes the decisions. “These are not decisions made by a machine, but based on a machine interpreting what has happened, rather than a human, and making a series of suggestions for action. Whether the weather is forecast, we can communicate or traffic is dictated by digital tools, we aspire to make 21st century medicine more digital and knowledge-enabled,” notes Monroy.

The project is financed with 1.85 million euros from the European Union’s European Fund for Transformation, Research and Sustainability and its implementation period is two years. “Then we have to provide these mathematical models that group together all the knowledge,” explains Monroy, who warns that it must be tested in the clinic with further projects that prove its effectiveness in clinical research standards that reflect the horizon that it reaches after the next four or five years.

“This is a project from a scientific point of view, which is at the edge of knowledge: there are things to invent and discover. From a technical point of view, it is a total vanguard,” Ramirez Orellana points out. He is optimistic: “We know what to do, where to look, they gave us money and we hope to succeed.”

Source: El Diario

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