The researchers of the Data Science and Artificial Intelligence Institute (DATAI) from the University of Navarra have developed artificial intelligence models to personalize immunological therapies in cancer patients.
The study analyzes data from more than 3,000 patients with lung cancer and bladder cancertwo of the most frequently diagnosed types of cancer in Spain in 2024, according to the Spanish Society of Medical Oncology.
Using machine learning models, researchers identified new genetic signatures specific to each stage of the disease and developed a system called “IFIT Index” (“physical immunity” index), which will allow therapies to be personalized, thus improving their effectiveness.
The IFIT Index is a measure or score that assesses the “immunological aptitude” of a patientwhich allows patients to be classified according to the risk they present at each stage of the disease. “This can help predict treatment response based on the activity of your immune system at different stages of cancer treatment,” says Rubén Armañanzas, head of the DATAI digital medicine laboratory and one of the lead authors of the study.
According to the expert, “immunotherapy represents one of the most promising frontiers in the fight against cancerand through the use of artificial intelligence models, we can further refine treatments based on each patient’s immunological profile.
The study from the University of Navarra was presented in Houston (United States)at the Society for the Immunotherapy of Cancer Conference (SITC 2024). This meeting brings together international leaders from academia, regulatory and government agencies, as well as representatives from the pharmaceutical industry, to present the latest advances in cancer immunotherapy.
IFIT Index: system to personalize cancer treatments
The investigation, which was nominated among the top 100 at the conferenceis based on the analysis of the cancer immunity cycle (CIC), which determines how signals from the immune system influence the effectiveness of immunotherapy treatment.
On this basis and using artificial intelligence tools, Researchers propose specific models of cellular activity depending on the molecular stage of the disease and have created the IFIT “physical immunity” index. This advance highlights the relevance of artificial intelligence in personalized medicine, offering new hope in the fight against cancer. The researchers note that the technique will continue to be refined in future joint studies with other types of cancer.
The works result from research camp organized by the Roche Institute for the centers of the imCORE Networkan international network that brings together leading centers of excellence in immuno-oncology from around the world to collaborate in the search for innovative approaches to cancer. This global collaboration, involving the Cancer Center Clínica Universidad de Navarra and other leading cancer research institutes from 10 countries around the world, highlights the collective effort in the search for innovative approaches against cancer. The Government of Navarra also supports some members of the study.
