Researchers at the Data Science and Artificial Intelligence Institute (DATAI) of the University of Navarra have developed new AI tools to create personalized cancer treatments based on a patient’s immune health, called “immunological fitness.”
Published in the Journal for ImmunoTherapy of Cancer, this study analyzed data from over 3,000 patients with lung and urothelial cancer, two of the most common cancers in the United States. The researchers used machine learning to find unique genetic markers at different stages of cancer and created the “IFIT score,” which measures each patient’s immune system status, or “immunological fitness.” This score helps doctors customize immunotherapy for better results.
“This tool can predict how well a patient might respond to treatment by evaluating their immune system’s activity at different cancer stages,” said Rubén Armañanzas, head of DATAI’s Digital Medicine Lab.
Immunotherapy is one of the most promising treatments for cancer, and AI technology allows doctors to adapt treatments to fit each patient’s immune profile. The University of Navarra presented these findings at the Society for Immunotherapy of Cancer (SITC 2024) conference in Houston, where they were recognized as one of the top 100 research presentations.
Using AI, the study identified specific cellular patterns that change with each stage of the disease, allowing doctors to better understand and predict immunotherapy effectiveness. This research, part of a collaboration through the imCORE Network, involves top cancer research centers in 10 countries and represents a global effort to improve cancer care through personalized medicine.
Source: medicalxpress
