Russian Scientists Are Developing Software to Predict Tumor Growth
The new program is expected to compare and assess different treatment regimens, taking into account individual patient characteristics.
Researchers at Volgograd State University are developing software aimed at improving cancer treatment outcomes. According to Maksim Polyakov, an associate professor in the university’s Department of Information Systems and Computer Modeling, the mathematical model and software will make it possible to predict and evaluate the potential effectiveness of different tumor treatment regimens using CAR-T therapy—a method in which a patient’s immune cells are modified in a laboratory to recognize and destroy cancer cells and are then returned to the body.
Find and Neutralize
Polyakov noted that the main challenge is that CAR-T therapy, which is effective for blood cancers, has shown limited effectiveness against the most common solid tumors, including breast, lung, brain, and other cancers. One of the key goals of modern cancer immunology is to understand why this barrier exists and how it can be overcome. The Volgograd team’s work is intended to help clarify the problem.
In addition, the new software will allow researchers to generate personalized forecasts of tumor responses and identify which treatment parameters may be critical for overcoming resistance. The project has received support from the Russian Science Foundation.
In Russia, all available resources—including advanced technologies—are being mobilized to improve early cancer detection, as earlier diagnosis significantly increases a patient’s chances of recovery. The country has previously registered an AI-based system called Galenos.AI, which can diagnose 16 types of cancer at early stages with accuracy of up to 98%.
Other Russian developments are also helping doctors make decisions more quickly, select therapies based on a tumor’s molecular profile, carry out more precise and less invasive treatments, and predict potential outcomes.
