Combining AI and MC Simulations for Real-Time Quantification of DNA Damage Response to Ionizing Radiation – ARSINOE

The ARSINOE project represents a significant advancement in the field of radiation therapy planning, leveraging artificial intelligence (AI) to optimize the treatment process. By integrating AI into Monte Carlo (MC) simulations, ARSINOE aims to predict the biological consequences of ionizing radiation (IR) exposure with unprecedented accuracy and speed.

This innovative approach offers several key benefits:
- Accelerated MC Simulations: ARSINOE introduces AI models to significantly reduce the computational time required for MC simulations, making them more practical for clinical use.
- Enhanced Accuracy: The project incorporates AI-powered models for particle track structure and chemical diffusion, significantly improving the precision of MC simulations.
- Expanded Applicability: ARSINOE extends the capabilities of MC simulations to include ultra-high dose rate (UHDR) radiation techniques and population-level damage assessment, offering new possibilities for cancer treatment and research.

To achieve these goals, ARSINOE will develop a comprehensive database by collecting and organizing data on IR-induced biological effects. Will develop and train AI models to predict cell damage and survival based on MC simulation data. Integrate the AI models into the Geant4-DNA MC toolkit, making these innovative techniques accessible to the broader scientific community.

By combining AI with MC simulations, ARSINOE has the potential to create personalized treatment plans, improve treatment outcomes and advance radiation therapy research. By harnessing the power of AI and MC simulations, ARSINOE offers a promising solution to the challenges faced in modern radiation oncology.