KAIST’s research team has developed an AI-driven technology that predicts B cell reactivity to neoantigens, marking a significant advancement in personalized cancer vaccine design. Neoantigens are unique protein markers found only on cancer cells, making them ideal targets for immune system attacks. While traditional cancer vaccines primarily focus on stimulating T cells, this new approach incorporates B cell reactivity, which plays a crucial role in generating long-lasting immune memory. By enabling the immune system to "remember" cancer cells, the technology aims to prevent tumor recurrence after treatment. The AI model analyzes individual patient data, including tumor mutations and immune system profiles, to identify neoantigens most likely to trigger a strong and durable B cell response. This personalized strategy enhances the vaccine’s ability to mount a sustained defense, moving beyond short-term immune activation. The system leverages deep learning to predict which neoantigens are most immunogenic and capable of eliciting high-affinity antibodies. This level of precision allows for the design of vaccines tailored to each patient’s unique cancer profile, significantly improving the potential for long-term protection. The development represents a major step forward in the evolution of cancer immunotherapy, bridging a key gap in current vaccine strategies. By integrating B cell responses into the design process, the technology not only boosts immediate anti-tumor activity but also establishes lasting immunity—offering the promise of durable remission and reduced relapse rates.