AI-Driven Identification of Tumor Targets
The Challenge of Neoantigen Prediction
Neoantigens, unique to individual tumors, are the ideal targets for personalized cancer vaccines. However, predicting which mutations will generate an immunogenic epitope is computationally complex. Neoantigen.ai solves this challenge with advanced deep learning models.
We analyze somatic mutation data from whole-exome sequencing, combining it with patient-specific HLA typing to simulate the complete antigen processing and presentation pathway.
Prioritization for Maximum Efficacy
Our platform goes beyond simple binding prediction, applying sophisticated filters to prioritize neoantigens that exhibit high predicted clonal prevalence, low central tolerance risk, and optimal T-cell recognition potential.
The result is a highly prioritized list of therapeutic candidates, drastically increasing the success rate of personalized vaccine manufacturing and clinical outcomes.
