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Superior Neo-Epitope Selection Powered by Advanced In-Silico Machine-Learning Algorithms

Traditional Neo-Epitope selection methods are cumbersome, non-validated and generate Neo-Epitopes that are mostly non-immunogenic or that can potentially trigger either an immune suppressive response or an adverse immune related adverse event.

EpiVax Therapeutics' Ancer® neoantigen in silico prediction platform, leverages EpiVax's EpiMatrix® and JanusMatrix™ algorithms, state-of-the-art tools that have been externally validated in several prospective vaccine studies and that are broadly utilized worldwide by pharmaceutical and biotechnology companies. Ancer® is designed to enable the discovery of highly immunogenic neoantigens for precision cancer immunotherapies. It is integrated into an end-to-end, GMP ready, robust and already established commercial-grade platform.


In addition, Ancer® (via JanusMatrix™) enables the rapid, in silico, discovery and removal of both:

  • The "Self-Like" inhibitory Treg neoepitopes that may trigger an immune suppressive response. 

  • The “Self-Like” cross-reactive neoepitopes that may trigger an immune related adverse event. 

Ancer® is differentiated from other Neo-Epitope prediction tools (the other tools are based on the publicly available IEDB and NetMHC based algorithms which we have shown to be inaccurate). Note that most approaches combine mass spectrometry or elution methods to increase the accuracy of their predictive algorithms. These additional steps are cumbersome and labor intensive. Ancer® does not require any other epitope selection methods, it is 100% in silico.

Importantly, we have performed head-to-head comparisons and we have showed, consistently, a significantly higher epitope prediction accuracy. Thus, leading to potentially more potent and precise therapeutic cancer immunotherapies.

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