Accelerate Precision Immuno-Oncology Development by Using Predictive Bioinformatics Algorithms for Neoantigen Peptide Synthesis

Neoantigens, also known as tumor-specific antigens, is a class of HLA-bound peptides generated by tumor-specific mutations. They are not present in normal tissues, thus neoantigen based personalized immuno-oncology drugs are a relatively new therapeutic avenue that have shown strong anti-tumor efficacy in the clinic. Neoantigen peptides have been widely reported to be difficult to synthesize due to their hydrophobicity, length, and charge. Leveraging extensive peptide synthesis experience, GenScript has developed NeoPre™, a predictive algorithm which is able to determine peptide synthesis difficulty based on sequence alone. NeoPre™ can then recommend the most efficient approach to successfully synthesizing peptides using one of GenScript's many synthesis platforms. This presentation will highlight how NeoPre™ identifies synthesis difficulty and review successful cases of difficult neoantigen peptide synthesis from several researchers.

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