thE CHALLENGE
While there has been a growing appreciation for the potential of neoantigen-based immune-oncology therapy, the industry faces two significant challenges in developing effective neoantigen treatments:
1) Low accuracy in predicting and choosing neoantigens;
2) Low delivery efficiency of cancer vaccines
The combined result is a low therapeutic potency of cancer vaccine treatments, which decrease the viability of neoantigen therapeutics for a broader range of cancer treatments.
Our Solutions
PepGene combines its unique advantages in both computational and experimental platforms to develop personalized cancer vaccines as a valid and low-risk treatment feasible to a wide range of cancer patients:
Novel Neoantigen Sources
The majority of current neoantigen predictions and investigations focus on somatic mutations such as SNVs and INDELs, which limits the sources of potential neoantigens. PepGene’s algorithm aims to cover neoantigens from both coding regions (SNV and INDEL) and non-coding regions, which has been reported to generate more neoantigens than coding regions.
AI Algorithm Engine
PepGene is building an AI engine to improve neoantigen predictions by using in-house generated data. It is also partnering with XtalPi to incorporate powerful physics interaction algorithms to further enhance the accuracy of neoantigen predictions.
Novel Delivery System
PepGene’s unique carrier-free vaccine delivery technology helps enhance the in-vivo half-life and the immune-activation potency of cancer vaccines. The robustness of the delivery technology has been well proven in the mouse model.
Our Therapeutic Strategies
Personalized peptide vaccine
(PPV)
Synthesize patient-specific cancer vaccines based on the patient’s unique neoantigen profile
Universal peptide vaccine
(UPV)
Match off-the-shelf cancer vaccines to the right patient based on the patient’s neoantigen profile