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IMMUNOENGINE

Neoantigen prediction platform

Fuelled by advances in genomic and proteomic technologies, personal promises to innovate cancer therapy and to target previously untreatable tumors. A critical part of developing such strategies is finding those antigens that have the potential to elicit a sufficiently strong immune response. For the past myNEO Therapeutics has been developing its antigen prediction platform, providing a robust pipeline focused on the identification and prediction of antigen targets within the full genome of tumors.

The process starts with the collection of both patient blood and a tumor biopsy.

Whole-Genome Sequencing data from matched tumor and normal DNA is required for each patient.

Following alignment of these reads to the genome, somatic gene alterations in the tumor genome are detected using a collection of algorithms called ‘neoX’.

Next, these somatic gene alterations are translated in-silico to obtain the tumor-specific peptides

In a last step, the peptides are prioritized using an immunogenicity predictor (neoIM) and two presentation predictors (neoMS and MHCrank).

OUR PROPRIETARY ALGORITHMS

Rapid selection of the most optimal targets

smORFin

Best-in-class algorithm specifically trained to identify smORFs in transcripts and to assess their coding potential for camyotopes.

neoMS

Best-in-class presentation prediction algorithm that takes into account the full antigen processing pathway.

neoIM

First-in-class immunogenicity prediction algorithm that predicts the activation of CD8+ T-cells by a given epitope.

OUR PUBLICATIONS

Scientific papers

Neoantigen-directed therapeutics in the clinic: where are we?

Where are we: Trends in Cancer – 2023

Challenges in neoantigen-directed therapeutics

Challenges: Cancer Cell – 2022

Improving T-cell mediated immunogenic epitope identification via machine learning: the neoIM model

neoIM model: BioRxiv – 2022

neoMS: attention-based prediction of MHC-I epitope presentation

neoMS: BioRxiv – 2022

Whitepapers

Liquid biopsies in personalized medicine – future and pitfalls

There is more to the genome: increasing the range of actionable high-confidence neoantigen discovery by whole genome sequencing

Optimal neoantigen prediction and selection – where’s the sweet spot?

How the gut microbiome affects cancer immunotherapy

Beyond SNVs and indels for neoantigen prediction in cold tumors

The promise of personalized cancer vaccination

Is immunotherapy the holy grail in the fight against cancer

Immunosurveillance and the importance of CD4 T-cells in cancers

Innovating immunotherapies,
transforming tomorrow

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