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NEO-ARS®

Neoantigen-Automatic Report System

NEO-ARS® is a comprehensive AI solution that identifies tumor neoantigens by covering the whole process, from NGS data analysis to 3D structure-based prediction of peptide-MHC (pMHC) binding using multiple algorithms.

NEO-ARS®

From Uncertainty to Precision Immunity: NEO-ARS®-Driven Cancer Vaccine Design

While immune checkpoint inhibitors are promising next-generation therapies, response rates remain limited to 10-30%,
leaving many patients without benefit. Consequently, neoantigen-based cancer vaccines capable of inducing patient-
specific immune responses have emerged as a vital alternative.
However, the difficulty in accurate and rapid prediction of immunogenic T cell epitopes has left many cancer vaccine
developers at the early R&D stage. NEO-ARS® technology addresses this bottleneck through AI-based 3D structural
analysis and T cell reactivity prediction.

Overcoming Entry Barriers in Personalized Cancer
Vaccine Development: NEO-ARS®

NEO-ARS Process Funnel Mobile

AI-Driven Neoantigen Target Discovery — Precision Targets for Personalized Cancer Vaccines

NEO-ARS® is an AI-driven platform that rapidly and precisely identifies tumor-specific neoantigens. Leveraging patient-derived
genomic data, it analyzes tumor-specific mutations and predicts their potential to be recognized by immune cells (T cells).
By automating complex processes—from NGS-based variant analysis to peptide–MHC binding prediction and immunogenicity
simulation—into a single AI pipeline, it rapidly predicts personalized neoantigen targets that are difficult to identify with conventional
methods. This enables enhanced precision in target antigen selection and accelerated development in the cancer vaccine and T cell
therapy fields.

Tumor-Only Variant Calling Based on NGS Data Analysis

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Tumor-specific mutations are extracted from patient genomic data to generate peptide candidates. Structure-based prediction based on each patient’s HLA genotype identifies mutant peptides likely to bind specific HLA molecules.

Peptide-Protein Docking and Binding Energy Calculation

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3D peptide–MHC structures are analyzed in silico. Binding poses are generated by molecular docking and optimized using a 3D CNN model. Binding energy and stability are evaluated to identify peptides with high MHC-binding potential.

T cell reactivity prediction

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T cell reactivity is scored by calculating a probability based on a correlation analysis between (i) the structural differences between mutant pMHC and wild-type pMHC and (ii) the experimental dataset of whether T cell responses are induced.

Final Selection of Neoantigen Candidates

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We prioritize final candidates through comprehensive evaluation of immunogenicity, pMHC binding affinity, and binding stability, and select CD8+ T cell epitopes suitable for use in cancer vaccines and TCR-T cell therapies. A list of personalized neoantigen targets is ultimately provided.

NEO-ARS® Pipeline

Physical docking

Mutant peptides

Wildtype peptides

3D CNN model

Multiple binding poses

STEP 1

pMHC Binding Energy

MD simulation

Multiple binding poses

STEP 2

T cell reactivity score

Neoantigen
candidates

Neoantigen candidates

Key Processes of NEO-ARS®

NEO-ARS Core Process Funnel
01

Patient-Derived Sample Collection

Tumor tissue and blood samples are collected for personalized vaccine development.

Tumor tissue and blood samples are obtained from patients to generate foundational data for genomic analysis. These data enable the identification of tumor-specific mutations unique to cancer cells.

02

Genomic Profiling Data Analysis

DNA and RNA sequencing is performed to identify tumor-specific mutations.

DNA and RNA sequencing is conducted on tumor tissues, and AI-driven analysis is used to precisely detect abnormal genetic variants. At this stage, tumor-specific mutations that serve as the starting point for neoantigen candidate discovery are selected.

03

Structure-Based Neoantigen Prediction

AI-based structural analysis is used to predict immune responsiveness.

For selected mutations, peptide–MHC binding prediction and T-cell reactivity simulations are performed. Binding affinity and stability are quantitatively evaluated through 3D docking and CNN-based modeling, enabling the identification of high-confidence targets with strong potential for immune recognition.

NEO-ARS®
04

Therapeutic Cancer Vaccine Design and Production

Manufacturing and preclinical PoC studies of cancer vaccines using diverse modalities including DNA, mRNA, peptide, viral vectors, and dendritic cells.

We design personalized therapeutic vaccines using various platforms (mRNA, DNA, peptides) based on predicted neoantigens. The use of refined antigens induces patient-specific immune responses, enabling precise targeting of cancer cells.

05

Personalized Vaccine Administration

Treatment through optimized vaccine administration to patients.

The custom-manufactured vaccine is administered to the patient, activating the immune system to selectively eliminate cancer cells. We perform follow-up monitoring to evaluate treatment response and immune durability.

Core Value of NEO-ARS®

90%

Accelerated Development Speed

From NGS data analysis to structure-based T cell epitope prediction in just days: Dramatically faster neoantigen cancer vaccine design.

4X

improvement in positive predictive value (PPV)

Precisely predicts highly immunogenic peptides binding to MHC molecules through our 3D structure-based approach.

100%

Personalized Design Capability

Derives optimal targets from patient genomics, enabling the development of fully personalized cancer vaccines and T-cell therapies.

3X

Expanded Application Scope

Ensures versatility and expandability of AI platform applicable across next-generation cancer immunotherapies, including cancer vaccines and TCR-T.

These figures are based on the results of internal projects and PoC studies conducted by Syntekabio between 2021 and 2025.

Key Applications

Personalized Cancer Vaccine Development

Contribute to increasing therapeutic response rates by developing personalized cancer vaccines for each patient using individual genomic profiling data.

Off-the-Shelf Cancer Vaccine Development

By analyzing cancer genome databases and cohort studies, we identify 'shared neoantigen' candidates commonly found in cancer patients that could be utilized as 'off-the-shelf' cancer vaccines and broad-spectrum immunotherapies.

Collaborative Research Projects

Expand our pipeline of innovative cancer immunotherapies by conducting preclinical and clinical collaborative studies with hospitals, research institutes, and biotech companies.

Vaccine Platform Expansion

Provides cancer patients with more treatment options by combining various vaccine technologies such as mRNA, peptides, and DNA, or T-cell therapies.

Business Model

NEO-ARS® is an AI-driven cancer immunotherapy design platform that identifies neoantigens (tumor-specific antigens, TSAs) by covering the whole process, from NGS data analysis to structure-based prediction of HLA class I-restricted immunogenic T cell epitopes using multiple algorithms. In particular, the ex vivo data we have already obtained through prospective studies with several clinicians regarding the prediction-validation of 'personalized neoantigens' provides strong evidence of therapeutic potential and establishes our leadership in next-generation cancer immunotherapy.

Antigen Type
Shared Neoantigen
Private Neoantigen
Therapeutic Efficacy
★ Moderate
★★ High
★★★ Very High
Immune Cell Activation
T Cells
T Cells, B Cells
Cancer Indications
hematological malignancies; blood cancers solid tumors

※ Compared to TAAs, neoantigens show stronger immunogenicity. Highly immunogenic TSAs provide better targets for personalized cancer immunotherapy, as they can induce a robust T-cell response without significant off-target effects on healthy tissues.

※ TCR-engineered T cell (TCR-T) therapy represents the next-generation approach for treating hematologic malignancies. Just as in cancer vaccine development for solid tumors, our AI platform's ability to accurately and rapidly predict neoantigens can dramatically accelerate development of adoptive T cell transfer therapy.

Accelerate your cancer vaccine pipeline —identify high-quality neoantigen targets now with NEO-ARS®

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