PIONEER™ & ObsERV™ Unlocking the power of neoantigens in the fight against cancer

Neoantigens are tumor-specific targets that arise from mutations that tumor cells gain during their evolution. PIONEER is able to accurately and efficiently identify a patient's neoantigen targets in a personalized manner. Using proprietary computational AI models developed at Evaxion, PIONEER has been developed to select the neoantigens that are most likely to generate a strong T-cell response and anti-tumor effect in each patient. The goal of our immunotherapies, derived from the PIONEER™ model, is to deliver therapeutic neoepitopes to patients in a way that trains patients’ own immune systems to specifically target and kill tumor cells with no or very limited adverse effects on healthy non-cancer cells.

Evaxers working in laboratory

Designing personalized cancer immunotherapies that transform patients' quality of life.

How we do it

Mutation and expression: Once biopsies have been performed, PIONEER identifies cancer-specific mutations by comparing DNA sequencing data from the tumor sample(s) and normal tissue sample using our proprietary AI-based somatic variant caller. Then, the expression levels of the genes found within the mutation are determined by analyzing tumor RNA sequencing data. PIONEER also calculates the mutation-specific expression levels using an in-house developed computational model.

Translation: PIONEER determines the effects of each cancer-specific mutation, as not all mutations result in altered protein sequences. Once non-synonymous mutations (where both the DNA sequence and the encoded amino acid are altered) are identified, the surrounding coding regions are translated into amino acid sequences, generating cancer-specific neoantigen sequences.

Personalized cancer immunotherapy: The identified neoantigens are put into our proprietary AI-based tool along with the patient’s HLA type, to identify the neoantigens that will be presented on the patient’s MHC molecules. PIONEER also predicts the likelihood of these neoantigens eliciting a T-cell response, which will trigger an immune response and tumor cell death. Additionally, for patients where DNA sequencing data from multiple tumor biopsies is available, PIONEER seamlessly integrates the data from each biopsy to target tumor-defining neoantigens. This means that, even though tumors continuously acquire novel mutations and do not necessarily encode and express the same neoantigens, PIONEER allows for the systematic eradication of the whole tumor as well as potential metastases in the patient.

Neoantigen administration: The selected neoantigens are manufactured and administered alongside standard-of-care, producing an anti-tumor effect in the patient.

Evaxers working in laboratory
Evaxers working in laboratory

Key advantages of PIONEER™

  • PIONEER is able to identify therapeutic neoantigens that drive a T-cell response with higher accuracy compared to predictions done by state-of-the-art public tools. Clinical interim data from the Phase 1/2a trial of EVX-01 demonstrated induction of neoantigen-specific T-cells in 100% of patients with an overall response rate of 67% compared with a historical overall response rate of 33-40% with anti-PD-1 treatment alone.
  • PIONEER identifies multiple neoantigens that can be incorporated in the immunotherapy to increase therapeutic effect and overcome issues related to cancer clonal heterogenicity and tumor immune escape.
  • PIONEER is clinically applicable, automated and deployable anywhere in the world. It has been through a process of validation according to the International Society for Pharmacoepidemiology's (ISPE) latest revised guide for Good Manufacturing Practice, or GAMP5, to ensure compliance with legislation and good practice regulations to maintain a high standard of quality.

ObsERV™

We have discovered that endogenous retrovirus (ERVs) are a potential additional source of cancer antigens that can be used in personalized cancer immunotherapies to complement neoantigens. We have developed a bioinformatics model that can identify ERVs based on sequencing data and design a personalized ERV antigen treatment. We have proof of concept that our method works in preclinical models. 

For Evaxion, it enables us to facilitate and improve our personalized cancer immunotherapy pipeline. We believe that adding ObsERV™ to PIONEER would potentially allow us to further improve the personalized cancer immunotherapies we design, targeting cancer indications that generally have fewer neoantigens. Evaxion has already started the discussion with the reg. authorities on how to include these ERV targets in a personalized neoantigen treatment in future clinical trials.

Current Product Candidates

Laboratory stock photo

EVX-02

EVX-02 is a novel, DNA-based cancer immunotherapy designed to induce a therapeutic immune response in the adjuvant setting in patients with Stage III and IV resected melanoma.

Cancer illustration stock photo

EVX-03

EVX-03 is an innovative, DNA-based neoantigen immunotherapy with an antigen-presenting cell (APC) targeting unit, intended for the treatment of advanced solid cancer.

Related Resources

<p>Evaxion’s AI technology identifies cancer vaccine targets associated with longer progression-free survival of melanoma patients in the EVX-01 Phase 1 clinical trial</p>

Jun 3, 2023

Press releases

Evaxion’s AI technology identifies cancer vaccine targets associated with longer progression-free survival of melanoma patients in the EVX-01 Phase 1 clinical trial

<p>Evaxion announces promising clinical Phase 1 data for its personalized cancer vaccine EVX-01</p>

May 25, 2023

Press releases

Evaxion announces promising clinical Phase 1 data for its personalized cancer vaccine EVX-01

<p>Endogenous viral elements constitute a complementary source of antigens for personalized cancer immunotherapy</p>

Mar 27, 2023

Publications

Endogenous viral elements constitute a complementary source of antigens for personalized cancer immunotherapy

<p>Interview about the ObsERV model with Per Norlén</p>

Mar 24, 2023

Presentations

Interview about the ObsERV model with Per Norlén

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