Evaxion A/S · NASDAQ:EVAX
Evaxion A/S — Evaxion Biotech — Investor Day (March 2024)
158 slides from Evaxion A/S's investor day presentation, Mar 19, 2024
Slide 1: R&D Day: AI-Immunology – a New Era in Vaccine Development
evaxion-biotech.com R&D Day March 19, 2024 AI-Immunology™ – a New Era in Vaccine Development AI-ImmunologyTM Powered Vaccines EVAX:NASDAQ
Slide 2: Agenda
Agenda SESSION 1 - Introduction CET / EST 14.00 - 14.10 / 9.00 – 9.10 Welcome 14.10 - 14.20 / 9.10 – 9.20 Evaxion overview - Setting the scene 14.20 - 14.35 / 9.20 – 9.35 AI-ImmunologyTM - A leading AI platform 14.35 - 14.55 / 9.35 – 9.55 EvaxMHC 4.0 - A cutting-edge AI building block 14.55 - 15.15
Slide 3: Forward-Looking Statement
Forward-Looking Statement This presentation contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. The words “target,” “believe,” “expect,” “hope,” “aim,” “intend,” “may,” “m
Slide 4: Session 1 – Introduction
evaxion-biotech.com SESSION 1 – Introduction AI-ImmunologyTM Powered Vaccines
Slide 5: Evaxion overview - Setting the scene
Evaxion overview - Setting the scene © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 5
Slide 6: Who We Are
Who We Are Evaxion is a pioneering TechBio company with a validated and leading AI–platform (AI-Immunology™) for fast and effective vaccine target discovery, design and development AI-Immunology™ allows for groundbreaking development of novel personalized and precision vaccines for cancer and infect
Slide 7: Why Are We Here: Saving and Improving Lives with AI-Immunology
Why Are We Here: Saving and Improving Lives with AI- Immunology™ 10 million deaths a year due to cancer* 7.8 million deaths a year due to infectious diseases** © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. * Source: WHO, ** Source: IHME, 7
Slide 8: Strategy: Three-Pronged Business Model Based upon AI-Immunology
Strategy: Three-Pronged Business Model Based upon AI-Immunology™ Multi-partner approach to value realization TARGETS Multi-partner approach focused around single or multiple vaccine target discovery, design and development agreements PIPELINE Own development programs for select high value programs;
Slide 9: Multidisciplinary Capability Set and State of the Art Facilities
We Have Built a Strong Multidisciplinary Capability Set and State of the Art Facilities Disease Biology Translational Target Discovery Medicine AI-Immunology™ Clinical Vaccine target discovery, Antigen Development design & development Design Vaccine & CMC Adjuvant Design Preclinical Development © Ev
Slide 10: AI-Immunology - Clinically Validated Predictive Capabilities
AI-Immunology™ - Clinically Validated Predictive Capabilities High prediction score of neoantigens (n=6) • AI response prediction Low prediction score of neoantigens (n=6) (PIONEER™ score) builds on the presence of high-quality tumour neoantigens Progression Free Survival Fraction of patients with •
Slide 11: Platform and Capability Set Drive Differentiation
Our AI-Immunology™ Platform and Multidisciplinary Capability Set Drive Differentiation • Our multidisciplinary capability set allows for: VALUE OF PLATFORM • Continuous iterative learning loops • Ongoing expansion of data sets with RISK OF FAILURE proprietary data • Rapid validation of AI prediction
Slide 12: Pipeline: Performance and Scalability of Our AI-Immunology Platform
Pipeline: Demonstrating the Performance and Scalability of Our AI-Immunology™ Platform * © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. *The data generated in the EVX-02 program actively informs the 12 development of the second generation EVX-03 DNA vaccine
Slide 13: Recent Highlights Confirm Strong Strategy Execution
Recent Highlights Confirm Strong Strategy Execution Collaboration with Leading Collaboration with Afrigen Private Placement with Closing of $15 Million Public Pharmaceutical Company Biologics Participation of MSD GHI Offering with Participation MSD GHI OCT-31 NOV-15 DEC-8 JAN-24 FEB-20 SEP-18 SEP-20
Slide 14: Several Important Near-Term Milestones
Several Important Near-Term Milestones Milestones Target EVX-B1 Conclusion of final MTA study with potential partner Q1 2024 AI-Immunology™ Launch of EDEN™ model version 5.0 Mid 2024 EVX-B2-mRNA EVX-B2-mRNA preclinical Proof-of-Concept obtained Q3 2024 EVX-01 Phase 2 one-year readout Q3 2024 Conclus
Slide 15: Agenda
Agenda SESSION 1 - Introduction 14.20 - 14.35 / 9.20 – 9.35 AI-Immunology™ - A leading AI platform 14.35 - 14.55 / 9.35 – 9.55 EvaxMHC 4.0 - A cutting-edge AI building block 14.55 - 15.15 / 9.55 – 10.15 BREAK SESSION 2 - Infectious Disease Vaccines 15.15 - 15.35 / 10.15 – 10.35 EDEN™ - Best-in-class
Slide 16: AI-Immunology – A leading AI platform
AI-Immunology™ – A leading AI platform © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 16
Slide 17: AI-Immunology - A Unique Differentiator
AI-Immunology™ - A Unique Differentiator © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 17
Slide 18: AI-Immunology - Clinically Validated Predictive Capabilities
AI-Immunology™ - Clinically Validated Predictive Capabilities High prediction score of neoantigens (n=6) • AI response prediction Low prediction score of neoantigens (n=6) (PIONEER™ score) builds on the presence of high-quality tumour neoantigens Progression Free Survival Fraction of patients with •
Slide 19: The EVAXION Journey
The EVAXION Journey Global Readiness for AI EDEN™ PIONEER™ RAVEN™ AI-DEEP™ ObsERV™ 2008 2016 2019 2020 2021 2022 2023 2024 EVX-01 EVX-02 IPO MSD MSD study study partner- share- © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. start start ship holder 19
Slide 20: Why The Need for AI-Immunology
Why The Need for AI-Immunology™ 10 million deaths a year due to cancer* 7.8 million deaths a year due to infectious diseases** We use the AI-Immunology™ platform to discover and assess the protectiveness of vaccine antigens and design candidates within hours, expediting the vaccine development proce
Slide 21: A Vaccine Teaches the Body to Fight an Infectious Agent or Disease
A Vaccine ‘Teaches’ the Body to Fight an Infectious Agent or Disease • A vaccine is a drug that is introduced into the body to trigger an immune response to prevent infection or to control a disease like cancer • A vaccine contain parts of the infectious agent or cancer that can trigger a successful
Slide 22: Key Areas for Building a Successful Vaccine
Key Areas for Building a Successful Vaccine DISEASE IMMUNE RESPONSE VACCINE DESIGN © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 22
Slide 23: The Key Areas of AI-Immunology
The Key Areas of AI-Immunology™ DISEASE DECODING IMMUNE RESPONSE DECODING VACCINE DESIGN © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 23
Slide 24: AI-Immunology is an Ensemble of Smaller Building Blocks
AI-Immunology™ is an Ensemble of Smaller Building Blocks Utilized Across the AI-Immunology™ Models SNVs EvaxMHC Precision design DISEASE DECODING Frameshifts HLA typing BIFROST HLA loss Epitope hotspots Personalized design © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 20
Slide 25: The Building Blocks of AI-Immunology
The Building Blocks of AI-Immunology™ 1 DISEASE DECODING Our disease decoding building blocks scan the disease of interest and pinpoint the weak spots for recognition by the immune system VIRUS BACTERIA CANCER © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 25
Slide 26: The Building Blocks of AI-Immunology
The Building Blocks of AI-Immunology™ 1 DISEASE DECODING SNVs Frameshifts Gene fusions HLA loss ERV antigens TME impact Clonality Expression Bacterial antigens Viral antigens Antigen conservation Treatment effect Neoantigens © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark,
Slide 27: The Building Blocks of AI-Immunology
The Building Blocks of AI-Immunology™ 1 DISEASE DECODING SNVs Frameshifts Gene fusions HLA loss ERV antigens TME impact Clonality Expression Bacterial antigens Viral antigens Antigen conservation Treatment effect Neoantigens 2 IMMUNE RESPONSE DECODING Our immune response decoding building blocks ran
Slide 28: The Building Blocks of AI-Immunology
The Building Blocks of AI-Immunology™ 1 DISEASE DECODING SNVs Frameshifts Gene fusions HLA loss ERV antigens TME impact Clonality Expression Bacterial antigens Viral antigens Antigen conservation Treatment effect Neoantigens 2 IMMUNE RESPONSE DECODING EvaxMHC HLA typing HLA frequencies Distance to s
Slide 29: The Building Blocks of AI-Immunology
The Building Blocks of AI-Immunology™ 1 DISEASE DECODING SNVs Frameshifts Gene fusions HLA loss ERV antigens TME impact Clonality Expression Bacterial antigens Viral antigens Antigen conservation Treatment effect Neoantigens 2 IMMUNE RESPONSE DECODING EvaxMHC HLA typing HLA frequencies Distance to s
Slide 30: The Building Blocks of AI-Immunology
The Building Blocks of AI-Immunology™ 1 DISEASE DECODING SNVs Frameshifts Gene fusions HLA loss ERV antigens TME impact Clonality Expression Bacterial antigens Viral antigens Antigen conservation Treatment effect Neoantigens 2 IMMUNE RESPONSE DECODING EvaxMHC HLA typing HLA frequencies Distance to s
Slide 31: How We Built ObsERV
How We Built ObsERV™ 1 DISEASE DECODING SNVs Frameshifts Gene fusions HLA loss ERV antigens TME impact Clonality Expression Bacterial antigens Viral antigens Antigen conservation Treatment effect Neoantigens 2 IMMUNE RESPONSE DECODING EvaxMHC HLA typing HLA frequencies Distance to self Protective an
Slide 32: How We Built ObsERV
How We Built ObsERV™ ObsERV™ 1 DISEASE DECODING 1st layer is decoding the disease HLA loss Expression ERV antigens HLA loss ERV antigens Expression 2 IMMUNE RESPONSE DECODING 2nd layer is decoding the immune response EvaxMHC HLA typing EvaxMHC HLA typing HLA frequencies Distance to self Protective a
Slide 33: AI-Immunology Models
AI-Immunology™ Models PIONEER™ ObsERV™ SNVs Frameshifts Gene fusions HLA loss HLA loss ERV antigens Expression Expression Clonality Neoantigens EvaxMHC HLA typing EvaxMHC HLA typing Distance to self Antigen quality Antigen safety Personalized design Antigen quality Antigen safety Personalized design
Slide 34: Pipeline: Performance & Scalability of Our AI-Immunology Platform
Pipeline: Demonstrating the Performance & Scalability of Our AI-Immunology™ Platform * © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. *The data generated in the EVX-02 program actively informs the 34 development of the second generation EVX-03 DNA vaccine
Slide 35: Building Future Models
Building Future Models EvaxNext™ 1 DISEASE DECODING ? ? ? ? ? ? ? ? ? ? ? 2 IMMUNE RESPONSE DECODING EvaxMHC HLA typing HLA frequencies Distance to self Protective antigens Epitope hotspots 3 VACCINE DESIGN Antigen quality Antigen safety B-cell antigen modelling B-cell antigen design Precison design
Slide 36: Building Block Architecture Enables Scaling to Other Therapeutic Areas
Building Block Architecture Enables Scaling to Other Therapeutic Areas CA NC ER © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 36
Slide 37: Summary
Summary • Evaxion is first mover in using AI for vaccine target discovery, design & development and clearly differentiated • AI-Immunology™ platform is trained in cancer and infectious diseases • AI-Immunology™ has been clinically validated • AI-Immunology™ is an ensemble of smaller building blocks
Slide 38: EvaxMHC our Central Building Block
EvaxMHC our Central Building Block PIONEER™ ObsERV™ EvaxMHC HLA typing EvaxMHC HLA typing Distance to self Antigen quality Antigen safety Personalized design Antigen quality Antigen safety Personalized design RAVEN™ EDEN™ EvaxMHC Protective antigens EvaxMHC HLA frequencies Epitope hotspots B-cell an
Slide 39: Agenda
Agenda SESSION 1 - Introduction 14.35 - 14.55 / 9.35 – 9.55 EvaxMHC 4.0 - A cutting-edge AI building block 14.55 - 15.15 / 9.55 – 10.15 BREAK SESSION 2 - Infectious Disease Vaccines 15.15 - 15.35 / 10.15 – 10.35 EDEN™ - Best-in-class model assessing protectiveness of B-cell antigens 15.35 - 15.55 /
Slide 40: EvaxMHC 4.0 - A cutting-edge AI building block
EvaxMHC 4.0 - A cutting-edge AI building block © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 40
Slide 41: EvaxMHC is a Central Building Block Across All Models
EvaxMHC is a Central Building Block Across All AI-Immunology™ Models © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 41
Slide 42: Adaptive Immune System Revolves Around MHC-Peptide-TCR Interaction
The Adaptive Immune System Revolves Around the MHC•Peptide•TCR Interaction Peptide T-Cell Receptor | TCR Major Histocompatibility Complex | MHC T-Cell © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 42
Slide 43: MHC Genes are the Most Diverse Genes
MHC Genes are the Most Diverse Genes Across All Individuals MHC: Major Histocompatibility Complex HLA: Human Leukocyte Antigen Human Class I MHCs: HLA-A, B, and C Class II: HLA-DR, DQ, and DP Currently 26,610 HLA class I alleles and 11,398 HLA class II alleles are known. © Evaxion Biotech A/S. All r
Slide 44: MHC-Peptide Predictors Classify Presentation
MHC•Peptide Predictors Classify Presentation for Millions of Peptides on Thousands of MHC Alleles © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 44
Slide 45: EvaxMHC Empowers ObsERV to Design ERV-Based Cancer Vaccines
EvaxMHC Empowers ObsERV™ to Design Efficacious ERV-Based Cancer Vaccines • Peptide-MHC prediction is a core element in ObsERV™ • Vaccine group designed after swapping out EvaxMHC with Gold standard tool • EvaxMHC vaccine group mounts stronger and sustained immune response and tumor protection © Evax
Slide 46: Proprietary Datasets for Underrepresented MHC Alleles
Evaxion has Generated Proprietary Datasets for MHC Alleles that are Underrepresented in Public Datasets HLA distance to train set vs Caucasian population frequency ● Population frequency (%) 20 Population Frequency [%] ● ● ● ● ● ● 10 ● ● ● ● ● ● ● ● ● HLA−C02:02 ● ● ● ● ● HLA−A68:01 HLA−C08:02 ● ● H
Slide 47: EvaxMHC4 Improvements Driven by Proprietary Datasets and Architectures
EvaxMHC4 Improvements are Driven by Proprietary Datasets, Novel Architectures and Training Strategy HLA distance to train set vs Caucasian population frequency ● 20 Integrating deep neural networks Population Frequency [%] 1. Population frequency (%) ● Output with Peptide-MHC data have ● ● ● ● ● pro
Slide 48: Conventional Peptide-MHC Predictions
Conventionally, Peptide•MHC Predictions are Driven by Deep Knowledge and Feature Engineering Prediction Dense Neural Network "Stretch" "Bulge" © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 48
Slide 49: Deep Learning Techniques Leverage Increasing Amounts of Data
Deep Learning Techniques are Used to Leverage Increasing Amounts of Data Encoder-Decoder Encoder-only E.g. machine translation E.g. autocomplete, ChatGPT Output Output Decoder Encoder Encoder Input Input © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 49
Slide 50: Deep Learning Techniques Leverage Increased Amounts of Data
Deep Learning Techniques are Used to Leverage Increased Amounts of Data Encoder-Decoder For Peptide•MHC modelling Representation P • Logical fit to model Peptide•MHC interaction • MHC Sequence as the "Input language" Decoder Encoder • Peptide + Encoded MHC is decoded to a binding yes/no answer MHC S
Slide 51: Deep Learning Techniques Leverage Increased Amounts of Data
Deep Learning Techniques are Used to Leverage Increased Amounts of Data Encoder-Decoder + Generative Adversarial Network For Peptide•MHC modelling Fake Peptide Representation P Decoder Decoder Encoder Encoder MHC Sequence MHC Sequence Real Peptide © Evaxion Biotech A/S. All rights reserved worldwide
Slide 52: Learning Connections Between MHC Class I and Class II Binding
Deep Learning Techniques are Used to Learn Connections Between MHC Class I and Class II Binding Transformer Architecture allow a combination of MHC class I and class II data Fine-Tuning Class I GAN Pretraining Classifier Training Class I & II Class I & II Fine-Tuning Class II © Evaxion Biotech A/S.
Slide 53: EvaxMHC is a State-of-the-Art Peptide-MHC Predictor
EvaxMHC is a State-of-the-Art Peptide•MHC Interaction Predictor © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 53
Slide 54: EvaxMHC is a State-of-the-Art Peptide-MHC Predictor
EvaxMHC is a State-of-the-Art Peptide•MHC Interaction Predictor © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 54
Slide 55: Peptide-MHC Predictions Impact Across AI-Immunology Models
State-of-the-Art Peptide•MHC Predictions Impacts Across Our AI-Immunology™ Models © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 55
Slide 56: Summary
Summary • Peptide•MHC interactions communicate self/non-self across cell boundaries • Peptide•MHC predictions are crucial for modern design of vaccines • EvaxMHC 4.0 is a major leap forward in Peptide•MHC prediction performance • Advances in Peptide•MHC prediction precision improves vaccine performa
Slide 57: Q&A Session
Q&A SESSION © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 57
Slide 58: Break
BREAK – Be Back at 15.15 CET / 10.15 EST © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 58
Slide 59: Agenda
Agenda SESSION 1 - Introduction SESSION 2 - Infectious Disease Vaccines 15.15 - 15.35 / 10.15 – 10.35 EDEN™ - Best-in-class model assessing protectiveness of B-cell antigens 15.35 - 15.55 / 10.35 – 10.55 RAVEN™ - Model for uncovering unique cross-protective T-cell antigens 15.55 - 16.15 / 10.55 – 11
Slide 60: Session 2 – Infectious Disease Vaccines
evaxion-biotech.com SESSION 2 – Infectious Disease Vaccines AI-ImmunologyTM Powered Vaccines
Slide 61: EDEN - Best-in-class model assessing protectiveness of B-cell antigens
EDEN™ - Best-in-class model assessing protectiveness of B-cell antigens © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 61
Slide 62: Global Deaths from AMR Infections Set to Skyrocket
Global Deaths from Antimicrobial Resistant (AMR) Infections Sets to Skyrocket 12 10 mil 10 mil 10 • 2020 - 10 million deaths a year due to cancer* 8 6 • 2020 - 1,3 million death of AMR infections** 4 • 2050 - 10 million death of AMR 2 1.3 mil infections** 2020 2020 2050 Cancer Deaths AMR Infection D
Slide 63: We Need AI for Accelerated Vaccine Development against AMR
We Need AI for Accelerated Vaccines Development against AMR Infections • Vaccines have a proven track-record of tackling AMR infections • Traditional vaccine development 'Reverse Vaccinology' is both costly and time- consuming, relying on luck to find protective antigen targets • We use our EDEN™ AI
Slide 64: How We Built EDEN
How We Built EDEN™ EDEN™ 1 DISEASE DECODING Bacterial antigens Viral antigens Antigen conservation EvaxMHC Protective antigens Bacterial antigens Viral antigens Antigen conservation B-cell antigen modelling B-cell antigen design 2 IMMUNE RESPONSE DECODING EvaxMHC HLA typing HLA frequencies Distance
Slide 65: EDEN Identifies Novel Protective Antigen Targets
EDEN™ Identifies Novel Protective Antigen Targets by Feature Recognition © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 65
Slide 66: EDEN Predicts Antigen Protectiveness and Ranks Proteome
EDEN™ Predict Antigen Protectiveness and Ranks Proteome © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 66
Slide 67: EDEN AI-Score Correlates with Protection
EDEN™ AI-Score Correlates with Protection Identifying Most Protective Antigens N. gonorrhoeae A. baumannii K. pneumoniae S. aureus Protective Significance Protective Significance Protective Significance Protective Significance (p-value) (p-value) (p-value) (p-value) EDEN prediction score EDEN predic
Slide 68: EDEN Outperforms Reverse Vaccinology
EDEN™ Outperforms Reverse Vaccinology EDENTM (top 40 rank) 23 potential novel protective targets EDEN screening of ~2000 proteins Time: 24 hours Intercell Novartis The 8 protective antigen targets Group A Streptococcus in top 40 EDEN rank 68 © Evaxion Biotech A/S. All rights reserved worldwide. Cope
Slide 69: Gonorrhea Skyrockets Today
Gonorrhea Skyrockets Today Gonorrhoea • Gonorrhea is a sexually transmitted disease 80.000 caused by infection with the Neisseria gonorrhoeae bacterium 70.881 70.000 • N. gonorrhoeae infections are often without 60.000 symptoms and untreated 50.000 • CDC classifies gonorrhea as an urgent threat due
Slide 70: EVX-B2: Two Superior Top Ranked EDEN Antigens
EVX-B2: Two Superior Top Ranked EDEN™ Antigens NG-EDEN-1 Multiple NG-EDEN-2 EVX-B2 N. gonorrhoeae strain proteomes processed by EDEN™ AI model % Protection % Protection EDEN AI score © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. Source: Gulati S et al. mBIO 2023 Oc
Slide 71: EVX-B2 Shows Unprecedented Broad Bacteria Killing
% Bacterial Survival % Survival W H W O 0 50 100 H 9 W O 07 H 9 W O 06 O H 90 N O 4 90 L W 2 H M G W O S H 90 11 W O 8 H 90 P O 5 91 M 2 N X J W N 15 H NJ48 O J 90 11 W 9 H N U O J 9 2 W W 01 6 W HO R2 F H 9 2 W O 14 0 H 91 Z O 1 90 W W 3 H O 2K 91 52 0 N V J6 SF0 2 3 N 34 J4 4 PI NJ D 1 © Evaxion B
Slide 72: EVX-B2 Antigen Shows Stronger Protection than Clinical Lead Antigen
EVX-B2 Antigen Shows Stronger Protection than Clinical Lead Antigen (NHBA) % Protection * * N.B: GSK, LimmaTech and Griffith University collaborate on © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. developing a Ng vaccine including the NHBA antigen 72
Slide 73: EDEN Identifies New Class of Antigens
EDEN™ Identifies New Class of Antigens with Potential Broad Applicability EVX-B2 antibodies attack the weak spot of the bacteria! Targeting bacteria during cell division © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. Source: Gulati S et al. mBIO 2023Oct 31; DOI: 10.
Slide 74: EDEN is Behind Several Infectious Disease Product Candidates
EDEN™ is Behind Several of Evaxion’s Infectious Disease Product Candidates * *The data generated in the EVX-02 program actively informs the development of the second generation EVX-03 DNA vaccine © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 74
Slide 75: Summary
Summary • EDEN™ AI-score correlates with protection identifying most protective antigens potentially enabling lower clinical risk • EDEN™ outperforms reverse vaccinology for faster and cheaper vaccine discovery • Our EVX-B2 vaccine is the solution against Gonorrhea • EVX-B2 shows unprecedented broad
Slide 76: Q&A Session
Q&A SESSION © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 76
Slide 77: Agenda
Agenda SESSION 1 - Introduction SESSION 2 - Infectious Disease Vaccines 15.35 - 15.55 / 10.35 – 10.55 RAVEN™ - Model for uncovering unique cross-protective T-cell antigens 15.55 - 16.15 / 10.55 – 11.15 BREAK SESSION 3 - Personalized Cancer Vaccines 16.15 - 16.35 / 11.15 – 11.35 PIONEER™ - Validated
Slide 78: RAVEN - Model for uncovering cross-protective T-cell antigens
RAVEN™ - Model for uncovering unique cross-protective T-cell antigens © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 78
Slide 79: RAVEN Distills Immunogenic Components into Enhanced Subunit Vaccine
RAVEN™ Distills the Immunogenic Components of a Pathogen down to an Enhanced Subunit Vaccine © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 79
Slide 80: T-Cell Epitopes Can Boost Subunit Vaccine Efficacy
T-Cell Epitopes Can Boost Subunit Vaccine Efficacy and Response Time Antigen Antigen Presenting Cell B cell T-helper cell © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 80
Slide 81: RAVEN Designed T-Cell Hotspot Primer Enables One-Shot Antibody Titers
RAVEN™ Designed T-Cell Hotspot Primer Enables One-Shot Antibody Titers © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 81
Slide 82: T-Cell Epitopes Can Provide Protection Against Pathogens
T-Cell Epitopes Can Provide Protection Against Infectious Pathogens Antigen Presenting Cell Infected Cell Killer T cell © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 82
Slide 83: RAVEN T-Cell Hotspot Vaccine Protects Against Lethal Challenge
RAVEN™ Designed T-Cell Hotspot Vaccine Provides Significant Protection Against Lethal Challenge Verified IFN-𝛾 response towards 88% (15/17) of the Vaccination with T-cell epitopes alone is sufficient for included hotspots protection against lethal infection in K18-hACE2/BL6 mice SARS-CoV-2 genome…
Slide 84: RAVEN Enables Multiple Strategies for T-Cell Vaccine Integration
RAVEN™ Enables Multiple Strategies for T-Cell Vaccine Integration Stand-Alone T-Cell Vaccine T-Cell Primer Vaccine T-Cell Grafted Vaccine • Extremely fast to produce • Extremely fast to produce • Simpler distribution and delivery • Can elicit broad but limited • Improves onset and quality of protect
Slide 85: RAVEN Models Components for T-Cell Response
RAVEN™ Models the Crucial Components for a Cytotoxic and Helper T-Cell Response 1. Viral Genomes 2. Target Population 3. Optimal T-Cell Hotspots Expression Epitope hotspots HLA frequencies Precision design Viral antigens EvaxMHC Antigen conservation © Evaxion Biotech A/S. All rights reserved worldwi
Slide 86: RAVEN Can Find Key Immunogenic Hotspots in Days
Using EvaxMHC, RAVEN™ Can Find Key Immunogenic Hotspots in Days © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 86
Slide 87: RAVEN Includes Modules for Structural Modelling
RAVEN™ Includes Modules for Structural Modelling 4. B-Cell Antigen 5. Enhanced B-Cell Antigen • EDEN™ Selected • Epitope Grafting • Viral Glycoprotein • Structure Stabilization Precision design Antigen conservation BIFROST B-cell antigen modelling B-cell antigen design © Evaxion Biotech A/S. All rig
Slide 88: Grafting of T-Cell Epitopes Into B-Cell Antigens Under Development
Intelligent Grafting of T-Cell Epitopes Into B-Cell Antigens is under development RAVEN identified T-cell epitopes can be grafted into B-cell antigens using AI autoencoders © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 88
Slide 89: RAVEN is Behind Several Infectious Disease Product Candidates
RAVEN™ is Behind Several of Evaxion’s Infectious Disease Product Candidates * © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 89
Slide 90: Summary
Summary • RAVEN is designed to find efficacious T- cell hotspots • RAVEN can design protective T-cell vaccines using technology from our personalized rapid production • RAVEN can choose T-cells to boost efficacy of B-cell vaccine candidates © Evaxion Biotech A/S. All rights reserved worldwide. Copen
Slide 91: Q&A Session
Q&A SESSION © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 91
Slide 92: Break
BREAK – Be Back at 16.15 CET / 11.15 EST © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 92
Slide 93: Agenda
Agenda SESSION 1 - Introduction SESSION 3 - Personalized Cancer Vaccines 16.15 - 16.35 / 11.15 – 11.35 PIONEER™ - Validated model for designing personalized Neoantigen vaccines 16.35 - 16.55 / 11.35 – 11.55 ObsERV™ - Leading model for designing personalized ERV-antigen vaccines 16.55 - 17.15 / 11.55
Slide 94: Session 3 – Personalized cancer vaccines
evaxion-biotech.com SESSION 3 – Personalized cancer vaccines AI-ImmunologyTM Powered Vaccines
Slide 95: PIONEER - Validated model for personalized Neoantigen vaccines
PIONEER™ - Validated model for designing personalized Neoantigen vaccines © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 95
Slide 96: Still a Need for Better Cancer Treatments
Despite the Advent of Cancer Immunotherapy there is Still a Need for Better Cancer Treatments Objective Response Rate • Cancer immunotherapy based on checkpoint inhibitors (CPI) has revolutionized the treatment of previously untreatable cancers such as melanoma • Only 20-30% of cancer patients respo
Slide 97: Neoantigen-Based Cancer Vaccines are the Next Evolution
Neoantigen-Based Cancer Vaccines are the Next Evolution of Cancer Immunotherapies Neoantigens are ideal cancer vaccine targets that: • arise from cancer-specific DNA mutations • are found specifically in tumors and absent from normal tissues • elicit potent, highly specific immune responses • synerg
Slide 98: Distinct Neoantigens Hinder a Universal Neoantigen Vaccine
Cancer Patients Have Distinct Neoantigens Hindering the Development of a Universal Neoantigen Vaccine © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. Cancer Genome Atlas Network (2015). Cell 161, 1681–1696. 10.1016/j.cell.2015.05.044. 98
Slide 99: Future Cancer Treatments Tailored to Each Patient
Future Cancer Treatments Will Be Tailored More Specifically to Each Patient Traditional Precision Personalized © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 99
Slide 100: How We Built PIONEER
How We Built PIONEER™ PIONEER™ 1 DISEASE DECODING SNVs Frameshifts Gene fusions HLA loss SNVs Frameshifts Gene fusions HLA loss Clonality Expression Neoantigens Clonality Expression EvaxMHC HLA typing Distance to self Neoantigens Antigen quality Antigen safety Personalized design 2 IMMUNE RESPONSE D
Slide 101: PIONEER Models Mechanisms that Generate Effective Neoantigens
PIONEER™ Models the Mechanisms Inside Cancer Cells that Generate Effective Neoantigens for Cancer Vaccines 1. Cancer-specific 2. Expression 3. Translation 4. Presentation 5. T-cell response 6. Clonal neoantigens mutation on MHC SNVs Expression Neoantigens EvaxMHC Distance to self Clonality Frameshif
Slide 102: PIONEER is Part of a Larger Process from Tumor to Treatment
PIONEER™ is Part of a Larger Process from Patient Tumor to Treatment Tumor and normal tissue samples Administration in combination with CPI DNA and RNA Manufacturing sequencing of personalized of samples vaccine Neoantigen vaccine designed by PIONEER™ © Evaxion Biotech A/S. All rights reserved world
Slide 103: PIONEER is Behind Several Oncology Product Candidates
PIONEER™ is Behind Several of Evaxion’s Oncology Product Candidates *The data generated in the EVX-02 program actively informs the development of the second generation EVX-03 DNA vaccine © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 103
Slide 104: EVX-01 - Personalized Neoantigen Vaccine in Metastatic Melanoma
EVX-01 - Personalized Neoantigen Vaccine in Metastatic Melanoma EVX-01 Phase 1 clinical trial (NCT03715985) … Stage IV Metastatic melanoma (N=12) … Peptide-formulated Primary endpoint: Safety and tolerability CAF09b … neoantigens … Selected secondary endpoint: … - Immune response induced by EVX-01 …
Slide 105: EVX-01 - Strong Phase 1 Clinical Data
EVX-01 - Strong Phase 1 Clinical Data Individual patient responses • Trial met the primary endpoint • Neoantigen-specific immune response in all patients • Clinical response in 8 out of 12 patients with 2 complete responders © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark,
Slide 106: PIONEER Scores Predict Immunogenicity & Clinical Response
PIONEER™ Scores Predict Immunogenicity & Clinical Response Neoantigens with higher PIONEER™ scores PIONEER™ scores are predictive of are more likely to be immunogenic clinical response p = 0.012 p = 0.014 © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. Median TMB: 17
Slide 107: Superior Neoantigen Quality Leads to Prolonged Progression-Free Survival
Superior Neoantigen Quality Leads to Prolonged Progression-Free Survival Independent of TMB EVX-01 patients stratified on median PIONEER™ score EVX-01 patients stratified on TMB p < 0.01 p > 0.05 © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 107
Slide 108: EvaxMHC is Required for Optimal Prediction of Neoantigens
EvaxMHC is Required for Optimal Prediction of Immunogenic Neoantigens 1. Cancer-specific 2. Expression 3. Translation 4. Presentation 5. T-cell response 6. Clonal neoantigens mutation on MHC EvaxMHC • Gold standard • MixMHCpred Garde et al. (2019). Immunogenetics 71, 445–454. 10.1007/s00251-019-0112
Slide 109: EvaxMHC is Required for Optimal Prediction of Neoantigens
EvaxMHC is Required for Optimal Prediction of Immunogenic Neoantigens © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 109
Slide 110: Summary
Summary • The PIONEER™ model selects relevant neoantigens for personalized cancer vaccines • PIONEER™ has been tested in two Phase 1 clinical trials and is being tested in an ongoing Phase 2 trial • PIONEER™ scores are predictive of neoantigen immunogenicity and clinical response to the neoantigen t
Slide 111: Q&A Session
Q&A SESSION © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 111
Slide 112: Agenda
Agenda SESSION 1 - Introduction SESSION 3 - Personalized Cancer Vaccines 16.35 - 16.55 / 11.35 – 11.55 ObsERV™ - Leading model for designing personalized ERV-antigen vaccines 16.55 - 17.15 / 11.55 – 12.15 BREAK SESSION 4 - Precision Cancer Concepts 17.15 - 17.35 / 12.15 – 12.35 AI-DEEP™ - Model for
Slide 113: ObsERV – Leading model for personalized ERV-antigen vaccines
ObsERV™ – Leading model for designing personalized ERV-antigen vaccines © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 113
Slide 114: Some Patients Have Few Quality Neoantigens
Some Cancer Patients Have Few Quality Neoantigens Underscoring the Need for Additional Antigen Source © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 114
Slide 115: Endogenous Retroviruses May be Promising Cancer Antigens
Endogenous Retroviruses (ERVs) May be Promising Antigens for Cancer Therapies • Ancient viruses that have integrated into the genome and are passed down through generations. • Constitute up to 8% of the human genome • Epigenetically suppressed in healthy tissue, but expressed in cancers • Examples o
Slide 116: ERVs May Facilitate Vaccines for Patients with Few Neoantigens
ERVs May Facilitate Personalized Cancer Vaccine Development for Patients with Few Neoantigens • Pan solid cancer investigation of neoantigens and ERV antigens • The number of neoantigens and ERV antigens Median ERV Antigen Burden is not correlated • Patients with few neoantigens could leverage ERVs
Slide 117: Patient Stratification with ERV Antigen Burden
Patient Stratification with the ERV Antigen Burden Supports Their Potential as Effective Cancer Antigens • CPI treated malignant melanoma patients • Genomic analysis of baseline tumor biopsies for neoantigens and ERV antigens • Low-TMB patients are stratified by ERV antigen burden • ERVs may facilit
Slide 118: ERVs Presented as MHC Ligands Predicted by EvaxMHC
ERVs Are Presented as MHC Ligands on Tumors and Can be Predicted by EvaxMHC Pak et al. (2021), Mol Cell Proteomics Tumor Cell Line © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 118
Slide 119: Leveraging Modular AI-Immunology Platform to Build ObsERV
Leveraging our Modular AI-Immunology™ Platform to Build ObsERV™ ObsERV™ 1 DISEASE DECODING HLA loss Expression ERV antigens HLA loss EvaxMHC HLA typing ERV antigens Expression Antigen quality Antigen safety Personalized design 2 IMMUNE RESPONSE DECODING EvaxMHC HLA typing HLA frequencies Distance to
Slide 120: ObsERV: New AI-model for Personalized ERV-Based Cancer Vaccines
ObsERV™: A New AI-model for Development of Personalized Cancer Vaccines Based on ERV Antigens • Fits into established clinical workflows • Requires standard RNA-seq of tumor biopsy and patient's HLA- type • Designed to identify potent ERV antigens that activate CD4+ and CD8+ T cells • Aiming to prov
Slide 121: ObsERV Designs Efficacious ERV-Based Cancer Vaccines
ObsERV™ Designs Efficacious ERV-Based Cancer Vaccines © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 121
Slide 122: EvaxMHC Empowers ObsERV to Design ERV-Based Cancer Vaccines
EvaxMHC Empowers ObsERV™ to Design Efficacious ERV-Based Cancer Vaccines • Peptide-MHC prediction is a core element in ObsERV™ • Vaccine group designed after swapping out EvaxMHC with Gold standard tool • EvaxMHC vaccine group mounts stronger and sustained immune response and tumor protection © Evax
Slide 123: EVX-03 Will Evaluate Personalized Cancer Vaccines
EVX-03 Will Evaluate Personalized Cancer Vaccines Leveraging Neoantigens and ERVs CCL19 EVX-03 Dimerization domain Neoantigen/ERV unit © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 123
Slide 124: Pipeline: Performance and Scalability of Our AI-Immunology Platform
Pipeline: Demonstrating the Performance and Scalability of Our AI-Immunology™ Platform © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 124
Slide 125: Summary
Summary • ERVs constitute a complementary source of cancer antigens • ObsERV™ enables development of ERV based personalized cancer vaccines • Preclinical proof-of-concept • IND ready for clinical testing (EVX-03) Garde, C. et al. (2023). Endogenous viral elements constitute a complementary source of
Slide 126: Q&A Session
Q&A SESSION © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 126
Slide 127: Break
BREAK – Be Back at 17.15 CET / 12.15 EST © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 127
Slide 128: Agenda
Agenda SESSION 1 - Introduction SESSION 4 - Precision Cancer Concepts 17.15 - 17.35 / 12.15 – 12.35 AI-DEEP™ - Model for predicting responses to cancer CPI immunotherapy 17.35 - 17.55 / 12.35 – 12.55 Addressing difficult to treat cancers with AI-Immunology™ 17.55 - 18.00 / 12.55 – 13.00 THANK YOU an
Slide 129: Session 4 – Precision cancer concepts
evaxion-biotech.com SESSION 4 – Precision cancer concepts AI-ImmunologyTM Powered Vaccines
Slide 130: AI-DEEP - Model for predicting responses to CPI immunotherapy
AI-DEEP™ - Model for predicting responses to cancer CPI immunotherapy © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 130
Slide 131: Checkpoint Inhibitors Are Widely Used as First Line Therapy
Checkpoint Inhibitors Are Widely Used as First Line Therapy • Cancers exploit immune checkpoints to impair the immune system • Checkpoint inhibitors remove the impairment and reinvigorate the immune system • Improved treatment of several solid cancers • Approved for an increasing number of cancer ty
Slide 132: Checkpoint Inhibitor Market Projected to Reach Almost $150 BN by 2030
The Market for Checkpoint Inhibitor Therapy Is Projected to Reach almost $150 BN by 2030 © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 132
Slide 133: Many Patients Do Not Benefit from Checkpoint Inhibitor Therapy
A Large Fraction of Cancer Patients Do Not Benefit from Checkpoint Inhibitor Therapy • Demand for continued development of immunotherapies • Demand for Identifying non-responders • Some patients get severe side effect • No established highly predictive biomarkers © Evaxion Biotech A/S. All rights re
Slide 134: PIONEER Biomarker Predicts Response to EVX-01 & anti-PD1
PIONEER™ Derived Biomarker Predicts Clinical Response to the EVX-01 & anti-PD1 Combination Immunotherapy © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 134
Slide 135: ObsERV Biomarker Stratifies Low-TMB Patients Treated with CPI
ObsERV™ Derived Biomarker Stratifies Low-TMB Cancer Patients Treated with Checkpoint Inhibitor Garde, C. et al. (2023). Endogenous viral elements constitute a complementary © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. source of antigens for personalized concer imm
Slide 136: Predict Non-Responding Cancer Patients with High Precision
Predict Non-Responding Cancer Patients with High Precision Benefits for patients and society • Redirection to better suited treatments Predict response • Avoid side effects from CPI treatment based on pre- therapy biopsy • Health care budget Genomic biomarkers • Driver mutations • Tumor microenviron
Slide 137: Leveraging Modular AI-Immunology Platform to Build AI-DEEP
Leveraging our Modular AI-Immunology™ Platform to Build AI-DEEP™ AI-DEEP™ 1 DISEASE DECODING SNVs Frameshifts Gene fusions HLA loss SNVs Frameshifts Gene fusions HLA loss ERV antigens TME impact Expression Clonality ERV antigens TME impact Clonality Expression Treatment effect Treatment effect EvaxM
Slide 138: Pre-Therapy Biopsy Data from 937 CPI Treated Patients
Pre-Therapy Biopsies Data from 937 CPI Treated Cancer Patients Were Collected for Model Development 4% 1% 5% 6% 50% 35% Metastatic Melanoma Metastatic Urothelial Cancer Renal Cell Carcinoma Metastatic Gastric Cancer Saliva Gland Carcinoma Thymic Carcinoma © Evaxion Biotech A/S. All rights reserved w
Slide 139: AI-DEEP Predicts 28% of Non-Responders with High Precision
AI-DEEP™ Predicts 28% of Non-Responders to Checkpoint Inhibitor Therapy with High Precision • Gold standard biomarkers (TMB and PDL1) fail to identify non-responding patients with high precision • AI-DEEP™ predicts 28% of non-responding patients with high precision • AI-DEEP™ could guide treatment d
Slide 140: ObsERV & PIONEER Biomarkers Important for Predicting Non-Responders
ObsERV™ & PIONEER™ Derived Biomarkers Are Important for Prediction of Non-Responding Patients • Feature ablation study ranks biomarkers according to their importance for the predictive performance • In-house models ranked among the most informative biomarkers out of an initial set of >2000 biomarker
Slide 141: Summary
Summary • AI-DEEP™ leverages PIONEER™ and ObsERV™ to predict clinical response to checkpoint inhibitor therapy • AI-DEEP™ can accurately identify a subset of non-responding cancer patients and may inform treatment decisions • We are currently exploring options for a commercial offering and further c
Slide 142: Q&A Session
Q&A SESSION © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 142
Slide 143: Agenda
Agenda SESSION 1 - Introduction SESSION 4 - Precision Cancer Concepts 17.35 - 17.55 / 12.35 – 12.55 Addressing difficult to treat cancers with AI-Immunology™ 17.55 - 18.00 / 12.55 – 13.00 THANK YOU and concluding remarks 18.00 - 19.00 / 13.00 – 14.00 Reception with drinks and snacks 143
Slide 144: Addressing difficult to treat cancers with AI-Immunology
Addressing difficult to treat cancers with AI-Immunology™ © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 144
Slide 145: Some Cancers Have Few Targets for Modern Cancer Vaccines
Some Cancers Have Few Targets for Modern Cancer Vaccines Ly m ph om M ye ell a lo B m c AM AL CL a L L L Alexandrov et al (2013) Nature 50, p415–421 Hilf et al (2018) Nature 565 p240-245 © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 145
Slide 146: Endogenous Retroviruses May be Promising Cancer Antigens
Endogenous Retroviruses (ERVs) May be Promising Antigens for Cancer Therapies • Ancient viruses that have integrated into the genome and are passed down through generations. • Constitute up to 8% of the human genome • Epigenetically suppressed in healthy tissue, but expressed in cancers • Examples o
Slide 147: The Immune System Targets ERVs in Blood Cancer Patients
The Immune System Targets ERVs in Blood Cancer Patients Saini et al 2020 – Nat. Com. Alcazer et al 2022 – Am J Hematol. Goyal1et al 2023 – Nat. Com. 23 unique ERV T-cell targets in 8 different HLA-A*02 epitopes identified Proof that ERVs are displayed on the AML/MDS patients in AML patients surface
Slide 148: Inclusion of ERV Targets Allows Vaccines in Difficult to Treat Cancers
Inclusion of ERV Targets Allows Design of Personalized Cancer Vaccine in Difficult to Treat Cancers Patient data sources (n= >15.000) TCGA TARGET PIONEER™ CGCI CCDI ObsERV™ MMRF NHGRI The Cancer Genome Atlas Program (TCGA) - Therapeutically Applicable Research to Generate Effective Treatments (TARGE
Slide 149: ERV Conservation Allows Design of Shared Vaccines
ERVs Conservation Allows for the Design of Shared Vaccines ObsERV™ 2.0 RAVEN™ HLA loss Expression ERV antigens EvaxMHC HLA typing HLA frequencies Epitope hotspots EvaxMHC HLA frequencies Epitope hotspots Antigen quality Antigen safety Personalized design Precision design Precision design BIFROST © E
Slide 150: ERV Conservation Allows Design of Shared Vaccines
ERVs Conservation Allows for the Design of Shared Vaccines ObsERV™ 2.0 Shared Vaccine © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 150
Slide 151: AML ERV Targets are Different Depending on Age
AML ERV Targets are Different Depending on Age ERV burden as a function of Age Significant difference between ERV expression in young and old AML patients Adults vs Children -log10(Adjusted P-value) Diagnosis Age ERV Burden Log2 Fold Change © Evaxion Biotech A/S. All rights reserved worldwide. Copen
Slide 152: Precision-Based Vaccines Potentially Improve Effect in Childhood AML
Precision-Based Vaccines Potentially Improves Effect in Childhood AML ObsERV™ 2.0 HLA loss Expression ERV antigens EvaxMHC HLA typing HLA frequencies Epitope hotspots Antigen quality Antigen safety Precision design Personalized design 152 © Evaxion Biotech A/S. All rights reserved worldwide. Copenha
Slide 153: Pipeline: Performance and Scalability of Our AI-Immunology Platform
Pipeline: Demonstrating the Performance and Scalability of Our AI-Immunology™ Platform © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 153
Slide 154: Summary
Summary • Targeting ERVs allows Evaxion to design vaccines for cancers that are difficult to treat with current vaccine approaches • With development of ObsERV™ 2.0, using building blocks from RAVEN™, shared vaccines can be designed for multiple different cancer types • Shared vaccines have a low ma
Slide 155: Q&A Session
Q&A SESSION © Evaxion Biotech A/S. All rights reserved worldwide. Copenhagen, Denmark, 2024. 155
Slide 156: Agenda
Agenda SESSION 1 - Introduction SESSION 4 - Precision Cancer Concepts 17.55 - 18.00 / 12.55 – 13.00 THANK YOU and concluding remarks 18.00 - 19.00 / 13.00 – 14.00 Reception with drinks and snacks 156
Slide 157: Concluding Remarks - AI-Immunology
Concluding Remarks - AI-Immunology™ • Holds the promise for a new era in vaccine discovery, design and development • Uses advanced AI and machine learning technologies • Outcompetes standard vaccine target discovery approaches • Identified targets hold the promise for addressing serious unmet needs
Slide 158: Thank you!
LinkedIn: evaxion-biotech.com Evaxion Biotech A/S Thank you! Please stick around for snacks & drinks AI-ImmunologyTM Powered Vaccines