8:30 am Chairs Opening Remarks

8:45 am Industry Panel to Address the Most Critical Questions for this Nascent & Emerging Therapeutic

Synopsis

• What is the best neoantigen prediction platform?
• What is the most robust approach to identifying the “right” neoantigen?
• How to best deliver a neoantigen therapy, vaccine or cell therapy?
• What type of vaccine, cell based, virus, RNA, DNA, peptide?
• Which approach is safer and more efficacious?
• Should the focus be on shared neoantigens or private neoantigens?

9:15 am Personalised Neoantigen Immunotherapy – Demonstrating Priming of CD8+ T cell Responses is a Key Step

Synopsis

• Typical solid tumor epithelial cells display class I HLA-presented neoantigens (not class II)
• Consistent priming of strong CD8+ T cell responses to these neoantigens is likely key to effective immunotherapy
• We will show phase one clinical and immunogenicity data from a heterologous prime-boost neoantigen immunotherapy program in solid tumor patients

9:45 am An Integrated Machine-Learning Approach to Improve the Prediction of Clinically Relevant Neoantigens

Synopsis

• Outline a high-performing machine learning approach, trained on mass spectrometry data, that predicts naturally processed and presented antigens
• Demonstrate how the predictor is integrated with several immune parameters, such HLA binding, in a deep learning layer to predict bona fide neoantigens
• Illustrate it’s application to significantly improve the identification of neoantigen targets for personalised cancer immunotherapy

10:15 am Speed Networking

Synopsis

This session is the ideal opportunity to get face-to-face time with many of the brightest minds working to advance cell therapies. Benchmark against the industry leaders and establish meaningful business relationships to pursue for the rest of the conference and beyond

10:45 am Morning Refreshments

PREDICTION & IDENTIFICATION

11.15 Driving Antigen Discovery in Cervical Cancer

  • Evaluating how personalised genome or transcriptome sequencing information is essential for neoantigen discovery using LC-MS technology
  • RNAseq allows variant mapping and identification of cryptic antigens
  • Pathogen-driven tumours harbour a range of so far unknown targetable, tumourspecific neoantigen

Nicola Ternette, Head of Immunopeptidomics, University of Oxford

 

11.45 Past and future developments in the use of AI heuristics for successful
neoantigen prediction

  • Overview of biological processes involved in neoantigen immunogenicity that are being
    approximated by using innovative computational biosimulation
  • Describing the clinical importance of increasing the True Positive Rate by using AI heuristics
  • Identification of missing datasets key to successful prediction , and which efforts are being taken in the landscape to overcome these.

Wim Van Criekinge, CSO, myNEO

 

12:15 Using Predictive Bioinformatics Algorithms to Determine Neoantigen
Peptide Synthesis Difficulty & Subsequent Production Methodology

  • NeoAntigen peptides have been widely reported to be difficult to synthesize due to their hydrophobicity, length, and charge.
  • Leveraging extensive peptide synthesis experience GenScript has developed
  • NeoPreTM, a predictive algorithm which is able to determine peptide synthesis difficulty based on sequence alone.
  • NeoPreTM can then recommend the most efficient approach to successfully
    synthesizing peptides using one of GenScript’s many synthesis platforms
  • This presentation will highlight how NeoPreTM identifies synthesis difficulty and review successful cases of difficult neoantigen peptide synthesis from several researchers

Raymond Miller, Senior Global Product Manager, Therapeutic Materials, GenScript
Biotech Corporation

CLINICAL TRANSLATION & MANUFACTURING

12:45 pm Lunch

Distinguishing Novel Neoantigen Discovery Tools for Development of Potent Tumorigenic Immune Responses

13.45 Identify HLA Class I and Class II specific TCRs in Pancreatic Cancer for
Individualized T Cell Therapy

  • Both HLA Class I and Class II epitope peptides were eluted from PDAC tumour tissue by using anti-pan HLA Class I antibody and anti-pan HLA Class II antibody, respectively, followed by mass spectrometry analysis. Approximately 20% eluted HLA Class I epitopes and Class II epitopes are overlapped
  • TCRs for selected epitopes were cloned and their homologous TCR clones can be identified in the tumor infiltrating lymphocytes from PDAC tumour tissue.
  • Antitumor activity of T cells engineered with the above cloned TCRs are tested

Lei Zheng, Associate Professor, John Hopkins School of Medicine

 

14:15 Disease-specific Immunopeptides for Generation of Soluble TCR Therapies

  • Patient tumor and healthy tissues were enriched for MHC class I peptides and
    identified by mass spectrometry
  • Population prevalence was used to prioritize tumor-selective immunopeptides as candidate targets
  • Soluble TCRs can be generated against disease-specific immunopeptides for
    development of targeted therapeutic strategies

Melanie Patterson, Principal Research Scientist II, Abbvie

 

14:45 AI in personalized cancer medicine – recent improvements and next steps

  • Recent development in AI driven prediction tools to drive neoantigen clinical therapy
  • AI identification of neo-antigens VS epitope discovery by assay based methods – Pros and cons
  • Next steps – where do we get data for training improved methods

Jens Kringelum, Director, Genomic Immuno-Oncology, Exaxion Biotech

 

15:15 Modelling Neoantigen Prediction

  • Advance neoantigen prediction
  • Analysing key features

Maren Lang, Head of Bioinformatics Research & Development, BioNTech SE

 

 

Optimizing Immune Priming in Neoantigen Based Cancer Vaccines for Enhanced Efficacy of Treatment

3:45 pm Afternoon Refreshments & Poster Session

4:15 pm ImmunoID NeXT: A Comprehensive Platform for Improving Neoantigen Prediction, Tumour Escape Mechanism Reporting, TME Assessment, & Tumor Heterogeneity Profiling for Immuno-Oncology

  • Sean Boyle Senior Director, Bioinformatics Applications, Personalis

Synopsis

• Improving neoantigen presentation prediction
• Applying immunopeptidomics and machine learning to more accurately predict neoantigens
• Detecting tumour escape mechanisms
• HLA LOH, antigen presentation machinery, and immunogenomics
• Profiling tumour heterogeneity
• Utilizing cell free DNA in order to more comprehensively identify neoantigens and tumor escape mechanisms

4:45 pm Whole Framome Cancer vaccination

Synopsis

• Discovery of the full potential of frameshift neoantigens as targets of cancer immunotherapy
• Personalized cancer immunotherapy using Framome neoantigen vaccines

5:15 pm A Personal Antigen Selection Calculator (PASCal) for the Design of Off-The-Shelf, Shared Neoantigen-Based Personal Vaccines

Synopsis

• Vaccine design approach for two types of personal vaccines, off-the-shelf with candidate CDx and personalized: leveraging Cancer Testis Antigens as nonmutated neoantigens
• Data reveal from phase I/II clinical trial with PolyPEPI1018 off the shelf vaccine against MSS mCRC – unprecedented immunogenicity and initial efficacy
• Improved selection of Personal Epitopes (PEPIs) that induce predictable cytotoxic T cell responses – exploring our personalised cancer vaccines proof of concept study
• How this technology leads to a shorter needle-to-needle time and a more scalable product

5:45 pm Chair’s Closing Remarks

6:00 pm End of Day 1 of Neoantigen Summit Europe