The steps for developing personalized BreakVax vaccines
Using the latest technological advances to deliver a scalable and cost-effective method for personalized cancer vaccine development

1. Multi-omic Analysis

Using our AWS cloud-based pipeline and mass spectrometry analysis to identify candidate peptides. AWS provides enormous scalability to ensure we can obtain results quickly even in high volume workloads


2. Proprietary AI-vaccine design model

Using our AI platform which is trained per-patient to select the most immunogenic peptide targets for each patient. Our unique approach gives BreakVax vaccines an edge by offering a greater degree of personalization


3. Personalized Cancer Vaccine

Peptides manufactured per-patient means each patient gets exactly the right peptides at exactly the right doses. This optimization means more robust immune responses and better patient outcomes


4. Combine CRC Proven Drugs

We add FDA approved drugs to enhance the percentage of antigens that result in new T cells

What is the process for each patient?


Mass spec per patient is scalable commercially


Time for analysis of each patient is coming down because each new generation of instruments improve efficiency


BreakBio trains its AI platform from scratch for each patient. We don’t train it on historic patient data, but use only the data from each individual patient. This strategy means our model learns from the context of each patient's immune system rather than an aggregate of many patient's immune systems, resulting in a truly personalized therapy


Costs of the new instruments have been declining so providers can have many instruments running concurrently. As prices continue to fall mass spec analysis will continue to become more accessible and economically viable


Thermo Fisher is the main technology provider and Bruker has good competing technology. Shimadzu from Japan, Sciex, and others are additional innovators in the mass spec space.


More commercial labs are investing in mass spectrometry equipment in the last 10 years indicating a likely continuation in the trend of greater mass spec accessibility and reduced costs

AWS cloud computing and Nextflow make the pipeline scalable


Our pipeline takes raw sequencing data of the patient's tumor and healthy tissues and uses data from various cancer research organizations to accurately identify the most immunogenic neoantigen targets for that specific patient

The pipeline uses Nextflow which enables efficient resource allocation and scalable parallelization to support large volumes of patient samples

AWS cloud computing allows almost unlimited automatic scalability of our Kubernetes-based cluster to supply any resources necessary for the Nextflow pipeline execution

History of mass spectrometry

  • Mass spectrometry was invented by Arthur Jeffrey Dempster and F.W. Aston in 1918 and 1919 respectively, resulting in a Nobel Prize
    for Aston in 1922.
  • Mass spectrometry methods have been in continuous development since its invention
  • In 2002, the Nobel Prize in Chemistry was awarded to John Bennett Fenn for the development of electrospray ionization (ESI) and this is key to what BreakBio does
  • Thermo Fisher is the leader in mass spectrometry with the Orbitrap technology being a big leap forward
  • Mass spectrometry can now be performed per patient fast and efficiently because of these new Orbitrap machines and better software
  • BreakBio’s AI platform means that the mass spec data can be rapidly analyzed to spot patterns and targets
  • As technology development continues and software improves, mass spectrometry will be possible for all patient’s tumor tissue much like gene sequencing of tumor tissue is now possible for all patients

Gene sequencing advancements

  • In 2003 the first human genome was sequenced at a cost of ~$300 million
  • By 2016, the cost to sequence one human genome was below $1,500
  • Today, whole genome sequencing can be obtained for under $400
  • llumina is the largest provider of short-read sequencing and continues to improve their technology to provide better accuracy at lower costs
  • Many labs competing to offer sequencing services using the Illumina platform means sequencing costs continue to fall
  • BreakBio uses the highest quality sequencing possible to have the best possible data for our AI/ML platform
  • The AI platform takes this and other data generated by BreakBio processes to instantly analyze on our high powered AWS Kubernetes cluster to find targets on that patient’s cancer cells