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N1TherapeuticsProgramming biology.
A woman walks her scruffy brown dog toward a small veterinary clinic

Neoantigen Retriever · Canine oncology

Personalized cancer vaccines.
Within reach.

We’re making personalized cancer vaccines accessible, starting with our best friends: dogs.

Origin

Project Rosie · Health & Sciences Prize, Google DeepMind's Gemma 4 Good Challenge.

Watch the Project Rosie demo

The personalized vaccine journey

Six stages. Many partners. One patient.

Follow one dog’s journey from diagnosis to personalized neoantigen vaccine treatment.

The owner and her dog meet a veterinary oncologist in a quiet exam room

01 · A dog arrives at the clinic

Start with the patient.

Your veterinarian assesses suitability and coordinates tumour and matched-normal samples.

Partner: Veterinary oncology clinic

Explore this stage

Could a personalized neoantigen vaccine be a suitable option for this dog?

The journey begins with a diagnosis. The veterinarian reviews the dog’s clinical history, assesses suitability and coordinates tumour and matched-normal sample collection.

Patient & consentClinical samples
DNA · TUMOUR / NORMALRNA EVIDENCE

02 · Understand the tumour

Every tumour tells a different story.

Sequencing reveals tumour-specific changes, RNA expression and the dog’s immune-genetics context.

Partner: DNA/RNA sequencing laboratory

Explore this stage

What has changed in this tumour that is absent from healthy tissue?

Tumour and matched-normal sequencing help identify tumour-specific changes. RNA evidence and patient-specific immune genetics add context.

Clinical samplesMolecular data
HIGHER PRIORITYLOWER PRIORITYCANDIDATES → SHORTLIST (QUALITATIVE)

03 · Neoantigen Retriever

Find the targets worth testing.

Neoantigen Retriever turns molecular evidence into an explainable shortlist of patient-specific targets.

Partner: N1 Therapeutics · Neoantigen Retriever

Assays and handoffs

Of thousands of changes, which few deserve laboratory time?

Our computational pipeline narrows tumour-specific changes into a ranked shortlist. DLA molecules help present protein fragments to the dog's immune system. We evaluate which tumour-specific fragments could be recognized.

  1. 1Identify tumour-specific changes
  2. 2Check mutant-expression evidence
  3. 3Evaluate compatibility with the dog's DLA molecules
  4. 4Consider tumour relevance
  5. 5Prioritize candidates for experiments
Molecular dataRanked candidate targets
T-CELLDLA + PEPTIDEDoes it bind?Do immune cellsrespond?Can they recognizethe tumour?ELISPOT WELLS

04 · Wet-Lab Validation

A prediction becomes a question for the lab.

A specialist laboratory tests binding, stability, immune response and tumour recognition.

Partner: Immunology laboratory or CRO

Assays and handoffs

Does it bind? Do immune cells respond? Can they recognize the tumour?

Computational ranking is a hypothesis. Experiments decide which candidates have real biological support before anything moves forward.

Binding / stability assaysELISpotTumour-recognition experiments
Candidate targetsExperimental evidence
mRNA · LIPID NANOPARTICLE

05 · Prepare the personalized vaccine

Translate evidence into a vaccine candidate.

Supported targets inform mRNA design, lipid nanoparticle formulation, manufacturing and quality assessment.

Partner: mRNA-LNP formulation & manufacturing team

Explore this stage

How do supported targets become something that can be safely delivered?

Candidates supported by evidence may progress to mRNA construct design, formulation, manufacturing and quality assessment. The lipid nanoparticle protects the RNA and helps deliver it into cells.

Supported targetsInvestigational vaccine candidate
The same dog, owner and veterinarian talk on a bench outside the clinic

06 · Return to the clinic

Measure. Learn. Improve.

If evidence and an authorized protocol support treatment, the veterinarian gives the vaccine and monitors safety and immune response.

Partner: Veterinary clinic & immune-monitoring laboratory

Explore this stage

How does the dog respond, and what can we learn for the next patient?

If laboratory evidence, product quality and an authorized clinical protocol support treatment, the veterinarian administers the personalized vaccine and monitors safety, immune response and clinical outcomes. Each case helps refine the workflow.

ObservationsBack to Neoantigen Retriever

The partner network

Find your place in the workflow.

  1. 01

    Veterinary clinic

    Toronto Animal Cancer Centre. Clinical collaboration in discussion

  2. 02

    Sequencing

    Donnelly Sequencing Centre. Prospective sequencing collaborator

  3. 03

    Neoantigen Retriever

    N1 Therapeutics. Computational prioritization

  4. 04

    Wet-Lab Validation

    Canine immunology laboratory / CRO. Options to identify

  5. 05

    mRNA-LNP manufacturing

    Bowen Li’s U of T lab or UBC RNA and Formulation Core. Prospective RNA/LNP options

  6. 06

    Clinic & monitoring

    Returns to the veterinary clinic

Feedback loop. Clinical observations inform the next round of prioritization.

For veterinary clinics

Bring personalized cancer immunotherapy closer to your patients.

  • 01Explore new possibilities for patients with cancer.
  • 02Connect tumour profiling with patient-specific vaccine design.
  • 03Work with coordinated sequencing, immunology and manufacturing partners.
  • 04Understand immune responses alongside clinical outcomes.

Start a conversation

Let’s discuss a collaboration.

Tell us about your clinic or laboratory, your area of expertise and the collaboration you have in mind.

Discuss a clinical collaborationshashank@n1therapeutics.com

Team and collaborators

AI engineering, genomics and cancer research.

Shashank Padala

Shashank Padala

Founder. AI Engineering & Product Leader

AI product leader and operator, previously at Amazon and Tesco PLC, and founder of Kirak Labs, a Toronto AI product studio. Brings an operations and AI engineering perspective to making personalized cancer immunotherapy cheaper, faster and more accessible. Independently built the award-winning Project Rosie prototype, then brought together researchers in cancer genomics and biology to strengthen it.

  • Master’s in Management, Innovation and Entrepreneurship · Queen’s University, Smith School of Business
  • Bachelor of Technology, Electronics and Communication Engineering · IIT Guwahati
Abhishek Ajay

Abhishek Ajay

Founding team · Translational oncology

Computational leader in translational oncology at the Case Comprehensive Cancer Center. Leads multi-omics strategy and a team of PhD researchers studying small-cell lung cancer, spanning biomarker discovery, ctDNA monitoring and drug-target assessment. Connects rigorous statistical analysis with decisions researchers and physicians can act on.

  • MS, Biostatistics · Columbia University, Mailman School of Public Health
  • Bachelor of Technology, Biotechnology · IIT Guwahati
Alexander Turco

Alexander Turco

Computational Genomics Collaborator

Contributes to Neoantigen Retriever’s computational pipeline development and scientific evaluation, bringing expertise in cancer genomics, deep learning and sequencing workflows. Collaborates with N1 Therapeutics alongside his Medical Biophysics PhD at the University of Toronto.

  • Doctoral research, Medical Biophysics · University of Toronto
  • Biology Research Specialization · McMaster University
Meet the team and collaborators

From hackathon to clinic

Where we are, and what comes next.

  1. Completed

    May 18, 2026

    Working prototype

    Project Rosie pipeline and demo submitted to the hackathon.

  2. Completed

    August 24, 2026

    Health & Sciences Prize

    Google’s Gemma 4 Good Challenge announcement.

  3. In progress

    October 2026

    Pipeline & clinical planning

    Neoantigen Retriever development and clinic-connected study planning.

  4. Proposed

    Next milestone

    Wet-Lab Validation

    Test prioritized targets with an immunology lab or CRO.

  5. Proposed

    Conditional next stage

    Clinical evaluation

    Progress only with supporting evidence and an authorized protocol.