Global Open Medical Infrastructure Network

Open infrastructure
for navigating
personalised
mRNA vaccine
design-and-review
pathways.

GOMIN is building shared maps and tools for medical pathways that are currently hard to navigate.

Global because expertise, trials, labs, and research may be distributed across countries.

Open because general knowledge maps and pathway templates can be shared and improved.

MIN

Medical Infrastructure Network because difficult pathways depend on many disconnected systems — hospitals, labs, researchers, ethics committees, trial teams, and qualified facilities.

GOMIN is an early-stage startup exploring how AI and global online resources could help patients, carers, clinicians, and researchers navigate complex pathways around personalised mRNA vaccine design more clearly — starting with glioblastoma cases in Australia as a narrow MVP. The long-term mission for GOMIN is to give patients and carers a clearer map of the personalised mRNA vaccine pathway across continents, connecting global resources together.

Join Discovery Interviews See What We're Building

Personalised neoantigen vaccine pathway

14 steps · diagnosis to redesign

Cancer diagnosis & standard-of-care context

Tumour sample acquisition

Tumour DNA/RNA & matched-normal sequencing ✦

Somatic mutation calling ✦

HLA or species-specific immune typing ✦

Neoantigen candidate prediction ✦

Candidate antigen prioritisation ✦

Expert immunogenomics review ✦

Therapeutic platform mRNA, peptide, or other

Manufacturability review ✦

Ethics, medical & regulatory approval

Administration & monitoring by qualified professionals

Response assessment ✦

Redesign upon feedback ✦

→ Repeat or advance to clinical pathway

For pathway education and platform positioning only — not medical advice, diagnosis, or treatment instructions.

The Problem

A GBM diagnosis leaves patients facing urgent questions with no clear map.

One doctor may say the chance is low. Another may suggest looking for trials. A third may ask for more molecular testing. Online communities, papers, AI tools, and patient forums may point in different directions.

Our working question

Can complex personalised medicine pathways become clearer, more structured, and easier for qualified people to review?

Share Your Experience →

Questions patients may face

Which records matter, and how to get them?
Is tumour tissue still available for testing?
Has molecular testing been done — and was it enough?
Does sequencing data exist, and is it usable?
Is personalised vaccine research relevant to this case?
What costs might arise, and who bears them?
What approvals or trial pathways may be required?
Which experts need to be involved?
Is there a treating clinician who can navigate this?
What questions should be asked — and when?

Today, much of this pathway is unclear, fragmented, and difficult to navigate. GOMIN is exploring whether better infrastructure can make that uncertainty more structured.

Case Study

Case Study: What it takes an individual to design, build, and test a personalised cancer vaccine.

The story of Paul Conyngham and his dog Rosie is a powerful glimpse into what may become possible — when AI, sequencing, expert networks, ethics pathways, manufacturing facilities, and determined human coordination come together. But it also showed how difficult the pathway can be.

"The challenge was not only the science. It was the coordination: finding the right experts, understanding data requirements, navigating ethics and institutional approvals, identifying manufacturing feasibility, and turning an urgent case into something that could be responsibly reviewed."

The pathway problem GOMIN is inspired by

Read the UNSW article →

Paul Conyngham crouching beside his dog Rosie in a backyard — With her tumours much smaller than they were, Rosie is a lot more mobile and energetic. Picture: Jake Willis

ABC Listen · Health Report

Thanks to AI, Paul can see the culprit of his dog's cancer

Listen on ABC

First output · In progress

Rosie Case Study
Report

A structured analysis of the pathway from diagnosis to personalised vaccine exploration — not a guide to copying Rosie's treatment. GOMIN's first public deliverable.

Table of contents

01Step-by-step workflow of the Rosie case
02Institutions, experts, and technologies involved
03What a motivated individual can and cannot responsibly do
04Where AI helps, and where qualified experts are essential
05Current scientific basis of personalised cancer vaccines
06Safety, ethics, and regulatory boundaries
07Bottlenecks that could become platform opportunities
08Open questions for collaborators, funders, and research partners

Request when released → Join collaborator list

GOMIN service pillars

Pathway education

Translate opaque medical R&D steps into safe, structured explanations for clinicians, carers, students, and builders.

Evidence readiness

Turn scattered papers, reports, repositories, and lab outputs into reviewable dossiers with gaps and assumptions clearly marked.

Workflow reproducibility

Audit computational workflows, check whether code runs, and identify what would be required before expert review.

Expert routing

Connect the right question to the right expertise: oncology, immunology, bioinformatics, regulation, ethics, and manufacturing.

GOMIN is not a platform for the general public to design, manufacture, or administer treatments. We do not provide diagnosis, treatment recommendations, or instructions for self-treatment. We help patients, carers, students, developers, researchers, veterinarians, and clinical teams safely understand, verify, connect, and reproduce complex personalised medicine pathways.

The pathway in depth

What does it take to design a personalised vaccine?

When Rosie's case is generalised, the path is not one simple leap. It requires a controlled chain of samples, sequencing, computational prediction, human review, manufacturing, approval, monitoring, and more.

Research spotlight · ImmunoNX

ImmunoNX is a useful example of where the field is heading: researchers describe a reproducible workflow using tumour DNA/RNA, matched normal DNA, HLA typing, pVACtools, pVACview, and IGV-supported expert review, with reported support for 185+ patients across 11 clinical trials and vaccine design in under three months.

Read the ImmunoNX paper →

A roadmap of the end-to-end journey

01Cancer diagnosis and standard-of-care context

02Tumour sample acquisition

03Tumour DNA/RNA and matched-normal sequencing

04Somatic mutation calling

05HLA or species-specific immune typing

06Neoantigen candidate prediction

07Candidate antigen prioritisation

08Expert immunogenomics review

09Therapeutic platform selection: mRNA, peptide, or other modality

10Manufacturability review

11Ethics, medical, and regulatory approval

12Administration and monitoring by qualified professionals

13Response assessment

14Redesign upon feedback

Steps with especially strong software / AI / workflow leverage: 03, 04, 05, 06, 07, 08, 10, 13, 14

What we are exploring

Seven prototypes under investigation.

GOMIN is exploring a set of tools to help patients and carers organise information, understand barriers, and prepare better questions — in collaboration with qualified professionals.

01 · Passport

GBM Vaccine Readiness Passport

A structured document helping patients and carers understand what is known, what is missing, and what may need to be discussed with qualified professionals.

Confirmed GBM diagnosis & pathology
Tumour tissue availability
Molecular testing & sequencing status
Clinician involvement & trial context

02 · Cost Map

Cost Map

Helps patients understand where costs may arise in the vaccine-readiness pathway and which costs depend on qualified providers or clinical-trial pathways.

Pathology retrieval & tissue access
DNA/RNA extraction & sequencing
Bioinformatics & candidate prioritisation
GMP manufacturing & administration

03 · Barrier Map

Barrier Map

A visual map of where the pathway may be blocked — before patients waste time, money, or hope.

Clinical trial vs expanded access context
HREC / institutional approval requirements
Manufacturing partner & sponsor requirements
Timeline and cost barriers

04 · Evidence Atlas

Evidence & Similar Case Atlas

An open, non-identifying knowledge layer for GBM vaccine-readiness — similar studies, trial signals, biomarker requirements, and evidence quality.

Similar GBM vaccine studies
Newly diagnosed vs recurrent GBM context
Known biomarker requirements
Human clinical vs preclinical evidence

05 · Question Pack

Expert Question Pack

Helps patients and carers arrive at expert conversations better prepared — structured questions by professional type.

Neuro-oncology & pathology questions
Trial coordinator questions
Vaccine researcher questions
Ethics & regulatory pathway questions

06 · Support Planning

Support & Care Planning

Glioblastoma affects more than treatment decisions. Structured support questions for the full scope of care.

Nutrition, psychology & counselling support
Financial & work/study planning
Home care, nursing & logistics
Advance-care & values-based planning

07 · Routing Board

Routing Board

A pathway-clarity tool showing possible next responsible routes — not a treatment recommendation engine.

Standard-care discussion
Trial search & molecular profiling discussion
Expert review vs research-only pathway
Not review-ready yet — what to do next

Open Infrastructure

Open medical infrastructure does not mean open patient data.

Patient records, case-specific expert notes, genomic files, and identifiable clinical data should remain private and permissioned. The word "open" refers to reusable, non-identifying knowledge that can become public infrastructure.

The principle

Public knowledge can be open. Expert review should be moderated. Patient data must remain protected.

What stays private

Patient records
Genomic files
Identifiable clinical data
Case-specific expert notes
Individual sequencing results

What can be open

Evidence maps
Patient-safe explainers
Pathway templates
Similar-case atlases
Trial-readiness checklists
Research challenges
Contributor tasks

Long-term vision

GOMIN starts with glioblastoma vaccine-readiness in Australia. Over time, the broader vision is to grow into a global open medical infrastructure network for difficult-to-treat diseases and rare medical problems — where complex cases can become clearer, more review-ready, and more research-connected.

Technology

Where AI / ML Could Help

Personalised medicine pathways involve large amounts of scattered information: medical records, pathology reports, imaging, molecular testing, sequencing files, research papers, clinical trials, regulatory pathways, costs, and expert opinions. GOMIN is exploring how AI and machine learning could help make this pathway clearer.

Case organisation

AI can help turn scattered records into a structured timeline — diagnosis, surgery, pathology, treatment history, imaging, recurrence, molecular testing, and treating team. The goal is not diagnosis. The goal is to make the case easier to understand and discuss.

Diagnosis & surgery timeline
Pathology & imaging
Treatment history
Current treating team

Missing-data detection

Machine learning can help identify what information appears to be missing before a personalised vaccine pathway can be responsibly discussed.

Missing pathology report
Unclear tumour tissue status
No molecular testing summary
Unknown sequencing status

Evidence mapping

Large language models can help search, summarise, and organise relevant literature, trials, and similar studies. All high-risk medical content should remain source-linked and human-reviewable.

Human clinical vs preclinical evidence
Ongoing & failed trials
Expert-reviewed sources
Patient-friendly explainers

Pathway & barrier mapping

AI can help visualise where a case may be blocked. This helps patients and carers understand what needs to be clarified next.

Missing data & cost barriers
No trial pathway or sponsor
No HREC or institutional approval
Timeline mismatch

Expert question generation

AI can help prepare structured questions for relevant professionals. The purpose is to support better conversations, not replace expert judgement.

Neuro-oncologist questions
Trial coordinator questions
Vaccine researcher questions
Ethics & regulatory advisor questions

Similar-case & resource recommendation

Recommender systems can help match a case or question to relevant resources. The system recommends the next useful question or resource, not a treatment choice.

Similar studies & public explainers
Clinical-trial categories
Relevant expert roles
Support services & evidence maps

Open knowledge contribution

AI can help turn repeated questions and bottlenecks into reusable public resources. Private patient data remains private. Reusable, non-identifying knowledge can become shared infrastructure.

Pathway templates & evidence maps
Patient-safe explainers
Trial-readiness checklists
Similar-case atlases & research challenges

Safety boundary

GOMIN does not use AI to diagnose, recommend treatment, design vaccines, manufacture medicines, or replace medical professionals. AI is used to help organise, map, explain, and route information around complex pathways.

Founder info

Led by deep commitment to the mission.

Ji Kim

Master of IT (AI) · UNSW · Software Engineer · Independent Researcher

Ji is driven by personal stories — the people behind complex diagnoses who deserve clearer maps, not more confusion. She believes that better infrastructure can make hard pathways more navigable, and that this work is worth doing carefully.

Her background spans software development, programming education, AI, games development, and web technologies. She enjoys designing and developing prototypes, supporting ambitious projects, and building communities around learning, research, and meaningful impact. Ji is currently seeking collaborators, advisors, funding, and venture program opportunities.

Connect on LinkedIn → Get in touch

Join the Discovery Phase

We want to learn from you.

GOMIN is currently in early-stage ideation. We are looking for people willing to share insight, feedback, and lived or professional experience.

We especially want to hear from

Glioblastoma patients and carers

Neuro-oncology clinicians and trial coordinators

Researchers in GBM, immunotherapy, or personalised vaccines

Molecular pathology, sequencing, and bioinformatics experts

Patient advocates and funders

Current collaboration needs

Scientific advisors

Neuro-oncology, bioinformatics, GBM immunotherapy, RNA therapeutics.

Technical collaborators

Medical AI, reproducibility, scientific software, data workflows.

Startup supporters

Mentors, venture programs, grant makers, early funders.

Join Discovery Interviews Contact the Founder

Open infrastructurefor navigatingpersonalisedmRNA vaccinedesign-and-reviewpathways.