onkommon.com
Programme R5
Computational Immuno-Oncology
Beyond TMB and MSI, what actually predicts benefit in Indian patients?
Coming soon
The problem
Immunotherapy is the highest-cost decision in oncology. Existing biomarkers select patients imperfectly, and every patient treated who will not benefit is both a clinical failure and a financial catastrophe for an Indian family.
The reference data underpinning those biomarkers barely includes South Asian patients.
The questions
- What predicts immunotherapy benefit in Indian patients, beyond tumour mutational burden and microsatellite status?
- Can neoantigen prediction be made reliable enough to guide selection?
- Which immune-evasion mechanisms dominate in the tumour types that matter here?
What we are contributing
Better selection is worth more to Indian patients and payers than almost anything else we could compute. Avoiding one futile course of immunotherapy saves a family more than most interventions save a health system.
Indian HLA diversity is under-represented in neoantigen prediction reference data, a gap we are positioned to characterise.
How the work is done
- Neoantigen prediction and HLA typing pipelines
- Immune repertoire analysis
- Deconvolution of immune composition from bulk data
- Microenvironment modelling with rigorous validation design
What it runs on
- Consented molecular and clinical data from our cohort
- Public immune datasets
- Matched treatment and outcome records
What it produces
- Response-prediction models
- Neoantigen pipelines
- Contributions to the immunotherapy consultation pathway
- Publications
Why it is not just science
How this changes care here
- Sharper immunotherapy candidacy assessment at the board
- A direct pharmaceutical collaboration surface
- Cost avoidance for families
Funding fit
Immunology and AI grants; pharmaceutical collaboration on response biomarkers.
What we are looking for
- Immunology collaborators
- Pharmaceutical partners for biomarker programmes
- HLA reference data for South Asian populations
Deliberately empty
Publications, funding and results
Nothing appears in this section until it exists in writing. No paper in preparation, no grant under review, no result not yet published. That rule applies with particular force to a research page.