onkommon.com
Programme R8
AI-Guided Drug Repurposing & Combination Design
Which approved drugs could work against India-priority cancers?
Coming soon
The problem
New oncology drugs are priced beyond the reach of most Indian patients. Approved medicines with known safety profiles and expired patents are the most realistic route to affordable options.
Combination space is unsearchable experimentally, there are far more plausible combinations than could ever be tested.
The questions
- Which approved drugs could be repurposed against targets relevant to India-priority cancers?
- Can generative models produce candidates that survive real medicinal-chemistry scrutiny?
- Which combinations are worth the cost of testing?
What we are contributing
This is the most capital-efficient route into therapeutics available to an institution of our size, no wet lab, no chemistry floor, no capital expenditure.
We are explicit that computational candidates are hypotheses. They require experimental validation by collaborators before any clinical claim, and nothing from this programme will be offered to a patient outside a registered trial.
How the work is done
- Generative molecular models
- Docking and molecular dynamics
- Property and ADMET prediction
- Graph neural networks and virtual screening at scale
- Combination-effect modelling
What it runs on
- Public chemical and bioactivity databases
- Target hypotheses from R5 and R6
What it produces
- Prioritised repurposing and candidate hypotheses
- Published methods
- A collaboration asset for pharmaceutical partners
Why it is not just science
How this changes care here
- No direct clinical use. Outputs are hypotheses for validation, not treatments.
- High-visibility science that attracts both funders and partners
Funding fit
AI and drug-discovery grants; industry collaboration; academic partnership for experimental validation.
What we are looking for
- Medicinal chemistry and experimental validation partners
- Compute funding
- Pharmaceutical collaborators
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.