The creator is building an AI system for oncology research in collaboration with an immunologist and data scientist. The project tests whether existing cancer datasets and drug signatures can predict which patient subgroups are likely to respond to treatments before clinical trials run, by modeling patterns across biological data in a structured way. The system has progressed beyond internal iteration and now requires validation from domain experts. They are seeking introductions to professionals in biotech, trial design, or translational oncology who can provide serious feedback and pressure-test the approach. The emphasis is on quality signal rather than volume of feedback.
AI systems can predict patient subgroup drug response from existing cancer datasets before trials run
Medium confidence
The project models patterns across biology in a structured way
High confidence
The system has reached a stage where domain expert feedback is more valuable than internal iteration
High confidence
Building systems to test thinking keeps advice honest
High confidence
No vendors were mentioned.
The creator's overall position toward the main topic discussed.