Feasibility review
Map data availability, missingness, cohort size, outcome definitions, and access requirements.
Possible outputData-readiness assessment and analysis scope.
Collaboration
Bring a question.
Build an evidence plan.
For academic investigators, biotechnology teams, and clinical research groups exploring treatment-response modeling.
Begin with a scoped discussion.
A useful collaboration starts with a defined population, treatment, outcome, and decision. We can discuss whether the available data can address the question and what additional evidence would be needed.
Potential collaboration topics
- Retrospective biomarker research
- Multimodal treatment-response modeling
- Independent model evaluation
- Research reporting and reproducibility
From scope to next steps
What a project could include
Model development
Specify baseline comparisons, preprocessing, feature selection, and patient-level evaluation.
Possible outputDocumented analysis and a reproducible modeling workflow.
Validation planning
Identify suitable external cohorts, uncertainty estimates, subgroup checks, and limits of intended use.
Possible outputEvaluation report and a plan for further validation.
Scope, deliverables, data access, timelines, and commercial terms are agreed for each project.
A useful first conversation
What to bring
A short, non-confidential summary is enough to begin.
- Your research question and intended use.
- Disease, treatment, cohort size, and outcome definition.
- Available data types and whether outcomes are linked.
- Study stage, key constraints, and desired deliverables.
Start a scientific conversation
What question is your
data ready to answer?
Tell us about your research objective, available data, and the decision your study needs to inform.
Discuss a project