Structured workflow
- 1Formulate treatment-effect question
- 2Define treatment, comparator, and outcome
- 3Specify cohort and key assumptions
- 4Upload and inspect dataset
- 5Review confounding and protocol framing
- 6Run causal estimation and inspect outputs
PrecisionMedicineAgent
Precision medicine through guided and auditable causal workflows.
For clinicians and researchers studying treatment effects from randomized and real-world data with explicit assumptions and stage-level control.
This workspace provides analytical support and transparent workflow control. It does not represent automated clinical decision-making.
Workflow status
Stage integrity
Artifact output
Effect estimate preview
Who it is for
Clinician investigators, clinical researchers, and RWE/biostatistics teams conducting treatment-effect analysis from trial and observational data.
Reliability model
Why teams trust it
- Target trial emulation principles
- Stepwise workflow validation
- Explicit assumptions and stage tracking
- Auditable artifacts and state reversion
Outputs
- Average treatment-effect estimates
- Subgroup and individualized effect insights
- Downloadable artifacts for review and continuation
Current maturity
Stabilization in progress
Workflow stabilization and real-world testing are active. Paper-in-progress and advanced privacy capabilities are presented as future phases.
Research context and roadmapNext step