ops digital twin

Site Start-up + Recruitment Simulation Ops Twin

A2A x MCP in Clinical Ops Digital Twin

Scenario Console

Therapeutic AreaPhase

Countries

Target Sample SizeRecruitment Duration (months)

avg_startup_days75

screen_fail_rate0.35

dropout_rate0.18

competition_index0.5

patient_pool_index0.6

Show agent messages in real-timeDeterministic Seed

Run History

Stored locally (max 5 runs). Each run keeps full context + event log.

A2A Conversation Thread

MCP-like Shared Context

Run a simulation to populate shared context.

Simulation Output

Run a scenario to generate recruitment and startup simulation outputs.

update log

Prototype Change Log

2026-03-01 · v0.2.0
Forecast Calibration & Confidence Layer
- - Added actual observation capture to track predicted vs actual enrollment error over time.
- - Implemented automatic parameter callback to tune startup/screen-fail/dropout/competition/patient-pool assumptions.
- - Added confidence panel with MAPE, signed bias, tracked points, and assumption shift diagnostics.
2026-03-01 · v0.1.0
Ops Twin MVP Launched
- - Added three-zone interface: scenario console, A2A timeline, and MCP-like shared context panel.
- - Implemented six-agent runtime with deterministic seeded simulation and ordered handoff workflow.
- - Added context patch/event-log model with diff drawer, JSON export, replay, and local run history.