Build a Synthetic Cohort Clinical Trial Protocol Amendment Simulator

Simulate the impact of proposed clinical trial protocol amendments on participant eligibility using synthetic cohort records. Quantify candidate pool expansion and flag potential protocol safety margin deviations.

Clinical Protocol Design Analyst

Ingest existing trial eligibility criteria and proposed amendment delta values.

Execute comparative eligibility queries across a benchmark synthetic patient repository.

Quantify marginal recruitment gain and calculate shifts in baseline cohort risk distributions.

Compile an amendment impact dossier with visual trade-off matrices for protocol review committees.

Interactive parameter slider interface comparing baseline vs amended criteria yields and demographic distributions.

Construct synthetic patient datasets with lab ranges, vitals, and condition histories or load open mock datasets. Starter examples below are synthetic. They are not downloaded records.

HL7 FHIR overview Apply FHIR Clinical Reasoning and ResearchStudy definitions to encode baseline and amended eligibility parameters.

crewai, pandas, pydantic. crewai coordinates multi-agent evaluation of protocol safety limits, recruitment delta calculations, and summary writing. Hosted LLM with reasoning capability for comparative clinical criteria analysis.

Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

Parses baseline and amended criteria configurations without numeric ambiguities.

Calculates net change in eligible synthetic subjects across stratified biomarker ranges.

Produces a structured impact scorecard detailing recruited delta and risk shift warnings.

Allows protocol analysts to download reproducible simulation manifests.

```json [ { "input": { "amendment_id": "AMD-42", "criteria_changes": { "platelet_count_min": { "baseline": 100000, "amended": 75000 } }, "synthetic_records": [ { "id": "S1", "platelet_count": 80000 }, { "id": "S2", "platelet_count": 120000 }, { "id": "S3", "platelet_count": 60000 } ] }, "expected_output": { "amendment_id": "AMD-42", "baseline_eligible": 1, "amended_eligible": 2, "net_gain": 1, "newly_eligible_ids": [ "S1" ], "safety_margin_flag": "mild_relaxation" } }, { "input": { "amendment_id": "AMD-43", "criteria_changes": { "platelet_count_min": { "baseline": 100000, "amended": 100000 } }, "synthetic_records": [ { "id": "S4", "platelet_count": 90000 } ] }, "expected_output": { "amendment_id": "AMD-43", "baseline_eligible": 0, "amended_eligible": 0, "net_gain": 0, "newly_eligible_ids": [], "safety_margin_flag": "no_change" } } ] ```

Research protocol modeling application; evaluated exclusively on synthetic data; no medical advice or care delivery. Use mock external writes. Require human review before any real deployment.