Generate realistic clinical trial synthetic data including study definitions, sites, subjects, visits, adverse events, efficacy assessments, and disposition. Use when user requests: clinical trial data, CDISC/SDTM/ADaM datasets, trial cohorts (Phase I/II/III/IV), FDA submission test data, or specific therapeutic areas like oncology or biologics/CGT.
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SKILL.md
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name
healthsim-trialsim
description
Generate realistic clinical trial synthetic data including study definitions, sites, subjects, visits, adverse events, efficacy assessments, and disposition. Use when user requests: clinical trial data, CDISC/SDTM/ADaM datasets, trial cohorts (Phase I/II/III/IV), FDA submission test data, or specific therapeutic areas like oncology or biologics/CGT.
TrialSim
Status: Active Development
TrialSim generates realistic synthetic clinical trial data for testing, training, and development purposes.
For Claude
Use this skill when the user requests clinical trial data, CDISC-compliant datasets, or regulatory submission test data. This is the primary skill for generating realistic synthetic clinical trial data.
When to apply this skill:
User mentions clinical trials, studies, or protocols
User requests CDISC, SDTM, or ADaM datasets
User specifies trial phases (Phase I, II, III, IV)
User mentions FDA/EMA submission data or regulatory requirements
User asks for adverse events, safety data, or efficacy endpoints
User mentions specific therapeutic areas (oncology, cardiovascular, CNS)
User requests SDTM domains (DM, AE, VS, LB, CM, EX, DS, MH)
Key capabilities:
Generate complete study definitions with protocol parameters
Produce subject-level longitudinal data with realistic patterns
Generate safety data (adverse events, labs, vitals) with MedDRA/LOINC coding
Create efficacy endpoints for various therapeutic areas
Output CDISC-compliant formats (SDTM, ADaM)
For specific trial phases, therapeutic areas, or SDTM domains, load the appropriate skill from the tables below.
Safety Guardrails
All data generated by TrialSim is synthetic and fictional. It must never be used for real clinical decisions, patient care, or regulatory submissions without explicit disclaimers.
Synthetic data only: All subjects, sites, adverse events, and results are generated/simulated. Always confirm this when presenting output.
No clinical advice: Never recommend treatments, prescribe medications, or interpret safety signals as if data were real. If asked "should this patient receive X?", remind the user this is synthetic test data.
Real codes, synthetic entities: Use real standard code systems (ICD-10, CPT, LOINC, SNOMED CT, MedDRA, RxNorm, NDC, NPI, ATC, HCPCS) for coding accuracy, but all people, sites, and events are fictional.
Do NOT generate: Real patient identifiers, actual investigator names, real site addresses, or any data that could be confused with actual clinical trial records.
Trigger Phrases
Activate TrialSim when user mentions:
"clinical trial" or "clinical study"
"Phase I/II/III/IV" or "pivotal trial"
"CDISC", "SDTM", "ADaM"
"FDA submission data" or "regulatory data"
"adverse events" or "safety data"
"efficacy endpoints"
Trial therapeutic areas (oncology, cardiology, etc.)
Integration Pattern: Use PatientSim for baseline clinical characteristics. TrialSim adds protocol-specific assessments (RECIST, NYHA class changes), randomization, and SDTM-formatted data.
Cross-Product: PopulationSim Integration
PopulationSim provides embedded real-world data (CDC PLACES, SVI, ADI) for evidence-based trial planning, site selection, and FDA diversity compliance. When geographies are specified, TrialSim grounds feasibility estimates and enrollment projections in actual prevalence and demographic data.
See populationsim-integration.md for detailed data-driven planning patterns, embedded data sources, and site selection examples.
Development Status
All skill files complete: core skills, Phase 1-3, SDTM domains (DM, AE, VS, LB, CM, EX, DS, MH), therapeutic areas, and RWE.
{"dataset":"ADTTE","records":[{"STUDYID":"ONCO-2025-001","USUBJID":"ONCO-2025-001-001-0001","PARAMCD":"PFS","PARAM":"Progression-Free Survival","AVAL":182,"AVALU":"DAYS","CNSR":0,"EVNTDESC":"Disease Progression (RECIST)","STARTDT":"2025-01-22","ADT":"2025-07-23"},{"STUDYID":"ONCO-2025-001","USUBJID":"ONCO-2025-001-001-0002","PARAMCD":"OS","PARAM":"Overall Survival","AVAL":365,"AVALU":"DAYS","CNSR":1,"EVNTDESC":"Censored (alive at cutoff)","STARTDT":"2025-01-29","ADT":"2026-01-29"}]}
Generative Framework Integration
TrialSim integrates with the Generative Framework for specification-driven generation at scale.
Profile-Driven Generation
Use profile specifications to generate trial subject populations. The Profile Executor samples demographics meeting I/E criteria, generates baseline disease characteristics, applies randomization, and creates screening assessments.
Journey-Driven Generation
Attach protocol journey specifications to create visit sequences. The Journey Executor generates protocol visits at specified windows, creates assessments per schedule, applies visit variance, and handles protocol deviations and early termination.
Cross-Domain Sync
When generating across products, TrialSim entities are automatically linked: