For consultants and in-house biostatistics teams

Choose a task. Try the example. Adapt the inputs.

Start with a browser demo, then use a local copy for your study. Every example is synthetic. This toolkit is reusable across organizations; it is not configured for a specific client or validated for every study design.

Whole-toolkit setup: Download once and use the point-and-click control panel for all local apps, examples and template projects. Preview every module.
Browser-only start: open the tracker or continuity workspace with no installation. The TRIALMON, lifecycle and UAT demos also run R in the browser on the published site; their first load downloads the runtime.

Find the right starting point

Track deliverables and exceptions

Open Study Tracker: stable task IDs, owners, dates, status, notes and change history. Browser-only use starts immediately. Python 3.10+ adds CSV/JSON imports and SQLite history. Double-click a launcher or use the hosting shortcut, then manage accounts and email through browser forms. Preview messages before enabling your SMTP service.

Adapt: use your task IDs and operational owners; agree which fields scheduled jobs own. Keep: download JSON for browser edits, or import it into SQLite. Offline file imports use the last supplied values; shared edits reject stale row versions.

Try Inputs and CLI Point-and-click setup

Prepare leave coverage or a handoff

The continuity workspace turns a job inventory into coverage risks and a handoff packet. No installation; local browser storage and JSON/CSV downloads.

Adapt: recurring jobs, named backups, runbooks, schedules and criticality. Check: backup coverage and runbook links; retain an exported copy before changing browser or machine.

Try CSV template Playbook

Review participant-safety signals

TRIALMON uses synthetic inputs to demonstrate participant-level review and a Safety Review Committee packet. It is a review aid; its demo thresholds are not universal clinical rules.

Adapt: the documented study data schema and prespecified review thresholds. Run locally: choose TRIALMON in the toolkit control panel, check packages, then click Start local app. Review the input checks and packet before study use.

Browser demo Setup and inputs

Monitor study milestones and trial risk

Lifecycle summarizes milestones and operational signals. Risk combines operational metrics and explicitly weighted tiers; weights and thresholds need study-specific review.

Run locally: choose Lifecycle or Risk in the toolkit control panel, check packages, then start the app. Replace the documented CSV inputs and verify the resulting indicators.

Lifecycle demo Lifecycle setup Risk setup

Plan IRT / RTSM acceptance testing

Test scripts, requirement traceability and a defect log support UAT. Automated gate checks package evidence for human review; they do not approve a vendor system.

Adapt: URS requirements, test IDs, expected results, severity and evidence. Run: use the UAT card in the toolkit control panel. The app's CSV export covers tests; preserve defect/traceability records separately.

Browser demo Setup and persistence Workbook

Reconcile hours and scope changes

Compare planned hours, effort spent and estimated effort at completion. Apply available slack and an explicit contingency; then consider deferral or a change order.

Adapt: the effort ledger, estimates, requested hours and reserve. Run: use the Hours card in the toolkit control panel. Verify assumptions and totals before using the result in a scope decision.

Setup and inputs Workbook Guide

Build study analyses and TLFs

Follow the worked bioequivalence study or configure the 221 R TLF programs through guided forms. The study has a pinned R environment; the R library has synthetic numerical and execution QC, with native SAS reference exports.

Adapt: design, estimands, populations, ADaM schema and shells. The SAS library has not been executed. Review the R methods and rerun QC for your study inputs.

Worked study Reproduce SAS shells R shells

Vaccine immunogenicity and reactogenicity browser R

Run directly in the browser with no R installation or toolkit download: upload and map CSVs for geometric summaries, paired fold rises, study-defined response rates and solicited reactions. Explicit limits, populations, visit labels and missing-data rules; complete results and SAS reference exports. Includes a scientifically reviewed illustrated learning companion and synthetic examples.

Run in browser Vaccine module Learning companion Open control panel

Explore methods, reporting and QC

Use the lifecycle simulation, carryover and C-QTc studies to examine stated assumptions. The pipeline register maps deliverables. The interpretation drafter has a number validator; its model step is a stub.

Adapt: only where the method and data contract match. The validation harness combines automated checks with explicit manual gates; a passing demo is not validation of a new study.

Simulation Carryover C-QTc Pipeline Drafter QC harness

One control panel for the complete toolkit

Follow the point-and-click setup guide: download and extract the complete ZIP, double-click Start Toolkit, create a private project from the examples, then choose a module card. Check dependencies, install supported R packages, start local apps, run the reproducible examples, upload documented inputs and export your project from the browser. The source examples remain available as a baseline.

All five Shiny apps are included: TRIALMON, lifecycle, UAT, risk and hours. SAS/R template libraries and local-model helpers have preparation and project-opening paths with their limits stated; they are not presented as finished analyses. Browser-only demos and references remain usable without a local runtime.

Optional terminal interface for R users

Rscript launch_app.R --list
Rscript launch_app.R --check
Rscript launch_app.R trialmon --install

The R launcher remains available. Package installation is explicit and user-local; the apps bind to your computer. See the setup guide for the browser-based workflow.

Move from the example to your study

Keep a complete checkout and preserve the example. Run its demo and checks first so you have a known baseline.
Map inputs explicitly. Keep stable IDs, expected column names, date formats and units. Replace demo owners, thresholds, weights and assumptions with reviewed values.
Exercise boundary cases. Try missing and malformed inputs, empty datasets and known exceptions. Compare key totals and decisions with a small independently checked example.
Choose persistence and access. Export browser work; back up local files. For the shared tracker, use the guided setup and choose a host when the team is ready. SMTP is needed only for live email; preview files work locally.
Document review for the intended use. Retain the input version, software version, results and reviewer decision under your organization's process.

SAS monitoring and local-language-model examples require their separately installed runtimes and explicit path, scheduler or mail configuration. They are configuration templates, not preconnected services. SAS monitoring setup · Local-model setup