📘 Documentation

TrialForge AI — Clinical Trial Intelligence Platform

Overview

TrialForge AI is a clinical intelligence simulation platform that transforms natural‑language clinical trial protocols into structured, quantitative insights. It is designed to support early‑stage trial design exploration, feasibility assessment, and risk analysis by researchers, methodologists, and innovation teams.

The platform enables rapid interrogation of assumptions before first‑patient‑in, helping teams reason about power, sample size, uncertainty, cost, and operational risk under realistic conditions.

Core capabilities

Protocol parsing

Natural‑language trial descriptions are converted into structured design parameters (arms, endpoints, sample size, follow‑up, effect assumptions).

Monte Carlo–based power simulations

Thousands of stochastic simulations estimate statistical power, confidence intervals, and sensitivity to assumptions.

Synthetic cohort modelling

Plausible enrolment, attrition, and outcome trajectories are generated to support scenario testing.

Risk & feasibility assessment

Statistical, operational, financial, and regulatory‑adjacent risk indicators are surfaced for discussion.

Cost & timeline estimation

High‑level projections to support early planning conversations (not budgeting or contracting).

CONSORT‑style participant flow visualisation

Clear, interpretable representations of enrolment, allocation, follow‑up, and analysis populations.

Typical workflow

  1. 1. Describe the trial. Provide a draft protocol or design narrative in plain English.
  2. 2. AI‑assisted extraction. Key design elements (arms, endpoints, duration, effect size assumptions) are identified and structured.
  3. 3. Simulation & analysis. Monte Carlo simulations are executed across thousands of iterations under defined assumptions.
  4. 4. Review & iteration. Results are presented with confidence intervals, risk indicators, and key metrics for expert review. Outputs may be exported, saved, or shared with collaborators.

Assumptions & limitations

  • Statistical models rely on simplifying assumptions and user‑supplied parameters.
  • Output quality depends heavily on the clarity, completeness, and plausibility of inputs.
  • Simulations explore possible outcomes — they do not predict real‑world trial results.
  • Results should always be reviewed and interpreted by qualified biostatisticians and clinical experts.

Governance & safety

  • No protected health information (PHI) or patient‑identifiable data is processed or required.
  • The platform does not provide clinical decision support, diagnostic guidance, or regulatory advice, and is not a medical device.
  • All functionality is intended for research, education, and methodological exploration only.
  • The platform is designed to augment expert judgement, not replace professional or regulatory review.

Citation

If referencing TrialForge AI in academic or scientific work, please cite as:

TrialForge AI — Clinical Trial Simulation Platform (2025). Research and educational use only.