Source: ncbi-nlp/TrialGPT
Local Repository: ./repo
Status: Integrated & Downloaded
TrialGPT is an NIH-developed framework for matching patients to clinical trials using LLMs. It provides a structured pipeline for trial retrieval, eligibility parsing, and ranking with evidence-based explanations.
- Trial Retrieval - Identify candidate trials from ClinicalTrials.gov.
- Criteria Parsing - Convert eligibility text into structured criteria.
- Patient Profiling - Summarize patient records into matchable features.
- Ranking + Explanation - Score trial relevance and provide justifications.
- Install dependencies
cd repo pip install -r requirements.txt - Run retrieval - identify candidate trials for a condition.
- Run matching - evaluate eligibility with structured criteria.
- Review outputs - validate by clinician or trial coordinator.
Input:
- Patient summary (structured or narrative)
- Condition keywords or diagnosis codes
Output:
- Ranked trials with relevance scores
- Criteria-level match explanations
- Missing data checklist
- Use TrialGPT for retrieval and initial ranking, then hand off to the Clinical Trial Eligibility Agent for deeper criterion-by-criterion analysis.
- Cache trial metadata (NCT ID, protocol version) to ensure reproducibility.
- Requires up-to-date trial metadata; outdated data can misclassify eligibility.
- LLM reasoning should be audited by clinical staff before enrollment decisions.