TrialGPT
Three-stage LLM framework (retrieval, criterion-level matching, ranking) that matches a patient summary to clinical trials from ClinicalTrials.gov; in the paper it cut clinician screening time by more than 40% in a pilot user study.
At a glance
What it does
TrialGPT is a large-language-model framework developed at the US National Institutes of Health that matches patient records to clinical trials. It analyses eligibility criterion by criterion, explains its reasoning in natural language, and ranks candidate trials for each patient.
Notable uses in oncology
In a Nature Communications (2024) evaluation, its criterion-level judgments reached 87.3% accuracy — close to physician experts — and a pilot user study showed a 42.6% reduction in screening time. The system was piloted on oncology trials managed at or related to the National Cancer Institute.
Tasks, data types and cancers
Architecture
Training data
None. TrialGPT performs zero-shot patient-to-trial matching by prompting a general-purpose large language model through the OpenAI or Azure API (the repository documents runs with GPT-4 / GPT-4-turbo); no model is trained or fine-tuned, so behaviour depends on the LLM that is plugged in.
Linked datasets
- evaluation ClinicalTrials.gov Open download — trial corpus the system retrieves from
Evaluation
| Benchmark / dataset | Metric | Value | External validation | Source |
|---|---|---|---|---|
| SIGIR / TREC clinical-trial cohorts | criterion-level accuracy vs. experts | 87.3% (paper) | yes | Source |
How to run
The code is open, but results depend on the LLM you plug in; patient data sent to a commercial API needs a compliant deployment.
Regulatory status and intended use
Regulatory status is quoted from the source linked above and can change. Research-use-only models must not be used for clinical decisions.
Limitations and bias
- LLM errors on nuanced criteria (lab thresholds, prior therapies); human review required.
- Privacy: patient text leaves the institution when using hosted models.
Sources
This page is educational — it is not medical advice and does not replace consultation with an oncologist. Diagnostic and treatment decisions are made solely by specialist physicians.