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TrialPanorama/TrialPanorama-database

Quick start The easiest way to download the dataset to your local is to use huggingface-cli. The specific command you can use is huggingface-cli download zifeng-ai/TrialPanorama-database --local-dir LOCAL_DIR --repo-type dataset where LOCAL_DIR should be replaced with the target directory you want to save your dataset to. Update history Aug.4 2025: updated tables with the full set of studies Dataset website: https://ryanwangzf.github.io/projects/trialpanorama… See the full description on the dataset page: https://huggingface.co/datasets/TrialPanorama/TrialPanorama-database.

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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Dataset Card

Quick start

The easiest way to download the dataset to your local is to use huggingface-cli. The specific command you can use is

huggingface-cli download zifeng-ai/TrialPanorama-database --local-dir LOCAL_DIR --repo-type dataset

where LOCAL_DIR should be replaced with the target directory you want to save your dataset to.

Update history

  • —Aug.4 2025: updated tables with the full set of studies

Dataset website: https://ryanwangzf.github.io/projects/trialpanorama


TrialPanorama

TrialPanorama is a large-scale, structured database and benchmark designed to support AI-driven tasks in clinical trial workflows—including systematic review and trial design. This repo hosts the database of clinical trials. To conduct benchmarking experiments on trial design and systematic review asks, check this dataset instead: https://huggingface.co/datasets/zifeng-ai/TrialPanorama-benchmark

Dataset Overview

  • —Aggregates over 1M clinical trial records from ClinicalTrials and PubMed
  • —Captures standardized elements such as trial setups, interventions, conditions, biomarkers, outcomes, and links to biomedical ontologies (e.g. DrugBank, MedDRA).
  • —Structured into multiple conceptual clusters and tables (e.g. trial-level attributes, protocol design, results, links)

Benchmark Suite

The dataset supports a suite of 8 benchmark tasks across two domains:

  • —Systematic Review:
  • —Study search
  • —Study screening
  • —Evidence summarization
  • —Trial Design:
  • —Arm design
  • —Eligibility criteria
  • —Endpoint selection
  • —Sample size estimation
  • —Trial completion assessment

Data Schema (Major Tables)

  • —`studies` — core metadata (e.g. study\_id, intervention type, sponsor type, start year, trial phase, recruitment status)
  • —`protocols`, `interventions`, `conditions`, `biomarkers`, `outcomes`, `results` — each standardized to a unified schema

 Use Cases

  • —Developing and evaluating LLMs and ML models for clinical trial-related tasks
  • —Benchmarking AI capabilities in trial search, screening, design, and summarization
  • —Conducting meta-analyses and exploring evidence synthesis across disease areas
  • —Enabling interoperability with biomedical ontologies to support richer clinical trial reasoning

Getting Started

 Citation

If you use TrialPanorama, we appreciate your citation:

@article{wang2025trialpanorama,
  title={TrialPanorama: Database and Benchmark for Systematic Review and Design of Clinical Trials},
  author={Wang, Zifeng and Jin, Qiao and Lin, Jiacheng and Gao, Junyi and Pradeepkumar, Jathurshan and Jiang, Pengcheng and Danek, Benjamin and Lu, Zhiyong and Sun, Jimeng},
  journal={arXiv preprint arXiv:2505.16097},
  year={2025}
}