ClinicalTrialsHub: Bridging Registries and Literature for Comprehensive Clinical Trial Access
Abstract
We present ClinicalTrialsHub, an interactive search-focused platform that consolidates all data from ClinicalTrials.gov and augments it by automatically extracting and structuring trial-relevant information from PubMed research articles. Our system effectively increases access to structured clinical trial data by 83.8% compared to relying on ClinicalTrials.gov alone, with potential to make access easier for patients, clinicians, researchers, and policymakers, advancing evidence-based medicine. ClinicalTrialsHub uses large language models such as GPT-5.1 and Gemini-3-Pro to enhance accessibility. The platform automatically parses full-text research articles to extract structured trial information, translates user queries into structured database searches, and provides an attributed question-answering system that generates evidence-grounded answers linked to specific source sentences. We demonstrate its utility through a user study involving clinicians, clinical researchers, and PhD students of pharmaceutical sciences and nursing, and a systematic automatic evaluation of its information extraction and question answering capabilities.
Cite
@article{arxiv.2512.08193,
title = {ClinicalTrialsHub: Bridging Registries and Literature for Comprehensive Clinical Trial Access},
author = {Jiwoo Park and Ruoqi Liu and Avani Jagdale and Andrew Srisuwananukorn and Jing Zhao and Lang Li and Ping Zhang and Sachin Kumar},
journal= {arXiv preprint arXiv:2512.08193},
year = {2026}
}