# Coupling Results Data from ClinicalTrials.gov and Bibliographic Databases to Accelerate Evidence Synthesis

> **NIH NIH R01** · BOSTON CHILDREN'S HOSPITAL · 2021 · $328,000

## Abstract

Project Summary
Clinical trials are foundational to evidence-based medicine, but results reporting from trials is incomplete and
frequently delayed. It is estimated that as many as half of clinical trials are not published and as many as half
of published trials underreport or misreport outcomes. This type of results reporting distorts the evidence
available to clinicians—particularly when it comes to assessing the safety of interventions like drugs and
devices—and may place patients at unnecessary risk. There is a critical need for novel methods to identify and
monitor drug safety data. Through the infrastructure provided by ClinicalTrials.gov, structured trial results
(including safety findings) are now becoming available for an increasing number of trials in a comprehensive
and timely fashion. However, access and use of these data in evidence synthesis tasks remain limited.
ClinicalTrials.gov is the largest single registry for clinical studies worldwide and includes more than 260,000
registered studies. Of the 108,941 completed trials registered with the site, 20% have uploaded results data for
a total of 7.85 million participants. Results data reported on ClinicalTrials.gov have the potential to fill gaps
created by delays and biases in published articles and provide an earlier and more complete overview of
available trial evidence. We propose to develop novel informatics approaches based on combinations of
information retrieval and machine learning methods to facilitate access and analysis of trial results reported in
this registry. Focusing on trials testing drug interventions in type 2 diabetes, obesity, and oncology, we perform
this work in three specific aims: 1) Develop semi-automated trial screening for identifying and aggregating trials
relevant to a clinical intervention; 2) Extract adverse event and safety outcomes data from results reported in
the registry; and 3) Perform validation studies to assess detection of adverse events and performance of semi-
automated meta-analyses of safety outcomes. Methods developed in this project will facilitate timely, broad-
scale use of trial results reported on ClinicalTrials.gov in order to augment the availability of comprehensive
and timely drug safety data. All methods will be made publicly available in order to support adverse event
monitoring and systematic reviews of drug interventions.

## Key facts

- **NIH application ID:** 10136717
- **Project number:** 5R01LM012976-03
- **Recipient organization:** BOSTON CHILDREN'S HOSPITAL
- **Principal Investigator:** FLORENCE BOURGEOIS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $328,000
- **Award type:** 5
- **Project period:** 2019-03-01 → 2023-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10136717

## Citation

> US National Institutes of Health, RePORTER application 10136717, Coupling Results Data from ClinicalTrials.gov and Bibliographic Databases to Accelerate Evidence Synthesis (5R01LM012976-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10136717. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*