> For the complete documentation index, see [llms.txt](https://help.bioinsight.illumina.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.bioinsight.illumina.com/correlation-engine/querying-and-interpreting-results/clinical-trials.md).

# Clinical Trials

**Clinical Trials** shows relevant entries from [ClinicalTrials.gov](https://clinicaltrials.gov/) that match your query term. Like Literature, it uses text-based search with biomedical tag-cloud filtering to help you contextualise your research within active or completed clinical studies.

{% hint style="info" %}
Clinical Trials results come from **text-based searches** of trial descriptions, not from genomic data correlations.
{% endhint %}

## What Can You Query?

Clinical Trials accepts any query term or keyword — genes, concepts (diseases, tissues, compounds), or free text.

## How to Query Clinical Trials

1. Enter your term in the query field.
2. Click the **Clinical Trials icon** in the app menu.

## Understanding Clinical Trials Results

Results are listed in order of relevance by default. To sort by date of last update, select **Date** from the sort drop-down above the results.

Each result shows the trial title, phase, status, sponsor, and a brief description. Click a trial to view its full ClinicalTrials.gov entry, including eligibility criteria, intervention details, and location information.

### Geographic Map

Trials with location data are displayed on an interactive map. As of v2.9.0, all trial location pins are present; earlier versions had intermittent issues with newer trial locations appearing on the map.

### Tag Cloud Filtering

Below the search bar, a **tag cloud** displays key biomedical terms extracted from the trial descriptions in the current result set. Tags are listed alphabetically; larger typeface indicates stronger association with your query term.

**To filter using a tag:** Click any tag in the cloud to restrict results to trials mentioning that term.

**To filter by tag type:** Click the filter category buttons (e.g., **Phenotype**, **Tissue**, **Compound**) to control which types of tags appear in the cloud.

**To filter by keyword:** Enter a term in the filter box below the tag cloud and click **Filter**.

**To reset filters:** Click **Clear all** to return to the original, unfiltered results.

{% hint style="info" %}
By default, the tag cloud is constructed from the top 50 results. Select 200 or 1000 from the drop-down on the far right of the filter bar to include more results — this produces a more informative cloud but increases compute time.
{% endhint %}

## Known Issues and Recent Fixes

* **v2.9.0 fix** — An issue where facet filters disappeared and reappeared when multiple facets were clicked has been resolved. An issue where location pins were missing for newer trials has also been resolved.
* If the map is not displaying correctly, try refreshing the page.

## Exporting Results

Use the standard **Export** functionality to download the current list of clinical trial results.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://help.bioinsight.illumina.com/correlation-engine/querying-and-interpreting-results/clinical-trials.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.