TrialHunt is the most powerful and accurate system to search and analyze clinical trial registry data from


Super-charged clinical trial registry data

Every day, tens of thousands of people search for information about clinical studies. But user-entered trial data can be inaccurate, incomplete, or inconsistent – and that means search results can be as well.

TrialHunt fixes and annotates trial registry data to help patients, doctors, researchers, and drug developers get more and better information from


“[Trials] reported in an imprecise or incomplete manner generally have limited to no societal value.”

– Deborah Zarin and colleagues, National Library of Medicine¹


Problems we're solving

Incomplete and Inaccurate Location Data

Almost 15% of records lack full city, state, and zip code information, and many city names include spelling errors and punctuation irregularities.

Variable Site Names

Trials at Massachusetts General Hospital can be listed as “Mass General Hospital,” “Department of Cardiology, Massachusetts General Hospital,” “MGH Division of Cardiology,” and other names.

Inconsistent Disease Names

There are distinct trials in for “uterine carcinosarcoma” and “mixed Mullerian mesenchymal tumor” – even though these are the same indication.

Missing Disease Relationships

It is currently impossible to identify all trials in for a group of diseases (like “hematologic malignancies”) without querying each individual disease separately.

Limited Analytic Capabilities

Physicians and patients are currently unable to map the locations of total and unfilled study seats by disease.


“Clinical trial participation stands at just 3 percent among U.S. adults with cancer. If clinical trials are to be successful, it is critical that more people get involved.” 

Francis Collins, Director, National Institutes of Health²


TrialHunt Solutions

Corrected Data

We fix missing and incorrect data on locations in trial records to enable more complete reporting of search results.

Expert Annotation

Our analytical and medical experts have resolved redundant and ambiguous disease names and mapped them onto the MeSH taxonomy.

Correlation With Other Data Sets

Our annotation enables users to cross-walk to geolocation data, U.S. Census data, PubMed, and other sources.


Sign Up.

Receive updates on TrialHunt and other news from Pharmagellan.

Name *

TrialHunt (patent pending) is a product by Pharmagellan ( To discuss how TrialHunt can help answer your specific questions about clinical trials, please contact us via email (