A Data Analyst’s Perspective
By Anastasia, Head of Centralized Monitoring and Analytics at Cyntegrity
In today’s world, with a wealth of information readily accessible, it’s easy to get overwhelmed. Many assume that having more information leads directly to better decisions, but that isn’t necessarily true. Only the information that directly answers your specific question, after being processed, cleaned, and presented correctly, can truly be valuable for informed decision-making.
Introducing the EMA Clinical Trials Map
Recently, the European Medicines Agency (EMA) introduced a novel way of presenting clinical trial data: the European Clinical Trials Map. After 20 years in data analytics and centralized monitoring, I confidently say that choosing a map format for clinical trial information was precisely the right decision.
You might wonder: “Ana, what’s new here? Most of this data can already be found on other websites, typically downloadable in table format for analysis.” That’s true, but while tables are practical for direct calculations, they can complicate decisions involving geographic elements and multiple variables. A map, however, provides an intuitive visual representation, significantly reducing potential errors.
Key Functionalities of EMA’s Clinical Trials Map:
- Geographical Visualization: Easily identify trial density across regions.
- Medical Condition Filters: Quickly isolate studies relevant to specific therapeutic areas.
- Recruitment Status Filters: Differentiate between actively recruiting and completed studies.
Why the EMA Map Matters
This initial release already provides substantial value. Users now have access to a detailed European Union map displaying clinical trials that actively recruit patients and those who have finished recruitment. The map supports filtering by Medical Condition and geographical areas down to regional and sub-regional levels.
What Can We Do With This Map?
First, let’s examine the filter panel. What information can we find there?
Image 1.: Before setting the necessary filters, we can see two key numbers at the top: Total Trials and Total Sites. Why are these numbers significant? Because they allow us to calculate the average number of trials per site: 8,738 Trials / 8,495 Sites = 1.03
This means that, on average, each site shown on the map is/was involved in at least one study.
Image 2.: Now, moving down the filter panel, the following filter is “Medical Condition.” Here, we can select a specific diagnosis (or multiple diagnoses) for our analysis. Let’s check Asthma, for example.
Be careful here: If you type “Asthma,” all types of asthma-related studies will be displayed on the map. But there’s another interesting insight—when we filter for asthma, we see 82 Total Trials across 949 Sites, meaning that 0.86 studies per site have been involved in asthma trials. Let’s remember this number and apply another filter.
Image 3.: Now, let’s check the box “Only show recruiting” and compare the numbers again: 30 Trials / 539 Sites = 0.56 studies per site. That’s a 35% decrease compared to the overall Asthma studies (both non-recruiting and currently recruiting).
This is good news (though not a guarantee) for those planning an asthma study because PROBABLY:
- There is currently less competition for studies.
- The chance of finding experienced sites (versus naïve or less experienced ones) is higher.
Next, we have two additional filters:
- “Country” (multiple choice)
- “View sites by” (options: Country – Region – Sub-region)
Set these filters according to your needs.
Practical Applications for Analysts
As an analyst, the real value lies in the geographical insights that a table format struggles to convey. Understanding where new disease cases are emerging and where active recruitment is concentrated helps refine recruitment strategies. If most potential patients reside in areas with heavy recruitment activity, it might be necessary to reconsider geographic targeting or delay studies to avoid competing for the same sites and investigators.
Future Enhancements and Expectations
Looking ahead, I hope EMA continues to expand this tool. Valuable additions could include more filters, such as recruitment end dates, study phases, and targeted patient numbers, alongside the ability to export data for detailed analysis.
Even in its current form, EMA’s Clinical Trials Map significantly enhances recruitment planning and operational decisions.
Thank you, EMA, for delivering an innovative tool that addresses critical analytical needs in clinical trial management!
