Introduction

In the world of data analytics, choosing the right graphic to highlight important trends is paramount. In clinical trial development, a bullseye chart is one example of a data visual used to provide a holistic view of the research on various diseases and therapeutic areas. Bullseye charts can neatly summarize a massive amount of data, allowing viewers to see overarching trends and drill down into the results. Below, we walk through a recent example of how we used this type of chart to paint a picture of the dermatology clinical trial landscape.

At Bracken, we are often asked to provide insights into the outlook of the drug development process around a therapeutic area, disease, or other niche. Often these areas do not have a complete data set around them or a consistent identifier, requiring a multi-team approach to find and process this data. Our standard approach involves our consulting and analytics teams brainstorming what data we can use to answer our question, what key identifiers in the data will best suit our needs, and what the output should look like. That is exactly what we did when we were recently requested to analyze rare diseases in the dermatology space.

Identifying Diseases

Our client was interested in understanding what dermatological diseases were being studied in clinical trials and providing a holistic view of the drugs used in these trials. The consulting team created a list of seven diseases for which we wanted to investigate the clinical trial landscape. 

• Cutaneous Lupus Erythematosus (CLE) 
• Cutaneous Crohn’s Disease 
• Pruritis 
• Vitiligo 
• Rosacea 
• Hidradenitis Suppurativa 
• Acute Radiation Dermatitis 

Identifying Trials

Bracken’s database, which utilizes Clinicaltrials.gov, was a great fit for this problem, as it contains all clinical trial data since 2010 with added layers of intelligence and tools to help us to search and categorize trials quickly. 

In a perfect world, we could simply search for all of the above diseases and identify trials where they are the target condition; however, the data can be messy, and with multiple common terms, misspellings, and a number of other issues we needed to be a bit more flexible with our query. The consulting and analytics teams searched through our dermatology data (using Bracken’s therapeutic area filter) to create a curated keyword list that would be more robust in identifying trials. After layering in these filters and adding the disease groupings to our data, we were finally ready to build our visual. 

Data Presentation

We wanted to view the progress of various drugs through the clinical development pipeline, specifically highlighting trials by phase, study status, and adding in additional data looking at the sponsor and start date for those trials. 

As mentioned previously, we knew that a bullseye chart could be a helpful tool to accomplish our goals. The below chart shows our final product, an interactive JavaScript chart that gives users a high-level view of trials for each of our rare diseases. This chart was built using the template provided by this blog, modified for our use case. 

Slices of the circle represent the disease indications, and the concentric circles show trial phases from unknown and Phase 1 through Phase 4 as the circles decrease in size. Icons in the rings are the drugs being used in the trials, and their shape identifies what the study status is. If you hover over an icon, you can see additional information such as what the name of the trial is, its NCT ID, the sponsor, and trial start date. Using that data, viewers can lookup full trial records in Clinicaltrials.gov that they are interested in to continue their research. 

These charts are robust and highly customizable, particularly when paired with an adaptable data set such as Bracken’s database, which utilizes Clinicaltrials.gov while connecting additional data sets and custom logic. Our consulting expertise and data analytics tools enable us to identify trials in a number of novel ways that aren’t natively available within the Clinicaltrials.gov data set, which help identify a myriad of additional elements in the clinical development space. Using this type of chart, you can investigate many clinical trial related topics such as what trials specific sponsors are developing, trends in a therapeutic area, or drugs being studied for applications related to specific conditions. 

Data can be messy. Analytics shouldn’t be. If you’d like to learn more about how Bracken’s analytics tools can help answer your questions, or working with Bracken's team of expert consultants, please reach out to our team by filling out our contact form.