The biopharmaceutical industry is characterized by the extremely complex nature of the work involved. Join a company in the life sciences industry and you will soon find yourself connected to a body of work that spans multiple organizations, multi-million or billion dollar budgets, and timelines of a decade or longer.
This complexity gives way to a phenomenon not possible in many industries: thriving hyper-focused niches. The worlds of site management organizations, adverse event reporting software, or subcutaneous drug packaging are some examples. These niches are narrow and specific, but because of the gravitas of the work involved many companies and hundreds of professionals are able to build an ecosystem around them.
I’ve focused much of my career in the niche described as medical imaging in clinical trials. I consult to companies in this ecosystem still while I lead BrackenData in building clinical trial intelligence tools. Because of this, it is by no surprise to anyone in my network that I’ve lead BrackenData to develop a medical imaging specific intelligence product: TrialFinder Imaging.
From developing this product we’ve curated a new dataset of imaging-specific clinical trial activity. I’d like to explain how this works, but the short of it is we’re sharing our data on the growth rates of medical imaging use in clinical trials.
Play with the interactive graph at the end of this post to see the number of medical imaging trials since 2000. Anyone with business associated with imaging core labs or imaging endpoints should find this insightful.
How We Retreive This Data
On a weekly basis we download all of the data from CT.g, clean it for errors, categorize much of the information, and then update our TrialFinder dashboard filters and visualizations.
TrialFinder Imaging takes this a step further from our standalone TrialFinder product by using a proprietary semantic text analysis process we’ve developed to categorize medical imaging trials. This is a fancy way of saying that our systems looks at all of the words used in all CT.g trail records to identify any protocol that indicates the use of medical imaging. The system creates a field for what kind of imaging modality is being used, then enables a TrialFinder user to filter the database by these imaging modalities.
For example, TrialFinder Imaging can identify any trial on CT.g that uses MRI. It can also take the filtering much further by showing things like tables of data on all Phase 2 trials with a start date in the last year, originated in the US, using Radiography.
The list of imaging modalities we currently filter on include MRI, CT, Tomography, Radiography, UltraSound, Nuclear Medicine, Echocardiography, DXA, OCT, Functional Near-Infrared Spectroscopy, Elastography, and Tactile Imaging.
The data used in the chart at the end of this blog post plots by start date any medical imaging trial registered on ClinicalTrials.gov.
We have data going back to 2000, but regulations about using CT.g weren’t enforced until 2007 (notable by the huge spike after 2007). For fair analysis, we’ll discuss trial activity since 2008.
The Growth Rate of Medical Imaging in Clinical Trials
From 2008 to 2016 the volume of medical imaging trials grew 27.3%, averaging 3.4% year over year.
In this 8 year span there have been 5 years of growth and 3 years of decrease. Decrease years are 2010, 2012, and 2013.
Since 2013, the last decrease year, we are observing a year over year growth rate of 6.3%, which is almost 1.9x our 8 year average.
In 2016 we saw the more medical imaging trials take place of any year in history, and the number is actually still growing as clinical operations teams are still registering 2016 studies on CT.g (a phenomenon we’ve mentioned in previous blog posts).
How to Use the Chart
Time is the x-axis, while count of NCT ID is the y-axis. Count of NCT ID is referring to the number of clinical trials in the dataset (NCT is the unique identification number given to a trail on CT.g). Th entire dataset is clinical trials on CT.g indicating the use of medical imaging technology.
Mouse over any bar to reveal the numbers for that year.
Use the expanding arrows icon in the bottom right to enable full screen mode.
Click the double down-arrows button in the top left to group the data by Month of Year.
Click the hierarchy button in the top left to drill-down data by every month since January, 2000.
Finally, toggle the down arrow in the top right and click on a time period to drill-down further into that specific time period.