Tracking Clinical Trial Samples: What Can Go Wrong Will

By Claire Anderson, clinical research specialist, Sampleminded

Early in my career, I accepted a position as a specimen tracking coordinator.  Only a few years out of college, I thought the title sounded impressive.  In actuality, I soon found myself pouring over hundreds of spreadsheets, sent from all over the world, trying to figure out what samples were available to analyze, and what was missing. 

I quickly realized that anything that could possibly go wrong did - samples listed as collected actually weren’t, items that were recorded as shipped were still on site, barcode labels didn’t match the paper documentation, or samples even seemed to disappear without a trace.  When emails and phone calls were not effective, I often resorted to hopping on a flight and personally digging through freezers in order to locate a handful of samples needed to close out a trial.

Simple miscommunications or clerical errors can be the difference between the success and failure of a clinical trial.  However, many clinics and labs are still tracking their sample inventory on spreadsheets as they did 10 years ago.  This method may be adequate for small labs with a close team, but it proves ineffective in multi-center clinical trials.

Is Sample Management Really That Important?

Most clinical trial protocols depend heavily on the analysis of biological specimens to meet study endpoints.  Sample collection requirements in these trials are becoming increasingly more complex due to the focus on biomarker analysis and precision medicine.  Sponsor organizations are also choosing to preserve a larger number of biological specimens for future research efforts. 

It is no longer enough to reconcile a check box on a Case Report Form (CRF) with results data to ensure the required samples were collected and analyzed.  Sample collection may be skipped due to the patient’s refusal or physical condition, an item could be inadvertently missed, or there may not be enough volume collected in a particular tube.  These types of things should be reported in detail so that intervention can be made quickly and in real time.  At a minimum, any sample management solution should be able to answer the following questions:

• What samples were collected?
• Were the requirements for the visit fulfilled?
• What happened to the samples?
• Where are they now?
• Were they consumed or destroyed?
• Are they available for further analysis?

Recording this specific information upfront will be invaluable later when investigators ask why data is missing, and will greatly reduce the amount of queries sent to the site.

Your Biggest Challenges May Not Be What You Think.

With Software Developer being #3 on the US News Top 100 Jobs for 2015, there is no shortage of talented engineers willing and able to create all kinds of software to track clinical trial samples.  Often the barriers to the adoption and success of a sample management project has very little to do with the software you choose, but how you choose to implement it.  Some of the common arguments for resistance to using sample tracking software include:

• The software is unreliable or slow
• The application is difficult to use or learn
• Too much data entry is required

By choosing a solution hosted on the cloud and with a robust disaster recovery and monitoring plan, there is no reason to expect less than a 99% uptime for your users.  This type of hosting is also typically less expensive since IT resources are shared among many customers.

As technologies that work seamlessly together have become more commonplace in our personal lives, we now have the same expectation of simplicity in our professional endeavors as well.  In order to lighten the burden on your site users, look for software that is configurable to your business process and study requirements.  By informing the system of expectations prior to study start, less entry is required by the site.  For example, you may be able to leverage barcode label information provided by kit manufacturers to eliminate the need of hand entering collection tube and specimen details.

To further reduce data entry, the sample management application you choose should also allow information to be imported or synced from other systems such as Electronic Data Capture (EDC), Laboratory Information Systems (LIS), and Clinical Trial Management Systems (CTMS).  To support these integrations, care should be taken to build a common vocabulary and data structure so that data is recorded in a consistent manner.

Where There Is A Will, There Is A Way.

Regardless of the challenges you may face in implementing a sample management solution, there are a couple ways you can streamline your sample inventory needs. 

Often, the easiest strategy to adopt is creating a virtual sample repository for the items collected in your individual trial or program.  A virtual repository compiles sample information received from each of your sites and labs and merges it together into a single database.  This can be done with a file import or through web service integration.  The advantage of this type of system is that each site can continue to use their preferred data collection method.  However, because data is collected in various formats, work will be required to ensure the data is consistent, and there may be holes in the sample custody or data received from the site.

The preferred option would be to implement a transactional system that records the sample information at each stage of the lifecycle, resulting in a full picture of how a sample was collected, processed, and transferred.  The system may also include storage management allowing you to not only know which site or lab is in possession of the sample, but also where it is located in the building, and how many times it has been in and out of the freezer.

Whether or not your organization will choose to implement a new system or improve on the one currently in place, my hope is that the clinical research community will continue to invest in more streamlined and efficient sample management processes.  After all, every research sample is extremely valuable - but only if you can find it first.