Clinical research has evolved a lot since public service announcements in the 1980s reminded parents to check-in on their children. These were not your typical hopeful, optimistic PSAs. The ominous voiceovers and eye-catching graphics were simple — yet powerful — warnings to parents across the United States.
"It's 10pm, do you know where your children are?" was a call to action.
Bad things are happening out there. Your children are at risk. Do you know where they are?
The same question can be asked of the countless study samples that traverse the globe every day.
We all know that clinical trials need reliable data from biological samples to produce meaningful results. But rarely do we know where our samples actually are. Understanding how they got there, and verifying who was involved, often proves even more challenging. Any loss of visibility ultimately creates gaps in a sample's lifecycle. These gaps make traceable chain of custody impossible for the majority of samples that our clinical trials depend on.
Bad things are happening out there. Your clinical data integrity is at risk. Do you know where your samples are?
Protocols are getting increasingly complex while outcomes are more dependent than ever on biological samples. Effectively managing these samples requires coordinating a complex chain of activities, performed by different research stakeholders, in different locations, in a very specific order.
Logistical efficiency is further impacted by our industry's reliance on:
It almost feels like most studies are designed to prohibit sample visibility.
What are the root causes of limited sample visibility, and how can they be addressed quickly and cost-effectively?
Begin with a system of record that transforms your study documents into structured, software-guided sample collection and management workflows. Then connect all of your research stakeholders — ClinOps teams, Research Sites, vendors, carriers/couriers, and analytical laboratories — to this system of record so that everyone is on the same page. Lastly, power every step of your sample collection, labeling, storage, and shipment process with smart lab kits that are guided by software, collecting important data along the way while ensuring compliance.
When protocol complexity collides with scale it results in more patients, more study visits, more time-points, more samples, and more shipments.
Hence the uptick in clinical outsourcing, and the general acceptance of a specialist model that unfortunately still relies on people — not software systems — to manage and mitigate operational risk for valuable biological samples. Today’s modern clinical trial dynamics challenge this traditional approach to sample management, which involves coordinating all the countless jobs that must be done across all participating research stakeholders. Here are just a few:
While specific sample management activities are unique to each Research stakeholder, they're often interrelated and interdependent.
Knowing sample disposition at all times — in real-time — requires everyone be connected to a centralized system of record that acts as the data infrastructure for all sample collection and management activities in the context of a specific clinical trial.
Be wary of vendors and analytical laboratories offering siloed solutions that slice off data and workflows for specific sample types. Remember — any gap in a sample's lifecycle breaks chain of custody, resulting in questionable data integrity.
With everyone on the same page you now have access to a tremendous amount of operational data. Your system of record can use this data to play "air traffic controller" for all the moving parts. This means getting lab kits to Research Sites, transforming those lab kits into valuable biological samples, and ensuring that those samples arrive to the right analytical laboratories on time, every time.
While everyone accepts the importance of laboratory manuals with clearly described sample collection, labeling, storage, and shipping procedures, best practices and SOPs are rarely structured as enforceable, guided workflows. This lack of quality control from sample collection to pre-analysis at the analytical laboratory makes visibility, and the associated chain of custody, nearly impossible. Because of this, study sample management has become an all too common failure point in our collective quest for better clinical data integrity.
Take a step back, and think about your own study's sample management strategy.
Are you overly dependent on things like paper or electronic lab manuals, hand-written tube labels, paper requisition forms, pre-printed shipping labels, reactive communication strategies, and manually scheduled courier pick-ups? Are you using a combination of phone calls, email chains, project management software, and spreadsheets as your system of record? Do you find yourself addressing a nonstop barrage of sample-related questions that begin with who, what, when, where, or why? Do you dread the inevitable protocol and lab manual amendments that create a cascade of problems that stretch all the way back to your lab kitting vendor?
Manual processes, coupled with no true system of record, leave Research Site staff, CRAs, and ClinOps teams stuck duplicating efforts over and over again. These manual processes not only create potential points of failure — they are points of failure that impact 60% of researchers.
A system of record that connects all research stakeholders, and has been designed around your protocol, lab manual, and pharmacy manual, provides the software guardrails you need to ensure that every step of your study's sample collection and management process is executed flawlessly.
Modern studies are increasingly reliant on more complex protocols, more patient visits, more time-points, and more samples to move clinical research forward.
Increasing sample collection requirements have transformed lab kits from a simple line item in your budget to mission critical status. This makes lab kit design critical to efficient downstream sample collection, labeling, storage, and shipment. While most vendors can accommodate lab kit configurations with simple labels and barcodes, rarely do you see technology-enabled lab kits streaming real-time data based on complex serialization strategies delivered just-in-time based on actual patient demand data.
The absence of smart lab kits leads to non-stop emails and phone calls between research stakeholders.
No system of record, no software-guided sample workflows, and no smart lab kits means constant communication to manually coordinate, patch, and synchronize sample data across spreadsheets.
Early-phase clinical trials often fail because they can't effectively triage all of the problems that inevitably pop up with reactive communication. As a result, primary safety and efficacy outcomes are often jeopardized by incomplete sample chain of custody that arises from missing data. This impact is magnified when you consider the patient populations that bear the greatest burden, such as rare disease and specialty oncology trials. A single sample being lost in one of theses trials could result in the failure of the entire clinical program.
Smart lab kits are a necessary component of sample visibility and traceable chain of custody.
Reliable sample data is the lifeblood of clinical research.
Knowing where all of your samples are, understanding how they got there, and verifying who was involved with their journey are all crucial to clinical data integrity. If you have to ask, your data is already at risk.
There are three steps to ensuring sample visibility for your next clinical trial:
An estimated 85% of clinical trials will experience serious delays, leaving ClinOps teams struggling to deliver their studies on schedule and on budget. Give your team a fighting chance by using solutions like Slope to drive visibility and efficiency across your clinical supply chain.