As stewards of clinical research, sites need to execute on protocol designs and study plans for every trial that they support with significant precision. As a result of the complex science that today’s innovative treatments and therapies demand, coupled with the need for the involvement of several vendors on every trial, executing on lab manual procedures can be a daunting task.
For any given patient visit on a single study, site personnel collect, process, store, and ship several different types of biospecimens, each of which may have their own unique handling instructions. When you multiply this complexity by several samples per visit, across several trials that are subject to frequent amendments and modifications, it’s easy to see how research sites may struggle to maintain near-perfect compliance with the most current protocol and lab manual for every single study.
The problem is not necessarily the study designs themselves, but the fact that most research site workflows still rely heavily on paperwork, spreadsheets, and a lack of standardization. So what facets of clinical trial planning and design can hinder traditional approaches to managing and improving research site compliance, and how?
Most research sites rely heavily on dense documents (such as lab manuals and protocols), paper trails, and spreadsheets to manage their lab kits, IP, other forms of clinical inventory, and patient samples. These processes already require a significant amount of manual work to maintain, but complex study designs and biospecimen plans bog them down even further. What elements of today’s trials are causing inefficiencies to buckle under even greater pressure?
A single protocol may contain variable visit schedules, in part because different patients who are screening or enrolling on the same study may have different sampling and visit requirements. Keeping track of these differences can be challenging, especially when a set of patients on the same trial may require different lab kits, biospecimens, data points, and more.
For early-phase studies that require a large amount of safety and efficacy data in the form of routine safety labs, biomarkers, and PK/ADA samples, site personnel may need to manage several biospecimens for a single patient visit. Each of these samples may require their own unique collection and return containers, their own unique processing steps, and their own unique storage and shipping requirements.
Late-phase studies may rely less on a large quantity of samples from each patient, and more so on high enrollment. Larger research facilities may be managing lab kits and samples for dozens, hundreds, or even thousands of patients for one study. These high-enrolling trials can place added strain on study resources.
Protocol amendments and other modifications that impact the lab manual may have downstream effects on research site workflows. Even though site personnel receive training on new versions of the protocol, study coordinators still may need to keep track of several changes that impact a single study — some of them subtle. Modifications may run the gamut of adding or removing a kit from a study, adding or removing a specimen collection from a specific lab kit, or even something as simple as a change in shipping frequency for a single sample.
Many research sites support several trials — and each trial may come with distinct lab kit vendors, CROs, couriers, central labs, specialty labs, clinical systems, and more. Managing the unique processes for each vendor involved on a trial can be cumbersome and difficult to keep track of — especially when certain vendor systems and processes may not be conducive to research site operations.
How do these common attributes of complex clinical trials put research site compliance at risk? For three critical components of running a clinical trial — lab kits, biospecimens, and data — traditional processes may not be up to snuff with the meticulous operations that today’s trial complexities demand.
Keeping track of lab kits across several trials and kitting vendors — especially when each study requires several unique lab kits — can be incredibly challenging.
As NCI-designated UPMC Hillman Cancer Center described in this case study, many research sites have historically relied on paper-based processes to manage lab kits, and each site staff member may have their own unique process for managing lab kits. These workflows are incompatible with complex lab kitting schemes; for instance, a research site may accidentally pull a Cohort C kit to collect samples for a Cohort A patient, even though these cohorts may have different sampling requirements.
Lab kits are also susceptible to changes over the life of a study because of protocol amendments and lab manual modifications. As a result of improperly managed lab kit inventory, site personnel may accidentally pull a lab kit that was designed under a previous version of the protocol or lab manual.
Complex or high-volume sampling across a research site’s clinical trial portfolio may complicate sample management workflows, thereby heightening the risk of missed collections, as well as lost or mishandled biospecimens.
Because of a dependency on static lab manuals that are dense and complicated in nature, it’s not uncommon for sites to miss a collection or unnecessarily collect a sample that only a subset of patients require. And with the sheer number of patients that enroll in late-phase trials, it can be easy to make accidental sample handling errors — from forgetting samples in storage freezers, to shipping a sample to the wrong lab or on the wrong day.
Frequent lab manual modifications can also make it easy for sites to accidentally follow outdated lab manual procedures. Without a robust, streamlined strategy for managing changes to sample workflows, study coordinators are more likely to commit sample collection or sample handling errors.
Patient samples often change hands multiple times before they leave a research site. In fact, throughout the sample handoff process, critical biospecimen data — from collection dates and times to critical administrative information — must carry with the sample.
Every trial, visit, and sample collected at a specific visit may require unique data points. This is especially true for complex trials, for which requisition forms may be more intricate in nature and therefore may require sites to document more data points. Unfortunately, site personnel may accidentally forget to record source data, or otherwise lose that data in translation — resulting in downstream lab and EDC queries that can put additional strain on study coordinators and jeopardize the timely reporting of critical patient lab results. Audit trails and source documents that are often paper-based and decentralized only intensify this burden.
Lab kit mismanagement can also have a downstream effect on the handling of sample data. If a study coordinator fills out the wrong lab requisition form for a specific visit, it will inevitably generate downstream queries.
Slope’s clinical trial execution platform for clinical inventory and sample management transforms static lab manuals into software-guided workflows that improve efficiency and drive sampling compliance under the most current versions of study documents. The best part? Slope is free for sites, and they can implement the platform across all the sponsors and trials they support.
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