The data you collect must be defensible and complete, and biological samples represent a critical source of that data. Therefore, to successfully execute a clinical trial, the sample management process also needs to be defensible and complete. It is crucial to have visibility into the entire sample journey, as it demonstrates protocol compliance and sample traceability. Lost or mishandled samples can significantly impact research sites, patients, data integrity, and study timelines.
Unfortunately, the current approach to overseeing study progress and managing risks during sample collection, processing, storage, shipping, and receipt is inconsistent. Limited visibility and reliance on reactive strategies both lead to gaps in sample traceability and non-standardized processes. This makes balancing sample management with available resources and budget an inevitable challenge.
So, what can you do? Traditionally, although every effort is made to trace biological samples, imperfections and shortfalls inherent to existing methods are acknowledged and accepted as a matter of course. The struggle to track every step and the reliance on multiple, disparate data sources usually lead to discrepancies, and leave us with only the hope that no critical samples are lost.
This guide is designed to empower you with effective sample management techniques, providing better oversight and insights. By enhancing your sample management practices, you can allocate more attention to your other sponsor responsibilities. Let’s dive in and optimize your sample management processes for successful clinical trials.
Sample management is the comprehensive oversight of the collection, processing, storage, shipment, receipt, analysis, and reporting of each patient’s biological samples in a clinical trial.
The sample journey entails the path taken by a biological sample from collection at the site to analysis at the receiving laboratory. To ensure accurate sample reconciliation, it is crucial to have documentation tracing the entire path, from the analytical lab back to the collecting site, patient, and the specific lab kit used.
The challenge in the traditional process is the lack of visibility into the sample’s chain of custody, resulting in uncertainties about sample integrity and location, and the risk of losing critical endpoints. Will the samples reach the appropriate lab in usable condition? Will they be processed in time to dose-escalate? Is the sample traceable back to the originating draw tube if a patient withdraws consent? These questions are just a few of the items that need to be addressed in order to have a robust sample management process.
In complex clinical trials, overseeing sample management poses numerous challenges as you prioritize patient safety and trial success. To help address these challenges, we have compiled a list of best practices designed to alleviate your concerns.
Samples play a significant role in supporting safety and efficacy endpoints, and have the potential to differentiate your IP. As such, considering the regulatory risks associated with samples is pivotal in your sample management planning for clinical trials. You must understand these potential risks and take proactive measures to mitigate them.
During your planning phase, it is essential to consider the following questions:
If you have answered no to any of these questions, you are opening yourself up to regulatory risk, especially if your samples contribute to safety, efficacy, and/or inclusion criteria. Prioritizing discussion around these questions and proactively mitigating these potential risks before and during your studies is crucial.
During a clinical trial, unexpected events can occur, such as encountering data issues that may delay patient enrollment or go unnoticed until later stages. However, creating standardized and systematic ways to identify, report, and take action for issues related to biological samples can help you mitigate the risks and avoid spending time and resources.
As you plan, aim to standardize your sample management process, taking the following questions into consideration:
Your study has started — patient samples are being collected, processed, and shipped to receiving labs. To meet your obligations of oversight, you review your sites’ activities as well as the lab results, making assumptions in between those two data points. This heavily manual process requires serious resourcing, especially considering sites and labs do not have visibility into other parts of the process.
That period during which you have to rely on guesswork is where issues — like a sample shipped to the wrong lab, or samples being missed — need to be found before they become more significant problems such as preventing dose escalation. The burden of finding the needle in the haystack lies with the sponsor.
Effective collaboration is crucial in mitigating study issues. By allocating resources for robust communication among all parties involved (sites, labs, sponsors), you can elevate awareness of existing problems, allowing for timely arrangements to prevent escalation. Additionally, establishing workflows that connect these parties and their activities can proactively prevent problems from arising. The combined approach of problem prevention through workflows and collaborative visibility significantly reduces study issues.
Sponsors have so many options for technology, and the decisions made have a direct impact on the success of their trials. Since the technologies chosen by sponsors are oftentimes ultimately used by sites, it is important to ensure the solutions align with site processes.
Picking the wrong solution can harm the study timeline and create more obstacles than it overcomes. The best practice is to listen to your sites about what they need to execute the trial more efficiently. Automating your sites’ sample management processes could prepare sites for patient visits, thus speeding up study timelines and helping your sites share patient data faster, increasing your visibility and study compliance.
To ensure the reliability of data derived from biological samples and demonstrate adherence in your sponsored study, it is essential to track the entire journey of each sample. Proper reconciliation requires the confirmation of patient-attributable final sample results without any gaps in the chain of custody.
The most effective approach is building comprehensive documentation for sites and labs, creating a complete audit trail that shows adherence to the study’s protocol-mandated sample collection requirements. This documentation enables consistent sample reconciliation and facilitates tracing each sample back to the individual patient and the specific time point of collection. To ensure a smooth and quality-driven process, sponsors should leverage automation rather than manual, labor-intensive processes to compile this documentation.
By implementing this practice, you enhance the integrity of sample management in your clinical operations, promoting data accuracy and accountability throughout the study.
In the dynamic landscape of clinical trials, unforeseen complications can arise, impacting study timelines and posing significant challenges. To effectively navigate such situations, it is crucial for clinical operations professionals to be prepared. While it may not be possible to anticipate every potential problem, proactive planning can help you stay ahead and mitigate the impact on your study. We recommend implementing the following practices:
By implementing these best practices, you equip yourself and your team to effectively handle complications, maintain study integrity, and minimize the impact of unforeseen challenges on your clinical operations.
Even if you follow every best practice, the sample management process still has visibility and traceability challenges — until now.
Slope’s clinical trial execution platform brings best-in-class sample management to sponsors facing challenges in biological sample management oversight, adherence, and reconciliation.
Slope’s platform is configured to the lab manual, protocol, and other study documentation, replacing unwieldy binders and providing site users with clear, digitized workflows for patient sample collection, storage, and shipping. As a result, sponsors can be confident that they can produce accurate reporting that their sites are adhering to the study requirements.
Protocol amendments should be managed systematically to avoid confusion about the protocol version or actions needed for patient visits. Slope streamlines amendment processes and provides adherence guardrails, empowering research sites to carry out their work seamlessly — even with changes.
Slope provides a single system of record with real-time insights as samples are collected and shipped. With robust integrations, real-time visibility and oversight, sponsors can trust the integrity of their clinical trial data without worrying about getting various sources of information and activities after the fact — leading to better, faster clinical trial decision making.
With Slope, sponsors no longer have to rely on data from error-prone manual processes to prove the chain of custody for samples. Our sample management solution provides true oversight and documentation for each step of the sample journey — from collection to lab-to-lab transfers to final analysis — all in one easy-to-use platform.
Patients are human beings, and providing a sample — especially those requiring invasive procedures — can sometimes be challenging for those with poor health. Better sample management enables better patient experiences. And better patient experiences contribute to the development of life-saving treatments.