Is Your Approach to Handling Lab Data Hurting Your Trials?

It’s no secret that without labs we wouldn’t have clinical trials. Labs perform the assays that generate the safety and efficacy data needed to support primary and secondary endpoints in the study protocol. Without labs, the data required to bring new drugs to market would simply not exist.

However, it's crucial to examine the role of labs within the broader context of clinical trial workflows. Laboratories depend on detailed sample metadata — such as patient demographics, collection dates and times, and more — to ensure that each sample meets the stringent requirements of the study protocol. This metadata not only validates the sample's compliance with study requirements, but also informs the subsequent testing and processing activities at the lab. Given the quicker accessibility of this metadata relative to the EDC, sponsors also often rely on it for sample tracking. 

Unfortunately, the metadata in lab databases is often incomplete or inaccurate due to issues with paper-based requisition forms. Lab queries can create gaps in data; and moreover, this metadata often hasn’t been reconciled with source data or EDC data until months after it has been collected, raising questions about its accuracy until a comprehensive QC of the data has been performed. 

Despite these issues, sponsors frequently use this data to inform decision-making and perform sample tracking. To make matters more challenging, data must be aggregated from various lab portals when multiple labs are supporting a single trial — heightening the burden of sample tracking.

Given its role as a critical data source in clinical research, lab data plays a key role in the reconciliation process. Sample metadata must be consistent and accurate across all sources, including the EDC and labs. 

This begs the question: How does the collection and transmission of sample metadata for labs exacerbate the challenges of data reconciliation? And beyond that, what impact do these challenges have on the execution of clinical trials?

Paper-based requisitions offer a traditional approach to capturing data for labs — but are they effective?

Labs traditionally capture data about samples from sites through requisitions. These forms are usually paper-based, requiring manual data entry by lab personnel. While this method has been a staple in clinical trials for decades, it is fraught with potential issues:

• Missing or erroneous sample metadata: Paper-based requisition forms are prone to errors such as missing information, discrepancies, and legibility issues. These errors can lead to lab queries that halt downstream processes — such as sample processing, shipment, and lab reporting — until the queries are resolved.
• Manual data entry: The manual nature of data entry demands a significant amount of time and resources from lab personnel. It also opens up additional risks for discrepancies due to human error.
• Reconciliation across multiple data sources: Since sample metadata exists across multiple lab databases and the EDC, these major data sources must be reconciled with source data. This reconciliation process is time-intensive for all stakeholders — including sites, CROs, labs, and sponsors.

What challenges do lab databases pose for data reconciliation?

The reconciliation of lab data with other data sources is a complex process. Several factors contribute to the challenges faced during this process:

• Multiple data sources: A single trial can involve multiple labs, each with its own database and data management practices. This means that data must be individually pulled and reconciled across multiple lab sources for a single trial.
• Manual processes: The manual entry of data across various sources by various people increases the likelihood of discrepancies. A change made to one source must be reconciled across all sources, further complicating the process.
• Dependence on lab portals: Sponsors often rely on reports pulled from lab portals for sample tracking. However, this data is often not reconciled at the point when it is used, leading to potential inaccuracies.

How do gaps in your lab data workflows impact your clinical trials?

Challenges associated with managing and reconciling lab data can have significant impacts on the efficiency and success of clinical trials:

• Data lag: The time it takes for sample metadata to make its way from the site to various labs is not conducive to real-time sample tracking. This means that most sponsors don’t have comprehensive, real-time visibility to their samples. 
• Delays in sample processing and reporting: Lab queries due to missing or erroneous sample metadata can halt downstream processes, leading to delays in sample processing and reporting of lab results.
• Increased time and resource burden: The manual data entry and reconciliation processes require a significant amount of time and resources from sponsors, lab personnel, site personnel, and other stakeholders. This can divert attention and resources away from other critical tasks.
• Dependency on incomplete, inaccurate data: Discrepancies between data sources can hinder sample tracking and delay sponsors’ ability to perform database locks, sample analyses, monitoring, and other critical activities. 

Click here to read our comprehensive guide on sample metadata management and data reconciliation

Slope's Biospecimen360™ software bridges the gap between study stakeholders so that you are getting the most from your lab data

Slope's biospecimen lifecycle software, Biospecimen360™, offers a range of solutions that address the challenges of capturing sample metadata for labs and reconciling that data — driving efficiency and accuracy in clinical trial execution.

E-Requisitions for accurate and compliant sample metadata collection

One of the key features of Biospecimen360™ is the use of e-requisitions. These digital requisition forms automatically capture compliant sample metadata and transfer it to labs through integrations. This process offers several benefits:

• Reduced queries: By capturing accurate and complete sample metadata the first time, e-requisitions reduce the likelihood of lab queries — minimizing delays in sample processing and lab reporting.
• Elimination of duplicative data entry: The automatic transfer of sample metadata to labs eliminates the need for manual data entry, reducing the risk of errors and discrepancies while driving efficiencies across sites and labs.

Integrations with labs and EDC

Biospecimen360™ integrates seamlessly with labs and the EDC, further enhancing data accuracy and efficiency:

• Additional reduction of repetitive data entry: By integrating with other clinical systems — including lab databases — Biospecimen360™ reduces the need for duplicative data entry across different stakeholders and data sources. This minimizes the risk of discrepancies and the need for extensive data reconciliation.
• Streamlined data reconciliation: The integration between Biospecimen360™ and the EDC simplifies the data reconciliation process. By transmitting the same data from Slope to labs and EDC, data is more accurate and consistent.

Centralized sample tracking

Biospecimen360™ provides a centralized platform for sample tracking, offering real-time visibility into sample status and metadata:

• Improved sample tracking: Sponsors no longer need to rely solely on sample reports from several lab portals for sample tracking. Biospecimen360™'s centralized platform provides real-time updates on the entire sample journey — from its initial state as a container in a lab kit at a site, through analysis or storage at the lab.
• Enhanced data analytics: The centralized capture and surfacing of sample metadata enables data analytics. Sponsors can gain valuable insights into sample activities, enabling quicker issue and trend identification and driving higher-quality trials.

On Thursday, July 25th, Slope will be hosting a live demo for sponsors that explores our lab-agnostic e-requisition solutions. Click here if you’d like to join the discussion.