How Can Clinical Trial Data Integration Streamline Biospecimen Data Entry and Reconciliation?

Clinical trials take place across a complex network of systems and vendors who manage patient samples and sample metadata. Each time biospecimens change hands, the associated metadata that identifies what the samples are, who they belong to, their chain of custody, and other data points that are relevant to sample testing/processing — must travel with them. 

Ideally, the data that moves with a sample — like patient demographics and sample collection times — should stay consistent throughout the entire journey. Pre-existing data should not change as it’s handed off from stakeholder to stakeholder, but additional data may accompany the sample as it carries along its journey from site to various labs and biorepositories.

Unfortunately, this is not what actually happens in practice. The flow of data from one stakeholder to another is oftentimes clumsy at best. Every person who touches patient sample data has to spend more time entering that data from one system or document into another system or document, resulting in inefficiencies and significant lags in accessibility to data for sponsors. What’s more, the data can also become lost or distorted in translation.

As a result, sponsors have to work with their vendors to perform data reconciliation, which involves the comparison of sample metadata across various sites, labs, source documents, and clinical systems to identify missing data or discrepancies between data. Unfortunately, the practice of reconciliation is incredibly time-consuming and demands many resources across virtually every stakeholder who supports the trial. In the end, some data may be irreconcilable — resulting in precious samples being discarded and valuable data points being excluded from the final study data.

Data reconciliation is also an essential task; in fact, database locks enable sponsors to leverage clean data at certain points throughout and at the end of a study so they can perform interim analyses and assess the state of their trial operations. These critical study decisions can’t be made without a clean, complete set of data.

Given the critical nature of sample metadata, what can sponsors do to make their data more accessible while also minimizing the need for data reconciliation? The answer involves data integrations that drive standardization.

How do data integrations work in clinical trials?

In order to understand how integrations work and how they can be beneficial in clinical trial execution, it’s important to understand how sample metadata traditionally moves.

The majority of sample metadata — such as patient demographics, visit information, collection dates and times, and sample identifiers, are captured at the site. Sites will record source data, record the data on requisition forms, and eventually enter the data in the EDC. The data from the requisition form is used to enter data into various lab databases, while the EDC data eventually feeds directly to sponsors and CROs. Each step of this complex workflow is highly manual, requiring someone to record the data on a document or within a clinical system. 

Data integrations accelerate and streamline the flow of data from one clinical system to another with minimal lag time and without the need for manual data entry. This not only saves stakeholders time and money at various touch points, but it also improves data integrity, eliminating contemporaneous risks to sample metadata that can lead to labor-intensive data reconciliation.

How do data integrations eliminate the need for duplicative data entry?

Repetitive data entry exists in clinical research because the various clinical systems that are deployed in clinical research are operated by disconnected stakeholders. Integrations bridge the gap between these different databases, using technology on the back end to automatically transmit data from one source to another.

Think about the number of times that the same data has to be manually entered for a single sample across its entire lifecycle: once by the administrator who captures the source data, once by the study coordinator who fills out the requisition form and enters the data (days or weeks later) into the EDC, once by the lab staff who accession the samples into the system, and potentially once again if the sample is traveling to other labs after that.

Rather than relying on manual data entry during each step of this process, sponsors can leverage integrations to automatically transmit sample data as soon as a patient visit has been conducted at the site. This can eliminate the burden on sites to fill out paper requisition forms and enter data into the EDC, while eliminating the need for labs to manually accession sample metadata into their systems. 

How do data integrations speed up data accessibility?

Every step in the journey of a patient sample represents additional time — not just because it takes time for a sample to physically move from one place to the next, but because it takes time for data to be entered along the way. Even once the data has been entered into one system, the quality and integrity of the data may be questionable. It takes sponsors a long time to piece all of the data together, as they have to manually pull reports and communicate with their vendors to pull together the latest information for each of their samples. 

Integrations can bring all of your sample metadata together in one place in real time so that sponsors no longer have to wait, run several reports, or talk to multiple stakeholders just to get the data they need on a routine basis. This in turn translates to streamlined sample tracking and reconciliation because of the connectivity between various databases.

How do data integrations reduce reconciliation?

It goes without saying that manual data entry introduces risk. Each time the same data has to be entered into a different source or system, it is prone to discrepancies. We explore this phenomenon in greater detail in our blog, “What Can the Game of Telephone Tell Us About Our Current Approaches to Sample Management?”

However, when data flows from one source to all of the downstream systems where it needs to be entered, the result is fewer discrepancies and less data reconciliation. This has the potential to not only speed up sponsor access to clean biospecimen data, but it also enables them to accomplish database locks well ahead of schedule.

How do data integrations enable clinical trial monitoring?

Monitoring requires sponsors to keep tabs on site activity and sample movement, as these activities have a significant impact on clinical trial outcomes and therefore should be a top priority. In order to adopt a centralized monitoring strategy and a risk-based approach, sponsors must be able to house all of their biospecimen data in one place so that they can keep a pulse on high-risk processes and quickly identify site-specific, patient-specific, and visit-specific trends. Ideally, this approach should involve bi-directional integrations that allow data to be transmitted to and from various systems in one central hub for biospecimen data. Systems integrations that enable operational logistics can also streamline lab kit management, reducing the burden on sites and kitting vendors, while reducing inventory waste and optimizing study budgets.

Use Slope’s software and integration capabilities to streamline your access to clean biospecimen data

Slope’s clinical trial execution platform is powerful. Our software not only gives sites an inventory and sample management platform that enables them to accurately and efficiently perform their daily tasks, but the platform automatically captures critical biospecimen data while site staff are conducting patient visits. Through integrations with key clinical systems, like EDC, LIMS, RTSM/IRT, and more, this data can be transmitted to important study stakeholders in real time, with the potential to eliminate paper requisition forms and repetitive data entry. In effect, Slope enables quicker access to more accurate, complete sample metadata that sponsors need in order to make critical decisions and labs need in order to process samples.

In addition, these integrations can be set up bidirectionally. This enables other study stakeholders to feed important information back to Slope, such as sample tracking information. Slope acts as a real-time hub for sample metadata, enabling fundamental clinical trial activities like sample tracking and monitoring. 

To learn more about how improved access to sample metadata can help you enhance your trials, check out our ebook, “Optimizing Your Clinical Trial Monitoring Strategy to Boost Research Site Compliance.”