Clinical trials have always been complex, but the last five to ten years have seen an increase in complexities due to the rising volumes of data involved. The expansion of decentralized and hybrid clinical trials has largely driven these changes, but data use in traditional site-based clinical trials is also growing.
Clinical protocols have also become much more complicated because of the more data collected in areas such as participant enrolment and trial milestones.
Increases in data require careful management, and new technologies also bring opportunities. Targeted data collection can increase the efficiency of clinical trials throughout different phases, support regulatory applications, and improve the overall transparency of processes. To deliver these goals, application programming interfaces (APIs) are crucial.
Enabling interoperability between different clinical trial systems
In a clinical trial, it is common for clinical research organizations (CROs) have multiple software systems and platforms in use to accomplish objectives. These can include electronic data capture (EDC) systems, surveys for electronic patient-reported outcomes (ePRO), e-consent forms, lab results, and images, as well as participant history. In addition, wearable technologies and remote monitoring capabilities open a new dimension for data acquisition of participants.
Across all these systems, there can be numerous user accounts for the same trial participant.
However, all systems must communicate with each other and share the most recent data in real-time, which is where the importance of APIs comes into focus to create a single source of truth.
Without effective APIs, there will likely be a lack of cohesion between systems, often resulting in siloed data and discrepancies. The other option is to use manual processes, which can significantly lengthen clinical timelines, and increase the costs and inefficiencies. Crucially, the use of APIs minimizes data errors across systems.
The advantage of APIs is the ability to move from a manual action to an automated workflow able to incorporate multiple platforms and user profiles. This creates many benefits for a clinical trial.
“When you go from a process that was done by a user manually to something automated, you gain the time; but also, you have the precision of that work – and the repeatability. So, it can be repeated over and over,” explains Majd Mirza, chief innovation officer at Viedoc. “All of these make the process more efficient.”
APIs also offer traceability, enabling more efficient audits. They facilitate seamless integration with downstream systems, allowing for real-time data fetching, data updates, or triggering actions across other systems as needed.
“With an API, the power is to be able to use this system in a workflow or as a part of a bigger automatic workflow, so that you can orchestrate and use that functionality of that system in a bigger workflow without any manual intervention,” says Mirza. “APIs are the backbone to making integrations possible,” he adds.
Strategic use of APIs in clinical trials
Adopting APIs requires a strategy with clearly defined use cases. Incorporating APIs into workflows and expecting results without a clear plan will likely be counterproductive and expensive.
Furthermore, it is vital that data can be trusted. If there are any discrepancies, it can undermine the reliability of data and potentially even impact regulatory approval.
Viedoc has considerable experience in implementing APIs within clinical trials, providing solutions that enable systems integration. A key product is the Viedoc API, which facilitates seamless and efficient data transfer between the Viedoc EDC and many other operating systems. Viedoc API allows for data to be imported easily and exported for backups.
Designed for both flexibility and power, the API meets the most complex integration needs. Clients can also customize the platform to meet specific challenges. Additionally, the Viedoc solution includes optimal management capabilities for users and sites, seamlessly integrating all systems into wider clinical processes.
“You need to have confidence in the relationship between the different systems so that you can trust the data,” adds Mirza.
To learn how about the advances in clinical data management, download the document below.
