Modern Software Development is Driving the Future of Clinical Research and Technology
The rising complexity of clinical research and its impact on spiraling R & D costs, data integrity, and patient burden is a well-documented trend that has been accelerating over the last decade as trial procedures become more complex, data volume multiplies, and technology solutions continue to fragment. What’s less documented are the emerging and enduring solutions for better management of clinical trial complexity.
A host of eClinical applications, including electronic data capture (EDC), interactive response technology (IRT), electronic trial master file (eTMF), and others provide the backbone of an intricately layered clinical trial infrastructure. These eClinical solutions initially brought more speed and accuracy in trial management, but they also represent a big part of the problem. Most are inflexible and incompatible with each other and not intuitive for the end user. They create disparate silos of data. Disparate data streams from multiple sources make it difficult to manage data across research processes. As the number and variety of eClinical tools increases, so does the risk of inconsistency, error, and inefficiency. (1) Often, these disjointed systems require costly workarounds and complex integrations.
Modern software approaches offer enormous opportunities to better manage complexity by simplifying data sharing and collaboration, enabling a single source of truth and introducing consumer-grade user experiences to patient-facing and site-facing trial tasks. This article discusses the evolution of modern software approaches in clinical research, and shares insights on how iterative advances are driving the future of agile, adaptive research.
The groundwork for modern software development is already complete.
Somewhere between 2012 – 2020, cloud computing eradicated the last vestiges of a paper-driven clinical research model by enabling:
- direct data capture
- centralized management of data
- rigorous data access controls
- real-time monitoring and analytics, among numerous other benefits (2)
It also elevated the importance of Chief Privacy Officers, to ensure compliance with HIPAA Security and Privacy Rule, FDA requirements, and other mandates.
If cloud computing revolutionized the archaic clinical research IT infrastructure, application programming interface (APIs) radically simplified the path to interoperability through the ability to easily and securely transfer data across systems, enabling safe collaboration between sponsors, business partners, the research community, and numerous software providers needed to support a clinical trial. By automating labor-intensive and manual processes, APIs improve quality. By seamlessly integrating systems, APIs reduce silos and duplicative data entry across the dozen or more systems used in a single clinical trial, that invariably involve 30% of redundant data collection.
Validated, re-usable integrations quickly replaced outdated practices of creating custom integrations for each piece of software used to support a clinical trial and reduced the chances of broken connectivity.
Microservices technology emerged in clinical research between 2016-2017 but was not widely adopted until later. As an architectural and organizational approach to software development, microservices deconstruct platform systems down into smaller application parts, or loosely connected functions. These application parts are independently deployable instead of being tightly woven into a monolithic infrastructure. (3) Key benefits include:
- Faster changes and updates (impacted parts don’t require redeployment of the whole application, and don’t increase risk of stability). (3, 4)
- Reduced risk of errors and delays through the ability to isolate changes and updates to the impacted parts instead of the whole application.
- More collaboration across developer teams and knowledge-sharing about the functional requirements for each critical task of a clinical trial workflow.
Among the greatest benefits of microservices are the ease and cost of maintenance and scale. With the pace of technological evolution, applications built from multiple small parts are less costly to maintain as more advanced technologies are introduced.
API-driven microservices adoption represents another big step towards clinical research interoperability through the ability to connect patchworks of integrated tools that are often difficult to coordinate and manage throughout the life of a clinical trial.
A hallmark of cloud computing, multi-tenant software architecture delivers software as a service (SaaS) platforms that allow groups of users across different locations to access a common application instance. (5) Highly configurable by design, configuration eliminates long validation cycles and the need for custom coding. For clinical trial solutions, multi-tenant SaaS solutions offers rapid delivery, lower costs, scalability, a menu of configurable applications, and continuous updates. Developers typically allocate separate databases for each tenant to ensure security and complete isolation.
Headless architecture is a newer application architecture with a separated front end and backend. (6) Also described as “API-first architecture,” it allows developers to take the core functions, databases, business logic and existing integrations from a digital application or several applications, and create a user interface, or connect a different front-end channel to create unique customer experiences. It essentially allows developers to select building blocks from different providers rather than from one platform vendor.
Conceived as flexible architectures that enable security, scale, and opportunities to customize the customer experience, headless architecture grew out of online retail innovation. Websites designed for digital commerce need to be optimized for good user experiences on a variety of screens and devices. Connecting multiple front-end interfaces to the same backend resulted in the most efficient way to optimize UX/UI across computers, and an array of mobile devices.
In the context of clinical research, headless architecture enables a single user interface as the front end for the user to access a range of eClinical tools, so that core applications (EDC, IRT, eCOA, CTMS) appear seamless to the project team and sites. In practical terms, front end functionality is completely user driven. The user experience is not compromised by any of the back-end system development.
Technology is ephemeral, even in clinical research applications. That’s why one of the greatest benefits offered by headless architecture is the readiness it provides for future platform additions and changes. (7)
Next generation IRT
As a behind-the-scenes engine, IRT systems power the most critical functions of a clinical trial, from simple to advanced randomization to drug supply and trial management.
Next-generation IRT technologies incorporate the core modern software development components for faster delivery, seamless integration with other systems, more visibility into study data and more flexibility to accommodate protocol changes during a study. Configuration methodologies put the user at the center of the system design process, shortening time to delivery and ensuring that the system meets functional expectations based on the evolving demands of clinical trial management.
As IRT capabilities continue to advance, sponsors can look forward to faster, more flexible system development and more operational efficiencies in newer systems, such as:
- Advanced configurability with room for customization to support one-of-a-kind and first-of-a-kind study designs.
- Adaptive designs and master protocols – Trials using adaptive designs are on the rise, which also increases the frequency of changes to treatment arms, drug supply or randomization approaches during a study. Flexible change implementation through web or mobile interfaces, without downtime or vendor support, is an increasingly essential IRT function.
- The range of emerging decentralized trial models offer the greatest expansion opportunities to IRT functionality, as IRT applications enter the patient’s domain. Home-based trial participation will advance more user-driven portal solutions, with API transactions powering a range of activities from managing visit schedules to drug shipment requests for at-home dispensing.
The complexity and collaborative nature of clinical research demands sophisticated software and data management solutions. While systematic implementation will likely remain as a longstanding challenge, modern software approaches are already enabling patient-centered research designs, efficiency and quality through:
- Broader industry adoption of API-driven activities and transactions that provide better connectivity across a patchwork of systems and reduce the need for manual work, which also reduces burden on over-tasked research staff.
- Functionality that allows for real-time, rapid modification and centralized implementation to accommodate protocol changes.
Consumer-grade and user-driven, field-tested experiences based on behavior and preferences to boost engagement, compliance and ultimately data quality.
- A pace of innovation – much faster than in previous years – that continually optimizes the patient experience based on choice and convenience as decentralized models continue to expand.
Ultimately, clinical research will remain an intrinsically human endeavor, but modern software approaches will assume a more significant role as an enabling partner in a high functioning collaborative research ecosystem.