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Data is the heart of clinical trials, so life sciences firms need to integrate their technology to keep data sources and trial portfolios up-to-date and secure.
As the past two years have certainly reinforced, the clinical landscape evolves at a rapid pace. For example, the coronavirus pandemic spurred the need for new vaccines. It took only 11 months1 for the first COVID-19 vaccines to go from the development stage to being granted emergency use authorization.
At the same time, technology keeps improving and changing the way we get work done. As a result, there is a near-constant need to adjust systems and ensure operations are up to date and compliant. To keep up with the latest industry updates—while keeping data sources and trial portfolios up-to-date and secure—technology integrations are front and center.
This article discusses the need for integrating clinical trial technology stacks, best practices for integration, and the steps organizations can take to make this happen.
Clinical trials are all about collecting data to prove whether a compound is safe and effective. High-quality and compliant clinical data relies upon the work of many individual teams working on everything from monitoring and management to TMF documentation, from study startup to subject and visit management, and even personnel tracking and vendor management.
All of these activities depend upon each other, which means the function-specific systems need to be able to communicate, share progress updates and reference information. The technologies used to manage the data for these various domains are often disparate. The very integrity of clinical trial data, therefore, depends on creating data consistency across the domains—ultimately dependent on the quality of your technology stack’s integration.
An integrated tech stack ensures all the tools and applications work together to provide a holistic solution for the integrity of your clinical trial data. If all functions are not available in a single system, validated integrations provide proof of control over your shared data. Integrations are a huge time-saver given the ability to automate data updates across systems that would otherwise be difficult, time-consuming, and prone to error if handled with a manual process. Better data management can even lead to faster clinical trials overall.2
While the value of integration is high, the project costs are not trivial. Fully tested and beneficial integrations require their own funding, requirements, and implementation work so it is important to know the best practices for a clinical trial technology integration before you jump in.
Appropriate planning is the first step in building any integration initiative. Look for the path of least resistance. Assess what is available in the environment already. If the expansion or reuse of an existing integration is possible, explore that opportunity as possibly a faster, more cost-effective option.
Once you scope the change and systems impacted, focus on the following five areas to uncover potential issues and resolve them before the integration goes live.
Investigate expected data volumes and learn the amount of time available for your integration to make data updates. System timeouts for long-running processes will revert your data or worse: leave partial updates in the target system. As a general rule, project the greatest possible volume your integration will need to handle.
Significant volume may result from day one for production, the introduction of new data sets from acquisitions, or significant portfolio growth. Your integration process needs the means to handle these stressing volumes, as easily as day-to-day operational data updates. Use boundary situations to give you the volume numbers to compare to the integration capacity within the available time frame.
You may need a little creativity around how you deal with large volumes, given available time for updates and your system or tool constraints. Solutions to deal with high volume stress are easier managed when identified, incorporated in the plan, and tested in advance.
Before you begin an integration, consider the types of data that will be shared. Master data may be stored in a central system or generated by a single system and shared across the domain. Evaluate the opportunity to pull this data directly from the authoritative source to assure the timeliness and veracity of your data.
For example, the Investigator's Brochure would be shared across clinical and regulatory systems. You will want these to be used in Clinical, although the authoritative system is in Regulatory. Gaining a thorough understanding of authoritative data sources will build a solid foundation for decisions on the direction of the integration.
Next, ensure your source and target systems are able to share the same data without creating errors. Historically, systems may have fields with the same name, but different sizes or data definitions. Your integration needs rules to document any data value or format changes to assure compliance. Whenever possible, maintain alignment to the authoritative source data definitions.
Another task on your to-do list is to investigate any triggers in the target system. For example, when entering the last visit for the site’s subjects, the last patient visit milestone completion may be triggered, and the date recorded. Be sure to plan for these triggered activities when testing the integration.
Getting a project like an integration done efficiently and effectively takes a team effort. With that said, it’s important to know the personnel and systems involved, their roles, and interest in delivering the project. Make these expectations part of the documentation and communication for the project. Misunderstandings in responsibilities may result in a redundant effort, incomplete activities, or system implementation failures. Avoid these pitfalls with effective team communications.
For post-implementation, you want to ensure all stakeholders are clear on who is responsible for the ongoing support of the integration. Assign decision-making rights for the evolution of the integration and align the stakeholders impacted by the integration.
Finally, agree on who owns decision-making authority for portfolio management and fiscal oversight of the integration over time. Changes to process, content, and upgrades will need funding and resource planning.
You have one remaining item to plan: Which studies to include? When you have studies that range from relatively new to long-running, not all may be reasonable candidates to use the integration. Understanding that variability in your study environment will help you determine if all your studies should have the integration turned on at launch or to identify the situations when you should disable integration updates.
Remember, even the most elegant integration solutions can have issues. Your implementation plans need to allow for the management of failures. Have options for correcting production data ready in advance such as restoring corrupted elements to their original state or utilizing a manual update to mitigate the issue. A viable backout strategy will reduce organizational stress, in case of an error.
With clarity on decision-making responsibilities, now consider staffing. A capable team is a vital factor in your project success.
Take a step back and answer these questions:
A capable team relies on the contribution of professionals from multiple areas. Technical expertise in integrations is a must. Partner technical expertise with subject matter experts from each system involved in the integration. These experts will need to speak to volume, business process, and system use.
Strong business analysis and project management will keep the project focused and moving forward while providing necessary progress updates to an engaged and supportive leadership team.
The support of the security, validation, and privacy teams is often overlooked in the initial planning. Engage these teams early to align on specific communication and requirement needs.
Team resources with demonstrated experience and the ability to dedicate the needed time to the project will improve the likelihood of your project success. Skilled resources reduce the risks of slips on timelines or budget overruns. External, specialized resources may be needed to supplement your team, if there is a lack of skilled internal resources with the ability to dedicate sufficient, focused time to the project.
It’s better to encounter issues early in the project execution than when you’re about to go live with the integration. You may end up with short-term costs but a better return on your integration investment by considering integration resourcing needs early—including people and the environment.
Now’s the moment you’ve been waiting for: implementing your integration. You’ve gone through all the planning and know the best practices, so now it’s time to flip the switch and move your portfolio data.
When an integration initiative is well-planned and successful, you reap many benefits including a reduced risk of failing compliance standards, enforced consistency across systems, and standardized data at an enterprise level rather than per system.
Active clinical trials generate data at an exponential pace. When you have a large volume of data, it’s best to have the systems integrated so you reduce the risk of costly errors and frustration. The life sciences industry is a tightly regulated space and failing to manage compliance jeopardizes not only your time and money but also the important therapy you’re trying to test and bring to market. Performing a technology integration right the first time often proves to be faster, cheaper and more compliant—and you won’t have to wonder if your data is correct because it will be standardized at the enterprise level.
Follow these best practices for clinical trial technology integration to keep your data secure and in compliance, moving you one step closer to bringing your product to market.
Teresa Montes is a Clinical Practice Lead for Daelight Solutions