Syneos Health adopts Oracle APEX to better manage clinical trials

Syneos Health adopted Oracle APEX to accelerate the build and long-term management of a database-centric clinical trials application, aiming for pixel-perfect UI fidelity, smoother integrations, and faster delivery under an aggressive deadline. The project team weighed traditional high-code stacks such as Java, Node.js, and React against low-code options, concluding that APEX could cut development time by roughly an order of magnitude—about 10 times faster—while requiring a smaller team (around a quarter of the developers). That speed mattered because the requirements and UI markups were already well defined, and the timeline left little room for a slower, more code-heavy approach.

The decision also hinged on how much business logic lived in the Oracle database. With a substantial portion of logic documented and implemented at the database layer, the team expected APEX to translate that structure more cleanly than platforms that force more logic into the application tier. That database-centric design reduced friction in standing up the application and made it easier to replicate the existing UI markup faithfully—possibly even improving it. Integration needs were another deciding factor: the application had to connect with many other systems, and the organization already had Oracle’s suite in place, making APEX a practical fit for an environment where data and services are already anchored in Oracle.

Beyond initial delivery, the team emphasized maintainability over a multi-year horizon. Low-code was framed not just as a way to ship the first version, but as a way to keep evolving the system for five to ten years as new team members join. The concern wasn’t only changing features; it was onboarding people without forcing them through massive documentation or deep rewrites. APEX’s learning curve was described as unusually low for interns: Syneos Health hires roughly 20–25 interns each year, and they typically become productive within three months. While mistakes can still happen and experienced guidance is needed to navigate specialized features, the core approach was said to be easy for newcomers to pick up.

The broader strategy ties APEX to Syneos Health’s “intelligent enterprise” push, where AI is treated as an operational layer across the organization. The company’s AI roadmap includes two streams: traditional AI/ML for predictions such as which sites enroll faster, how quickly patients can be enrolled, and which sites need a “nudge”; and generative AI aimed at accelerating customer-facing work. Examples include an APEX application that can draft a new clinical trial protocol from scratch, plus a tool that lets users ask questions against a lengthy protocol document and get answers about what’s happening inside it.

A further planned capability—an “PDC” application—targets monitoring and oversight. With thousands of projects running simultaneously and project teams managing many sites, AI is used to distill and summarize site-level activity, surface risks and issues, and bubble up what project managers should focus on each morning. The transcript also outlines how AI becomes usable in practice: it requires data, knowledge/model training (not necessarily in APEX), and an algorithmic model, but the AI must be delivered through a UI/UX that feels non-intrusive. APEX’s REST handlers are positioned as the bridge, enabling AI algorithms to be exposed via APIs across cloud environments and inserted into the right screens to change business outcomes—without making users think about the underlying platform.