Managing Trial Complexity: Tips for Effective Technology Adoption

As new technologies come to market, clinical researchers are faced with a challenge common to many industries: which clinical trial technology solutions should they adopt, and how can they implement them effectively to realize the promised gains to productivity and insight?

Andrew Mould, Assistant Professor of Neurology at Johns Hopkins University and Director of the Data Coordinating Center at the BIOS Clinical Trials Coordinating Center, has spent over a decade navigating the evolving technology landscape across dozens of trials in neurology and beyond. He recently connected with the Prelude team to share helpful insight into how to evaluate and implement technology to drive real impact and innovation without introducing unnecessary complexity. Read on for key takeaways from the discussion.

Sorting through the Noise

Determining when new technology will actually add value starts with a few simple yet often elusive questions: What problem are you trying to solve? Is the value generated by a new technology solution greater than the costs (including time, resources, and added complexity) to adopting? Mould calls attention to the importance of this risk-benefit analysis, recommending researchers evaluate where the technology fits and what impact it is expected to have.

By first identifying specific operational challenges and tailoring the solution to directly address those pain points, teams can focus their time and energy in the areas where the impact will be greatest. Is participant retention suffering? Are you losing eligibility data between screening and enrollment? Do consent errors create bottlenecks?

Once the problem is clear, the appropriate technology becomes easier to identify. For instance, electronic consent systems aren’t cutting-edge, but they solve a fundamental problem that plagues paper-based processes: human error. Missing signatures, incorrect dates, illegible handwriting can all derail participant enrollment and create costly protocol deviations.

Mould notes that electronic consent and patient-reported outcomes capabilities, while perhaps not exciting, represent a significant advancement in lowering barriers for patient participation in trials. Sometimes the best innovation issimply removing friction from existing processes.

Integrating Tech, Data, and Humans

Technology selection is only half the battle. Often, a more pressing challenge is integration: ensuring new tools work seamlessly with existing systems and workflows.

Consider the challenge of pooling data from multiple sources. A trial might need to pull lab results from hospital systems, patient-reported outcomes from a mobile app, and imaging data from radiology platforms. Without thoughtful integration planning, teams may be left with data silos, manual transfer work, and increased error risk.

To increase your odds of success with incorporating new technology:

• Start with standards. Using established data standards and formats from the outset makes avoiding siloes easier. Consider not only basic data collection, but how to manage things like training records and regulatory documents.
• Plan for interoperability. Map out which systems will need to communicate to successfully run the trial. Build with APIs and data bridges in mind from day one to centralize knowledge and streamline operations.
• Maintain the human element. Even sophisticated automated systems need human oversight. Validation checkpoints ensure technology augments human judgment rather than replacing it entirely.

As Mould explains, “Having these human element double checks are imperative [in] that seamless integration of the tech”. For example, one might leverage technology for hemorrhage detection but also provide visual thumbnails for human review to quality check the automation.

Measuring What Matters

To ensure that technology is actually improving a trial, it is critical to monitor key metrics tie to specific operational goals.

Are you trying to accelerate enrollment? Track time from first contact to randomization. Looking to improve data quality? Monitor query rates and protocol deviations. Want to reduce site burden? Measure time spent on administrative tasks.

The key is establishing baseline metrics before implementation, then tracking changes over time. Without this discipline, it can be easy to confuse activity with progress and to stay busy implementing technology without seeing meaningful operational improvements.

Looking Forward

As the clinical trial landscape continues to evolve and new technology continues to emerge, the temptation to chase every innovation will only grow stronger.

But the most successful trial teams will be those who maintain strategic discipline by resisting the siren call of shiny new tools and instead focusing relentlessly on solving real problems, integrating thoughtfully, and tracking their success with concrete metrics.

Technology should make clinical trials more efficient, more participant-friendly, and more likely to generate reliable data. When it does that, everyone benefits: sponsors get better insights, sites save time, and most importantly, participants have better experiences contributing to medical progress.

Successful clinical research does not hinge on adopting every new innovation or technology. Instead, it relies on having the right technology to solve specific problems, implemented well, in service of clearly defined goals.

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Interested in learning more about strategic technology implementation in clinical trials? Check out the full webinar for more tips and specific examples from the Johns Hopkins BIOS team.