The challenge
Our client had ambitious recruitment targets for an active clinical trial but lacked the data to understand what was working and where opportunities lay. They needed help identifying failing sites, boosting performance, and improving the overall design to meet their goals within the planned timeframe
The analysis
We began with a comprehensive evaluation of both the clinical trial performance data and the broader therapy area. Our data science team built a complete dashboard showing live metrics on recruitment, site activation, and screening rates. Alongside this, our consultants conducted a landscape review that assessed available epidemiological data, site infrastructure, and the geographic spread of eligible patients.
We layered in data on existing site performance, looking at throughput, dropouts, and patient mix. From there, we developed a list of underperforming sites to cut and promising ones to activate
The solution
The client received a fully interactive trial intelligence board, allowing them to monitor performance and drill into site-level insights. We made clear, actionable recommendations on:
- Which sites to close and which to prioritise
- Where to find untapped patient pools based on epidemiology
- How to optimise diversity by changing screening criteria
- What actions would most improve timelines and outcomes
This was paired with a structured set of trial design enhancements to ensure learnings were embedded for future phases.
The value to the client
The combination of tailored software, expert consulting, and robust data helped the client rapidly course-correct their recruitment strategy. They not only hit their targets, but also gained a repeatable system for ongoing trial optimisation. Their clinical and operational teams now collaborate through the same platform to monitor, improve, and make decisions faster.
Ongoing support
The dashboard we built continues to evolve with their needs. We support weekly with updates, monitor external data sources for changes in the landscape, and are now integrating trial protocol suggestions based on real-time metrics to help refine future trial designs.
