As a leading biotech company, our client’s global clinical trials are critical to the development of life-saving treatments and therapies. However, the site selection processes depended on disparate, subjective inputs from clinical operation leads across different regions and therapeutic business units. Additionally, new FDA regulations requiring proportional inclusion of underrepresented groups underscored the need to address diversity gaps in their patient recruitment strategies and to support registration. Recognizing the recent urgency of these challenges, the organization looked to Point B to provide expertise at the intersection of people, process, data, and technology, within clinical trial management.
The Challenge
The biotech’s leaders recognized their need for a solution that would overhaul their fragmented manual clinical trial site selection process. The existing manual system relied heavily on the subjective expertise of country-specific clinical operations leads within different therapeutic areas, resulting in inefficiencies and missed opportunities to identify optimal trial sites for patient recruitment and retention.
Key challenges included:
- Siloed data insights: Site selection was based on individual internal trial team knowledge rather than comprehensive, centralized data approach, along with external incidence/prevalence data and other relevant sources.
- Manual processes: Sites were vetted through labor-intensive, non-standardized methods across multiple therapeutic business units, such as tracking site enrollment, screen failures, protocol deviations, and retention using non-centralized Excel spreadsheets or basic tools like Microsoft Paint causing significant delays.
- Slow time-to-enrollment: The lack of automated and accurate site prioritization or pre-filtering led to significant delays in clinical trial enrollment timelines, while increasing protocol deviations and retention issues increased costs.
The Opportunity
Point B identified an opportunity to empower our client by designing and implementing a solution that combined and automated internal site records, external vendors demographic datasets, prevalence and incidence data, and advanced geospatial analytics. This approach would allow the client to efficiently target optimal global trial locations and improve trial start-up timelines and enrollment needs.
By introducing machine learning and interactive visualization tools, the solution aimed to address the dual challenges of operational inefficiency and manual dependencies. To accomplish this, Point B fostered a cross-functional, collaborative workgroup to establish a scalable framework for expanding site selection, while monitoring enrollment/retention rates and disparities across therapeutic business units.
Our Approach
To solve our client's challenges, Point B deployed a comprehensive, data-centric approach tailored to the unique complexities of clinical trials.
Establishing a Project Management Framework
Our team first established a robust project management framework to guide every phase of the engagement. This framework ensured alignment with stakeholders across analytics, operations, medical, and IT functions. Regular status reports, periodic meetings, and timeline reviews kept the project on track while providing transparency and sharing best practices across business units.
Enabling Population Analytics
Point B partnered with our client’s Insights & Analytics team to develop a population analytics tool, which became the core of our solution. This tool integrated population demographics, clinical trial history, site performance, and patient-risk factors into a centralized interface.
This new capability enabled:
- Visualization Frameworks: Our client could now access intuitive map views to visualize site locations, automatically generated using latitude and longitude data. This replaced manual mapping efforts and provided an instant, geospatial understanding of site distribution.
- Scoring Algorithms: Machine learning algorithms scored sites based on enrollment and risk factors (e.g., screen failures, retention, protocol deviations), enabling better prioritization of trial locations.
Integrating External Data
We then worked to combine our client’s internal historical trial data with multiple external datasets, such as census information, epidemiological data, and additional site and claims data vendors. For regions lacking granular demographic data (e.g., France and Germany), alternative approaches, such as ancestry data, were used as a proxy.
Enhancing Reporting and Collaboration Tools
Point B supported our client in designing enhanced reporting capabilities to monitor trial enrollment, retention, and performance over time. By creating centralized data repositories and tools like data dictionaries, stakeholders were able to collaborate more effectively across departments and systematically share site metrics.
Scalability and Knowledge Transfer
To ensure long-term scalability, Point B worked closely with key functional teams to facilitate training and knowledge transfer. This ensured that internal stakeholders could independently manage and expand their population analytics capabilities following Point B’s involvement.
Point B remains a trusted partner, supporting ongoing enhancements and planning for future scalability.
Project Results
Our partnership resulted in significant advancements across our client’s clinical operations:
Improved Operational Efficiency
The new map interface automated the previously manual site-tracking methods, saving valuable time and improved site performance metrics for clinical operations teams. Site identification processes are now more comprehensive and objective, powered by real-time geospatial data.
Scalable Data Framework
The enabled population analytics capabilities provided an automated, repeatable, and data-driven framework that can be scaled to additional countries in the future. With foundational work from Point B in place, our client began collecting census and population data from regions that were previously excluded from their site selection scope.
Enhanced Collaboration and Confidence
Stakeholders reported higher confidence in their decision-making processes. Key team members transitioned from manual, subjective, decentralized methods to an automated, unified, and evidence-based approach. A clinical operations lead described the project outcome as a game-changer, noting that the automated map visualization had replaced hours of manual effort previously done using basic tools.
Looking Ahead
Point B is proud to have helped our client establish the foundation needed to drive clinical trial access while improving recruitment and retention rates. With newly automated processes enabled by advanced analytics and machine learning, our client is well-positioned to expand their data capabilities across new geographic regions, while further refining their performance scoring algorithms.
Point B remains a trusted partner, supporting ongoing enhancements and planning for future scalability. Together, we’ll unlock enhanced operational efficiency across multiple therapeutic areas, ensuring clinical trial access while reducing manual efforts, allowing our clients to keep their focus on the patient.
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