Site Intelligence is the Key to Overcoming Long Standing Clinical Trials Challenges

By Chas Kielt, Program Director, Industry Solutions Marketing, Reltio

The path to commercialization for every FDA approved drug and cleared medical device in the United States began with a clinical trial. Recruitment of study sites and principal investigators (PI) are fundamental first steps in starting a clinical trial. However, identifying the right healthcare providers (HCP) and healthcare organizations (HCO) often presents vexing challenges. Without a clinical trials network in place, patient recruitment cannot start.

The science should be the hard part. But the first hurdle to a successful trial of a new drug or device is the testing itself.

Research published in Contemporary Clinical Trials (2018) reports that 86 percent of clinical trials do not reach recruitment targets within specified time periods. Another 19 percent of registered trials were closed or terminated early because they could not accrue enough participants. The authors note that, “Failures in meeting recruitment goals have important scientific, financial, ethical, and policy implications.”

More recently, Jessica Langbaum, Ph.D., director, Alzheimer’s Prevention Registry, wrote in Clinical Leader that, “The current approach to clinical trial recruitment is prolonged, costly, and inefficient and often causes major delays and challenges for research across multiple disease states. The vast majority (85 to 90 percent) of studies in the U.S. experience significant delays in recruitment and enrollment.1 Nearly one-third of trials under-enroll, and only 7 percent meet their target enrollment number on deadline.2

Now stop to consider that these preceding statistics were pre-COVID. Access, decentralization, and trial modalities became issues as COVID-19 took study sites and PIs off-line, and study subjects - patients - quarantined. Clinical trials moved online, in step with many other aspects of our business and personal lives, enabled by wearable technology and remote monitoring. Looking beyond the usual geographic areas and including under-served populations became critical factors that determined whether a study launched, was put on hold, or was canceled.

Michael Lauer, deputy director for extramural research at the US National Institutes of Health, told The Lancet in August 2020 that the effect of COVID-19 has been enormous. Thousands of trials -- around 80% of non-COVID-19 trials -- were stopped or interrupted.

The human cost of delayed innovation and commercialization of therapies for other disease states remains to be quantified. But there is an opportunity to make up lost ground, and perhaps even accelerate clinical trials, by using data in new ways and capitalizing on AI and machine learning to more quickly and efficiently enroll clinical trials.

Data-Driven Insights for Precise Recruitment and High-Quality Research Studies

Reltio launched a new cloud service in March 2021 that enables Pharmaceutical Research & Development Teams and Contract Research Organizations (CRO) to centralize detailed data about study sites and principal investigators.

Reltio Enterprise 360 Site Intelligence is a cloud-native SaaS platform that helps mitigate the challenges and barriers of finding the right scientists, medical professionals, and clinical settings to participate in clinical trials by providing unified, reliable, and real-time data for:

  • Third-Party Industry and Reference Data
  • Operational and Analytical Data
  • Healthcare Organization (HCO) Data
  • Healthcare Provider (HCP) Data
  • Actionable insights powered by AI and machine learning
  • Identifying relationships with proprietary graph technology

Connected Graph technology is unique to Reltio Enterprise 360 Site Intelligence. HCOs, HCPs, PIs, and study sites are often connected in many-to-many relationships. Reltio Connected Graph can quickly identify content preferences, influence in a disease area, prescribed products, and clinical trial participation that traditional databases cannot. The graph models interrelationships and dynamic hierarchical information for an at-a-glance view. These insights are valuable.

AI provides insight into key considerations for clinical trials. These include study site and PI performance on past studies, relationships with competitors, areas of expertise, site logistics, and other important data.

In sum, rich HCO and HCP profiles provide information to confidently select the optimal study sites and researchers with the highest potential to contribute to a successful clinical trial. And in the dynamic life sciences industry, Reltio’s “progressive stitching” enables in-house clinical trials teams and CROs to augment or change attributes associated with a Master HCO or HCP profile. This insight increases efficiency and speed, as well as potentially providing a competitive advantage.  

While Reltio Enterprise 360 Site Intelligence is new, the company’s first customers were life sciences and pharmaceutical companies. In fact, 9 of the Top 10 pharmaceutical companies use Reltio Connected Data Platform for drug Research & Development, commercialization, direct-to-consumer marketing, and distribution management (sales & marketing). Multiple CROs, including Bioclinica, IQVIA, and Syneos Health use Reltio for master data management. We understand what data you need to be successful. And we have been delivering it to our customers in real-time on a secure, cloud-native, multi-domain MDM software as a service (SaaS) platform for nearly 10 years.

Learn more about Reltio Enterprise 360 Site Intelligence and the company’s extensive life sciences experience here


  1. Dowling NM, Olson N, Mish T, Kaprakattu P, Gleason C. A model for the design and implementation of a participant recruitment registry for clinical studies of older adults. Clin.Trials 2012 Apr;9(2):204-14. PMCID:PMC3325341
  2. Strasser JE, Cola PA, Rosenblum D. Evaluating various areas of process improvement in an effort to improve clinical research: discussions from the 2012 Clinical Translational Science Award (CTSA) Clinical Research Management workshop. Clin.Transl.Sci. 2013 Aug;6(4):317-20. PMCID:PMC3740438
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