How Sponsors Can Support Sites with Data Analytics to Meet New Trial Diversity Regulations

Clinical Researcher—June 2023 (Volume 37, Issue 3)


Rohit Nambisan, MS, MA


Clinical trial participation amongst minority groups in the U.S. is woefully inadequate—a challenge that has plagued this industry for years. In December 2022, substantive diversity, equity, and inclusion (DEI) legislation was signed into U.S. law and went into effect in February 2023 to help correct the significant disparity and hold sponsors responsible for ensuring that their trials represent diverse patient participant populations.

No one doubts the inherent value of broader representation in clinical trials; however, sites are burdened with delivering DEI enrollment requirements. Without an effective strategy, such regulation might impact the ability to carry out any research at all, according to conversations with industry research professionals.

“Everyone realizes the benefits of representative populations as participants in clinical trials,” said a clinical operations executive at a multinational pharmaceutical company in an April 2023 interview. “Now the issue has more to do with how granular regulations might get, how it fits into overall drug development strategies, and whether it might ultimately hinder our ability to address the requirements across all regions of development while controlling for costs and ensuring scientific rigor.”

While sites are responsible for participant enrollment, now sponsors must actively provide diversity guidance and support during protocol design and study start-up. Sponsors will need a reliable mechanism to ensure a diverse representation of participants in their trials or risk derailment.

Supporting Sites with Data Analytics

One way to mitigate potential impacts is for sponsors to enable their site partners with systematic data analytics. Sponsors and contract research organizations (CROs) need to manage ever-growing volumes of data in real time to ensure that trials meet planned timelines while addressing the diversity plans they have submitted to the U.S. Food and Drug Administration (FDA). Yet managing such data is difficult across all stakeholders, particularly given the rapidly expanding and disparate array of trial data sources out there.

According to a 2021 study by Tufts University, Phase III clinical trials generated an average of 3.6 million datapoints, or three times the amount of data collected by late-stage trials in 2011. Lokavant’s internal analysis suggests that by 2030 these clinical trial datasets will skyrocket to seven times that of 2011.

Today’s avalanche of data is both a blessing and a curse. Data are only useful if they can be analyzed effectively across all teams, which grows more challenging due to novel data types and increasing data volume. With the new DEI requirements, data analysis and open communication will become even more important—and more onerous. For small to mid-size biopharma companies, this could be devastating.

Fortunately, advanced data analytics can shift the paradigm in clinical trial operations. Technology that centralizes data sources drives machine learning models that anticipate clinical trial events (and their impact on trial execution) and empowers sponsors to notify sites when they see a risk signal, mitigating challenges before it is too late. Such technology reduces friction with outsourced vendors, improves data transparency, and unifies complex interactions across stakeholders participating in the trial to ensure that each has the right information at the right time, optimizing trial conduct.

When sponsors, CROs, and sites are reviewing the same data, they can make important real-time decisions for the success of their trials, including those involving recruitment to meet enrollment numbers. Toward this end, artificial intelligence (AI)-based platforms are already proving their value. In one case, results revealed a 70x improvement in enrollment forecast accuracy, more than $1 million in savings from participant retention, and six months’ time savings from detecting site noncompliance issues.

“Smart companies are starting to leverage advanced technology and data analytics to better predict the progress of trials,” added the same clinical research professional quoted earlier. “There’s a huge advantage in being able to leverage robust statistical monitoring to see trends in data and be able to identify trials that might be going off track before it is too late. Ultimately, that will save sponsors a lot of time and money and help align with sites—particularly with DEI initiatives.”

Preparing for the Next Frontier

Diversity challenges are the next frontier for advanced analytics in clinical trials. Data-driven technology gives sponsors and vendors complete, continuous visibility into the progress of planned DEI initiatives. Data-agnostic predictive platforms can generate important insights into, just for example, which sites offer access to diverse and indication-specific participant populations—across a wider set of data sources than have been utilized traditionally.

Where sponsors have historically contracted with the same, familiar sites so the pool of participant data is, likewise, homogenous, they can instead use these new data-driven insights to engage with a broader range of sites. A system that leverages multiple data sources provides insights that maximize diverse recruitment and minimize bias at the outset of a clinical trial.

In addition, real-time analytics can provide rapid feedback to sites on the diversity of their randomized participants. This empowers sites, which have typically been disenfranchised from study conduct analytics, to make timely adjustments in terms of optimizing recruitment plans in-line with diversity requirements.

A Call to Action for Sponsors to Share Data Analytic Insights with Sites

Now that the FDA is requiring adherence to diversity plans, it’s crucial that sites and sponsors align on and collaborate with trusted analytics. Clinical trial sponsors and CROs have even more to manage, more data to assess, and more risk. Sites have the task of recruiting a representative population for the trial and ensuring its success through the collection of high-quality data. Diligence from stakeholders in all of these roles is critical for expediting novel therapies to patients.

Anticipating when a trial is veering off the established plan for diversity and population representation is critical, and doing so before the end of the trial or enrollment period is paramount. If a sponsor can act quickly and notify the site, site managers can pivot and ensure that the trial stays on track to hit all its milestones.

The new DEI requirements in the U.S. represent an important formal step in ensuring that clinical trials reduce outcome bias while producing the information that researchers need to prove that novel therapies are truly safe and efficacious. Now it is up to sponsors to do their part to address disparities that have plagued healthcare, and to empower and collaborate with sites on execution.

Rohit Nambisan, MS, MA, ( is CEO and Co-founder of Lokavant. Trained as a neuroscientist, he is an experienced product development leader for organizations in the realms of pharmaceuticals, medical devices, personalized medicine, health information technology, healthcare data and analytics, and AI. Prior to his work with Lokavant, he was most recently the Head of Digital Product at Roivant Sciences and the Head of Product at Prognos Health.