Machine learning’s role in advancing clinical trials diversity

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May 22, 2023, 11:43 AM EDT


The year 2020 was a watershed moment for many reasons, but notably, it cast a light on the pervasive health and social inequities that have long marred the U.S. The COVID-19 pandemic hit diverse populations disproportionately hard, as Deloitte and others have noted. Additionally, the tragic deaths of George Floyd, Breonna Taylor and others provoked an uproar over systemic racism that permeates society, including healthcare. This period of societal upheaval has also underscored the necessity of novel approaches involving techniques like the use of machine learning in clinical trials, to ensure that diverse populations are represented.

Such disparities in healthcare were further highlighted when Moderna, soon to become a critical player in the vaccine race, faced a glaring revelation in late 2020. Only 24% of participants in their phase 3 study were from communities of color, despite these communities bearing the brunt of the COVID-19 pandemic. In September of the same year, the company discovered that merely 7% of trial participants were African Americans, while they represent 13% of the total population.

“This discrepancy would not have been acceptable, not only from the perspective of representing the right populations in the study but also for future vaccine adoption and uptake,” said Rohit Nambisan, CEO and co-founder of Lokavant, a clinical trial intelligence platform. But Moderna, acknowledging the issue, took steps to ensure a more inclusive and representative study of its vaccine’s efficacy. By adjusting their participant demographics to mirror the population most affected by the pandemic, they succeeded in prioritizing clinical trial equity for their COVID-19 vaccine.

Policies and regulations promoting DEI in clinical trials

In the face of this challenge, FDA is gradually rolling out new policies promoting diversity, equity and inclusion (DEI) in clinical trials. Under section 3601 of Food and Drug Omnibus Reform Act (FDORA), for instance, drug and device clinical studies must include a diversity action plan when filing certain trial documents to FDA. In April 2022, the agency published draft guidance to help optimize diversity in clinical trials.

“We observe a lot of enthusiasm among sponsors today in developing their diversity plans and complying with these guidance documents and initiatives,” said Craig Lipset, founder of Clinical Innovation Partners and former head of trial innovation at Pfizer.  “But guidance is not a mandate.”

Diversity plans are fundamentally compilations of diverse strategies, which typically focus on three key areas: fostering trust, ensuring a representative patient pool and maintaining trial accessibility. “These tend to be the primary areas of investment. Then, sponsors do their best and wait for the outcomes,” said Lipset, who also serves as co-chair for the Decentralized Trials and Research Alliance.

One challenge is that FDA’s guidance document has a caveat “stipulating that if you fail to meet your plan, revert to us and we’ll assess if post-marketing surveillance is needed for specific populations,” Lipset said. “There’s almost an acknowledgment and expectation that implementing these plans is challenging, and accountability isn’t necessarily a given.”

“The vital part of our conversation here is how we can make these plans more feasible and intelligent using data,” Lipset emphasized. “We’re not just looking at dashboards to count the Caucasians we enrolled versus the others we didn’t.” Instead, the goal is to infuse intelligence, prediction and recommendations to the process. “In this way, we’re not merely throwing strategies at the problem and claiming we tried, but we are assessing which strategies make the most sense and are positioned to deliver,” he noted.

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