If COVID-19 vaccines have taught us anything about clinical trials, it’s that hitting anticipated trial completion dates is critical to saving lives. Many clinical trials, in general, are designed without the end patients in mind, often conducted in centralized medical facilities instead of directly within communities. 

Decentralization is essential for enrolling and maintaining diverse populations within clinical trials and will be key for sponsors and operators to implement, especially as Congress encourages the Food and Drug Administration (FDA) to overhaul policy around clinical trial design. New technologies such as machine learning to optimize site selection and patient enrollment will also be crucial to hit trial timelines.

Congressional scrutiny around diverse enrollment heats up

In July, the House Appropriations Committee unveiled plans to beef up the FDA’s fiscal year 2022 budget to the tune of $300 million more ($6.17 billion overall, a 5% increase) to innovate clinical trials and make them more inclusive by improving outreach to underrepresented populations. The House committee also encouraged the FDA to increase women and minority recruitment in clinical trials, while fostering innovative trial designs that “complement and speed the FDA regulatory processes.”

This initiative launches as clinical trials for Biogen’s Alzheimer’s drug Aduhelm continue to spark criticism from patient advocacy organizations, such as UsAgainstAlzheimer’s, for recruiting primarily white patients. The group noted in a June statement that Black and Latino Americans were “woefully underrepresented” during these critical trials.

Studies for drugs like Aduhelm are complicated by certain underlying healthcare inequities and the need to access high-tech imaging (e.g., PET for amyloid confirmation, MRI for safety follow-up) and infusion centers throughout the course of the study. The need to take time off each month to reach these centers places a large burden on individuals from certain geographies and socioeconomic groups.

Sponsors should be aware of these regulatory changes and ensure their clinical trials are adaptively designed to reach and maintain diverse populations or face challenges with future FDA drug approvals. For example, the FDA has advocated for enhancing recruitment efforts mid-trial, which will increase the need for readily available information on new sites to onboard quickly during the trial. Machine learning-powered enrollment technology, such as Citeline Study Feasibility, can analyze this type of data to support site optimization for faster patient recruitment.

Biogen’s post-marketing study could face enrollment challenges

Biogen’s Aduhelm, after receiving accelerated FDA approval, must now complete a Phase IV confirmatory post-marketing study of its own drug within a nine-year window. These surveillance studies are often required, but part of the challenge for Biogen will be to maintain a randomized controlled trial, all while Aduhelm is already available on the market. It will be important to watch how Biogen conducts this study, including who it enrolls and where, and how feasible it will be to retain patients over an extended period.

On the flip side, several medical centers have stated they won’t administer the drug because of questions about safety and efficacy, which could impact enrollment efforts for the trial once it begins. Some patients will also not be eligible to receive Aduhelm until the reimbursement decision by Medicare in April (with a proposed decision expected in January). Furthermore, there may be plenty of volunteers for Biogen’s trial given the list price of $56,000 per year, while the Phase IV trial would provide the drug at no cost.

If recruitment in the U.S. still proves challenging, especially as Phase III trials continue for similar drugs, Biogen has the option to conduct the confirmatory trial overseas where the drug is not yet available. Enrollment tools that optimize country selection can help clinical trial sponsors like Biogen that are in competition to enroll patients state-side. Citeline Study Feasibility arms study sponsors with the predictive insights needed to optimize country and clinical trial site selection and enrollment duration, ultimately increasing overall probability of enrollment success.

Will COVID-19 vaccine boosters face an enrollment cliff?

Following a historically successful vaccine, Pfizer is already gearing up to file for Emergency Use Authorization (EUA) for its COVID-19 vaccine booster this fall, after kicking off trials for a customized vaccine targeted at the Delta variant later this month. The FDA has indicated it won’t rely just on applications for boosters, but will also consider lab data, clinical trial data, and real-world evidence when considering approval. But, with vaccine hesitancy barely budging, it’s clear any new clinical trials will face uphill enrollment battles.

Putting a greater emphasis on decentralizing clinical trials by taking them to where patients live, while also using available technologies to optimize the enrollment process, will be crucial as new COVID-19 vaccine clinical trials, like the ones Pfizer will be conducting, begin.

A recent study from Informa Pharma Intelligence measured patient attitudes on the clinical trial process following the start of the pandemic. The data revealed that 47% of respondents who had not participated in a clinical trial were not able to find a nearby trial location, while a sizable 67% said they would be more likely to participate in a relevant trial if it were in their community.

This data is not surprising as many COVID-19 therapeutics were primarily centered in medical facilities and contract research organization sites, creating issues with the diversity of patient pools. However, a few sponsors were forced to allow patients to participate in a remote capacity, effectively reaching them in their own communities and enabling sponsors to tap into a broader patient set.

As we continue tackling COVID-19 and move to address new diseases, the same lessons around adaptive clinical trial design must be implemented, especially as FDA policies lean more toward inclusion and innovation. Post-COVID clinical trials need to modernize by leveraging decentralization, diversity, and innovative technologies like machine learning to enhance enrollment efforts and, most importantly, save more lives.

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