Real-world data may help in seeking US rare disease drug approvals

FDA seen as reacting favorably in reviews of treatment applications: Paper

Marisa Wexler, MS avatar

by Marisa Wexler, MS |

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The U.S. Food and Drug Administration (FDA) has responded favorably, in recent years, to the use of real-world data in applications that seek approval of new treatments for rare diseases — especially when the therapy has a dramatic and clear effect — a team of researchers concluded in a new review study.

“The FDA generally accepted [real-world data] studies demonstrating a large effect size despite [any] noted concerns and criticisms,” the researchers wrote.

“However,” the team noted, “the agency expressed concerns about overall quality and comparability of [real-world data] with trial data for some applications.”

Some red flags were noted, specifically regarding differences in patients’ clinical characteristics at a study’s start, as well as “missing information, and potential bias and measurement errors.”

Titled “A systematic review of real-world evidence (RWE) supportive of new drug and biologic license application approvals in rare diseases,” their work was published in the Orphanet Journal of Rare Diseases. The review was funded by Moderna, a Massachusetts-based biotech company.

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Typical trial paradigms often don’t work for rare diseases

When testing a new treatment, a clinical trial is the gold standard for telling if the therapy works in a given population. Traditionally, such trials will enroll a large number of patients matching specific criteria, with some participants given the experimental therapy while others are given an inactive placebo or standard of care treatment.

But when it comes to extremely rare disorders like AADC deficiency — estimated to affect about 1 to 3 per 100,000 live newborns in the U.S. — this paradigm is often impractical or impossible. There typically aren’t enough patients to enroll in a large, statistically robust clinical trial.

One potential alternative to the classical clinical trial design is to use real-world data to contextualize the effect of a treatment in development. For example, researchers may compare outcomes from patients who received an experimental therapy in a trial with outcomes from earlier natural history studies that tracked the progression of the same disease without treatment.

Now, a team of scientists looked at what impact real-world data had on the regulatory process in the U.S.

The scientists reviewed 20 applications for rare disease treatments that were submitted to the FDA between January 2017 and October 2022. All of them included real-world data.

Overall, the FDA responded favorably to real-world evidence in nine applications, but expressed concerns in the other 11.

To learn more, the team delved into the FDA’s praises and critiques, with the aim of providing guidance for researchers working to get U.S. approval for future rare disease therapies.

“Our review provided a detailed analysis of the applications employing [real-world evidence], the key aspects of [real-world data] submitted, as well as the impact on FDA decision-making and inclusion as part of the approval,” the researchers wrote.

The hope is that this paper “helps researchers and developers in enhancing their understanding of the science and the specific elements that the FDA is willing to accept or reject within [real-world data] studies for [rare diseases],” the team wrote.

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Real-world data comparisons can provide evidence for FDA applications

The scientists found that most applications generally took measures to ensure patients in real-world data were demographically and clinically similar to those in trials, so that comparisons could be drawn reliably.

“However, the FDA commented on differences in patient population and/or missing information on key elements,” which were not addressed in most applications, the team wrote.

[This finding] highlights potential benefits of appropriately conducted [real-world evidence] studies in [rare diseases], which can strengthen the clinical evidence for efficacy comparison and contextualization to support product approval efforts, particularly when a large magnitude of effect is observed for the new intervention.

Thus, when the regulatory agency responded favorably to real-world data, it was often in the context of therapies with fairly large effect sizes. In other words, these were medications that radically altered the course of the disease, so there was a dramatic difference between treated patients and untreated real-world data that was unlikely to be explained by bias or measurement errors.

This finding “highlights potential benefits of appropriately conducted [real-world evidence] studies in [rare diseases], which can strengthen the clinical evidence for efficacy comparison and contextualization to support product approval efforts, particularly when a large magnitude of effect is observed for the new intervention,” the researchers said.

When the FDA raised concerns about the inclusion of real-world information, a common sticking point was that patients in the real-world data had different demographic or clinical characteristics than those in trials — which makes it hard to draw reliable comparisons. Real-world evidence also tends to be messier, and sometimes measurements aren’t available, which were noted as concerns in some applications.

This result “highlights key areas for improving the [real-world data] to appropriately contextualize and compare it with clinical trial populations,” the researchers wrote, concluding that these findings can help researchers who are working on future applications for rare disease therapies.