Moving Mountains with Shared Data

Starting in the 1950s, a group of researchers, including the legendary Sidney Farber, were working on different pediatric cancers when they realized no one of them would have enough patients to understand the biology of these individual conditions or whether or not a treatment worked.

They understood they needed to work together if they were going to make a difference for patients and shared a vision for cooperative research that effectively secure and sustain research funding over time.  

Katie Donohue, acting director of the Division of Rare Diseases and Medical Genetics at the U.S. Food and Drug Administration, said that in the 1950s and 1960s, the dramatic effect of their work could be seen in the growing survival rates of pediatric cancers. Within 50 years, the survival rates for some of these cancers have reached 90 percent from an average of about 10 percent.

“A lot of that benefit came from the early years of collaboration. I want that for every patient with a rare disease. I want all of them to be able to see in our lifetimes and their lifetimes, the survival rates in their communities shoot up like that,” said Donohue. “This cooperative research model is the only thing I’ve seen that has accomplished that. We’re coming up hard on the limits of what one investigator can do by themselves. The children’s oncology group has given us an example of how we can work together in order to do this better.”

Donohue’s comments came during the opening session of a two-day conference on data sharing and its potential to accelerate therapeutic development for rare diseases. The event, held by the Duke-Margolis Center for Health Policy and the U.S. Food and Drug Administration, ran August 18 and 19. A replay of the panels is available online

Donohue focused on the benefits of data sharing and argued that people should keep the end in mind, which impacts patients with rare diseases.

She noted that data sharing could be scary. Academics are concerned about their ability to publish and don’t want to be scooped. Patient organizations are worried about data security and protecting the privacy of patients. And drug companies are concerned about protecting their commercial interests.

Donohue acknowledges they all have legitimate concerns, but we’ve already seen that there are effective models for accomplishing data sharing without compromising these things and pointed to the pediatric oncology network’s success for the benefits of this type of collaboration.

As an example of the various ways data sharing can pay off, she pointed to a clinical trials simulator for Alzheimer’s disease that the Critical Path Institute created. The simulator allows a user to adjust critical parameters such as frequency of study visits, sex, genetic factors, and endpoint measures to improve clinical trials’ design. 

No such tool exists today for rare disease clinical trials but creating one would provide a much more exact roadmap of what a trial sponsor would need to demonstrate that a therapy is helping patients. 

“We don’t want to have the first-generation trial fail to detect a treatment that’s actually helping patients. We don’t want to make that kind of mistake, but most of our chance for avoiding that is right here—it’s in having the answers to some of those questions as we’re planning the trial. If we don’t have a tool like this, it’s like flying blind,” Donohue said. “The point of the data sharing is really to support these kinds of simulators so that we can make sure that we’re designing the best possible trial for a treatment, a trial that has the best chance of success.”

Tiina Urv, program director with the Office of Rare Diseases at the National Center for Translational Science at the National Institutes of Health, opened the session by discussing the challenges of rare disease drug development, including the high cost, long time frames, and small patient populations. 

“We need to work faster. We need to work cheaper. We need to work with higher quality studies and data. And that is the only way we’re going to become sustainable,” said Urv. “What we need to do is develop some new strategies.”

She stressed the importance of collecting high-quality data and following fair principles and good data practices from day one. “When you first start collecting any type of information you’re collecting, you want to impose quality onto it,” she said. “The research that you’re doing needs scientific rigor. Science needs to be reproducible, and you need to be transparent in your actions so people can learn from not only when you do well, but when you fail.”

She talked about the need for researchers and patient organizations to look beyond their own silos and consider the big picture and not just what they need to do next, but what they need to deliver a therapy to someone with a rare disease. 

Urv talked about the importance of collaboration as a way to address common challenges. That can be in the form of clinical trial networks and using innovative models, such as basket trials or umbrella trials to allow drug developers to move faster and do more with less. But she also talked about the importance of advocacy groups to establish natural history studies, develop tools, outcome measures, biomarkers, and common data elements to enable clinical trials. 

“Alone, rare diseases are like snowflakes,” she said. “They’re very fragile, but if you work together, they can form things like glaciers that can actually move mountains.”

RARE-X shares that vision. It believes it can help remove barriers to collaboration through its federated data platform and help patient organizations build the types of rigorous and high-quality data sets required. Together, we will move mountains.

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