Longitudinal studies that track patients’ experiences can inform and accelerate the drug approval process for rare diseases.
Pictured: Row of black computer servers with small lights / Adobe Stock, Gorodenkoff
Developing treatments for rare diseases, which in the U.S. are defined as affecting fewer than 200,000 people, often means working in the absence of clear data about a disease’s progression, symptoms or standard of care.
To address these challenges and accelerate drug approvals, researchers are increasingly leveraging natural history datasets—longitudinal studies that track patients, sometimes over decades.
Two recent announcements—the world’s first treatment for Friedreich’s ataxia (FA), whose approval was based in part on a natural history database, and a new data-sharing agreement between industry and nonprofit partners to investigate myopathy—underpin just how helpful these studies can be in establishing new collaborations to tackle rare diseases.
“The natural history studies are really contributing a lot toward these approvals for rare disease treatments,” J. Warren Huff, CEO of Reata Pharmaceuticals—the Texas-based biotech that developed the recently approved FA drug—told BioSpace. “Especially for diseases that progress very slowly . . . there often isn’t another way to move forward.”
Insights from the Past
The FDA typically requires at least two clinical trials to approve a drug candidate, but it can be difficult to amass enough patients with a rare disease to complete two trials, or it may be unethical to withhold treatment when randomizing patients into a placebo group.
In 2019, the FDA released industry guidance describing how natural history studies can be leveraged alongside a single trial to meet the requirements for approval under its orphan drug designation. In 2022, more than half of all novel drugs were approved along this pathway as treatments for rare diseases.
This coupling of natural history studies and orphan drug designations has since produced new therapies for previously untreatable diseases. In 2017, for example, the FDA approved BioMarin’s Brineura to treat late infantile neuronal ceroid lipofuscinosis type 2 (CLN2), and two years later, Novartis’s Zolgensma received contentious approval as a treatment for spinal muscular atrophy (SMA).
Last year, the FDA approved the first new drug in five years for ALS based on one clinical trial and an additional analysis of trial participants who continued the treatment and lived longer than expected.
Reata’s recent drug approval for FA—an inherited, degenerative disease that leads to impaired motion and a shortened life expectancy—is based on a collaboration with a patient advocacy group called the Friedreich’s Ataxia Research Alliance (FARA), which has collected data on more than 1,300 FA patients since 1999.
This information informed the development of Reata’s Phase II clinical trial, including how the team determined their primary and secondary outcomes and what constituted a reasonable endpoint.
The researchers were also able to draw on participants from the natural history study to show that disease progression slowed by 55% in trial participants who took the drug for three years compared to those who did not.
When the drug received FDA approval in February 2023, it was “the achievement of a lifetime,” Huff said, noting that it likely wouldn’t have been possible without Reata’s partnership with FARA.
Open Science Comes to Industry
With so little known about many rare diseases, drug treatments are often only possible when academia, industry, and advocacy groups come together. Ultragenyx, a California-based biotech company focused on rare and ultra-rare diseases, recently announced a data-sharing agreement with the Critical Path Institute (C-PATH), an FDA-affiliated nonprofit that maintains a platform for aggregating rare disease research.
Specifically, Ultragenyx will be sharing data from its former monitoring program of more than 300 patients with Hereditary Inclusion Body Myopathy (HIBM), a rare genetic disorder that causes progressive skeletal muscle atrophy. Only 2000 patients have been diagnosed worldwide. The company’s data will become one of two studies in the C-PATH platform related to HIBM, and together, the research provides baseline information for a large chunk of patients.
“Natural history is really important, really near and dear to my heart,” P.K. Tandon, senior vice president of data sciences and department of strategy at Ultragenyx, told BioSpace. He added that open data sharing is “the responsible approach to drug development.”
Each time Ultragenyx considers a new disease, the company first checks to see whether natural history studies have been done, and if not, undertakes them itself, Tandon said.
“Good natural history is so critical, and those who are smart use natural history data very effectively in getting their product approved.”
Studies of the Future
Depending on the disease, not all natural history studies need to go on for decades, but they do need to be conducted intentionally if they are to be useful in advancing new treatments, said Emily Bratton, a category lead at the health information technology and clinical research consulting company IQVIA.
Bratton, who co-authored a 2019 white paper on natural history studies, told BioSpace that for these studies to be most effective, they should be designed and run like a clinical trial. This means setting explicit criteria for participants, developing prospective (and not retrospective) analyses, and establishing realistic endpoints.
“It’s a different mindset when collecting information to potentially inform an outcome or a primary endpoint of a trial,” she said.
Fortunately, Bratton added, rare disease patients are often some of the best experts on their conditions, and working with patient advocacy groups can not only put researchers in touch with more patients but also with trial sponsors or other academics studying a specific disease.
When so little is known about a condition, it helps to pool as much collective knowledge as possible, she said, and bringing patients into the scientific process helps to build rapport. In the past, for example, patients have been able to share details that in turn informed protocols, she noted.
“Even something as simple as just understanding their day in the clinic can ease the burden of data collection.”
Amanda Heidt is a freelance science writer and editor based in Moab, Utah. To learn more, follow her on Twitter (@Scatter_Cushion) or visit www.amandaheidt.com.
