Bridging the data-to-study gap to solve Rare Disease research challenges

The IBM and Graticule partnership for rare disease

By | 4 minute read | May 24, 2021

Pediatrician with face mask and toddler in medical practice

A rare disease is defined as a condition that affects fewer than 200,000 people in the U.S. There may be as many as 7,000 rare diseases, and according to the National Institutes of Health, the total number of Americans living with a rare disease is estimated to be 25-30 million. Researchers have made progress in learning how to diagnose, treat, and even prevent a variety of rare diseases. However, there’s still much to do since most rare diseases have no effective treatments.

The main reason there are few treatment options is there’s not as much opportunity for pharmaceutical companies, or other life science organizations involved in healthcare research, to recoup the costs of developing new treatments for small patient populations. Due to work of patient advocacy groups like the National Organization for Rare Disorders, the United States Congress passed the Orphan Drug Act in 1983 to encourage drug development and other treatments for rare diseases. Despite the incentives and advantages the act provided, such as a specialized regulatory process from the Food and Drug Administration, clinical trials that focus on rare diseases still face many challenges today.

There’s a “data-to-study” gap that is contributing to the many rare disease research challenges, including patient identification and demonstrating the value of a treatment. To help solve for these problems IBM Watson Health is partnering with Graticule to close the gap by combining diverse real-world data from the IBM MarketScan® Research Databases and the IBM Explorys® Therapeutic Datasets with Graticule’s rare disease and analytical expertise to help accelerate research for rare diseases.

Rare disease patients are rare

One of the biggest obstacles facing the clinicians and industry leaders who conduct rare disease research is patient identification. The patient communities who are eligible to participate in these clinical trials are very small, which limits the study designs these trials can use. Also, the small patient numbers make it very hard for a trial to recruit enough people to meet their data collection goals and obtain usable results.

For drugs or treatments in the clinical development stage, an accurate patient identification model can be built to identify rare disease and high-risk patients in real-world datasets.  Yet organizations often don’t have access to the volume or quality of data they need to help them recruit patients. Even if they do have access to suitable data, there’s often a gap in the expertise needed to analyze real-world data and to get the most value from that data.

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Uncovering real-world costs and benefits

Another major challenge life science organizations often face is demonstrating the value of a rare disease therapy to regulators and other stakeholders. The small number of patients for rare diseases often means that many therapies have high costs per patient. Yet there are many things beyond pricing and costs that need to be considered when determining how valuable a therapy is, such as improvements in quality of life, reductions in the need for caregivers, and effects on disease progression.

There are real-world data methods that can help demonstrate these harder-to-measure benefits and help life sciences organizations provide additional evidence to show their treatment has a meaningful impact, even if the prevalence of the disease being treated is small. Yet many organizations don’t have experience working with real-world data models.

Teaming up to close the gap 

One way researchers are solving this “data-to-study” gap is by forming collaborations with organizations that have rich collections of patient data, such as diverse claims and EHR data, and experts who have a deep understanding of real-world data.

By combining strengths, IBM Watson Health and Graticule will offer real-world evidence solutions that help life science organizations solve challenges in rare disease research, such as clinical trial recruitment, creating external control arms and treatment reimbursement.

“Our partnership allows for complex solutions beyond data licensing or basic data linking for rare disease clients,” says Julie Krommenhoek, Vice President and Global Sales Leader, IBM Watson Health Life Sciences. “It really focuses on working backwards from what the client needs for their decision making. With this collaboration between Watson Health and Graticule, we’re going to begin bridging the data gap that we see clients facing when trying to conduct clinical studies and bring new treatments to market.”

Some of the research objectives IBM and Graticule hope to achieve include:

  • Understanding disease progression better by examining the natural history of rare disease patients
  • Comparing the effectiveness and safety of medical devices in real-world settings
  • Determining treatment patterns and examining the adoption of new drugs in market
  • Learning insights about new drugs that are not approved yet for reimbursement

“Patients and physicians often fail to obtain an accurate diagnosis for rare diseases or effectively document subtypes, and many are not aware of new medicines,” says Dan Housman, Graticule co-founder and chief technical officer. “By partnering with IBM, we’re offering creative options to solve the patient identification problem, including enrichment and analysis of IBM’s large-scale aggregate datasets to build models that predict or stratify patient risk.”

By working side by side, Graticule and Watson Health will promote collaboration with clients to pursue new opportunities and identify unmet needs in rare disease research. This collaboration will support rapid innovation to test new concepts and offer creative solutions. These solutions may be offered by working directly with rare disease organizations or extending the capabilities of the rare diseases clinical research network of CROs, consulting firms, health systems and technology companies.

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