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The Challenges of Advancing Rare Disease Trials

Feb 28, 2020 - 4 min read
The Challenges of Advancing Rare Disease Trials

There are about 7,000 rare diseases affecting over 400 million people worldwide with more discovered every year.

Yet, only 500 therapies have been approved.1

Since the 1993 Orphan Drug Act, the number of rare disease designations has skyrocketed. With global sales forecasted to reach $262 billion by 20242, the orphan drug market is growing at a rate (11.3%) twice as fast as overall pharmaceuticals. In 2019 alone, 21 of 48 novel drug approvals (44%) were to treat rare diseases.3 By 2024, orphan drugs will account for a third of the R&D pipeline and 20% of all prescription dollars worldwide.

Despite a strong market context and financial and regulatory incentives, rare disease trials still face numerous challenges.

Major obstacles include the diversity and limited understanding of each disease, as well as difficulties identifying and treating small populations. These are further compounded by geographic dispersion of patients, clinicians and investigators, a multitude of regulatory uncertainties, and the challenges in designing studies for effective execution.

The first step to successfully initiate, design, expedite, and execute orphan drug development is to understand the complexities of rare diseases.


In the U.S., rare diseases are defined as disorders affecting fewer than 200,000 individuals. Collectively, there are nearly 30 million Americans4 battling a rare disease and about 50% of them are children. Of these, less than a third will live to see their fifth birthdays.5

Understanding the burden of rare diseases – the substantial physical, emotional, and financial tolls on patients and loved ones – and managing the patient and family experience within a study are critical to its success.

There are several key components to improving the efficacy of a study, including:

  • Proactively engaging all stakeholders to foster a collaborative approach that facilitates recruitment and retention
  • Removing constraints on patients to participate and complete a trial
  • Rapidly engaging sites, investigators, and patients to confirm acceptance of the study design
  • Ensuring access to experts and exceptional standards of care to positively influence the patient experience and enable trial success

As patients’ clinical signs and symptoms are often debilitating and/or life threatening, efficient and non-burdensome data collection is key. Limiting the frequency of site visits and invasive tests helps reduce patient burden and drive research participation. In-home clinical trial support is often necessary to encourage patients to remain engaged.

Geographic dispersion of small patient cohorts and scarcity of medical experts for any specific disease are common. Multiple sites and multinational collaboration are often required and must be managed across a divergent landscape of clinical regulations throughout the study. To help mitigate these challenges, collaboration of local experienced scientific and regulatory professionals is needed. This collaboration can also create opportunities for innovation in novel trial designs and rationale for the use of new biomarkers in early phase investigation.


Acquiring and managing data is highly complex. As patients and their caregivers know their condition most personally, they tend to be actively engaged with doctors, other patients, and advocacy groups. Their knowledge can be used to develop 'patient-centric' trials which leverage statistical techniques that maximize the value of the data derived from a small, heterogeneous group of subjects.

In turn, researchers and clinicians require technology to seamlessly capture and integrate data, including critical biomarker measurements not only from clinics and labs, but also data captured from sensors, apps, images, omics, EHR systems and real-world data sources. Complex data management workflows across randomization, drug supply, coding, and safety must be automated and available at all times.

Because rare diseases often result in a shortened lifespan,6 time from diagnosis to treatment must be expedited. Leveraging quality omic data and applying machine learning algorithms to help analyze the data faster, drives timely decisions, and can improve efficacy and safety while significantly speeding up the time to drug commercialization.


In order to adequately define clinical targets, input from Key Opinion Leaders (KOLs) on diagnostics, outcome measures, and processes is critical to help inform trial design and study metrics from the start.

One of the main challenges is to navigate and manage unclear diagnostic criteria and testing strategies. Another is the lack of validated surveys for Patient Outcomes Assessments, which may slow accurate patient identification. Finally, biomarker identification is complex, making it difficult to differentiate patients.

Early access to relevant biomarker identification will help accelerate diagnosis, identify which patients will respond to studied therapy, and understand etiology of the disease to identify next-generation therapies.

Additionally, quality omic data combined with clinical electronic data capture (EDC) and application of machine learning algorithms can accelerate timely decisions on efficacy and safety during the conduct of a trial. Technology must help drive insights across one or multiple trials, streamlining the integration and analysis of omic data to accelerate the discovery of novel biomarkers.

Trial historical data also helps compare actual patient-level data of identified former trial patients with current patients in treatment. Synthetic Control Arm™ and Synthetic Control Database solutions help explore data-driven insights and analyses to fuel decision-making while protecting patient experience and privacy.


Identifying key opinion leaders, reference centers and patient associations around the world is crucial in engaging and retaining qualified investigators with studied disease expertise and adequate resources to conduct a trial.

Investigators will influence success by selecting countries with a sufficient number of suitable study participants, determining patients’ accessibility, and identifying centers of excellence with therapeutic and operational capabilities to execute the trial.

As many rare diseases are progressive, severely debilitating and/or fatal, progressing trials even from Phase I to II can be challenging. Children who survive to adulthood face difficulties transitioning from pediatric to adolescent to adult care. Frequently, symptoms of the studied disease will evolve.

Over time, treatments also require multiple specialties because comorbidities are common. Care coordination in the context of an interventional study becomes important, and non-site data collection necessary. For example, treatment may involve multiple specialties such as neurology, psychiatry, endocrinology, cardiology, and physical therapy. Assuring care and data coordination in the context of an interventional study is critical.


Conducting rare disease clinical trials is complex. “Getting it right” from the beginning is critical for all stakeholders, in particular for patients and their caretakers.

Technology specifically designed to address rare disease challenges – improving patient enrollment and retention, discovering, capturing and managing data, identifying clinical targets, capturing omic data, identifying biomarkers and expediting trial execution – is crucial. Medidata designs and delivers the technology that every day will advance rare disease clinical trials.


  1. or Global Genes. ‘RARE Diseases: facts and Statistics’.
  4. Congress US. Public Law 97-414. Orphan Drug Act. 1983
  6. The needs of the few. Nature. 2010:466–160.
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