The Role of Technology in Rare Disease

Imagine living with a condition so rare that even your doctor may have never seen it before. For millions around the world, this is a daily reality. But thanks to groundbreaking technological advancements, hope is rising for those affected by rare diseases—conditions that often go undiagnosed, untreated, or misunderstood for years.

In this blog, we explore how modern technologies like AI, genomic sequencing, telemedicine, and big data are revolutionizing the way rare diseases are identified, researched, and managed.

What is a Rare Disease?

In the United States, a rare disease is defined as one that affects fewer than 200,000 people. Globally, there are over 7,000 known rare diseases, affecting an estimated 300 million people (National Organization for Rare Disorders [NORD], 2023). Due to their rarity, many patients face delayed diagnosis—sometimes taking over five years to receive an accurate diagnosis (EURORDIS, 2020).

1. Genomic Sequencing: Unlocking the Blueprint of Disease

Genomic sequencing, particularly whole genome sequencing (WGS) and whole exome sequencing (WES), has emerged as one of the most powerful tools in rare disease diagnosis. These techniques analyze the patient’s DNA to detect mutations or genetic anomalies linked to rare disorders.

A 2021 study in The New England Journal of Medicine found that WGS increased diagnostic yield by 31% in previously undiagnosed pediatric rare disease cases (Stark et al., 2021).

Source:

Stark, Z., et al. (2021). Prospective comparison of genome sequencing with exome sequencing and microarrays for diagnosing conditions in infants: A multicenter cohort study. The New England Journal of Medicine, 385(22), 2046–2056. https://doi.org/10.1056/NEJMoa2109017

2. Artificial Intelligence (AI) for Faster and More Accurate Diagnosis

AI algorithms are now capable of scanning medical images, lab results, and genetic data to detect patterns associated with rare diseases. Tools like Face2Gene, for instance, analyze facial features to assist clinicians in identifying rare syndromes with genetic causes.

According to a study published in Nature Medicine, AI-driven tools improved diagnostic accuracy by 20–30% in clinical genetics (Gurovich et al., 2019).

Source:

Gurovich, Y., et al. (2019). Identifying facial phenotypes of genetic disorders using deep learning. Nature Medicine, 25, 60–64. https://doi.org/10.1038/s41591-018-0279-0

3. Telemedicine Expands Access to Rare Disease Specialists

For many rare disease patients, geographic distance from medical experts can delay care. Telehealth bridges this gap by allowing virtual consultations with specialists, reducing travel burdens and increasing access to expert care.

During the COVID-19 pandemic, telemedicine use surged, and a 2021 report from the National Institutes of Health (NIH) emphasized its ongoing benefits for rare disease care coordination, especially in rural or underserved areas (NIH, 2021).

Source:

National Institutes of Health. (2021). Telehealth in rare diseases: A promising path forward. https://www.nih.gov/news-events/news-releases

4. Big Data and Patient Registries Drive Research

Technology also plays a crucial role in aggregating data. Rare disease registries and databases—powered by cloud computing and AI—help researchers track patient outcomes, study disease progression, and even match patients to clinical trials.

Platforms like Global Rare Disease Registry (GRDR) and RD-Connect offer open access to anonymized patient data to accelerate global collaboration and discovery (National Center for Advancing Translational Sciences [NCATS], 2023).

Source:

NCATS. (2023). Rare diseases clinical research network. National Center for Advancing Translational Sciences. https://ncats.nih.gov/rdcrn

5. Wearable Technology for Monitoring

Smartwatches and medical wearables are increasingly used to monitor symptoms and collect real-time data, which is especially valuable for conditions with fluctuating or unpredictable symptoms. This data provides insight into daily quality of life and can inform treatment adjustments.

Challenges That Remain

Despite progress, technology isn’t a silver bullet. Challenges include:

Cost and accessibility of advanced genetic testing.

Data privacy concerns in genomic databases.

Healthcare provider training on using AI and tech tools effectively.

Yet, the promise far outweighs the hurdles—especially when we consider the lives that may be changed or saved.

Final Thoughts

The marriage of technology and medicine is opening new doors for people living with rare diseases—transforming despair into diagnosis, and uncertainty into understanding. As innovation continues, we believe that technology will not just help identify rare diseases but will one day help prevent and cure them.

References:

Gurovich, Y., et al. (2019). Identifying facial phenotypes of genetic disorders using deep learning. Nature Medicine, 25, 60–64. https://doi.org/10.1038/s41591-018-0279-0

National Institutes of Health. (2021). Telehealth in rare diseases: A promising path forward. https://www.nih.gov/news-events/news-releases

National Organization for Rare Disorders. (2023). Rare Disease Database. https://rarediseases.org/

NCATS. (2023). Rare diseases clinical research network. https://ncats.nih.gov/rdcrn

Stark, Z., et al. (2021). Genome sequencing versus exome sequencing and microarrays in infants. NEJM, 385(22), 2046–2056. https://doi.org/10.1056/NEJMoa2109017

EURORDIS. (2020). The Journey to Diagnosis for Rare Disease Patients in Europe. https://www.eurordis.org/