Rare diseases bring with them a multitude of challenges for those affected, their relatives and care providers. Modern technical solutions, based among other things on methods of medical informatics, offer great opportunities here.
Typically, the first major burden for those affected is getting the correct diagnosis. Unfortunately, this is often a lengthy and complex process accompanied by a range of corresponding challenges.
For example, in a survey conducted by EURORDIS of 12,000 patients with rare disease, over 40% of patients are initially misdiagnosed (fig 1). Moreover, results from the survey show that patients visit an average of 7.3 physicians before an accurate diagnosis is given, with an average time to diagnosis between 7.6 to 5.6 years in the US and UK, respectively.
Adapted from EURORDIS-Voice of 12,000 patients
A multitude of medical informatic solutions exist to help health care providers identify and confirm rare disease diagnoses, particularly for rare diseases arising on a genetic basis, which account for an estimated 80% of cases.
Freely available, searchable, comprehensive online databases of genetic disease phenotypes and human genes are available through resources, such as the Online Mendelian Inheritance in Man (OMIM) database, accessible through the NCBI database portal.
Together with newer AI-based searchable database applications, including FindZebra , Phenomizer, and image based genetic syndrome identification tools, such as Face2Gene,healthcare providers are bolstered in reducing diagnostic odysseys by an ever-increasing armamentarium of resources to construct a rare disease differential diagnosis.
Once a most likely diagnosis is identified, healthcare providers can utilise existing additional bioinformatic repositories to identify potential genetic testing laboratories, such as the Genetic Testing Registry (GTR). This a searchable centralised database of genetic tests, also accessible through the NCBI database portal, facilitates molecular confirmation of clinical suspicion.
Once a diagnosis has been reached, innovative software solutions can support the search for the right but often also rare experts. Here, comprehensive databases, such as se-atlas or Orphanet, can provide support, as well as the American College of Medical Genetics and Genomics (ACMG) “Find a Genetic Clinic” searchable database.
Medical informatics is also facilitating connections between clinicians, researchers, and patients. For example, resources such as the Matchmaker Exchange use a network of application programming interface-connected genomic and phenotypic data to match individuals with a shared interest or experience in similar rare genetic disorders and genetic variations. Another avenue for creating connections is social media. However, while social channels do offer opportunities, they also harbour risk.
In the case of rare diseases, there is a need to collect data tailored to the respective disease. Disease-related patient registries are particularly well-suited for this purpose. Due to their specificity, the quality-assured data these registries collect is much more suitable than the pure analysis of health care data. However, integrating analysis of such register data with health care data analysis can be advantageous.
Two aspects are challenging here. On the one hand, the usually small stakeholders of a particular rare disease often only have access to limited resources and possibilities to build up a register that fits the data models of state-of-the-art systems.
On the other hand, researchers who could derive great benefit from such data sources have little chance of finding these data treasures in the first place. The experts are often widely distributed, which makes cooperation difficult.
A similar barrier is also found in data collection. In most cases, different data sets are not coordinated, and as a result they are only compatible with each other to a limited extent. Difficulties at the organisational and legal levels can further complicate the issue of data management.
One important goal of initiatives like the European Joint Programme on Rare Diseases (EJP-RD) is to support researchers to find available resources for rare disease research activities, such as data sets or biomaterial.
To achieve this, different sources are identified, brought together, and made searchable via a metasearch functionality. That cooperation, which is that important in the research of rare diseases, is directly supported by technical solutions.
When addressing those mentioned challenges, medical informatics approaches offer good opportunities to improve the situation. For example, through IT support of the so-called FAIR (Findable, Accessible, Interoperable, Reusable) criteria.
FAIR criteria acts a guide for data producers and publishers as the landscape for medical informatics matures. With greater volumes of data being shared and distributed online, it is important to develop functional infrastructure that prioritises accessibility.
With a foundation of easy-to-access information, healthcare providers and life sciences companies can dedicate more time to developing new therapeutics and treatment options for patients.