There are more than 7,000 rare diseases identified, with 30 million of people affected in EU and US, however, only a fraction of them have approve treatment available. Orphan drugs are intended to treat diseases so rare that sponsors are reluctant to develop them under usual marketing conditions.
Rare diseases are characterized by several unmet needs and one of them, probably the most important, is the difficulty to make a right and timely diagnosis. This delay in diagnosis can have significant life-changing or life-shortening consequences for patient as the accurate and early detection of diseases and the differentiation from other disorders are essential for proper disease management.
At the Orphan Drugs & Rare Diseases Global Congress 2018 in London, the Director of research, INSERM and a Founder of Orphanet, Ségoléne Aimé, the trends in rare disease patient data collection management and analysis in Europe are divided in six topics.
To begin with, the first trend is related to the use of data and knowledge management to increase the efficiency of what physicians do with consensus on the goals. Data are available from primary sources, surveys, trials, publications (scientific articles, patent), real word data for organized sources (electronic health records, pharmacovigilance data, care management database) and unorganized sources (internet, social media).
The second trend is about open sources as open science aim to make scientific research, data and dissemination, accessible to all levels of an inquiring society with open literature and open data.
One example of this trend is the European open science cloud (EOSC) that is large infrastructure to support and develop open science and open innovation in Europe and beyond. This can be possible with a trusted access to service and system, a reuse of shared data across disciplinary social and geographical borders, a globally interoperable and accessible with a systematic and professional data management.
The majority of the challenges are social rather than technical with also a shortage of data experts and an archaic system of rewards. Furthermore, this trend is already developed in The European Bioinformatics Institute (EBI) and on Orphanet.
There is also over expectations around big data, that are mentioned as a third trend, the benefits about real world data from non-organised sources, can provide evidence beyond clinical research studies and can generate new hypothesis. However, cannot support casual conclusion and cannot generate evidence for decision making. Real world data from an organised source, instead, can assess the care and the health outcomes in routine clinical practice and can inform the application of evidence.
Trend 4 and 5 are about Registries and cohorts, as they are infrastructure that should be supported and are precompetitive tools. Registries are an important asset for rare diseases, with 695 RD registries in Europe. Data collections are priorities in national plans in all EU countries as rare diseases are one of the priorities in public health. The reason for prioritisation is that they are key instruments to develop clinical research, only way to pool data, and vital to assess feasibility.
One example of this trend is that EMA wants to establish a strategy to promote disease registries. They plan to do so by anticipating the needs and identify outcomes to consider. Registries should be established as early as possible when a product is in development and data need to be compatible across registries using international standards for semantic interoperability.
The last trend focuses on the European data protection, a new regulation was necessary to take into account the changes triggered by new technologies, such as the increasing use of internet and electronic means in healthcare and telemedicine. The General Data Protection Regulation (GDPR), which comes into effect in May, contains a raft of measures intended to strengthen citizen’s rights as regards the process of consent for the collection, use and sharing of their personal data.
In conclusion, Globaldata believes that open science is an opportunity for the rare disease community and following the FAIR principles for scientific data management (findable, accessible, interoperable and reusable), Big data will improve the diagnosis of rare diseases by physicians and they can access to them throughout the world.