A rare disease (RD) is defined in the US as those diseases affecting less than 200,000 people. It is estimated that 400 million people globally are affected by rare diseases. Most rare diseases have a genetic etiology, but it takes an average of 5 years for rare disease patients to receive an accurate diagnosis. Moreover, nearly 95% of rare diseases lack an FDA-approved treatment. 30% of children with a rare disease are not expected to see their fifth birthday because of diagnostic delay and lack of effective therapeutic interventions. However, ever-increasing amounts of data collected and managed for genetics and biomedical evidence present new opportunities for breakthroughs to improve diagnosis and treatments in rare diseases. Advanced biomedical informatics approaches hold great promise to support diagnosis, drug discovery, and clinical trials. The ability of computational technologies to identify novel patterns in data, particularly data from different sources (e.g., multi-omics, patient registries, and so on), can be used to overcome current challenges (e.g., poor diagnostic rates, lack of treatment standards, misunderstood etiology and so on). Innovations in science, technology and the use of big data and AI analytics are enabling great leaps forward with rare disease.
We also like to explore biomedical applications in translation process to move the basic research advances into practice so as to benefit patients quickly and efficiently. In this workshop, we would like to focus on applications of biomedical informatics in translational research and rare diseases and provide a communication opportunity for data scientists in RD research.