Abstract

A rare disease refers to any disease with very low prevalence individually. Although the impacted population is small for a single disease, more than 6000 rare diseases affect millions of people across the world. Due to the small market size, high cost and possibly low return on investment, only in recent years, the research and development of rare disease drugs have gradually risen globally, in several domains including gene therapy, enzyme replacement therapy, and drug repositioning. Due to the complex etiology and heterogeneous symptoms, there is a large gap between basic research and patient unmet needs for rare disease drug discovery. As computational biology increasingly arises researchers' awareness, the informatics database on rare disease have grown rapidly in the recent years, including drug targets, genetic variant and mutation, phenotype and ontology and patient registries. Along with the advances of informatics database and networks, new computational models will help accelerate the target identification and lead optimization process for rare disease pre-clinical drug development.

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