Tackling rare disease with big and small data
Why we need workable models for combining very large datasets with the very small
Big data promises to create valuable insights in rare disease. Technologies such as next-generation sequencing and natural-language processing, alongside whole-exome analyses and other novel scientific approaches, are helping clinicians treat patients who previously had no therapeutic options. At the same time, deep interrogation of smaller patient samples can provide information of great benefit to developers of orphan drugs. Realizing the full potential of big data will require models that can also integrate intelligence from datasets that are small, writes Pete Chan.