May 20, 2016

BioHIT TALK | Using Text Mining to Discover Repositioning Opportunities for Orphan Drugs and Rare Diseases | Dr Sherri Matis-Mitchell

Visiting speaker Dr Sherri Matis-Mitchell will give a talk on “Using Text Mining to Discover Repositioning Opportunities for Orphan Drugs and Rare Diseases” on Wednesday 25/5.

Abstract

On September 21, 2015, the FDA announced that it awarded 18 research grants totaling more than $19 million from the Orphan Products Grants program, to study and treat rare diseases that affect over 30 million people. While 30 million seems like a large number of patients, this is spread over 7000 rare diseases, where a disease that impacts fewer than 200,000 people in the United States is classified as a rare disorder. Because these diseases affect so few, the little information that’s available is buried in a vast bulk of literature on well-studied conditions affecting larger numbers of patients. This aspect makes the problem of identification of relationships between rare diseases and drugs a good candidate for text mining. In this webinar, we will introduce text mining as a methodology and discuss how it can provide an advantage over traditional keywords searching for rare diseases and orphan drugs. We will also review how to use text mining can be used to identify rare diseases and their relationships to potential target genes and potential treatment in the published literature, as well as relationships of orphan drugs to new disease indications.

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