Case Study
Examining Rare Disease Biology With Natural Language Processing Text Mining At Takeda
NLP extracts genotype–phenotype associations for the Hunter Outcome Survey
Sep 30, 2022

Takeda’s ongoing support of the HOS patient registry, and its desire to better understand the biology of this rare disease, require continual scanning of the literature for publications on the disease, mutations of the key gene IDS and associated phenotypic information. With well-crafted NLP queries, Takeda was able to search the literature to pinpoint 461 relevant papers, extract around 380 unique IDS mutations with >95% precision and recall, and to associate these with related phenotypic information.

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