Precision Medicine has a tremendous potential to positively impact human health, particularly for rare diseases. Natural language processing (NLP) provides research and clinical teams with the power to effectively mine scientific and EHR data sources. Genotypes-phenotypes associations can be revealed that inform rare disease diagnoses in the clinic, and provide a landscape for drug discovery and development.
Within the clinical arena, in order to understand the best treatment pathway for a particular rare disease patient or group of patients, it is important to be able to access and analyze information from the unstructured parts of clinical records as well as the structured. In the pharma industry, there is a rich landscape of gene-disease and gene-mutation information buried in unstructured text such as scientific literature.
Linguamatics NLP-based text analytics unlocks the value from sources such as electronic health records (EHRs), scientific literature, conference abstracts, or internal reports.
In this webinar, you will learn how NLP is being used to transform unstructured source data into clinical and research decision support insights for rare diseases, and hear about some of the latest precision medicine initiatives including use cases from University of Iowa, Takeda and Sanofi:
- Computational phenotyping with the Human Phenotype Ontology
- Genotype-phenotype data mining for rare disease patient stratification
- Landscape of rare disease biology from literature for drug development