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NLP in Precision Medicine: Real-World Clinical and Research Applications

Precision Medicine has a tremendous potential to positively impact human health. AI techniques such as natural language processing (NLP) provide research and clinical teams with an exciting opportunity to realize that potential by effectively mining scientific and EHR data sources to better understand how genetics, environment and lifestyle factors can determine the best approach to prevent or treat disease with tailored approaches. This can be at the clinical level, or within drug discovery and development.

Within the clinical arena, in order to understand the best treatment pathway for a particular patient or group of patients, it is important to be able to access and analyze information about many different aspects of patients’ lives beyond just their medical history.

In the pharma industry, the annotation of high-throughput biological screens, such as next generation sequencing (NGS), can provide information for pharmacogenomic-related tailored drug development, from biomarker discovery and target evaluation, through to patient stratification and clinical profiling.

However, many of the sources needed for understanding detailed clinical phenotypes or genotype-phenotype relationships are unstructured text, which is not easily analyzed. I2E’s 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, and hear about some of the latest precision medicine application areas including:

  • Computational phenotyping with the Humana Phenotype Ontology
  • NLP-based assessment of variants of unknown significance in medical literature
  • Genotype-phenotype data mining for rare disease patient stratification

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