The Current State of the Art for Natural Language Processing in Pharma
The need for NLP for precision medicine in Pharma is evident from the vast amount of time and money it takes to provide precision medicine by extracting data manually from clinical documents. To provide precision medicine, we need to match patients to clinical trials, recommend relevant clinical guidelines for each patient, collect real-world data at scale, automate the summarization & validation of clinical trial documents and build patient cohorts based on medical history, condition, and biomarkers. These NLP challenges often require a processing pipeline similar to the one below to automate the process of extracting structured data from clinical documents, clinical trial forms, etc.
In this free eBook, we’ll outline:
- Key NLP Tasks to enable pharmaceutical uses cases Biomedical NER (BioNER)
- Assertion Status Detection
- Text De-Identification
- Relation Extraction & more