Posts from October 2019

It is well known that the drug discovery and development process is lengthy, expensive and prone to failure. Starting from the selection of a novel target in discovery, through the multiple steps to regulatory approval, the overall probability of success is less than 1%.

One factor is that the majority of diseases are multifaceted, hence the challenge is identifying the most appropriate patient populations who will respond to specific interventions. A stratified approach has proven beneficial in a number of cancers and genetic diseases, and pharmaceutical companies have a strong interest in understanding how to find the sub-populations of patients to ensure the most appropriate therapies are tested in clinical trials, and applied in broader clinical use.

The ultimate aim of a stratified approach to medicine is to enable healthcare professionals to provide the “right treatment, for the right person, at the right dose, at the right time”; and there are many research initiatives (governmental, private, public) on-going to develop the appropriate knowledge and models.


Linguamatics NLP-Based Phenome Extraction from the EHR

On October 24 Benjamin Darbro, MD, PhD, Associate Professor of Pediatrics, Stead Family Department of Pediatrics at the University of Iowa, and Alyssa Hahn, doctoral student in the Interdisciplinary Graduate Program in Genetics at the University of Iowa, will present the webinar "The Use of Natural Language Processing to Improve Phenotype Extraction for Precision Medicine.”

How does NLP support precision medicine and improve patient clinical care?

Precision medicine focuses on disease treatment and prevention, taking into account the variability in genes, environment, and lifestyle between individual patients. 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 detailed information from the medical records of patients, and ideally broader aspects beyond their medical history.