Learning more about drugs understanding in the market
How can pharma product managers efficiently learn how their drugs are faring with patients in the market?
Product managers and teams in pharmaceutical companies need to know what patients and healthcare professionals are reporting and asking about their drugs as they are used in the market, in order to discern trends and patterns and respond appropriately. Real world data (RWD) on drug usage and patient behaviours is available in multiple formats from myriad sources, but mining these disparate structured and unstructured sources with traditional manual search and curation is time-consuming and inefficient.
Novo Nordisk wanted to accelerate, automate and scale this process to provide enhanced access to the extracted information for superior and actionable insights.
Natural Language Processing-based Text Mining at Novo Nordisk
Novo Nordisk was already using the Linguamatics NLP platform in-house on multiple individual text mining projects with good success (e.g. reducing a publication gap analysis from three-to-four people for six weeks to a few hours). They wanted to capitalise on this success for real world data about their diabetes therapeutic products, from medical affairs team, healthcare professionals, and patients.