Understand the scientific landscape with pharma insights generated from multiple disparate data sources
Finding the right information in a sea of structured and unstructured data sources is a real challenge. Important contextual information is often missed and there is insufficient time to spend on strategy development and decision making.
Unstructured data and document sources can cover a broad range of sources, such as literature, conference abstracts, medical liaison notes, news, social media, regulatory reports and more. Conventional scientific search methods can be very time-consuming and imprecise for targeted evidence review. Searching and combining information from many sources can be a repetitive process across therapy areas or topics of interest, which can lead to search fatigue and reduced staff productivity.
NLP text mining can extract the key facts, using relevant ontologies and focused queries, transforming data from different evidence streams into actionable intelligence for decision making. Capturing and integrating the information from a range of document sources can build a landscape of scientific, strategic and commercial knowledge, a pharma insights platform or “hub”.
The NLP Insights Hub integrates and transforms the information from a variety of document streams into easy-to-consume pharma insights dashboards. The Insights Hub allows you to see “the whole picture” and enables evidence-led decision-making, in a timely manner.
With the NLP Insights Hub you can:
An NLP Insights Hub provides visualizations and common search strategies created by domain experts and NLP data scientists to give users a head-start with their tasks.
NLP Insights Hub use cases have been developed for discovery, development, regulatory affairs, commercial and more. Multiple data sources are integrated and combined to provide the necessary landscape of information to solve critical problems.
Novo Nordisk are developing an innovation insights hub for Early Scientific Intelligence, to enable their R&D community to uncover innovative and new development potentialities. Combining data flowing from scientific papers, conference abstracts, patents, news feeds, and tech transfer offices from universities around the world. This provides an early view of potential opportunities for e.g. in-licensing or external collaborations, to improve their R&D pipeline.
Knowledge management across discovery and development
Merck developed a knowledge integration platform, SIM (selective information modules); with an automated NLP workflow to enable a federated search of external biomedical content in drug discovery and development, providing data for alerts and dashboards. (Published in McEntire et al (2016); https://www.sciencedirect.com/science/article/pii/S1359644616300757.)
At GSK, the Biopharm Product Development and Supply (BPDS) integrate both internal and external regulatory information (e.g. RTQs, FDA Warning letters, BLA review reports), to capture changes in regulatory guidelines, requirements, risks etc. This Insights Hub supports Biopharma regulatory affairs, risk management and regulatory surveillance, providing targeted information on the changing regulatory environment globally.
Chaya Duraiswami, GSK, presented at Linguamatics TMS 2018.
HEOR evidence landscape
HEOR evidence landscape for IBD, Crohn’s, and ulcerative colitis across Latin America; project for top 10 Pharma to integrate sci literature, conf abs, CT.gov, FAERS; including Spanish, French, extract and dashboard key epidemiological metrics to assess unmet need and market potential.
Real world data
Real world data for 360˚ world view for a newly launched product for medical affairs and product teams.
Novo Nordisk US have built a cloud-hosted insights hub integrating a mix of MSL conversations, medical information requests from HCPs, literature, news, conference abstracts and social media.
The COVID-19 Insights Hub enables users to tackle short, medium and longer-term questions to confront the COVID-19 pandemic, such as: